Report for
CEATI INTERNATIONAL Inc. 1010 Sherbrooke Street West, Suite 2500 Montreal, Quebec, Canada H3A 2R7 Website: www.ceati.com
HYDRAULIC PLANT LIFE INTEREST GROUP (HPLIG)
CEATI REPORT No. T102700-0371
HYDROELECTRIC INDUSTRY’S ROLE IN INTEGRATING WIND ENERGY
Prepared by Thomas L. Acker, PhD Flagstaff, Arizona, United States
Sponsored by The 2010 Participants of the Hydraulic Plant Life Interest Group (HPLIG)
Technology Coordinator Alastair M. Wilson
February 2011
Hydroelectric Industry’s Role in Integrating Wind Energy
This report was prepared by Thomas L. Acker, Ph.D., (CONTRACTOR) and administered by CEATI International Inc. (“CEATI”) for the ultimate benefit of CONSORTIUM MEMBERS (hereinafter called “SPONSORS”), who do not necessarily agree with the opinions expressed herein.
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Copyright © 2011 CEATI International Inc. All rights reserved.
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Hydroelectric Industry’s Role in Integrating Wind Energy
ABSTRACT
Over the past decade, the cost of wind energy has become competitive with wholesale power prices. Combined with its positive environmental attributes and public demand for clean energy resources, the expectation is that the magnitude of wind power contributing to the electrical supply mix will continue to increase, perhaps someday exceeding 20% of the electrical energy served. Wind energy, however, is inherently variable and subject to inaccuracies in prediction. This variability and uncertainty manifest themselves in the power system through the need for increased ancillary services of regulation and load following, as well as increased reserve requirements. To deal with the uncertainty and variability of wind energy, power system operators need increased amounts of flexible generation resources. These resources can respond quickly to variations in “load net wind,” helping to maintain the balance between load and generation and to provide reserves that cover for missed load and wind power forecasts. In both these respects, hydropower may be ideally suited to integrate wind power in a power system. Hydropower, however, has certain aspects of its operation that require special consideration with regards to wind integration, primarily because hydro facilities have numerous priority functions such as flood control, orderly delivery of water to downstream users, safe navigation, etc., that make these facilities highly valuable public resources but also may limit their flexibility in power generation. The purpose of this report is to perform an in-depth review of the literature related to wind integration, especially in systems with hydropower. The report describes the salient aspects of wind integration, summarizes the literature, and characterizes the hydroelectric industry’s role in wind integration, with the objective of providing the basic information required for hydro plant operators and planners to understand the issues related to wind integration and to outline an appropriate role for the hydro electric industry.
Keywords: Wind Integration, Hydropower, Wind Power Forecasting, Renewable Energy
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ACKNOWLEDGEMENTS
This report was prepared under CEATI International Agreement No. T104700-0371 with the sponsorship of the following participants of CEATI’s Hydraulic Plant Life Interest Group (HPLIG):
Company Name (listed in alphabetical order) Province Country /State Allegheny Energy Supply PA USA Ameren UE IA USA American Electric Power VA USA Avista WA USA BC Hydro Generation BC Canada Bonneville Power Administration OR USA Brookfield Renewable Power QC Canada California Department of Water Resources CA USA Capital Power Corporation AB Canada Chelan County Public Utility District WA USA Columbia Power Corporation BC Canada Douglas County PUD WA USA Duke Energy NC USA ESB (Electricity Supply Board) Ireland Eugene Water and Electric Board OR USA FirstLight Power MA USA FortisBC Inc. BC Canada Fortum Generation AB Sweden Grant County Public Utility District WA USA Hetch Hetchy Water & Power CA USA Hydro Tasmania TAS Australia Hydro-Quebec QC Canada Korea Hydro & Nuclear Power Co. Korea Korea Water Resources Corporation Korea Manitoba Hydro MB Canada Mighty River Power New Zealand Nalcor Energy, Churchill Falls NL Canada Natural Resources Canada ON Canada New Brunswick Power Generation Corporation NB Canada New York Power Authority NY USA Newfoundland and Labrador Hydro NL Canada North American Hydro WI USA Nova Scotia Power Inc. NS Canada Ontario Power Generation ON Canada Pacific Gas & Electric CA USA Portland General Electric OR USA Puget Sound Energy Inc. WA USA Rio Tinto Alcan QC Canada Sacramento Municipal Utility District CA USA SaskPower SK Canada SHEM France Snowy Hydro Limited NSW Australia Southern California Edison CA USA
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Hydroelectric Industry’s Role in Integrating Wind Energy
Southern Company AL USA Tacoma Power WA USA Tennessee Valley Authority TN USA TransAlta Energy Corporation AB Canada TransCanada Pipelines AB Canada U.S. Army Corps of Engineers OR USA U.S. Bureau of Reclamation CO USA Vattenfall AB Sweden
The investigators are grateful to CEATI for the opportunity to work on this interesting issue. The constant support and guidance by the CEATI Technology Coordinator Alastair M. Wilson, as well as Project Monitors Chris Brown of Puget Sound Energy, Hans Bjerhag of Fortum, and Jim DeHaan of U.S. Bureau of Raclamation, was greatly appreciated by the investigators.
The contractor wishes to express his gratitude to Mr. Carson Pete, Mr. Mark Bielecki, Mr. Jason Kemper, and Mr. Harvey Boyce, all of whom were contributing authors to this report.
The authors wish to express their gratitude to the organizations that granted permission for their figures to be reproduced in this report.
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EXECUTIVE SUMMARY
Wind integration into the electrical power system has become of increasing consequence over the past ten years. The price of electricity produced by wind energy is competitive with wholesale power prices and with new thermal power plants, the reliability of the equipment typically exceeds 98%, and it offers price stability as contracts for wind power are typically set-up for the life of the project. Furthermore, the potential magnitude of the wind power resource, though it varies from country to country, is immense, and wind power does not emit any greenhouse gases or require any water consumption for cooling requirements during generation. Collectively, these attributes provide powerful motivation to system planners, regulators, and the public at large to request that wind power occupy a greater portion of the electrical energy supply mix. As a result, the global installed capacity of wind power has increased dramatically during the last decade, and this growth is expected to continue over the next several years. Thus, wind integration will grow in importance and urgency.
When contemplating wind energy, perhaps the point of view of most relevance is that of society: what is the overall benefit of incorporating wind power into the electrical system, and what are its prospects for leading to an economically and environmentally sustainable energy future? Such a holistic view has led to policies and practices that have encouraged the incorporation of wind power into electricity supplies. Wind power, however, has different operating characteristics when compared to traditional electric power generation resources. In this regard, two features of wind power stand out: 1) due to the nature of the wind, the power derived from it is inherently variable; and 2) predicting the wind power is challenging and, therefore, there will always be uncertainty in its prediction. This variability and uncertainty of wind energy manifest themselves in power system operation through the need for increased ancillary services of regulation and load following, as well as increased reserve requirements. Generally speaking, when one refers to “wind integration,” the implication is not the holistic view of wind power’s impact on electrical costs to the consumer or benefit to society, but rather to the integration impacts and costs due to the wind’s variability and uncertainty on system operation and planning. The same philosophy was adopted in this report, primarily because addressing these integration issues is where the flexible generation resources of hydropower can be of greatest utility. Hydropower can provide the balancing and reserves needed in electrical systems that incorporate wind power, and can benefit economically from the opportunity that arises in doing so. The additional electrical system balancing requirements introduced by wind power, if met by hydropower, could lead to an increase in operations and maintenance at hydropower plants. For hydro utilities to partake in wind integration, the various issues of relevance to their hydropower facilities need to be identified and addressed. Gaining an understanding of the wind power impacts on power system operation, and the potential for hydropower to meet these needs, is the primary objective of this report. Thus, the main topics addressed in the report are as follows: Wind power: aspects of wind energy relevant to integration in electrical systems with hydropower, especially as pertaining to the wind power’s variability and uncertainty. Power system integration of wind energy: review of experiences. Hydropower: capabilities and limitations in addressing wind integration impacts. Conclusions: role of hydropower in wind integration.
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In addition to this information, the report contains appendices that provide an extensive bibliography of reports related to wind integration, a review of relevant literature related to wind integration in systems with hydropower, an overview of wind power technology, costs, and policies, and a discussion of methods to quantify wind integration impacts and costs.
Hydropower’s fundamental advantage in integrating wind power lies in the agility of its generators in meeting rapid changes in net load, thus providing system ramping, the ability to shift periods of energy production (storage), and supplying fast responding reserves (spinning and non-spinning). These resources are of great value in a power system that incorporates a high penetration of variable and uncertain generation resources, such as wind power. Hydropower also has the ability to provide voltage support to wind systems by supplying reactive power. As many wind power plants are located in remote sites, the long transmission lines and the use of induction generators tend to be ‘reactive deficient’. Thus, opportunity exists for hydropower producers to benefit financially from providing these services.
Hydropower, by virtue of its water impoundment, also has the opportunity to develop unique market products for wind integration customers. “Storage and shaping” products or short-term balancing supplied for wind integration (to compensate for missed forecasts and unexpected ramps in net load) may be of value to electricity customers and utilities. There may also be opportunities for pumped storage hydropower (PSH) in wind integration, where wind integration is one component of the value proposition, especially in systems where the wind penetration exceeds 30%. Furthermore, to the extent that wind and hydropower vary on different timescales and are available at different times of the day or year, they can be complementary resources.
The ability to provide ancillary services, reserves, or energy storage via hydro power varies from plant to plant and by location. Hydro facilities with small reservoirs and not tasked with flow re- regulation may have the potential to provide regulation, reserves, load following, and energy storage on a time frame of several hours to days. Hydro facilities with large storage capacities have the greatest potential as a system balancing resource by providing quick-start ancillary services and the ability to shift water and energy releases for days to several months. With regards to wind integration in systems with hydropower, however, there are many issues and constraints: Priorities. Hydro facilities often have multiple priority functions that take precedence over power generation tends, and limit the flexibility of a hydro power plant. Environmental Issues. Flow restrictions may exist to comply with environmental regulations, thus inhibiting flexible operation of the power plant. Availability and interconnected river systems. Factors limiting the availability of hydro generation will also limit their ability to integrate wind. Complex organizations. Understanding the authority and priority structure of a hydropower plant is key in defining the available flexibility for purposes such as wind integration. Proper methods to allocate the costs and benefits need to be devised, especially in systems with many stakeholders. Determining the impacts. Understanding the impacts of wind generation on net load, system balancing requirements, and both physical/O&M and economic impacts on hydro power. Scheduling intervals and markets. Infrequent scheduling intervals, combined with inaccurate forecasting, may lead to a significant amount of reserve being allocated over the hour of operation and suboptimal use of the hydropower. Increasing the frequency of the scheduling interval can relieve the requirement for unnecessary reserves and allow more flexibility in the
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use of hydro generation resources. Liquid markets or balancing area cooperation are two additional ways of to infuse flexibility into the electrical system. Despite these issues and constraints, hydropower still possesses significant flexibility and is capable of integrating large amounts of wind power, as discussed in detail in the report. A number of directions for future research are also identified, as related to the integration of wind power into systems with hydropower.
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TABLE OF CONTENTS Page ABSTRACT ...... iii ACKNOWLEDGEMENTS ...... iv EXECUTIVE SUMMARY...... v 1.0 Introduction ...... 1-1 2.0 Wind Power: Characteristics of Importance to Electrical System Planning and Operation ...... 2-1 2.1 Production Characteristics...... 2-1 2.2 Variability of Wind ...... 2-2 2.3 Geographic Diversity ...... 2-7 2.4 Forecasting...... 2-7 3.0 Power System Integration of Wind Energy: Review of Experiences ...... 3-1 3.1 Wind Power Penetration Levels...... 3-1 3.2 Wind Integration Costs and Challenges: Handling Variability and Uncertainty ...... 3-2 3.3 Special Concerns Pertaining to Wind and Hydro Integration ...... 3-6 3.4 Typical Impacts and Costs of Wind Integration ...... 3-9 3.5 Integrating Wind in Different Market Structures...... 3-11 3.6 Recent Wind Integration Rate Cases...... 3-13 3.7 Resources Related to Wind Integration...... 3-13 4.0 Hydropower: Capabilities, Limitations, and the Role of Hydroelectric Industries in Wind Integration...... 4-1 4.1 Physical Characteristics of Hydropower ...... 4-1 4.1.1 Generator Characteristics ...... 4-1 4.1.2 Run-of-the-River Hydro ...... 4-3 4.1.3 Hydro with Storage...... 4-3 4.1.4 Pumped Storage Hydro ...... 4-4 4.1.5 Availability of Hydro...... 4-4 4.1.5.1 Capacity Factor ...... 4-5 4.1.5.2 Diurnal, Seasonal, and Annual Trends...... 4-6 4.1.6 Interconnected River Systems...... 4-8 4.2 Multi-purpose Hydropower ...... 4-9 4.2.1 Priority Functions ...... 4-9 4.2.2 Flow and Power Constraints ...... 4-10 4.2.3 Planning of Resources...... 4-11 4.3 Hydropower System Flexibility – Institutional, Organizational and Legal Issues.. 4-12 4.4 Conclusions: The Role of the Hydroelectric Industry in Wind Integration ...... 4-16 4.4.1 Opportunities...... 4-17 4.4.2 Issues and Constraints ...... 4-19 4.4.3 Impacts on hydropower operations and maintenance...... 4-20 4.4.4 Areas of future research...... 4-21 5.0 References ...... 5-1
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APPENDIX A. Review of wind integration literature ...... A-1 APPENDIX B. Bibliography of Wind Integration Reports ...... B-1 APPENDIX C. Overview of Wind Power: Technology, Costs, Penetration, and Policies .. C-1 C.1 Wind Technology...... C-1 C.1.1 The Commercial Wind Turbine...... C-1 C.1.2 Turbine Components ...... C-4 C.1.3 Offshore Wind Technology ...... C-5 C.2 Costs of Wind Energy ...... C-6 C.3 Wind Energy Penetration ...... C-9 C.4 Policies ...... C-11 APPENDIX D. Methods to Quantify Wind Integration Impacts and Costs...... D-1
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LIST OF TABLES Page Table 3-1: Individual and aggregate variability of wind and load. (Source: NBSO-ERNB, 2007)...... 3-3 Table 3-2: Increases in regulation requirements to account for three standard deviations (99+%) of additional variations due to wind. (Source: Zavadil 2006) ...... 3-5 Table 3-3: Incremental reserve requirements for various scenarios of the Avista Corporation wind integration study. (Source: EnerNex 2007)...... 3-8 Table 3-4: Impacts of wind integration from several recent U.S. case studies. (Source: Wiser 2009)...... 3-10 Table 3-5: Categorized estimations of operating reserve requirements for the Minnesota Balancing Authority with estimated load in 2020. (Source: EnerNex 2006)...... 3-10 Table 3-6: Summary of some results from the Phase 2 of the NYSERDA study. Note: UCAP denotes unforced capacity or probability of being available when called upon (calculated as installed capacity minus forced outage rate). (Source: Piwko 2005) ...... 3-11 Table 4-1: Historical hydro plant capacity factors for 58 hydropower plants operated by the USBR. (Source: United States Bureau of Reclamation)...... 4-6 Table B-1: Comprehensive list of wind integration reports...... B-1 Table C-1: Wind power resource table at 10 m and 50 m heights. (Source: AWEA) ...... C-7 Table C-2: Cost and performance difference between turbines from two generations with differing technologies (Source: AWEA) ...... C-7 Table D-1: Characteristics of two major classes of models used in wind integration studies...... D-6
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LIST OF ILLUSTRATIONS Page Figure 1-1. Wholesale power prices and wind power prices over the past several years in the United States. (Source: Wiser and Bolinger 2009) ...... 1-1 Figure 1-2: A holistic perspective of the value derived from incorporating wind into a utility system. (Source: Acker 2007a) ...... 1-2 Figure 1-3: Time scales of importance in wind integration, when considering the ancillary service impacts due to the variability and uncertainty of wind energy. (Source: National Renewable Energy Laboratory)...... 1-4 Figure 2-1: Mean annual wind power density at 80m height (2003 data). © Source: Environment Canada, Canadian Wind Energy Atlas, 2003; used with permission...... 2-1 Figure 2-2: Time frames of wind variability relative to electrical system operations. (Source: Piwko 2004)...... 2-3 Figure 2-3: Variability of wind speeds within a single wind power plant. (Source: Wang 2005)...... 2-4 Figure 2-4: Example of diurnal patterns of load and wind for single month in New York. (Source: Piwko 2004)...... 2-5 Figure 2-5: Example of annual wind capacity factor and annual peak load for single year in New York. (Source: Piwko 2004)...... 2-6 Figure 2-6: Correlation between seasonal load and hydro inflow (left), and correlation between historical load and wind resources (right) in Hydro-Québec. (Source: PERI 2002)...... 2-6 Figure 2-7: Correlation coefficient of wind power step changes vs. distance between wind power plants. (Source: Wan 2005)...... 2-7 Figure 2-8: Common forecast error metrics versus forecast horizon from an actual wind power plant data. (Source: Bielecki 2010)...... 2-8 Figure 3-1: 10-minute variability percentiles for simulated wind power. Installed capacities for Scenarios A, B, C, and D were 254, 895, 1445, and 1994 MW, respectively. (Source: Wang 2005) ...... 3-4 Figure 3-2: Summer ramp requirements for cases with and without wind generation. (Source: EnerNex 2004)..... 3-5 Figure 3-3: The decay of the variability of the wind as more sites are added to a region. (Source: NBSO- ERNB, 2007)...... 3-7 Figure 3-4: Two-year running average of annual departure of wind speed and hydro runoff from their respective mean annual values. (Source: Zavadil 2006)...... 3-9 Figure 4-1: Typical efficiency curves for multiple-unit hydropower plants. (Source: Oak Ridge National Laboratory) ...... 4-3 Figure 4-2: Historical record of Colorado River flows. (Source: USGS 2004) ...... 4-5 Figure 4-3: Diurnal generation distributions by month. (Source: Pete 2010)...... 4-7 Figure 4-4: Daily averaged generation for Glen Canyon power plant. (Source: Pete 2010)...... 4-8 Figure 4-5: Glen Canyon Dam generation capability and end-of-month (EOM) water elevation accompanied by monthly peak demand generation. (Source: Pete 2010; data provided by the U.S. Bureau of Reclamation)...... 4-11 Figure 4-6: A practical configuration for integration of wind and hydropower resources. (Source: Acker 2010).... 4-13 Figure 4-7: Sample results from the NREL/GE Western Wind and Solar Integration Study showing the hourly dispatch of power from Hoover Dam during a week in April. (Source: Pete 2010)...... 4-15 Figure C-1: Evolution of wind turbine size over time. (Source: EWEA)...... C-2 Figure C-2: Illustration of wind turbine components. (Source: Wind Energy Development Programmatic EIS).....C-3 Figure C-3: Example of a wind turbine power curve with observed data. (Source: Acker 2007a; power curve provided by 3TIER)...... C-4 Figure C-4: U.S. Installed wind power project costs. (Source: Wiser 2009)...... C-6 Figure C-5: Average O&M costs for U.S. wind projects. (Source: Wiser 2009)...... C-9 Figure C-6: The top 10 countries in terms of cumulative installed wind power capacity. (Source: EWEA) ...... C-10 Figure C-7: International wind power penetration levels. (Source Wiser 2009)...... C-11
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Figure D-1: Range of time- and geographic-scales that may be of interest in wind integration studies. (Source: Holttinen et al. 2008)...... D-1 Figure D-2: Determining the impact and costs of wind integration by comparing the costs of operating two variations of an electrical system, one with wind and one with some other set of generation resources. (Source: Söder and Holttinen 2008)...... D-4 Figure D-3: Block Diagram Representation of one method used in detailed wind integration studies. (Source: EnerNex 2004)...... D-5
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1.0 Introduction
Wind integration into the electrical power system has become of increasing consequence over the past ten years. The price of electricity produced by wind energy is competitive with wholesale power prices and with new thermal power plants (e.g., see Figure 1-1 for recent prices in the U.S.), the reliability of the equipment typically exceeds 98%, and it offers price stability as contracts for wind power are typically set-up for the life of the project. Recent wind resource estimates by the U.S. Department of Energy suggest that there is the physical potential to develop in excess of 10,000,000 MW of 30% or greater capacity factor wind power in the United States (after removing windy lands that are not suitable for development due to factors such as National Park land, urban areas, wetlands, steep slopes, etc.).1 This is approximately 10 times the current electrical capacity in the United States. Significant potential exists in other countries as well, though the magnitude varies considerably from country to country. Furthermore, wind power does not emit any greenhouse gases or require any water consumption for cooling requirements during generation. Collectively, these attributes provide powerful motivation to system planners, regulators, and the public at large to request that wind power occupy a greater portion of the electrical energy supply mix. As a result, the global installed capacity of wind power has increased dramatically during the last decade, from 15,400 MW in 2000 [IEA 2008] to in excess of 145,000 MW at the beginning of 2010.2 This momentous growth is expected to continue over the next several years, thus wind integration will grow in importance and urgency.
Figure 1-1. Wholesale power prices and wind power prices over the past several years in the United States. (Source: Wiser and Bolinger 2009)
An overall, “holistic” perspective on the value of incorporating wind energy into an electrical system is presented in Figure 1-2. The green bar shown displays the positive financial benefits of wind energy, typically normalized per megawatt-hour (MWh) of wind energy production over the course
1 Refer to the Wind Powering America website: http://www.windpoweringamerica.gov/wind_maps.asp 2 Wind Powering America Update, January 2010, http://www.windpoweringamerica.gov/filter_detail.asp?itemid=746
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of a year. The largest component of the positive benefits, as shown in the figure, is the marginal value of the wind energy; that is, its value in displacing other energy purchases or expenses. This marginal value depends upon when the wind blows and is greater if the wind power is coincident with peak loads. The red bar shows the various costs associated with incorporating wind energy. The dominant cost is the actual cost of the wind energy, which is typically purchased via a long-term contract. Transmission costs can also be significant because the best wind resources are often located far away from the loads and require new transmission, and this has therefore been specifically identified as a potential cost. Indeed, access to existing transmission in addition to creation of new transmission will be crucial to incorporation large amounts of wind energy on the grid. The “integration costs” shown on the bottom of the red bar is the additional cost incurred in planning and operation due to the uncertainty and variability of the wind energy. Overall, there is generally a net benefit due to wind energy, represented by the blue bar in Figure 1-2, the magnitude of which varies from utility to utility based upon each system’s generation resources, load, wind resources, operational rules and constraints, and the market within which it operates. The “other benefits” shown correspond to non-monetized benefits, such as avoided carbon emissions, etc.
Capacity value
Marginal value of wind energy Other benefits Tax credits / Tariffs Benefits Combine all Net benefit Other credits benefits and costs or cost
Cost of wind Costs energy
Transmission costs “Integration” costs Figure 1-2: A holistic perspective of the value derived from incorporating wind into a utility system. (Source: Acker 2007a)
In its essence, wind originates from uneven heating of the earth’s surface by the sun, which in turn drives seasonal and diurnal patterns of global air circulation and establishes the prevailing wind patterns. Superimposed on top of these wind patterns are regional and constantly changing weather systems that, combined with the effects of local topography, result in a wind resource that is inherently variable. Over the past several decades, the atmospheric science community has developed increasingly accurate numerical weather prediction (NWP) models that forecast the state of the atmosphere and expected weather over the next several days. These models have benefited greatly from the continual advancement in computing technology and accompanying decrease in costs, along with improvements in available weather data required as boundary conditions. NWP models are used as a primary input in weather predictions, including forecasts of wind speed, direction, and precipitation. These forecasts, in turn, are fed into wind power prediction algorithms, and are
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Hydroelectric Industry’s Role in Integrating Wind Energy especially useful for forecasts beyond the eight hour forecast horizon. Moreover, as the wind energy forecasting profession matures, forecasters are gaining more skill in developing wind power forecasts using a combination of NWP models, statistical techniques, and learning algorithms that improve with experience. That said, the non-linear nature of the fundamental equations that describe atmospheric motions impose limitations on the ability to predict the weather, and thus, wind forecasts are intrinsically inaccurate. These inaccuracies lead to an uncertainty in wind power forecasts.
The variability and uncertainty of wind energy manifest themselves in power system operation through the need for increased ancillary services of regulation and load following, as well as increased reserve requirements. Generally speaking, when one refers to “wind integration,” the implication is not the holistic view of wind power’s impact on electrical costs to the consumer, as inferred in Figure 1-2, but rather to the integration impacts and costs due to the wind’s variability and uncertainty on system operation and planning (the bottom segment of the red bar in Figure 1-2). The same philosophy will be adopted in this report, primarily because addressing these integration impacts is where the flexible generation resources of hydropower can be utilized. Hydropower can provide the balancing and reserves needed in electrical systems that incorporate wind power, and economic benefits may arise from this opportunity.
Figure 1-3 depicts the time frames of system operation and planning that are impacted by wind integration. Though the terminology may vary from system to system and country to country, the essential functions of balancing the system are the same. Wind power’s variability will enhance the short-term minute-to-minute fluctuations (referred to as regulation in this figure) as well the longer- term system ramping (depicted as load following), and its uncertainty will influence the scheduling and unit commitment. At wind power penetration rates up to 1 or 2% of the peak system load, wind power is not very noticeable to the electrical system operator. That is, the wind energy appears as negative load, and so instead of operating the system to meet the load alone, it is operated to meet the load less the wind generation (referred to as “load net wind” or “net load”). At small penetration levels, the system operator is not concerned with missed wind power forecasts (or having no wind power forecast at all), or the small increment of variability that wind power adds to an already variable load since the load and “load net wind” signals are quite similar. Beyond this threshold, however, wind power can have a noticeable impact, causing the load net wind to differ from the load alone. Many regulatory bodies, political institutions, or customers are requiring large percentages of their electrical energy to be derived from renewable energy resources (up to 30% in some locales), and since wind energy will supply a significant fraction of this energy in some cases, wind integration has become an important issue for electrical balancing area authorities.
In addition to increasing the ancillary services required in operating the electrical system, wind energy also behaves differently than traditional dispatchable generation resources. At penetration levels beyond the 1 to 2% level, this behaviour requires the electrical system operator to be cognizant of the wind power forecast, its expected accuracy, and to have a realistic understanding of the variability in its output. Furthermore, wind power contributes only a portion of its rated capacity as firm capacity to run the system (e.g. its Effective Load Carrying Capability or ELCC). In essence, absorbing wind power at significant levels into traditional utility operation requires a paradigm shift in how the system operator and planner views generation from non-traditional renewable energy resources, such as wind power. Despite these challenges and the associated costs to accommodate them, wind energy can have a positive system benefit and reduce the overall cost to serve load.
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Days
Unit System Load (MW) Commitment
Time (hour of day) 04812 16 20 24
tens of minutes to hours day seconds to minutes Load Scheduling Regulation Following
Figure 1-3: Time scales of importance in wind integration, when considering the ancillary service impacts due to the variability and uncertainty of wind energy. (Source: National Renewable Energy Laboratory)
To deal with the uncertainty and variability of wind energy, system operators typically need access to flexible generation resources, though flexible load management (e.g. load response, smart grid technologies, etc.) is also appropriate. These resources must respond quickly to variations in load net wind, helping to maintain the balance between net load and generation, and provide reserves that cover for missed wind power and load forecasts. In both these respects, hydropower is ideally suited to complement the integration of wind power into a system. One of the foremost questions that need to be addressed in wind and hydropower integration is whether hydropower systems imposed with current generation limitations can handle the system balancing impacts due to the variability and uncertainty of wind power. A major concern that may arise from the hydro system’s point of view involves the change in operation and costs that ensue wind integration. Hydro generators are intrinsically agile and capable of meeting rapid changes in the demand. Many hydro facilities have relatively low capacity factors (low 20’s to mid 40’s %), thus, those with substantial water impoundment can often contribute significant spinning or non-spinning reserves to the electrical system. This provides a short- to medium-term buffer for the wind power’s limitations in predictability without interfering with the ability of the hydro to meet other system demands that ultimately conflict with hydropower production.
Hydropower, however, has certain aspects of its operation that require special consideration with regards to wind integration. Hydro facilities often have numerous functions or priorities, such as flood control, navigation, recreation, irrigation water deliveries, etc., that make these facilities highly valuable public resources. Often superimposed on top of these priority activities are environmental regulations that dictate certain aspects of operation, such as flow constraints for fish survival or improvements in wildlife habitat. To the extent that the other purposes of a hydro facility or constraints on its flow supersede power production, the flexibility of its generators can be limited. Furthermore, hydropower plants are usually found on interconnected river systems where the output of one hydro facility affects all of those downstream. By no means do these factors prohibit
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the use of hydro power to aid in wind integration, but they do represent real issues that require addressing.
Given this background information, the objectives of this report that will be addressed in the subsequent chapters are as follows:
Wind power: aspects of wind energy relevant to integration in electrical systems with hydropower, especially as pertaining to the wind power’s variability and uncertainty. Power system integration of wind energy: review of past experiences. Hydropower: capabilities and limitations in addressing wind integration impacts. Conclusions: role of hydropower in wind integration.
In addition to these chapters, the appendices include an extensive bibliography of reports related to wind integration, a review of relevant literature related to wind integration in systems with hydropower, an overview of wind power technology, costs, and policies, and a discussion of methods to quantify wind integration impacts and costs.
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2.0 Wind Power: Characteristics of Importance to Electrical System Planning and Operation
2.1 Production Characteristics
Wind power is a unique resource that encompasses many benefits when included as part of the electrical generation mix. However, due to the nature of its dependence upon meteorological phenomenon, wind power also presents a distinctive set of characteristics that must be understood by electrical system planners and operators. Wind is generally taken to be non-dispatchable and functions primarily as an energy resource that can allow for reductions in otherwise necessary fossil fuel production. It is non-trivial to quantify wind power’s contribution as a capacity-serving entity in the traditional sense, although it is capable of providing some level of capacity. The intermittent nature of wind is often characterized in terms of its variability and uncertainty. The variable nature of wind refers to the fact that there are constant fluctuations in the output levels, and the uncertainty refers to the level of inaccuracy always present in predicting wind power in both magnitude and time.
In general, the characteristics of wind power output are regionally specific, and areas that possess favourable wind resources are often located far from load centers. Figure 2-1 presents a rough overview of annual wind power density distribution throughout Canada, and is representative of wind resource maps made for many countries.3 Wind plant development is based on a careful balance of sufficient wind resources, land acquisition, proximity to transmission, and power purchase agreements (PPAs) by utilities, independent system operators (ISOs), or other load-serving entities (LSEs).
Figure 2-1: Mean annual wind power density at 80m height (2003 data). © Source: Environment Canada, Canadian Wind Energy Atlas, 2003; used with permission.
3 Accessed March 2010 at http://www.windatlas.ca/en/maps.php?field=E1&height=80&season=ANU.
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The production characteristics of wind plants are generally modeled and monitored in detail both during the pre-development and operational phases. At a given site, turbine layout schemes are chosen to optimize usage of prevailing winds and topographical features, combined with other site specific constraints such as road access, right-of-ways, soil conditions, etc. To the extent that is practical, turbines are spaced such that “upstream” units will not interfere with the wind flow into “downstream” units. The nameplate (or installed capacity) of a wind power plant is equivalent to the sum of the rated capacities of each individual turbine. The energy production of a wind power plant is characterized by its “capacity factor,” which is calculated by dividing the total annual energy produced at the plant by the amount of energy that would have been produced if the plant was operating at nameplate capacity for the entire year. Typical annual capacity factors range from 20- 45%.
The “capacity value” of a wind power plant generally refers to its ability to serve load at desired times. For example, a region that consistently receives wind during the peak load hours of its respective service area will have a high capacity value. Several methods are employed to calculate or approximate the capacity value of wind, although none is universally agreed upon as the industry standard [Milligan 2005, Holttinen 2004]. The capacity value of wind is highly influenced by the non-dispatchable nature of the resource, making it a difficult metric to calculate. Perhaps the most accepted method to quantify the capacity value is to compute the Effective Load Carrying Capability (ELCC). The ELCC is complex to compute, and requires multiple years of wind data to determine a reliable estimate. Previous studies have suggested that the capacity value of a wind resource can vary from 10% up to a maximum of its capacity factor, and is generally somewhere in between [Smith et al. 2007]. Storage options, such as pumped-hydro, can allow delivery of energy to occur at more desirable times; however, there will always be an associated loss in efficiency.
2.2 Variability of Wind
Wind is a meteorological phenomenon that is variable on all timescales. The output of a wind power plant can vary in real-time, in scales of minute-to-minute that match the regulation timeframe, and in scales of several minutes to hours that correspond to load following timeframes. Variability on scales of several hours ahead to the day-ahead can influence scheduling and unit commitment. Figure 2-2 shows the overlapping of wind variability with electrical system operations.
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Hydroelectric Industry’s Role in Integrating Wind Energy
Figure 2-2: Time frames of wind variability relative to electrical system operations. (Source: Piwko 2004)
Variations in wind power output are somewhat analogous to the variations in system load that are encountered on all timescales. At wind power penetration levels above 1% to 2% of peak system load, the overall system variability is affected by both load fluctuations and wind fluctuations. System planning concerns are eased if the variability from wind is absorbed into the inherent load variability. In other words, the impact of wind power variations is less significant when taken together with variations in the load; this is because some of the wind power variations occur in the same direction as the load variations (i.e., wind power increases as load increases), while others occur in the opposite direction. The overall result is an incremental increase in the variability of the system’s net load (load minus wind power) that is less than the sum of the variability of each of these constituents considered separately [Kirby 2000]. Despite this fact, the concept of incorporating variable generators is different from the traditional approach of using dispatchable generators to meet a variable load.
The variability of power output from a wind plant is driven by the variability of the wind speed at the plant. Wind speed can vary significantly within a single wind power plant, as shown in Figure 2-3. Therefore, the power curve for a single turbine cannot be used to extrapolate the output from an entire power plant, and it is difficult to predict an entire plant output based on coarse wind speed inputs alone. Short-term variability of wind output is also affected by the momentum of the turbines themselves. Second-to-second variations in wind velocity at an individual turbine will not necessarily lead to matching variations in wind power, as the inertia associated with very large wind turbines mitigate their responsiveness to such fluctuations.
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Figure 2-3: Variability of wind speeds within a single wind power plant. (Source: Wang 2005)
Wind variability is often quantified by ramping events, or changes in power output that occur over a specified amount of time. System planners and operators may find it useful to determine the spread of step changes in wind power output on the sub-hourly, hourly, and multi-hourly timescales. Ancillary service requirements necessary to accommodate the variability of wind may be better anticipated when the maximum size, average size, and standard deviation of these step changes are understood. It is not common for the output of an entire wind plant to change significantly on sub- hourly timescales, such as ten minutes (aside from rare but extreme wind events, during which turbines reach cut-out speeds and shut down to avoid mechanical damage). However, it can be common for the wind plant output to change by levels exceeding 50% of capacity on the hourly timeframe due to frontal passage and other meteorological events. Typical levels of 10-minute step changes in power output from a single wind plant are on the order of a small percentage of plant capacity. Wan from the National Renewable Energy Laboratory in the United States has published a series of reports describing the variability of wind power output on several time scales, which are excellent resources to consult for anyone requiring an in-depth understanding of these variations [Wan 2004, Wan 2005, Wan 2009].
In many instances, quantifiable trends exist in the diurnal, seasonal, and annual output of wind production. The annual capacity factor of a wind plant, as discussed previously, can be separated into a seasonal, monthly, or diurnal value by understanding the trends in wind output. There can be considerable variability in the capacity factor during different hours of the day or seasons of the year. Cross-correlations between these patterns and load patterns are of key interest to system planners and operators. An understanding of diurnal wind patterns can have implications in the unit commitment timeframe, and seasonal or annual patterns may affect long-term planning concerns.
Diurnal, or daily cycles in wind output are typically the result of patterns of heating and cooling of the earth. The consistency of these patterns is important to understand, and the correlation between diurnal wind and load trends provides the basis for quantifying the capacity value of wind. Figure 2-4 shows one example of how the diurnal patterns of wind and load were overlaid during a one-
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month period in New York. In this particular case, the wind output is not well correlated with the load; however, this correlation can varies considerably as one considers different wind power plant locations across the globe.
Figure 2-4: Example of diurnal patterns of load and wind for single month in New York. (Source: Piwko 2004)
Seasonal and annual trends in wind output are important to system planners and operators for long- term planning and resource acquisition. Many regions experience “windy” seasons, during which it may be appropriate to adjust fossil fuel purchases or schedule maintenance for generating units that may scale down production during these times. Alternately, periods of low wind may necessitate increased consumption of other resources. Figure 2-5 shows an example of annual correlations of wind and load in New York. Seasonal peaks do not coincide in this case. There is generally no causal relationship between wind output and load levels, but it is possible for seasonal correlations to exist due to climatological conditions such as wind events occurring during colder times of the year when load levels are high. Experiences from summer peaking regions have shown no or slightly negative seasonal correlation between wind production and load [Acker 2007a]. On the other hand, experiences from winter peaking regions have shown a positive correlation between wind power production and load [Matevosyan 2006].
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Figure 2-5: Example of annual wind capacity factor and annual peak load for single year in New York. (Source: Piwko 2004)
Seasonal trends in wind power output may be of particular interest in electrical systems that contain significant amounts of hydro power, in order to understand if the timing of the two resources is complementary. Investigations have been conducted to understand correlations between seasonal variability of wind output, load, and hydro availability [Denault 2009, PERI 2002, and Zavadil 2006]. As an example, Figure 2-6 demonstrates the alignment of hydro inflow and load levels (shown on left), as well as wind resources with load (shown on right) for Hydro-Québec [PERI 2002]. A system planner can infer from such information what value the wind power may provide in serving the load, and at which times significant wind integration impacts can be expected. When integrating wind power, it is important to understand how well the wind power will align with the load, the timing and magnitude of ancillary services that will be required, and how these items correspond to the availability of hydropower. More generally, an understanding of the seasonal patterns of load, wind power, and hydro availability are necessary for long-term planning of generation resources.
Figure 2-6: Correlation between seasonal load and hydro inflow (left), and correlation between historical load and wind resources (right) in Hydro-Québec. (Source: PERI 2002)
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2.3 Geographic Diversity
Many of the aforementioned characteristics of wind power are influenced by the geographic diversity of the wind plants. Load Serving Entities (LSEs) that seek to integrate large amounts of wind power may receive power from several wind power plants that are geographically dispersed, possibly being separated by hundreds of kilometres. The diurnal, seasonal, and annual trends of each of these wind sites may be different, which can lead to an overall “smoothing” effect to the wind component of the generation mix. Short-term variability may also be reduced. Figure 2-7 shows the correlation coefficients for various sizes of step changes in wind power production as a function of distance between wind power plants. Correlations for step changes are smaller for shorter time steps, suggesting overall short-term variability between multiple spatially diverse wind power plants to be minimal.
Figure 2-7: Correlation coefficient of wind power step changes vs. distance between wind power plants. (Source: Wan 2005)
2.4 Forecasting
Forecasting plays a major role in contemporary wind integration, particularly with respect to the day- ahead unit commitment process and the hour-ahead commitment and dispatch process. A number of private companies exist that provide state-of-the-art wind speed and wind power forecasts to wind power developers, transmission system operators and planners, and other stakeholders. Some balancing areas and Independent System Operators (ISOs), such as the Electric Reliability Council of Texas (ERCOT), also generate their own forecasts and provide them to scheduling entities [Wiser 2009]. The Mid-West ISO and New York ISO also implemented centralized forecasting procedures [Wiser 2009]. Wind power forecasts are not perfect, but they can be powerful tools for system planning and are necessary to reduce the uncertainty component of wind generation.
Wind speed forecasts are typically based upon either the output of Numerical Weather Prediction (NWP) models that approximate the physics-based fluid-dynamic equations that describe the air motions in the atmosphere, on statistical techniques, or a combination of the two. NWP methods
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Hydroelectric Industry’s Role in Integrating Wind Energy rely upon a set of initial and boundary conditions derived from atmospheric and ground-based measurements, and solve for properties such as the wind velocity, temperature, and pressure at the desired spatial (down to 1-km) and temporal resolutions (e.g. 10-minute). Wind turbine power curves, site-specific attributes, and a blend of statistical methods are then used to transition from wind speed to wind power forecast values. The focus of many forecasting efforts is to generate predictions of wind power output during horizons of interest to system planners (i.e., hour-ahead, several hours ahead, and day-ahead). These predictions often come as time series values in ten- minute or hourly increments, and sometimes include a confidence interval.
Forecasting is used by the majority of LSEs that incorporate a significant amount of wind power, and it has been shown to reduce the uncertainty component and integration costs associated with wind power [Piwko et al. 2004, Smith et al. 2007]. The quality of forecasts used may help to reduce part of the integration costs. Accurate forecasts can reduce the need for system operators to use peaking generators to fill gaps between production and load that may occur due to wind uncertainty. Forecasting errors are quantified by a variety of metrics, some of which are shown in Figure 2-8. The mean absolute error (MAE) and root mean square error (RMSE) are the most common metrics used. Forecasting errors tend to increase at larger forecast horizons (number of hours ahead of real- time). The mean bias is the average value of the forecast error at the given forecast horizon (i.e., a negative bias suggests that the wind power was under-predicted on average). Efforts are ongoing to improve forecast accuracy and advance implementation of wind power forecasts in the control room, including prediction of large wind ramping events.
Figure 2-8: Common forecast error metrics versus forecast horizon from an actual wind power plant data. (Source: Bielecki 2010)
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3.0 Power System Integration of Wind Energy: Review of Experiences
Wind integration efforts have been carried out globally on scales ranging from small to large wind penetration levels in a variety of power system structures. Common methodologies and areas of focus have evolved as a result of industry experience with wind integration studies and implementation. Typically, the impacts of wind are assessed in terms of overall integration cost, added levels of ancillary services for regulation and load following, and possible increases in reserve requirements (recall, this integration cost relates to the bottom section of the red bar shown in Figure 1-2). The variability and uncertainty of wind power must be accommodated without compromising system reliability.
Wind integration studies are the primary vehicle for understanding the impacts and costs. They are generally conducted prior to project development, often relying on simulated wind power data along with load data, and incorporate projected growth for the study period or project lifespan. Working commitment and dispatch algorithms are then used to simulate system operation (economically) with assumptions about market and fuel prices. Wind forecasts can be included to capture the uncertainty component of forecasting errors that will be faced during actual operations. This allows for reserve requirements and reliability concerns to be evaluated.
The purpose of this chapter is to describe the state of the art in wind integration, and review the relevant experiences. This chapter is organized into the following sections: Wind power penetration levels Wind Integration Costs and Challenges: Handling Variability and Uncertainty Special Concerns Pertaining to Wind and Hydro Integration Typical Impacts and Costs of Wind Integration Integrating Wind in Different Market Structures Recent Wind Integration Rate Cases Resources Related to Wind Integration
3.1 Wind Power Penetration Levels
The challenge facing wind integration studies is to assess the integration impacts by quantifying the difference between operating the bulk power system with a proposed level(s) of added wind power versus without wind power (or with only current or planned levels of wind power). The level of wind power in a power system is known as the wind power penetration level. The wind power penetration level may be defined by either energy (i.e., total electrical production coming from wind energy over the course of a year divided by the total electrical energy consumed in the associated balancing area over the same time period) or capacity (i.e., the installed nameplate capacity of wind power divided by the peak system demand). Either of these approaches to defining the wind penetration level may be applied to a specific area (local). For instance, the local average energy production coming from wind may be above 100% in a small balancing area within a renewable energy zone (REZ), in order for the system-wide (i.e., interconnection-wide) wind penetration level to reach a more modest level of 20% [Piwko et al. 2010]. Likewise, the wind penetration level during a specific period may be of interest, such as a day with high load and low wind production or low load and rapidly changing wind production.
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Hydroelectric Industry’s Role in Integrating Wind Energy
In 2008, the U.S. Department of Energy (DOE) published a major wind power report called 20% Wind Energy by 2030: Increasing Wind Energy’s Contribution to U.S. Electricity Supply [U.S. DOE 2008]. This comprehensive report detailed the feasibility of generating 20% of the U.S. electricity demand (e.g. 20% penetration by energy) with wind power by the year 2030. The study found that installed wind capacity would have to increase to about 300,000 megawatts (MW). The installed capacity in the U.S. at the end of 2009 was approximately 35,000 MW.4 The report concluded that significant changes would be needed in the American energy market, along with transmission and manufacturing upgrades. The projected impacts of 20% wind generation include: reductions on the order of 825 million metric tons of CO2 annually, 4 trillion gallons of water savings, increased energy security through a diversified energy portfolio, and domestic job creations. The DOE study found that cost increases for the 20% wind scenario would be as little as $0.06 cents (in 2006 U.S. dollars) per kilowatt-hour of total generation. Initial capital costs would be high, but long-term energy costs would be lower due to decreases in operation, maintenance, and fuel costs.
3.2 Wind Integration Costs and Challenges: Handling Variability and Uncertainty
Ideally, all of the challenges with integrating wind into the bulk power system are quantified in terms of a financial cost per unit of energy (e.g., $/MWh). Such costs are known as the wind integration cost, and a primary goal of most wind integration studies is in quantifying the wind integration cost associated with various sensitivity scenarios (e.g., wind power penetration level or generation mix). Other goals may be to describe system characteristics, transmission overlays, estimated emissions, reliability impacts, or spot market price impacts both with and without wind. Whatever the study’s focus, it is the unique characteristics of wind power that challenge system operators and drive the need for load serving entities (LSE) to understand wind integration issues. The wind integration cost, then, may also be defined as the cost associated with balancing the added variability and uncertainty of a system with added levels of wind energy.
Uncertainties in power system demand are based on the lack of accuracy in predicting load and wind power. Since demand patterns are not entirely deterministic, system operators already incorporate imperfect forecasts of demand as part of the capacity planning process and also for day-ahead scheduling decisions. Scheduling decisions will take into account planned maintenance, optimal operating capacities, and reserve requirements. Depending on the load net wind forecasts and the market rules, scheduling decisions may be updated as “real-time” operations approach. For example, an hourly energy trading market may allow energy transactions for the following day to proceed up to 5 AM local time, at which time a local (nodal) or zonal market clearing price is established. The 19-hour window, between 5 AM and the beginning of the next day, is known as the forecast closure window. However, at 11 PM, as more information pertaining to the demand forecast (load net wind) and unplanned events becomes available for the first hour of that next day, there may be an opportunity to update scheduling decisions and conduct spot market energy transactions for the next hour, depending on the specific system market rules. Even this hour-ahead load forecast will be imperfect. With a large addition of wind power, the uncertainty in the load net wind forecast can be significantly higher than the load forecast alone. Since the atmospheric measurements mentioned in Chapter 1 of this report are only updated twice daily, very short term wind forecasts typically have more uncertainty, as measured by the RMSE and other criteria, than load forecasts. When both of these forecasts are integrated in the control room, the errors associated with both forecasts may be offset. As an example, consider a negative wind forecast error of 100 MW (more wind was forecast
4 Refer to the Wind Powering America website: http://www.windpoweringamerica.gov
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than observed), which could be offset by an unexpected industrial customer load loss of 100 MW (e.g., a 100 MW smelting facility emergency closure). This example highlights a circumstance where the forecast uncertainty for wind and load is negatively correlated. A similar example could be constructed where the errors are positively correlated and combine. In general, however, wind and load forecast errors are not correlated (some will be additive, some offsetting, but most with no relationship). Since they are mostly uncorrelated, the contribution of the wind generation to the net load forecast error is determined by computing the square root of the sum of the squares (RSS) of the wind forecast error and load forecast error.
Even with perfect knowledge of future wind conditions, wind power signals contain significant variability that contributes to the variability inherent in the load. Again, the degree to which wind and load are correlated will determine how challenging it will be to provide ancillary services to balance the system. An example of a modeled wind resource that was found to be almost perfectly uncorrelated with load is shown in Table 3-1 from eastern Canada, where the standard deviations of hourly averages of net load were only slightly higher than the square root of the sums of squares of load and wind individually [NBSO-ERNB, 2007].
Table 3-1: Individual and aggregate variability of wind and load. (Source: NBSO-ERNB, 2007)
Power system variability occurs on all timescales. Every market will have different rules regarding closure before real-time operations begin; this is also true where markets do not exist and transactions are dominated by bi-lateral trades. Prior to this closure, scheduling decisions can still be made regarding commitment of units and import/export energy trades. In a wind integration study, transmission-constrained cost production models are used to determine the most economically efficient way to commit units and simultaneously respect operating and contingency reserve requirements for handling net load variability in real-time between closure periods. Subsequent to this closure, a system operator is locked into economically dispatching those previously committed generation units. In addition to economically dispatching these units, n-1 contingency reserve requirements must be met so that no bulk power component would be overloaded should the largest single generator or portion of the transmission system fail.
Operational impacts of wind integration are frequently assessed in terms of wind variability and uncertainty, and the majority of wind integration studies separate these impacts into timescales that correspond to electrical system operations. In the US, these time scales are commonly referred to as regulation, load following, and unit commitment. Regulation is the shortest of these time scales and refers to fluctuations in load occurring on scales of seconds up to several minutes. This short-term variability will generally be handled by automatic generation controls (AGC).
In Wang (2005), a year of simulated wind power data were incorporated for variability analysis. Figure 3-1 shows the 10-minute variability percentiles of the simulated wind power in terms of
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installed capacity, and quantifying wind variability on this timescale allows system operators to gauge the amount of increased ancillary services (if any) that will be needed for within-hour regulation and/or load following due to wind. In this particular case, 97.5% of all 10-minute changes in wind power output (both upward and downward) were less than 8% of installed capacity, with values as low as 4% for the highest installed capacities. The maximum 10-minute fluctuations for Scenarios A, B, C, and D were 32.3%, 22.6%, 14.4%, and 13.0% of nameplate capacity, respectively.
Figure 3-1: 10-minute variability percentiles for simulated wind power. Installed capacities for Scenarios A, B, C, and D were 254, 895, 1445, and 1994 MW, respectively. (Source: Wang 2005) Added levels of regulation due to wind power are often calculated as the capacity needed to cover greater than 99% of minute-to-minute wind power variations. Because these short-term variations of wind power are uncorrelated with those due to load, the combination of the short-term variations of both can be computed via the root sum of the squares [Acker 2007]. To determine the amount of required increased regulation, one takes the difference between the regulation required with and without the wind and multiplies it by a number ranging from three to five. This number is a safety margin that depends on which utility does the calculation, and is higher for more conservative utilities. An example calculation of the regulation required in a study is provided in Table 3-2. In this particular case, regulation amounts tend to increase (on a percentage of capacity basis) with greater wind penetration levels.
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Table 3-2: Increases in regulation requirements to account for three standard deviations (99+%) of additional variations due to wind. (Source: Zavadil 2006)
The effects of the variability of wind on the regulation timescale is generally less problematic than on longer-term timescales, at least when the aggregate output of a plant or several plants and the rotational inertia of several turbines is included [Wan 2005]. The load-following timescale of 10- minutes to hours is subject to more variability, especially when only the output from a few, spatially concentrated wind power plants is being integrated. Load following concerns include ramping events in net load or loads that must be accommodated by the generation mix on-line during any given hour. Figure 3-2 shows such hourly changes in load and net load for the control area in EnerNex (2004) with and without the wind component. Larger hourly changes in power production occurred when wind was included (refer to blue bars on right side of plot in Figure 3-2). This figure represents the additional ramp requirements for integrating 1500 MW of wind generation into a 10,000 MW (projected peak demand for 2010) control area [EnerNex 2004]. The increased need to accommodate larger ramps when wind was included demonstrates the need for greater load following capabilities, both in the upward and downward ramping directions.
Figure 3-2: Summer ramp requirements for cases with and without wind generation. (Source: EnerNex 2004)
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Hydroelectric Industry’s Role in Integrating Wind Energy
Finally, the unit commitment time frame lasts from several hours to days. Generating units will be scheduled based on expectations of diurnal load trends that may be somewhat consistent or variable (e.g. weekday vs. weekend). Wind power forecasts generally include day-ahead predictions that can aid in unit commitment concerns, especially when large weather fronts corresponding to periods of high wind or, conversely, no wind at all is expected.
As noted before, the wind’s relative variability will decrease as more wind turbines are installed on the system. This is especially true over the shortest time scales. For this reason, the “limit” to integrating wind into any power system remains a fuzzy debate (the limit is not technical, but what is economically practical). As more data and better methodologies become available, this “limit” has increased in parallel with the maximum wind power penetration levels studied [Holttinen 2008]. Of course, what is technically feasible is not necessarily the most economical. Therefore, integration studies typically limit policy recommendations to what is needed to make integrating various levels of wind power technically possible at the most reasonable cost, based on: changes to transmission planning, balancing area consolidation, and market structure rules [Piwko 2010, Corbus 2010].
As wind penetration levels increase, however, there will come a point where the resulting regulation and load following requirements will exceed existing system resources. At this point, it will become necessary to either “spill” wind, add new dispatchable generation, or add storage. Spilling wind involves shutting down some wind turbines during peak wind production. This will decrease the capacity factor of the wind power plant and lower its value. Building new dispatchable generators to provide additional regulation and load following services is another option. This would involve building additional flexible generating resources (e.g., gas turbines, hydro generators). Finally, adding additional storage would involve building new pump storage hydro plants, or some other new form of storage (e.g., compressed air energy storage, etc.), though these have yet to penetrate the electricity market. These plants would store energy during high wind periods, for use later when the wind is low.
The variability and uncertainty of the wind will be less of a challenge when integrating wind power in a system with wind turbines that are spatially well spread. Cross-correlations of wind forecast errors have been shown to decay exponentially with distance between sites, with the intensity of decay greater for longer forecast horizons [Focken 2002]. A similar exponential decay function describes the relationship between the number of wind turbines and aggregated average magnitude (absolute value) of hourly swings or change from the previous hour’s production. For example, the decay in magnitude and standard deviation of average hourly swing for an aggregated output as that output is spread across up to eight sites across eastern Canada is shown in Figure 3-3 [NBSO-ERNB 2007]. Geographic diversity benefits, such as a relatively less variable and more predictable output, can be expected when the development of wind power plants occurs across a large region, rather than in a concentrated fashion.
3.3 Special Concerns Pertaining to Wind and Hydro Integration
The degree to which wind and hydropower production complements one another has been investigated in a number of regions, with particular interest in future development or increased wind penetration levels. The fast-ramping capabilities of hydro have the ability to balance wind’s variability on the regulation and load following timeframes. Wind and hydro integration studies often focus on seasonal correlations between the two resources, which apply to unit commitment
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concerns. Loutan (2007) indicated that load-serving entities (LSEs) with access to hydro generation are able to integrate wind more easily. However, some hydro regulation capacity (especially downward) may be lost if hydro units are run at low levels to accommodate periods of high wind [Loutan 2007].
Figure 3-3: The decay of the variability of the wind as more sites are added to a region. (Source: NBSO-ERNB, 2007)
In 2003, the U.S. Department of Energy (DOE) created the Wind and Hydropower Technologies program, which began assessing the feasibility of using hydropower to accommodate the wind power on the electrical grid system. The U.S. DOE division known as the Wind and Water Power Program is currently tasked with supporting technological advancements and implementation of wind and hydropower technologies.5 The International Energy Agency (IEA) began “Task 24: Integration of Wind and Hydropower Systems” in 2004 to evaluate global efforts pertaining to this subject. The Task 24 Final Report, due out in 2010, will provide a summary of several international case studies involving the wind/hydro integration, including a matrix tool used to characterize the study techniques and results of the case studies.6
EnerNex Corporation completed a wind integration study in 2007 for Avista Corporation’s hydro- dominated control area of the Northwestern U.S. to estimate regulation and load following requirements. Three scenarios were considered with different ways of utilizing hydro resources, and each wind penetration scenario was conducted under conditions of low, average, and high hydro availability. Wind installments were taken to occur solely in the Columbia River Basin, a 50/50 mix between the Columbia Basin and Montana, and two cases of further diversified geographical locations. Table 3-3 summarizes the incremental reserve requirement results for four penetration
5 Refer to U.S. DOE Wind and Water Power Program website: http://www1.eere.energy.gov/windandhydro/index.html 6 Refer to IEA Task 24 website: http://www.ieawind.org/Annex_XXIV.shtml
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Hydroelectric Industry’s Role in Integrating Wind Energy and wind diversification scenarios. The relative amount of reserve requirements increases with wind capacity, however, the growth is not linear. These types of results are commonly used to determine wind integration impacts.
Table 3-3: Incremental reserve requirements for various scenarios of the Avista Corporation wind integration study. (Source: EnerNex 2007)
The availability of the hydro to provide regulation and load following to accommodate wind will depend on a variety of factors, and many integration studies seek to establish seasonal or annual correlations between wind and hydro trends that will affect system planning and unit commitment. In 2006, a study was completed for the Western Area Power Authority (WAPA) in the U.S. to determine the effects of integrating five levels of wind penetration. Comparisons were made between hydro runoff in the Missouri River Valley Basin and wind resources from North and South Dakota. A small inverse correlation was found between the two resources, indicating the possibility of annual or seasonal synergy. A two-year running average of wind and hydro departures from their mean annual values is shown in Figure 3-4. The departure from mean values for wind and hydro were of opposite sign about 60% of the time.
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Figure 3-4: Two-year running average of annual departure of wind speed and hydro runoff from their respective mean annual values. (Source: Zavadil 2006) A 2009 study by Denault et al. to assess the how well wind and hydropower work together in serving load in Québec used probabilistic methods to perform risk analysis of resource adequacy with aggregated wind and hydro production versus hydro alone. Risk assessment was based on the probability of production deficits occurring from a lack of hydro and/or wind inflows. The study found that the risk decreased when wind and hydro are utilized together for penetration levels up to 30%.
3.4 Typical Impacts and Costs of Wind Integration
The typical impacts and costs of wind integration are generally reported as ancillary services costs attributed to the addition of wind to current system operations. Studies often report incremental integration costs at various levels of wind penetration. Table 3-4 gives a summary of integration impacts from several U.S. studies [Wiser 2009].
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Table 3-4: Impacts of wind integration from several recent U.S. case studies. (Source: Wiser 2009)
The impacts of wind integration are also reported in terms of the actual amount of ancillary services required, often categorized as operating reserve requirements. Two good examples of this are from the recent wind integration studies performed for Minnesota and New York. Table 3-5 shows the amount of reserve required for various wind penetration levels for the Minnesota Balancing Authority [EnerNex 2006]. Another good example was provided in the two-part wind integration study conducted by GE for the New York State Energy Research and Development Authority (NYSERDA) in 2004-2005 [Piwko 2004, Piwko 2005] to investigate operational impacts of generating 10% of system peak load from wind power in 2020. This report is often viewed as the most comprehensive of its kind [Loutan 2007, Smith 2007], and many other studies have adopted similar procedures when designing wind integration studies. The study found it feasible to integrate 10% wind penetration without any major changes to contemporary system operations or existing transmission.
Table 3-5: Categorized estimations of operating reserve requirements for the Minnesota Balancing Authority with estimated load in 2020. (Source: EnerNex 2006)
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Table 3-6: Summary of some results from the Phase 2 of the NYSERDA study. Note: UCAP denotes unforced capacity or probability of being available when called upon (calculated as installed capacity minus forced outage rate). (Source: Piwko 2005)
The capacity value of the wind was calculated to be about 10% of the installed capacity by using loss of load probability (LOLP) methods for on-shore wind resources. A summary of some key results from Phase 2 of this study is shown in Table 3-6. These results show the estimated impacts of 10% wind penetration for various timeframes of interest to system operations. Increases in regulation and load following levels are given, as well as estimated increases in planning errors that will affect unit commitment.
3.5 Integrating Wind in Different Market Structures
In the U.S., deregulation was enacted to open up the energy markets to competition and to facilitate a more transparent market with the three natural monopolies of the power system (distribution, transmission, and generation) separated. Transmission owners became obligated to consider an interconnection and transmission service request from an independent power producer (IPP), with no preferential treatment above a similar request from any other provider, including the transmission owning company. Into this open and competitive system, IPPs, such as wind generators, have flourished. If not for these market changes, advances in wind technology may not have been utilized by vertically integrated utilities. A brief review of how the U.S. grid has partially
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transformed from a regulated monopoly to a free market, structured within an open-access tariff system with interconnection requests for wind generators “clogging” the queue7, follows. It is worth noting that while extensive portions of the grid have reorganized into market-based areas, many still function as vertically integrated utilities.
Even before deregulation, vertically integrated utilities would voluntarily pool their resources, when a common good was realized. For example, the Southwest Power Pool began in 1941 when a WWII aluminum factory required more power than the entire state of Arkansas could generate.8 Lacking time to build generation facilities, the now Regional Transmission Organization (RTO) was born as neighbouring utilities kept the plant running 24/7 for the remainder of WWII. Since deregulation, loose affiliations of vertically integrated utilities have evolved into independent system operators (ISOs) and RTOs. These entities have facilitated (sub-hourly) spot markets, futures markets, centralized scheduling, centralized dispatch, and centralized forecasting operations. Another trend is from zonal markets, where energy prices are cleared across broad zones, to nodal markets, where energy prices may be specific to a bus. Not all such innovations have been implemented by all ISOs and RTOs; however, the trends have moved these LSEs towards more efficient, liquid markets whose costs and benefits have been vetted to benefit the majority of market participants, including wind power producers. These LSEs are mandated to plan and evolve in a manner which facilitates the realization of member states’ renewable portfolio standards or goals.
Other utilities, especially in the West, remain outside the control of ISOs or RTOs. Coordination between such utilities is limited, and they are largely self-reliant to serve load through internal generation sources and occasional bi-lateral contracts with neighbouring utilities. In such environments, wind integration may be more of a challenge.
The variability and uncertainty of wind may be best accommodated by market structures with strong hour-ahead and day-ahead scheduling. Ideally, sub-hourly markets will become more commonplace and will prevent the need for unnecessary reserves. Wind forecasting becomes more accurate when closer to real-time, and the ability of wind facilities to update schedules in the near-term can decrease regulation and load-following impacts. Although some power systems impose financial penalties for conventional generators that do not deliver as scheduled, such penalties for wind facilities may be prohibitive to development. At the same time, system operators can have the option to curtail wind to prevent over-generation or to accommodate for scheduling errors. Recently, the New York ISO obtained approval from the Federal Energy Regulatory Commission (FERC) to curtail wind power plants for economic purposes, which requires them to submit bids as dispatchable generators [Wiser 2009].
Cooperation by neighbouring balancing authorities and dynamic scheduling may mitigate some of the market challenges associated with wind integration. Reserve sharing and Area Control Error (ACE) diversity exchange practices can reduce overall ancillary service usage. This may be especially true in systems with hydro, whereby a set amount of hydro in one balancing area could be used to integrate larger amounts of wind from nearby areas. The Midwest ISO has already taken such steps by becoming the principle balancing authority for a large region in the Midwestern U.S. [Wiser 2009].
7 Over 300GW of interconnection requests from wind generators are currently listed through the Open-Access Same-time Information System (OASIS) in the US. 8 Accessed March 2010 at http://www.spp.org/publications/Intro_to_SPP_Presentation.pdf
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3.6 Recent Wind Integration Rate Cases
Some of the challenges associated with determining the wind integration costs are difficult to pinpoint as the methodology for objectively establishing a unit cost attributable to wind energy is a subject of debate. Although attempting to establish a fair policy for attributing each player’s responsibility in a complex, interconnected power system whose electrons follow the rules of physics rather than market rules may seem academic, recent rate cases highlight the challenges as wind integration cost decisions become established in tariffs and regulatory rulings. For example, cost allocation and recovery decisions are being established now in the Mid-West Independent System Operator (MISO) and Southwest Power Pool (SPP) regions. The outcomes will establish how transmission expansion costs will be recovered as wind power plant interconnection requests have dominated the interconnection queue process following FERC Order 2003.
Recent wind integration rate cases offer more proof of the importance of these issues. Bonneville Power Administration (BPA) initially proposed charging wind generators over $11/MWh to recover the costs associated with integrating wind in the BPA system. BPA argued that it should not be required to bear these costs for energy that is balanced within its system since the majority of this energy is exported out of its system. The wind industry argued that this would establish a precedent that would deter new wind installations within BPA and that BPA was unfairly including items that had not been established as wind integration costs. Eighty percent of BPA’s initial price proposal of $11/MWh consisted of “embedded costs” and “opportunity costs”. The 2010 wind integration rate, established after a couple of years of stakeholder discussions, has been established at about half of the initial proposed rate. BPA has promised to examine the rate issue again as wind integration study methodologies evolve.
A more recent wind integration rate case is evolving in Wyoming, where Rocky Mountain Power and the Interwest Energy Alliance, a trade group representing renewable energy producers, are preparing to face off in hearings before the Wyoming Public Utility Commission, scheduled for April, 2010.9 Interwest is challenging the details of the methodology used to ascertain wind integration costs in the wide range of $9.96-$11.85/MWh. As Interwest points to a long list of studies that found much lower integration costs, the ramifications of overestimating wind integration costs become a risky, litigious venture. Clearly, wind integration has transformed from an obscure branch of academia to one that will have lasting legal and financial implications for all energy market participants and utility customers.
3.7 Resources Related to Wind Integration
A number of organizations exist that are on the cutting edge of global wind integration efforts. Hydro utilities or producers serious about wind power integration can find valuable information, learn about industry experience, and collaborate with colleagues dealing with the same issues by consulting one or some of these organizations. Those organizations shown in bold below are of most relevance:
Asociación Empresarial Eólica (aee) – Spanish Wind Energy Association http://www.aeeolica.es/
9 Accessed March 2010 at http://www.interwest.org/documents/documents/2009-08-07_Interwest_Comments_RMP_IRP.pdf
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American Wind Energy Association (AWEA) http://www.awea.org/ Canadian Wind Energy Association (CanWEA) http://www.canwea.ca/ European Wind Energy Association (EWEA) http://www.ewea.org/ Global Wind Energy Council (GWEC) http://www.gwec.net/ Integration of Variable Generation Task Force (IVGTF) http://www.nerc.com/filez/ivgtf.html International Council on Large Electric Systems (CIGRE) http://www.cigre.org/ International Energy Agency (IEA) http://www.iea.org/ Irish Wind Energy Association (IWEA) http://www.iwea.com/ National Renewable Energy Laboratory National Wind Technology Center (NREL-NWTC) http://www.nrel.gov/wind/nwtc.html National Wind Coordinating Collaborative (NWCC) http://www.nationalwind.org/ U.S. Department of Energy’s Wind Powering America program http://www.windpoweringamerica.gov/ Utility Wind Integration Group (UWIG) http://www.uwig.org/
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4.0 Hydropower: Capabilities, Limitations, and the Role of Hydroelectric Industries in Wind Integration
One of the foremost questions that need to be addressed in wind and hydropower integration is whether hydropower systems imposed with current generation limitations can handle the system balancing impacts due to the variability and uncertainty of wind power. A major concern that may arise from the hydro system’s point of view involves the change in operations and costs that ensue from wind integration. Ideally, hydropower would be able to provide a short- to medium-term buffer due to the wind power’s limitations in predictability without interfering with the ability to meet other hydro system demands that ultimately conflict with hydropower production. Indeed, for hydro utilities to partake in wind integration, the various issues of relevance to their hydropower facilities need to be identified and addressed. However, even within the current constraints and regulations imposed on hydro systems, hydropower remains one of the top balancing resources with a clean, inexpensive, and responsive generation resource capable of managing wind integration issues.
This chapter describes prominent characteristics of hydropower generation that are significant to wind integration, including the restrictions that may be imposed on a hydro facility. The ability of hydropower to provide ancillary services and reserves is highly dependent on the type and capacity of the plant, storage capability, required priority functions, flexibility of operation, and level of coordination between plants that lie on the same river system. Selected case studies will provide further insight into the feasibility, functionality, and variety of different hydro system configurations.
4.1 Physical Characteristics of Hydropower
This section addresses the physical characteristics of hydropower facilities pertaining to hydro generation and the availability to address the potential use in ancillary and system balancing services.
4.1.1 Generator Characteristics There are currently three main types of hydropower generators that are commonly used in hydropower facilities, namely: the Francis, Pelton, and Kaplan turbine generators, each having the capability of achieving efficiencies in the 80-90% range. The available capacity or available unit power output, P, is directly related to the difference in height between the water behind the dam and the turbine:
P = η Q h
Where η is the efficiency of the hydro turbine, is the specific weight of the water, Q is the flow rate of the water, and h is the height of the water level above the turbine. For any given hydro facility, the operating and hydrological conditions can vary substantially; therefore, turbines will be selected based on their performance characteristics and specific applications.
Pelton turbines are known as impulse turbines and are selected for high head and low flow rate applications. High pressure flow is directed through a nozzle, thus increasing the flow velocity, which is then focused onto distinctively designed cups or buckets. These cups or buckets, once impacted, redirect the flow, resulting in a change in momentum causing the rotor upon which the bucket is attached to spin. Other commonly used turbines include the Kaplan and Francis turbines.
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Francis turbines are considered more versatile since they operate efficiently over a large range of flow rates and at medium to high head levels. Kaplan turbines are used principally in low head applications. Kaplan and Francis turbines are known as reaction turbines, and work on the principal of expanding high-pressure flow across turbine blades causing a low-pressure region as the flow is accelerated across the blade, creating lift and causing the rotor to spin [Dixon 1998]. One pitfall to this design is that under certain operational conditions, the local low-pressure region can fall below the vapour pressure of water, causing vapour bubbles to form. This process is known as cavitation and can cause damage to the runners. Additionally, under certain operating conditions, a vortex may form in the draft tube causing undesired vibrations, thus resulting in damage to the physical structure of the turbine. This is referred as the “rough zone”. Operating turbines under these conditions (which occur while running a unit at partial load) can cause adverse effects on the blades and structure, reducing overall efficiency (20-50%) and potentially leading to blade or rotor failure. Having the capability of using multiple and different generator units at different output levels on a large hydro system presents some operational flexibility and operation in the “rough zone” or during cavitation can be mitigated.
In terms of wind integration, more units ramping due to net load variations could cause the overall hydro plant efficiency to be reduced. This is attributed to increased variations in unit loading, thereby causing units to operate with a lower average efficiency. For example, Figure 4-1 shows typical efficiency curves for a multiple-unit hydropower plant (note, in this figure, HG is defined as the gross head, which is the vertical distance between the top of the penstock to the point where the water is discharged from the turbine). Due to the quadratic nature of turbine efficiency curves, the curves tend to drop off more sharply than they rise. Thus, all else being equal, more movement of the units would cause the average production efficiency to decrease. Additionally, if a system operator employs hydro resources for the benefit of system balancing, a plant operator may be required to set hydro units at a lower overall efficiency point than if being run to maximize production or profits. This effect depends upon how close to peak efficiency the units are normally operated, and whether it is possible for the units to be loaded more efficiently. Intuitively, this possibility of decreased unit efficiency and increased unit cycling will lead to higher operating costs. The magnitude and extent of these increased operational costs can only be correctly determined using a production cost simulation of the power system that includes a detailed model of the hydropower system, and a good understanding of how the frequency and magnitude of unit cycling corresponds to maintenance costs. Söder (1994) conducted such a study in Sweden to investigate the effect on unit efficiency of using the hydropower plants along one river to supply the increased balancing requirements in net load caused by small amounts of wind energy. This particular study showed very little impact on unit efficiency. Furthermore, the Bureau of Reclamation has proposed a general methodology to determine production costs related to ancillary services (regulation, spinning, non-spinning, and replacement reserves, voltage support, and black start) of hydro generation involving multiple units with multiple plants and varying operating parameters [Bauer 1999].
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Figure 4-1: Typical efficiency curves for multiple-unit hydropower plants. (Source: Oak Ridge National Laboratory) 4.1.2 Run-of-the-River Hydro Run-of-the-river hydropower facilities are considered to have very low or no storage capabilities, thus resulting in low head applications. These facilities utilize the flow of water as it comes down the river or canal to generate power. More often, some level of storage is implemented (hours to weeks) giving these hydropower plants some flexibility. Often, many hydro plants are built in succession along a river downstream from a large, high storage facility. Some of these dams may be utilized for re-regulating flow discharge from the large facilities, thereby helping to manage flow downstream. Dams that re-regulate flow as a priority often have relatively low flexibility and provide minimal ancillary services. Hydro facilities with small reservoirs and who are not tasked with flow re- regulation may support adequate potential for regulation, reserves, load following, and energy storage purposes on a time frame of several hours to days.
4.1.3 Hydro with Storage An essential quality inherent in hydropower equipped with storage is the ability to use the stored water when there is a demand for energy. Historical hydro use has been based on the optimization of generation and avoidance of spill, resulting in many facilities with very large storage capabilities that have parallel objectives of flood control and regulated water releases. Hydro facilities with large storage capacities have the highest potential as a system balancing resource by providing quick start ancillary services and the ability to shift water and energy releases for days to several months. These qualities are highly desired in terms of system integration with wind power. For example, during windy time periods, it may be possible to decrease overall hydro flow and accumulate this resource for later use. In mountainous areas with high precipitation levels, hydro facilities may be built with smaller storage capabilities and lower flows, but have high hydrostatic heads. A prime example is the use of snowmelt as a primary storage mechanism on the shorter time scale.
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4.1.4 Pumped Storage Hydro Pumped storage hydro-electricity (PSH) relies on the principle of producing electricity (generation mode) during high-demand periods through the release of water from an upper reservoir via pipes connected to turbines located at the discharge to a lower reservoir. During low-demand periods, water is pumped from the lower reservoir by motoring the generators (pumping mode), to replenish the water level in the upper reservoir. This process is known as “load factoring,” and roundtrip electrical energy efficiencies can reach levels in the range of 70% to 80% [Tester 2005]. Profitable economic use of PSH relies on low pumping prices during off-peak hours and a high value of generation during peak demand hours. As an example to illustrate this point, if a PSH plant with 70% overall efficiency is assumed for a pumped hydro facility, the minimum price differential between the peak and off-peak time periods required to break even is 1.43; that is, on-peak market prices would have to be 43% higher than off-peak pumping prices. As the overall efficiency increases, this percentage is reduced (e.g. only 17% higher for an 85% efficiency PSH plant).
The greatest value of PSH is typically derived from its ability to load factor, taking advantage of high on-peak power prices and low off-peak prices. As wind power is incorporated at large penetration levels into the utility system, it has the effect of lowering the spot price, since it is always a “price taker.” As a consequence, the value of PSH in load factoring may increase or decrease, depending on the timing of the wind power (when it is generated) and its effect on spot prices. For the purpose of load factoring, the value of PSH is essentially independent of wind energy, except in the case where the wind power increases the need for peak power (for example, depending on how generation fleets are expanded over the next several years as the wind penetration increases), and its influence on spot prices.
Beyond load factoring, the generators used in PSH are flexible units and can be used to supply the ancillary services required due to the variability and uncertainty of wind power. When the value of providing ancillary services exceeds that derived from load factoring, it could be beneficial to devote PSH toward providing these services in lieu of, or in combination with, load factoring. Results from recent wind integration studies have demonstrated that the economic opportunity arising from providing ancillary services required by wind integration alone are not sufficient to justify new PSH (in the range of $4,000/kW). In a study conducted in Colorado, it was found that at a 10% wind energy penetration level, benefits from PSH were minimal [Zavadil 2006]. In a recently conducted Western Wind and Solar Integration Study, results showed the benefits to system balancing provided by PSH do not justify the costs of building new PSH until wind penetration levels exceed at least 30% [Piwko 2010]. However, new PSH could be feasible if the value proposition is conceived with provision of ancillary services being just one component in its economic justification. It is also likely that at higher penetration levels of wind power (greater than 20% or 30%), storage will become a more valuable system resource, and thus more PSH will be justified.
4.1.5 Availability of Hydro From a mechanical/electrical point of view, hydropower generators are among the most reliable in the electric power industry. Thus, hydropower availability is more dependent upon a multitude of other factors, the most prominent being the annual precipitation. As an example, Figure 4-2 shows the annual flow volume measured in the Colorado River in the Southwestern United States. As can be seen, the variations in flow from year-to-year can be quite considerable. This type of variation directly impacts the energy production from hydro power facilities, though the extent of the impact
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is lessened on river systems with significant reservoir storage. Because of this potential for dramatic variations in river flows, and because multi-annual droughts and wet periods do occur, hydro systems typically engage in long-term coordinated planning with the intent to mitigate adverse impacts and to optimize the use of the hydro resource under all conditions. Beyond precipitation, hydropower units are often constrained in non-apparent and distinctive ways based on many underlying, project-specific factors such as biological, contractual, environmental or legal requirements. These constraints, along with planned maintenance outages, tend to limit the flexibility and availability of hydro generators at certain times. Careful consideration must be given to the availability of hydropower due to these factors. With respect to wind integration, the factors limiting hydro generation will also limit their ability to integrate wind. However, given that wind integration is addressed in the context of the variability and uncertainty of the entire system net load and not in isolation, existing planning processes should be capable of adequately addressing these concerns.
Figure 4-2: Historical record of Colorado River flows. (Source: USGS 2004)
4.1.5.1 Capacity Factor
Generally, hydropower facilities have relatively low average capacity factors, on the order of 20% to 45%. The actual capacity factor at a given plant may vary substantially from year-to-year due to changes in annual precipitation and reservoir levels. These low capacity factors can be attributed to the fact that hydro power plants are typically sized to handle near maximum river flow, which only occurs for a portion of the year, and therefore have more capacity available than water to run through the system. Table 4-1 lists the United States Bureau of Reclamation’s (Reclamation) historical hydro data for the past ten years, showing variation in the average capacity factor across 58 hydro power plants. Reclamation is the second largest producer of hydroelectric power in the western United States.10
10 Accessed March 2010 at http://www.usbr.gov/main/about/
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Table 4-1: Historical hydro plant capacity factors for 58 hydropower plants operated by the USBR. (Source: United States Bureau of Reclamation) All Installed Gen Spilled Fiscal Hydro Capacity FY Net Water Water Capacity Year Sites (MW) (GWh) (mAF) (mAF) Factor 2000 58 14745 47283 176.2 9.67 36.8 2001 58 14751 34424 131.6 2.85 26.8 2002 58 14758 39548 148.3 4.19 30.8 2003 58 14786 37999 144.1 5.17 29.6 2004 58 14805 37530 151.5 6.51 29.1 2005 58 14834 37530 144.0 5.49 29.4 2006 58 14842 44437 168.8 17.81 34.4 2007 58 14859 40529 153.8 4.01 31.4 2008 58 14876 41016 147.5 7.13 34.6 2009 58 14876 39620 135.4 9.08 30.6
From a system operator’s perspective, hydro generation can be considered as a capacity-rich and energy-poor resource. Hydropower does have great value when it comes to balancing the system net load; normal units have the capability to be at full output within 10 to 15 minutes for non-spinning reserves, and less than a second for spinning reserves. It is very important for planners and operators to have and rely on this generation capacity during peak time periods. As more wind power is introduced into the power system, the value of the reserves provided by hydropower could well increase.
4.1.5.2 Diurnal, Seasonal, and Annual Trends
With the exception of some run-of-the-river systems or hydro plants that are highly regulated (e.g., due to environmental regulations), power operations at hydro plants are not held at a consistent level throughout the day. Generation levels depend upon several factors such as the load, hydrological conditions, and other system priorities. In the daily time frame, generation is often a function of system demand, producing most of the power during on-peak hours where the most economic value is gained. For example, Figure 4-3 illustrates monthly averaged diurnal generation for Hoover Dam in the USA, with many months exhibiting both morning and afternoon peak loads and low generation during the nights.
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Diurnal Plots -- October 2005 - December 2006 1200 Oct05 Nov05 1100 Dec05 Jan06 Feb06 1000 Mar06 Apr06 900 May06 Jun06 800 Jul06 Aug06 Sept06 700 Oct06 Nov06 600 Dec06
500
Average Daily Generation(MW) Daily Average 400
300
200
100
2 4 6 8 10 12 14 16 18 20 22 24 Hour
Figure 4-3: Diurnal generation distributions by month. (Source: Pete 2010)
The variations in these diurnal patterns can be attributed to seasonal trends. For example, in the arid regions of the Southwest, seasonal and annual trends can be observed based on factors such as high demand for power during the summer months due to agricultural and cooling load demands coincident with high irrigation water deliveries. An example of a seasonal and annual trend can be observed in Figure 4-4, where the daily average generation at the Glen Canyon Power Plant has been plotted for a 15-month period. Circled are highlighted seasonal variations in generation. Within each season are several smaller weekly “bumps” that show higher generation during the week and lower on the weekends. In terms of wind-hydro integration, this adds another level of complexity in understanding the correspondence between the net load (wind and system load patterns) and the availability of hydro generation. For example, in the state of Arizona, the windy season resides in spring months corresponding with relatively low system load demands. During high summer load months, the wind resource becomes diminutive. Thus, the greatest need for system balancing of net load at high wind penetration levels will be during the spring months when the hydro power production may be low, or when units are traditionally out for maintenance. This could potentially increase the value of the ancillary services and reserves at the regional hydro facilities during these times.
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Figure 4-4: Daily averaged generation for Glen Canyon power plant. (Source: Pete 2010)
4.1.6 Interconnected River Systems River systems may contain multiple hydropower plants, and since the water released from an upstream plant will eventually pass through all downstream plants, their operations are interconnected. On any single river system, several factors will influence the interaction and operation of sequential hydro power plants. One method of optimizing hydro system operation is to build a large reservoir storage, high-head, upstream hydropower plant followed by smaller, run-of- the-river type facilities. This generally allows the most flexible operation of the system, especially if operation of the dams is coordinated by a single owner/operator. Even if the system does not have a single owner/operator, the system can be run in an optimized, coordinated fashion if the various owners agree to do so. A good and perhaps unique example of this type of coordination is Mid- Columbia Hourly Coordination Agreement,11 which seeks to optimize the hydropower production out of the seven dams located on the Columbia River in central Washington, USA, beginning with the very large Grand Coulee dam and extending downstream for six run-of-the-river type dams. An example of a river system with multiple facilities and a single owner/operator is the Missouri River with six large dams controlled by the U.S. Army Corps of Engineers [USACE 2006]. Normally, large public utilities or governments finance hydropower projects due to long payback periods, use of public lands, and the required capital costs.
Hydropower facilities may also be owned, operated, and regulated by several organizations, which is often the case. In this sense, the river system can no longer be operated as a “single unit” from a single operator’s point of view. Without consideration and coordination between other facilities, one
11 Grant County Public Utility District, The Electric Flyer, Vol. 18, Issue 3, March 2009. Accessed March 2010 at http://www.gcpud.org/aboutus/news/publications/electricflyer/2009/mar09.pdf
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plant’s operation could possibly force downstream hydro facilities to run in a sub-optimal manner (deplete reservoirs, cause spilling without generation, changing water schedules, etc.). Additional complexities and restrictions due to water availability and priority functions can further constrain the system flexibility. Such is the case of the Columbia River system with over forty hydro facilities, running through two countries and four states, and owned and operated by numerous organizations. Several higher priority functions can also limit generation during certain months of the year and require cooperation among the hydro plants along a river. An example of an environmental priority is the survival of Salmon on the Columbia River. Fulfilling the obligations of this priority requires cooperation among the various facilities’ operators for optimization on the system [Acker 2006].
Unlike thermal power systems, where fuel is available for use whenever it is required, hydro power must be utilized within a certain time frame. For power plants that are part of very large dams and reservoirs, this time frame can extend to several months. However, for smaller power plants with only modest reservoir storage, there is limited flexibility as to when the water must run through the generators, as dams can overfill and spill water or be depleted of their water. This is especially true on interconnected river systems with many small storage hydro power plants. Given this situation, hydro power facilities that participate in wind integration need to understand the flexibility and reserves required to deal with changes in the variability and uncertainty of net load, in order to understand how best to participate in addressing this need.
4.2 Multi-purpose Hydropower
Hydropower plays a very important role in balancing load with generation, through provision of low-cost electricity, the ability to follow load variations, and to provide reserves. However, hydro systems typically serve multiple purposes and are often bound with environmental and regulatory issues that constrain their use in providing system balancing. These multiple purposes are typically the motivating factors in planning, building, and operating hydro facilities, and thus define the priority functions of the facility. The following section describes several of the most important hydro system priorities, how they define flow and power constraints, and how long-term planning is used to forecast capacity and energy production.
4.2.1 Priority Functions Construction of a dam and hydropower facility is motivated by, and results in, a number of benefits to society, often serving regional growth. These benefits translate into multiple priority functions of the hydro facility, and consequently, operational parameters that define power plant flexibility. The most common of these higher priority functions are listed below:
Flood Control Environmental, Wildlife, and Fishery Considerations Agriculture/Urban Water Demands Navigation Purposes Recreational Purposes Power Generation
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How these functions are prioritized varies from country-to-country and by region and river systems within countries. The second priority listed (i.e., environmentally related considerations) was likely not a priority at the time of planning and construction of many facilities, but later became one as the impacts on wildlife of the various hydro impoundments or hydropower operations became understood. With respect to the United States, the functions listed above are in a typical order of priority, with hydropower generation being last. In some countries, such as Canada or in the Nordic countries, hydropower operations may be one of the highest, or the highest, priority of a dam.
4.2.2 Flow and Power Constraints It can be said that “authority, priority, and markets” drive scheduling of power production in optimized hydropower systems.12 Authority is generally assigned during conception, planning, and approval of a hydro facility, along with its priority activities and intended benefits. The priority functions of a hydro facility then dictate the water operations at a dam and the conditions under which power generation can occur. From a power production point of view, the priority activities essentially define the flow and power constraints within the given hydrological conditions. For example, if irrigation water deliveries are a top priority in defining water releases from a dam, they will also define the capacity and energy available.
Of the priority functions, environmental factors can drastically affect hydro operation, constraining power operations to a fraction of their intrinsic flexibility. Ironically, many states in the U.S. with the highest renewable mandates for electrical power often have highly regulated hydro resources due to environmental factors (e.g. hydropower in the California systems). With regards to wind integration, the flexibility and reserves provided by hydro generation are of the most value. Thus, in order to facilitate wind integration and derive any of the financial benefits thereof, it is important to understand both the flexibility available at any given hydro power plant, or system of hydro plants, and to understand the magnitude and timing of the hydro resource that is required by the wind integration. As an example, a project conducted for the Grant County Public Utility District, No. 2, in Washington State, USA, studied the potential impact of wind integration on environmental flow constraints (fish protection flows from Priest Rapids Dam) and power generation constraints (not exceeding a maximum generation level for reliability purposes). Results from this project demonstrated that at low (2%) to modest (18%) levels of wind penetration, impacts on flow and reliability requirements will occur. The report also suggests that these impacts occur primarily at certain times during the year when hydro flexibility is constrained, and that they are likely manageable [Acker 2007b].
Hydro production is naturally dependent on hydrological conditions, which effectively show up as flow constraints at certain times. For example, extended wet spells can cause hydro power plants to run near or at capacity for long periods, limiting or even eliminating their flexibility. Prolonged periods of drought will also inevitably reduce available capacity and flexibility of the system. Consider the southwest region of the U.S., where the natural flow of the Colorado River is currently experiencing its lowest ten-year average over the last one hundred year period, and has consequently de-rated the available capacity during peak demand hours at many hydro facilities by nearly 20%.13 The generation at any hydro power plant is dependent upon the flow rate and the head height. To the extent that the head height decreases, so does the available generating capacity and the potential
12 Brennan Smith, Oak Ridge National Laboratory, USA. 13 Source: The Colorado River Reservoirs Annual Operating Plan for 2010 dated January 5, 2010.
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to provide reserves. As an example, Figure 4-5 shows the available generation capacity during peak system demand (the X’s) at Glen Canyon Dam over the past several years, along with the elevation of the water behind the dam. As can be seen, a drop in elevation of 100 ft can reduce overall capacity by nearly 300 MW, as shown by the historical Lake Powell elevations and power plant production levels. Similar conditions and impacts are affecting Hoover Dam and Lake Mead downstream of Lake Powell and Glen Canyon Dam.
To summarize, flow and power constraints due to priority functions of a dam define the generation flexibility of a hydro power plant. Within this flexibility, hydro power owners and operators will typically maximize the economic benefit of the resource. Provision of ancillary services and reserves for system balancing represents an economic opportunity. However, in order to capitalize on this opportunity, it is important to understand both the available flexibility and the magnitude and timing of the hydro resource that is required to facilitate wind integration. This is naturally dependent upon the hydro project, balancing area generation resources and load, and the variability and uncertainty of the wind power. When considering the potential for wind integration, one must consider the concerns stemming from the interactions between priority functions, various organizations and stakeholders that establish authority, and diverse economic environments that may ultimately limit the overall flexibility of the hydro system. Developing a good understanding of these factors is crucial to wind integration.
Figure 4-5: Glen Canyon Dam generation capability and end-of-month (EOM) water elevation accompanied by monthly peak demand generation. (Source: Pete 2010; data provided by the U.S. Bureau of Reclamation)
4.2.3 Planning of Resources As evident from the case of Glen Canyon Dam, hydrological resources can be variable over long- term periods; therefore, long-term planning must be conducted to guarantee adequate generation to meet anticipated future loads well in advance. In an interconnected river system, joint planning of water resources among owners and operators is typically performed to secure overall operations and resources while observing constraints and priorities present along a river system and on individual
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generation facilities. Long-term planning enables an extensive plan where details can be based on monthly targets to optimize anticipated resources. The results from planning enable utilities and transmission system operators to develop short-, mid-, and long-term generation plans. Furthermore, such plans typically define the hydropower resources that could be available under low, average, and high precipitation levels, based upon the historical record. As time progresses and hydrological conditions fluctuate from predicted values, the current plan can be altered and updated, allowing for the difference in generation resources to facilitate a balanced system load. Examples of such long-term plans can be found via the Pacific Northwest Coordination Agreement,14 and the Missouri River Master Manual.15 Pertaining to wind integration, this long-term planning helps define the minimum and expected levels of generation that may be available to meet load, as well as the flexibility of the generation and amount of reserves.
4.3 Hydropower System Flexibility – Institutional, Organizational and Legal Issues
The foregoing focus of hydro system flexibility persistently leads to the power plant’s subservience to higher priority functions, assorted organizations, and stakeholders that establish authority over operational practices. Furthermore, at many locations, additional laws and regulations, organizations, and agreements may preside over the hydro system. One example defining organizational and legal complexity is the governing hydro facilities on the Colorado River System. While Reclamation manages operations and power generation at several hydro facilities in the lower Colorado region, the Western Area Power Authority (Western), another Federal agency, distributes and markets the power with public and privately owned utility groups based upon bilateral agreements. The power and water customers are primarily governed by a body of laws and regulations collectively known as the “Law of the River.” With over 50 laws, acts, documents, regulatory agencies, and organizations overseeing the Colorado River, it is regarded as one of the highest regulated river systems in the Southwest region (Underwood, 2005). With respect to Hoover Dam, which is one of the largest hydro facilities located on the river system, priority function constraints result in an inability to move water usage deliveries from month to month for the benefit of power generation. However, within a time period of a month, considerable scheduling flexibility is allowed and downstream hydro facilities allow re-regulation of flow from Hoover, assisting in overall system flexibility.
The point of the preceding example is that, in addition to the constraints that may be present at a hydro facility limiting flexible use of the resource, there may also be a layer of organizational complexity on top of this, with multiple organizations possessing authority over operations. Since each organization that wields authority has its own interests in mind, it is unlikely that any significant operational changes will occur without consensus and demonstration that the benefits yielded by the hydro system, or protection of the environmental assets thereof, are not diminished via wind integration. Thus, in the short-term, the most practical method of hydropower participating in wind integration is to understand what flexibility exists in the system as is, and utilize it to the maximum benefit of the owner (which may or may not be for wind integration).
This discussion leads to the concept of a “practical” configuration of a system for wind and hydropower integration, as shown in Figure 4-6. The red dashed lines in this illustration indicate directions of data/information flow to or from the transmission system operator that is in charge of
14 See http://www.nwd-wc.usace.army.mil/PB/oper_planning/pnca.html or http://www.nwd- wc.usace.army.mil/PB/97PNCA_Conformed.pdf. Accessed March 2010. 15 See http://www.nwd-mr.usace.army.mil/mmanual/mast-man.htm. Accessed March 2010.
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balancing the system. The wind generation is absorbed into the power system and used to meet some portion of the load. The hydropower generation, along with the rest of the generation resources on the system, then goes to serve the “net load” remaining after wind is subsumed into the system. The important point here is that the purpose of the balancing resources is to meet the needs of the entire system and not to try to smooth the variations or cover the missed forecasts of the wind alone. Another important point in the figure is that the system operator has the authority to use the hydro power, within its constraints, to serve the needs of balancing the system and economically meeting the net load. This is not the case with many utilities in the U.S. that incorporate hydropower. Efforts that lead to a system with this configuration, or something that operates functionally in this manner, will aid in permitting hydropower’s participation in wind integration. The challenge is to make sure the various beneficiaries of the hydro system maintain their specific benefits, or are compensated if they do not. To demonstrate this will require a detailed study of the power system, for example, using cost production modeling, which is capable of modeling the various aspects of the hydro system and can estimate the benefits and impacts on hydro.
Balancing Area Trans.Scheduling Sys. Operator Entity
Thermal Loads Generation Power to grid to Power
Power to grid Power to grid Transmission/Distribution Hydro Wind Power to gridPower to Power Power
Transmission Power from grid Interconnections
Figure 4-6: A practical configuration for integration of wind and hydropower resources. (Source: Acker 2010)
An example of a recent power system study that considered hydropower in some detail is the Western Wind and Solar Integration Study (WWSIS) conducted by GE on behalf of NREL in the USA.16 In this study, GE performed a cost production simulation using their Multi-Area Production Simulation17 (MAPS) model to determine the operational impacts of incorporating up to 30% wind energy and 5% solar energy to meet the 2017 load obligation in the WestConnect footprint in the Southwestern United States (Arizona, Colorado, New Mexico, Nevada, and Wyoming). The
16 See http://wind.nrel.gov/public/WWIS/. Accessed March 2010. 17 See http://www.gepower.com/prod_serv/products/utility_software/en/downloads/10320.pdf. Accessed March 2010.
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simulation was very detailed in many respects, performing a transmission-constrained, hourly cost production simulation which was focused on assessing the feasibility and cost implications on operations due to the variability and uncertainty of wind and solar energy. The overall conclusion of the study was that these high levels of wind and solar penetration are possible, and can be handled operationally.
An important assumption in this study concerning electrical system organization was that there would be significant balancing area cooperation, and that all balancing areas in the study footprint would cooperate in addressing system imbalances. Indeed, if this were not the case, some balancing areas would be overwhelmed by the balancing requirements. Following the logic of balancing area cooperation, the hydro resources were committed and dispatched in the MAPS simulations for the benefit of the system (e.g., not for the benefit of recipients of the federal hydropower or the entities that may schedule for them). While this method of employing the hydro is not consistent with current operations, it did permit an investigation of the potential for system balancing and meeting peak loads with the hydropower resources in the footprint.
In performing a simulation, the MAPS program does not track the water balances, head heights, etc., at the individual hydro power plants, but rather it uses a “rational” dispatch algorithm that honours monthly min/max values for hydro production at each facility, along with the cumulative energy output per month. Figure 4-7 shows a plot of the hydro production at Hoover Dam for a week in April from the MAPS simulation. This particular week was selected because it was the week during the year that exhibited the greatest magnitude of wind power production, as well as variability in the wind production, and presented the most significant challenges in system balancing. The black trace on the plot is the historical production pattern from 2006, and the blue trace is the production pattern as dispatched by MAPS, assuming there was no wind or solar in the system generation mix (the MAPS simulation producing these results used the historical 2006 system loads scaled up to an expected level in 2017). Note the degree of similarity in the production patterns between the actual and simulated: the MAPS simulation tended to dispatch the hydro more for peak shaving than for handling hour-to-hour fluctuations in the load. An important point here is that while the rational dispatch can well demonstrate how hydro could be used to assist in system balancing, it does not necessarily do a good job reflecting the constraints present in the hydro system that cause its actual use to deviate from the peak shaving. This is an important area for improvement in future integration simulations.
The red line in Figure 4-7 shows the production pattern as dispatched by MAPS, assuming 20% wind energy and 3% solar energy, while honouring the 2006 historical monthly min/max and energy production. In this scenario, while MAPS still preferred to dispatch the hydro for peak shaving, it needed to back down the hydro at times to accommodate the high level of wind power, and at other times it needed to ramp the hydro to meet system ramping requirements.
When interpreting this plot, especially comparing the actual and no-wind cases, it is important to realize that the system load being addressed in the MAPS simulation was the aggregate load for the entire WestConnect footprint. Thus, the hourly fluctuations of the net load are relatively less variable than in smaller systems, and the entire set of generators in the footprint is available to meet load fluctuations, factoring in transmission constraints. This is a benefit of aggregation as the load variability of any two systems is typically independent (except the morning and evening ramps).
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During this week in the simulation, the most valuable asset of the hydro was its ability to move energy generation from one period to another, to provide system reserves, and to provide some ramping/load following. Some sub-hourly regulation was provided by Hoover in the MAPS simulations, but these variations do not show up in the plots of hourly average generation. In this regard, the amount of generation devoted to regulation at Hoover was not available for dispatch and load following in the MAPS simulation.
As is perhaps evident from the WWSIS results, a challenge for the hydro industry is to understand the impacts on hydro due to wind integration, and estimate the effects on O&M costs that will arise. The results presented for Hoover Dam show less cycling of the units and larger morning/evening ramps, which may not be intuitive and is not a result that will apply generally to other facilities. Another challenge is to estimate the value that hydro provides in balancing a system with such large amounts of wind/solar. Other scenarios were considered in the WWSIS that demonstrated that hydro contributed significant value to the system in meeting the net load, a topic that is further addressed in the WWSIS final report (Piwko 2010) and in Pete (2010).
Week of April 1500 Hoover Actual Hoover No W ind HH Hoover L20R HH
1000 Generation(MW)
500
0 Tues-11 Wed-12 Thur-13 Fri-14 Sat-15 Sun-16 Day
Figure 4-7: Sample results from the NREL/GE Western Wind and Solar Integration Study showing the hourly dispatch of power from Hoover Dam during a week in April. (Source: Pete 2010)
Another organizational aspect of importance in wind integration deals with how power/energy is traded. With the conditions for hydro power generation, set by the constraints combined with the organizational flexibility of the resources, the system operator or operator of the hydro facility then tries to make best use of the resource, which is frequently the most economic use of the hydropower to the benefit of the owners. This, in turn, is dependent upon the market conditions that exist. Whether the market is a liquid market with many actors, such as the various North American ISOs or the NordPool, or sales and purchases of power and/or ancillary services are done via bilateral
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transactions arranged directly between utilities, the hydropower will likely be utilized for its highest economic benefit. For some hydropower utilities that utilize their resources for peak shaving / load factoring, there will be competition between using the hydropower (or rather, some relatively small portion of it as dictated by the enhanced balancing requirements of the net load) for ancillary services and reserves versus energy sales during high load hours (HLH), where the value of the power is high. In these instances, the value of providing the ancillary services and/or reserves must overcome the opportunity cost in foregoing an energy sale during HLH.
4.4 Conclusions: The Role of the Hydroelectric Industry in Wind Integration
When considering wind integration into the power system, there are a number of perspectives that one can adopt. For example:
A holistic view of the power system and the influence of incorporating wind power on the consumer, including cost to serve load, environmental implications, local economic development, etc. The point of view of a thermal-based electricity producer: coal-fired steam plant, natural gas combined cycle or simple cycle, nuclear, etc. The perspective of a hydropower owner/operator. The perspective of a wind power developer. The point of view of a vertically-integrated utility. The perspective of a transmission system operator or balancing area authority. The oversight role of regulatory agencies or policy-setting entities. The point of view of non-governmental agencies, such as environmental advocacy groups, economic development agencies, etc.
The point of view adopted is important in interpreting the impacts of wind integration. For example, integrating a large amount of wind power into a predominantly thermal power system could result in less revenue for many thermal-electric power producers, especially those whose costs are on the margin. In this case, the consumer may be well pleased with the wind power, but not the existing thermal power generators. As another example, consider a large power system with a diverse set of generation resources, liquid power markets, and expected load growth. For such a system, wind power could be the lowest cost expansion alternative. Antithetically, one could envision a hydro- dominant utility with excess generation resources and little load growth. In this instance, adding wind power to a low-cost hydro system may not benefit the rate payers at all. Next, one might consider the impact of wind power development on economic development in a state, province, or country, and the potential for rural development that may not otherwise occur. This point of view may be dissociated from the cost of electricity to the consumer, but it does address an important aspect of what is ultimately an investment of funds supplied by the public. As is evident from these few examples, the topic of wind integration can have many faces and many interpretations.
Of these view points, the most appropriate is likely the holistic view of the power system; this is also the most multifarious and difficult to evaluate. For the purpose of this report, the perspective adopted is that of a hydropower producer or utility, with the intention of identifying the opportunities that exist in wind integration as well as the constraining factors and sources of costs. Conclusions related to these topics will be addressed below, followed by areas of future research.
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4.4.1 Opportunities At present, there are three main reasons for incorporating wind power into a power system: economic (competitive to other generation sources, stable price), political (state and government policies and incentives driving clean energy), and environmental (emits no carbon or other emissions, no water consumption). The main challenges that inhibit its more rapid assimilation into the power system are the facts that it is non-dispatchable (except for turning it off), it varies over time scales of importance to system operation, it is primarily an energy resource with limited capacity value, there are uncertainties in its prediction, and system operators and planners are unfamiliar and inexperienced with the behaviour of wind power or how to properly incorporate it into control room operations. These challenges, however, present an economic opportunity to generation resources that can help make up for these deficiencies by supplying the ancillary services and reserves necessary to compensate for them. Thus, the first and perhaps primary opportunity for hydropower in integrating wind energy is via provision of ancillary services, reserves, and short- to mid-term storage of energy.
The fundamental advantage of hydropower in integrating wind power lies in the agility of its generators in meeting rapid changes in net load, providing system ramping, its ability to shift periods of energy production (storage), and its supply of fast-responding reserves (spinning and non- spinning). These resources are of great value in a power system that incorporates a high penetration of variable and uncertain generation resources, such as wind power, that rely on constantly changing renewable resources. For example, in the Arizona Public Service (APS) Wind Integration Study the integration costs were determined for a 10% penetration of wind energy (which equates to ~16% penetration by capacity with 1,260 MW of wind power and a peak load near 7,900 MW for the system). Results of the study showed that the cost of increased minute-to-minute regulation due to wind energy was over $1M/year, about $8M/year to compensate for increased hour-ahead uncertainty due to wind forecast errors, and over $3M/year to deal with day-ahead forecast errors due to wind energy (Acker 2007). Thus, opportunity exists for hydropower producers to earn these revenues. Hydropower is also low-cost electrical generation, and therefore has an economic advantage in providing these services as compared to every other resource. Hydropower also has the ability to provide voltage support to wind systems by supplying reactive power; since many wind power plants are located in remote sites, the long transmission lines and the use of induction generators tend to be ‘reactive deficient’.
Another advantage of using hydro power over thermal generation relates to the low capacity factor of hydropower. Thermal generators can alter (reduce) production schedules to accommodate periods of high wind power, but doing so equates to lost revenue since their fuel source is effectively continuous and they could otherwise earn revenue during these times. Hydro, on the other hand, has a limited fuel source in its water, and provided that spill can be avoided, there is the potential to use the hydro power later at no loss of revenue, and potentially allow for excess power to be exported to neighboring balancing areas during high load hours [PERI 2002]. Hydro units can also start very quickly (on the order of ten minutes from dead start to full power) at a relatively low cost when compared to thermal generators. Simple cycle or combined cycle natural gas turbines that are valuable in system balancing typically have minimum run times, minimum down times, and relatively high start-up and marginal costs. Each of these factors put them at a competitive disadvantage compared to hydropower. Furthermore, utilities employing gas turbines may incur additional costs associated with day-ahead gas reservations being substantially different than the actual gas utilized during the day of operation [Zavadil 2006].
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Hydropower, by virtue of its water impoundment, has the opportunity to develop unique market products for wind integration customers. “Storage and shaping” products have been previously offered by some hydropower utilities and are examples of products where the wind power is subsumed into a utility’s net load, then redelivered some time later (e.g. one week) as constant and consistent energy. Products such as these can be of value to customers, and essentially remove the variability and uncertainty of wind energy from the customers’ planning and reallocates it to the hydro utility. Other products that have shorter time frames, such as hourly balancing supplied for wind integration (to compensate for missed forecasts and unexpected ramps in net load) may be of value to customers and involve less uncertainty/risk than the storage and shaping products. Furthermore, these products could be devised to provide balancing for a certain amount of wind power, or to provide a certain amount of balancing. The latter of these two gives the hydropower operator some certainty in knowing how much of its resource needs to be available for balancing on any given day. Products such as these could be sold on long-term contracts or on a day-to-day basis. Another idea is devising a wind integration product that combines the flexibility of hydro with demand-side load-response. This combination could create a very flexible tool for wind integration, with the load response helping the hydropower balance the net load during the relatively few hours of the year when flow or power constraints are onerous.
There may also be opportunities for pumped storage hydropower (PSH) in wind integration. However, previous wind integration studies have shown that revenues that one could earn using PSH to balance the net load are insufficient to justify new PSH at wind penetration levels of up to 30% [Piwko 2010]. However, if the value proposition for new PSH is built upon a few potential revenue sources (especially energy arbitrage) with wind integration as one component, then it may be justified. Furthermore, if the wind penetration were to climb well above the 30% penetration level, it is quite possible that PSH could be justified to help balance the system net load. PSH, or any form of energy storage, should be considered in the context of its value as a system resource.
To the extent that wind and hydropower vary on different timescales, they can be complementary resources. Wind tends to vary much more than hydro on a daily and sub-hourly basis. However, looking at the time frame of several months to a year, wind power tends to be less variable than hydropower. As an example, Westrick et.al. (2003) present some data indicating that the integrated summer (May through September) volatility from year-to-year at a site in the Northwestern US is about 15% for wind power (average capacity), and about 35% for hydro power. Thus, there may be benefits to hydro-dominant utilities in incorporating wind power, especially those responsible for meeting load and with expected load growth.
The potential opportunity to provide ancillary services, reserves, or energy storage via hydro power varies from plant to plant. Hydro facilities with small reservoirs and not tasked with flow regulation may have the potential to provide regulation, reserves, load following, and energy storage on a time frame of several hours to days. Hydro facilities with large storage capacities have the greatest potential as system balancing resources by providing quick start, ancillary services, and the ability to shift water and energy releases for days to several months.
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4.4.2 Issues and Constraints There are a number of issues and constraints that have been identified concerning hydropower’s role in integrating wind energy. These issues relate primarily to the flexibility of hydropower, which is of greatest value in wind integration. They are summarized below:
Priorities. Hydro facilities are often built with multiple purposes/functions in mind that lead to a number of societal benefits. These benefits translate into multiple priority functions at a hydro facility, and consequently, operational parameters that constrain the flexibility of the power plant. Priorities that supersede power generation tend to limit the flexibility of a hydro power plant.
Environmental Issues. On river systems where hydro operations detrimentally affect the ecology or wildlife, there are often modifications to, or restrictions on, flow operations that are intended to benefit the affected aspects of the environment (e.g. survival of fish species, etc.). These restrictions are often regulated, and consequently, are among the highest priorities, and thus they inhibit flexible operation of the power plant.
Availability. With respect to wind integration, the factors limiting the availability of hydro generation will also limit their ability to integrate wind. However, given that wind integration is addressed in the context of the variability and uncertainty of the system net load and not in isolation, existing planning processes should be capable of adequately addressing these concerns. In terms of wind-hydro integration, this adds another level of complexity in understanding the correspondence between the net load (wind and system load patterns) and the availability of hydro generation.
Interconnected river systems. Hydro power must be utilized within a certain time frame related to flow in the river. For power plants that are part of very large dams and reservoirs, this time frame can extend from days to several months. However, for smaller power plants with only modest reservoir storage, there is limited flexibility as to when the water must run through the generators, as dams can overfill and spill water or be depleted of their water. Optimum utilization of the hydro resource across several hydro plants requires cooperation and coordination among plant owners/operators. This is especially true on interconnected river systems with hydro power plants at smaller dams where the flow releases from upstream dams affect all facilities downstream.
Complex organizations. Due to the multifaceted tasks performed by some hydro facilities, and the multiple beneficiaries of these tasks, multiple organizations, regulations, and laws may be in place that govern operation of the hydro facility and define the authority. While some hydro facilities have a relatively straight-forward organization with power as a priority, others do not. Understanding the authority and priority structure for a hydropower plant or system is key in defining the flexibility available for purposes such as wind integration.
Determining the impacts. This issue relates to understanding the impacts of wind generation on net load and system balancing requirements, and understanding the impacts (both physical and economic) on hydro power. For example, a hydro plant that maximizes it profits by peak shaving may suffer some opportunity costs in reallocating a portion of its resource for
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ancillary services required by wind power. The economic implication of this reallocation should be understood prior to implementation. It is not uncommon for misconceptions to exist concerning the actual impacts of wind integration (often overestimated), the flexibility required to address these impacts, and the flexibility available at hydropower plants in the time scales of importance, especially those with non-power constraints. Thus, when assessing the impacts, costs, and opportunities represented by wind integration, it is important to perform system studies using methods sufficiently detailed to provide an accurate assessment of these impacts and associated economics.
Scheduling intervals and wind forecasts. Infrequent scheduling intervals combined with inaccurate forecasts lead to a significant amount of reserves being allocated over the hour of operation. Increasing the frequency of the scheduling interval can relieve the requirement for unnecessary reserves and allow more flexibility in use of generation (hydro) resources. Liquid markets or balancing area cooperation are two additional ways of to infuse flexibility into the electrical system.
Impacts of wind integration in systems with hydropower. A challenge for the hydro industry is to understand the impacts of wind integration on hydropower, and to estimate the effects on O&M costs that will result. It is important to understand both the available flexibility and the magnitude and timing of the hydro resource that is required to facilitate wind integration. This is naturally dependent upon the hydro project, balancing area generation resources and load, and the variability and uncertainty of the wind power. When considering the potential for wind integration, one must consider the concerns stemming from the interactions between priority functions, various organizations and stakeholders that establish authority, and diverse economic environments that may ultimately limit the overall flexibility of the hydro system. Developing a good understanding of these factors is crucial to wind integration. From a broader point of view, it is also important to understand the competing effects of operation to comply with environmental regulation versus supplying balancing and/or energy storage needed due to the interactions of wind power with the net load.
Cost allocation. In high wind penetration scenarios, where hydropower may be utilized to the benefit of power system balancing, a good understanding of the value of the hydro resource and magnitude of its use needs to be developed. Proper methods to allocate the costs and benefits need to be devised. Owners and operators of the hydropower need to be properly compensated for providing balancing services to the benefit of the system.
Forecasting of hydro resources and integration requirements. Pertaining to wind integration, long-term estimation and planning of the hydro resource helps define the minimum and expected levels of generation that may be available to meet the load, as well as the flexibility of the generation and amount of reserves.
4.4.3 Impacts on hydropower operations and maintenance The primary influences on hydropower operations and maintenance that arise due to the impacts of wind integration are as follows:
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Potentially altered schedules for unit maintenance, allowing units to be on-line during periods of time when the system operator requires a high amount of generator flexibility and reserve to accommodate changes in the net load brought about by wind integration. Altered/increased ramping of units that may lead to increased O&M issues and costs. More hydro units providing regulation, and the changes in O&M that may arise.
4.4.4 Areas of future research Based upon a review of the literature, the expected impacts of wind integration in systems with hydropower, and the potential role for hydropower in wind integration, the following areas/topics for future research have been identified:
Development of better planning tools: Devise electrical system cost production models that do a good job at resolving hydro system operation with its constraints, and are capable of incorporating wind power and wind power forecasts. This is an immediate need for improving wind integration studies in systems with hydropower.
Application of planning tools: Use improved planning tools to conduct thorough cost production studies of electrical system operation that investigate the impact of wind integration on system constraints, unit cycling, operational costs, etc.
Cooperative research. Capitalize on hydropower’s long legacy of cooperation and create study groups to investigate and address wind integration. Create organizational structures that facilitate wind integration that will permit cost allocation to be properly distributed.
Relating unit cycling to O&M. Understanding the mechanisms driving unit O&M costs in such a manner that reliable estimates of altered O&M costs could be devised based upon estimated impacts on wind integration.
Education amongst stakeholders. There are many questions and misconceptions concerning wind integration among stakeholders in the hydro community, and these need to be addressed.
Market and transaction intervals. Investigate ways to develop liquid markets that will benefit both wind and hydropower, alter system scheduling practices to permit more frequent power system transactions, and/or promote balancing area cooperation in handling system imbalances.
Revised market or system operations rules: Create system operational set-ups that allow more frequent (sub-hourly) schedule changes (e.g. scheduling of generation, allocation of reserves, etc.). In general, the closer to the hour of operation a wind forecast is made, the more accurate it will become. The more accurate the forecast is, the fewer reserves will be required, leaving more flexibility in the system to meet net load deviations and allowing the hydropower to be used more effectively in balancing net load variations and for meeting the load.18
18 For example, refer to www.bpa.gov/corporate/WindPower/docs/presentation-BalancingActforWind.ppt. Accessed March 2010.
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Balancing area size. Investigate the effect of larger balancing areas or multiple balancing areas that cooperate on system balancing and reserve sharing in order to create conditions where wind integration is more practical. These arrangements will permit more wind power to be integrated using the existing flexibility in the hydro power system.
Small hydro systems. Research wind integration in hydro systems with a relatively small water impoundment. This will help smaller hydro facilities with limited flexibility better understand the expected impacts and what is possible regarding wind integration.
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5.0 References
Acker, T. L., Knitter, K., Conway, K., and Buechler J. (2006). “Wind and Hydropower Integration in the Grant County Public Utility District, Washington, ” Proceedings of the 2006 Hydrovision Conference, Portland, Oregon, USA, July.
Acker, T., Buechler, J., Broome, S., et al. (2007a). “Final Report: Arizona Public Service Wind Integration Cost Impact Study,” Northern Arizona University, October. Available at http://www.wind.nau.edu/.
Acker, T.L, Buechler, J., Knitter, K., and Conway, K., (2007b). “Impacts of Integrating Wind Power into the Grand County PUD Balancing Area,” Proceedings of the 2007 AWEA Windpower Conference, Los Angeles, CA, June.
Acker, T.L., (2010). Chapter 7: Task 24 Integration of Wind and Hydropower Systems, in “IEA Wind Energy Annual Report 2009,” Implementing Agreement for co-operation in the Research, Development, and Deployment of Wind Energy Systems, PWT Communications: Boulder, CO, Available Summer 2010 at www.ieawind.org.
Bauer, M., Murphy, D., Ketchum, R., et al., (1999). “A Method for Calculating Production Costs for Ancillary Generation Services,” Bureau of Reclamation.
Bielecki, M., Kemper, J, Acker, T. (2010). “Characterization of Errors in Wind Power Forecasting,” Master’s Thesis, Northern Arizona University. Available from the NAU Cline library at http://www.nau.edu/library
Corbus, D., et al., (2010). “Eastern Wind Integration and Transmission Study,” NREL Subcontract Report, 2010. Available at: http://www.nrel.gov/wind/systemsintegration/pdfs/2010/ewits_final_report.pdf
Denault, M., Dupuis, D., Couture-Cardinal, S. (2009). “Complementarity of hydro and wind power: Improving the risk profile of energy inflows,” Energy Policy, 37, pp. 5376-5384.
Dixon, S. L., (1998). “Fluid Mechanics and Thermodynamics of Turbomachinery,” 5th Edition, Oxford: Elsevier Butterworth-Heinemann, Chapter 9 Hydraulic Turbines.
EnerNex Corp. and Windlogics Inc. (2004) “Xcel Energy and the Minnesota Department of Commerce, Wind Integration Study – Final Report,” http://www.uwig.org/XcelMNDOCStudyReport.pdf, accessed April 2010.
EnerNex Corp. and Windlogics Inc. (2006) “Minnesota Wind Integration Study, Volumes I and II,” http://www.puc.state.mn.us/docs, accessed April 2010.
EnerNex Corp. (2007) “Avista Corporation Wind Integration Study Final Report,” http://www.uwig.org/AvistaWindIntegrationStudy.pdf, accessed April 2010.
Focken, U., Lange, M., Monnich, K., Waldl, H.P., Beyer, H.G., Luig, A., (2002). “Short-term Prediction of the Aggregated Output of Wind Farms – a Statistical Analysis of the Reduction of the
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Prediction Error by Spatial Smoothing Effects,” Journal of Wind Engineering and Industrial Aerodynamics, Volume 90, pp. 231-246.
Holttinen, H., (2004). “The Impact of Large Scale Wind Power Production on the Nordic Electricity System,” Doctoral Dissertation, VTT Technical Research Centre of Finland.
Holttinen, H., Meibom, P., Hulle, F., et al., (2008). “IEA Wind Task 25: Design and Operation of Power Systems with Large Amounts of Wind Power,” International Energy Agency report available at: http://www.ieawind.org/AnnexXXV/PDF/Final%20Report%20Task%2025%202008/T2493.pdf
IEA, (2008). “IEA Wind Energy Annual Report 2007”, International Energy Agency, July. Available at http://www.ieawind.org/AnnualReports_PDF/2007/2007%20IEA%20Wind%20AR.pdf
Kirby, B., Hirst, E., (2000). “Customer-Specific Metrics for the Regulation and Load-Following Ancillary Services,” ORNL/CON-474, Oak Ridge National Laboratory, Oak Ridge, TN, January.
Loutan, C., Hawkins, D., Blatchford, J., et al. (2007) “Integration of Renewable Resources: Transmission and operating issues and recommendations for integrating renewable resources on the California ISO-controlled Grid,” California Independent System Operator. Available at http://www.caiso.com/1ca5/1ca5a7a026270.pdf
Mannwell, J., McGowan, J., and Roberts, A. (2008). “Wind Energy Explained,” McGraw–Hill, New York, Chap. 2. And Chap. 3.
Matevosyan, J. (2006). “On the Coordination of Wind and Hydropower,” Proceedings of 6th International Workshop on Large-Scale Wind Power Integration, October.
Mays, L. W., Tung, Y. (2002). “Hydrosystems Engineering and Management,” Englewood: Water Resources Publications LLC, Chapter 1 Introduction to Hydrosystems.
Milligan, M., Porter, K., (2005). “Determining the Capacity Value of Wind: A Survey of Methods and Implementation,” Proceedings of WINDPOWER 2005, Denver, CO, May 15-18. NREL/CP- 500-38062.
New Brunswick System Operator: NBSO (2007). “Maritimes Area Wind Power Integration Summary Report.” Available at: http://www.uwig.org/NBSO_Wind_Study_Project_Final_Summary_Report_May_2007.pdf
Pete, C. M., (2010). “Implications on hydropower from large-scale integration of wind and solar power in the West: results from the Western Wind and Solar Integration Study,” Thesis Report, Northern Arizona University Mechanical Engineering Department. Available from the NAU Cline library at http://www.nau.edu/library
Piwko, R., Boukarim, G., Clark, K., et al. (2004). “The Effects of Integrating Wind Power On Transmission System Planning, Reliability, and Operations, Report on Phase 1: Preliminary Overall Reliability Assessment,” Prepared for the New York State Energy Research and Development Authority, by General Electric’s Power Systems Energy Consulting, Schenectady, NY.
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Piwko, R., Xinggang, B., Clark, K., et al. (2005). “The Effects of Integrating Wind Power On Transmission System Planning, Reliability, and Operations, Report on Phase 2: System Performance Evaluation,” Prepared for the New York State Energy Research and Development Authority, by General Electric’s Power Systems Energy Consulting, Schenectady, NY.
Piwko, R., Clark, K., Freeman, L., Jordan, G., Miller, N., (2010). “Western Wind and Solar Integration Study,” NREL Subcontract Report. Available at http://wind.nrel.gov/public/WWSIS/
Princeton Energy Resources International (PERI), Vermont Environmental Research Associates, (2002). “Wind and Biomass Integration Scenarios in Vermont, Summary of First Phase Research: Wind Energy Resource Analysis,” Prepared under DOE project, number DE-FG01-00EE10762, March.
Smith, C., Parsons, B., Acker, T., et al. (2007). “Best Practices in Grid Integration of Variable Wind Power: Summary of Recent US Case Study Results and Mitigation Measures,” Proceedings of the European Wind Energy Conference, Milan, Italy. May.
Söder, Lennart (1994). “Integration study of small amounts of wind power in a power system,” KTH Report TRIRA-EES-9401. Accessed March 2010 at http://www.eps.ee.kth.se/personal/lennart/lennart_integration94.pdf
Söder, L. and Holttinen, H. (2008). “On methodology for modeling wind power impact on power systems,” Int. J. Global Energy Issues, Vol. 29, Nos. 1/2, pp.181-198.
Tester, J., Elisabeth, D., Driscoll, M., el al. (2005). “Sustainable Energy: Choosing Among Options,” Cambridge: Massachusetts Institute of Technology Press, Chapter 16 Storage, Transportation, and Distribution of Energy, pp. 658.
Underwood, D. B., (2005). “The Law of the River: A Primer,” The Metropolitan Water District of Southern California, CLE International. Additional Information available at http://www.usbr.gov/lc/region/g1000/lawofrvr.html
U.S. Department of Energy, (2008). “20% Wind Energy by 2030: Increasing Wind Energy’s Contribution to U.S. Electrical Supply”, Produced for the U.S. Department of Energy by NREL, DOE/GO – 102008-2567, July.
USACE (2006). “Missouri River Mainstem Reservoir System, Master Water Control Manual, Missouri River Basin,” Reservoir Control Center, U. S. Army Corps of Engineers Northwestern Division. Available at http://www.nwd-mr.usace.army.mil/mmanual/mast-man.htm
USGS (2004). USGS Fact Sheet 2004-3062, version 2, U.S. Department of the Interior, U.S. Geological Survey, Available at http://pubs.usgs.gov/fs/2004/3062/
Wan, Y., (2004). “Wind power plant behaviors: analyses of long-term wind power data,” National Renewable Energy Laboratory, Technical Report, NREL/TP-500-36551. Available: http://www.nrel.gov/docs/fy04osti/36551.pdf
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Wan, Y., (2005). “A Primer on Wind Power for Utility Applications,” National Renewable Energy Laboratory, Technical Report, NREL/TP-500-36230, August. Available: http://www.nrel.gov/docs/fy05osti/36230.pdf
Wan, Y., (2009). “Summary Report of Wind Farm Data,” National Renewable Energy Laboratory, Technical Report, NREL/TP-500-4438, May. Available: http://www.nrel.gov/docs/fy09osti/44348.pdf
Wang, R. Baker, D., (2005). “Alberta Wind Power Variability Study,” prepared by Phoenix Engineering Inc., submitted to Alberta Electric System Operator.
Westrick, K., Storck P., and Froese, G., “Reliance on Renewables – The Synergistic Relationship between Wind and Hydropower,” proceedings of the AWEA Windpower 2003 Conference, Austin, Texas, May 2003.
Wiser, R., Bolinger, M., (2009). “2008 Wind Technologies Market Report”, produced for the U. S. Department of Energy by NREL, NREL Report No. TP-6A2-46926; DOE/GO-102009-2868, July.
Zavadil, R. M., (2006). “Wind Integration Study for Public Service Company of Colorado,” Xcel Energy. Available at www.nrel.gov/wind/systemsintegration/pdfs/colorado_public_service_windintegstudy.pdf
Zavadil, R. (2006). “WAPA Wind Integration Study,” EnerNex Corporation, Knoxville, TN.
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APPENDIX A. Review of wind integration literature
This appendix presents a brief summary of the papers and reports that are most relevant to the topic of this compilation, allowing the reader to refer to the report for further information on a desired subject.
Acker, T., Buechler, J., Knitter, K., Conway, K., (2007). “Impacts of Integrating Wind Power into the Grant County PUD Balancing Area,” proceedings of the AWEA WINDPOWER 2007 conference, Los Angeles, CA, USA, June.
This report presented a study to analyze the impacts of integrating three levels of wind penetration into the hydro-dominated system of the Grant County Public Utility District of Washington State. Reliability and environmental constraints were investigated, as well as impacts of wind integration on regulation and load following concerns. The study found that penetration levels up to 19% capacity penetration would lead to impacts on system flow constraints and generation limits if only included in the day ahead planning process, and that these impacts would, and probably could, be handled within the day of operation.
Ancona, D., Krau, S., Lafrance, G., Bezrukikh, P., (2003). “Operational Constraints and Economic Benefits of Wind-Hydro Hybrid Systems – Analysis of Systems in the U.S./Canada and Russia,” European Wind Energy Conference, Madrid, Spain.
This report provides a discussion of two case studies pertaining to wind and hydro integration. The first case study involved operating and economic impacts foreseen when theoretical wind power produced in Vermont was allowed to be sold into the New England Power Pool (NEPOOL) alone, versus also being exported into Hydro-Québec and potentially integrated with available hydro resources. It was concluded that the value of wind could be increased by 22% when sold to Québec during times of peak load if a perfect correlation existed between wind production in Vermont and system load in Hydro-Québec.
The second case study involved a comparison between the Vermont/Québec exchange and a wind-hydro integration example in Northwest Russia. The purpose of this component of the report was to assess wind and load correlations in cold-weather climates. The report concluded that wind-hydro integration may be even more favourable in cold climates due to the fact that windy periods tend to correspond to high load periods (cold months), and may also occur when hydro resources are reduced due to frozen water.
Benitez, L., Benitez, P., Van Kooten, C., (2008). “The economics of wind power with energy storage,” Energy Economics, Vol. 30, pp 1973-1989.
A mathematical optimization program was created to analyze the economic and environmental impacts of adding wind to the Alberta electric system at four different scenario arrangements. The study investigated the ability of hydro storage to mitigate wind variability. The program calculated the amount of additional peak generating capacity that
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would be necessary to accommodate the wind. A range of estimated electricity costs from
wind are given, as well as estimated CO2 reduction costs. It was concluded that adding pumped hydro storage could provide sufficient reserves to meet peak load requirements, thus negating the need to build additional peak-load gas generator units.
Castronuovo, E., Lopes, J., (2005). “Bounding active power generation of a wind-hydro plant,” Proceedings of the PMAPS-2004 (8th International Conference on Probabilistic Methods Applied to Power Systems). September 13-16, 2004, Ames, Iowa, USA.
An optimization method is presented that estimates expected power production levels at wind facilities. Forecasted wind production was treated as a stochastic variable, and confidence intervals were determined for the predicted range of power production levels. The model was validated with real wind power data from Portugal. The study concluded that market participation by wind power plants is increased when energy storage options are incorporated. The proposed optimization process was aimed to determine effective ways to integrate hydro resources with wind to decrease uncertainty levels in overall production.
Denault, M., Dupuis, D., Couture-Cardinal, S., (2009). “Complementarily of hydro and wind power: Improving the risk profile of energy inflows,” Energy Policy, 37, pp. 5376-5384
Wind power was investigated as a means to decrease the chances of water inflow shortages in Québec. Simulated wind power output was compared with historical hydro levels from 1958 through 2003 to determine if wind could offset the risks associated with hydro shortages. The report concluded that all levels of wind penetration considered (up to 30%) will reduce the risk profile of water inflow shortages compared to a total hydro system. The risk value of wind can be estimated in TWh for any amount of wind added to the generation mix.
Hirst, E., (2002). “Integrating Wind Energy with the BPA Power System: Preliminary Study,” Consulting in Electric-Industry Restructuring.
This preliminary study considered the operational planning impacts for the day-ahead unit commitment, intrahour balancing, and real-time operations associated with integrating wind into the BPA system. The BPA system is one of the largest hydro-based balancing areas (by percentage) in the US. The study concluded that large amounts of wind could be integrated into the BPA system due to the flexible balancing abilities of the hydro capacity.
Holttinen, H., (2004). ‘The Impact of Large Scale Wind Power Production on the Nordic Electricity System’, Doctoral Dissertation, VTT Technical Research Centre of Finland, December.
Operational concerns and market impacts are investigated for hypothetical integration of significant wind penetration into the Nordic electricity system. Wind variability levels,
reserve requirements, integration costs, market spot price impacts, and CO2 reductions are discussed. Available at http://lib.tkk.fi/Diss/2004/isbn9513864278/.
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Holttinen, H., Meibom, P., Hulle, F., et al., (2008). “IEA Wind Task 25: Design and Operation of Power Systems with Large Amounts of Wind Power,” International Energy Agency.
An international effort to summarize the wind integration and interconnection studies up to the middle of the last decade culminated in this treatise. The findings showed that the integration costs associated with wind penetration levels up to 20% of gross demand (50% of peak demand) account for less than 10% of the wholesale value of wind energy and must be compared to the benefits of wind energy. The time scale of most importance in these studies was ten minutes to six hours. Some of the other topics covered include transmission constraints, storage, grid reinforcement, and the capacity value of wind. Available at http://www.ieawind.org/AnnexXXV/PDF/Final%20Report%20Task%2025%202008/T24 93.pdf
Hurdoway, D., et al., (2005). “Studying Short-Term Effects of Integrating Wind in a Hydro System: Manitoba Hydro Case Study,” Proceedings of the Waterpower XIV Conference, Austin, TX, July.
This study investigated the short-term costs and system impacts of integrating wind into the Manitoba Hydro operation portfolio. Impacts of wind variability and uncertainty, as well as increased ancillary service requirements were considered. The AUTO Vista model was used to simulate system operation with hydro, transmission, and external energy dimensions, with the ultimate goal of estimating wind integration costs.
IEEE Power & Energy Magazine, (2007). “Special Issue on Wind Integration: Driving Technology, Policy, and Economics”, IEEE Power & Energy Special Issue, Volume 5, Number 6, November/December.
This special issue on wind integration presents an array of articles directed towards the details and issues associated with wind power integration. In this issue, J. Charles Smith and Brian Parsons (guest editors) investigate the developments in wind technology and systems in the United States where their featured column reviews the state of renewable energy penetrations defined by national and state governments producing a variety of renewable portfolio standards. Additionally, they investigate the national policies supporting renewable development in Europe where the wind capacity has become so large, wind plants must be treated as an integral part of the electric system.
The following six featured articles are presented in this issue with the main authors listed:
“To Capture the Wind” by Bob Thresher, et al. This article reports the status of current and future wind energy technologies including capacities, costs, turbine size, and technology advancements in turbine design. Results show wind technology has evolved over the past decade, reducing capital costs, improving reliability and efficiency enabling wind energy to be competitive with conventional power generation.
“Queuing Up” by Bob Zavadil, et al.
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This article investigates issues and challenges with the interconnection queue in the United States, highlighting the processes and activities (policy and regulatory developments, modeling and study results, challenges with interconnections, and a look forward to designing wind plants to “look like” conventional generators) related to securing approval for interconnection into the transmission grid.
“Accommodating Wind’s Natural Behaviour” By Ed DeMeo, et al. This article investigates the advances in insights, methodologies, and methods for wind plant integration. Several results and impacts on system reliability are highlighted from recent integration studies, including: 2006 Minnesota Wind Integration Study, Colorado 20% Capacity Study, California Intermittency Analysis Project, Ontario Wind Integration Study, and the Avista Wind Integration Study.
“What Comes First” by Richard Piwko, et al. This article investigates the concerns, policies, and issues related to transmission planning and competitive market operation for delivery of wind energy from remote generation. Rules related to operating, markets, and energy imbalances for intermittent generation of wind are explored, including what the New York ISO and new FERC policies are undertaking to maximize the benefits while maintaining high reliability and providing fair compensation to all participants in a competitive generation market. Results from the New York ISO conclude common themes to help integration of wind power, such as large balancing areas, large markets, and the availability of fast sub-hourly markets are found to help integrate wind power.
“Predicting the Wind” by Bernie Ernst, et al. This article investigates the models and methodologies used for wind forecasting for utility operation planning, including development and ongoing research on numerical weather prediction models and power output prediction models. Results show combinations of several different models can reduce RMSE by up to 20%, shorter forecast horizons will lead to lower prediction errors, and aggregating wind power over a large area leads to significant reductions of forecast errors and short term fluctuations in generation.
“European Balancing Act” by Thomas Ackermann, et al. This article investigates the issues and impacts involved with high wind penetration levels on the balancing and frequency control in Europe. Several case studies are examined that investigate grid integration issues, frequency response and fault ride-through (FRT) requirements, and balancing and frequency support of the Spanish, Irish, and German electrical power systems. Results show that aggregating wind plants over large geographical regions, larger balancing areas, and operating the power system closer to the delivery hour will reduce integration costs. Additionally, appropriate grid codes in particular to FRT and frequency requirements are essential for high wind penetration levels over 15%.
IEEE Power & Energy Magazine, (2009). “An Update on Wind Integration”, IEEE Power & Energy Special Issue, Volume 7, Number 6, November/December.
This is the third special issue on wind integration devoted to the details and issues with wind power integration. J. Charles Smith and Brian Parsons (guest editors) review some of the
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technical and policy activities that will provide a future direction to wind integration by enlightening on the DOE 20% wind by 2030, the NERC Integrating Variable Generation Task Force, the Production Tax Credit, the Renewable Electricity Standard, and carbon policy.
The following seven featured articles (with the main authors listed) are presented in this issue giving an update on the technical aspects and the how the IEEE Power & Energy Society is changing its structure to provide direct acknowledgment to renewable energy.
“A Whirl of Activity” by Richard Piwko, et al. This article investigates the technical challenges and methods used for integrating increasing levels of wind generation into power grids developed by the formation of wind working groups such as the Wind Power Coordinating Committee (WPCC).
“Up with Wind” by Dave Corbus, et al. This article investigates the challenges of integrating increasing levels of wind power into the electrical power system. In particular, three key aspects are emphasised and scrutinized of recent large regional wind integration studies: wind data development, transmission analysis, and the modeling of wind integration scenarios.
“Change in the Air” By William Grant, et al. This article investigates the operational challenges that balancing authorities see related to wind power production and prediction. This article reveals how different grid and market operators are addressing this issue and why forecasting plays an important role in mitigating operational costs. Additionally, current forecasting methods and practices, as well as future challenges in improving forecasting are addressed.
“Islands Breezes” by Mark Matsuura This article presents the challenges, issues, and economical forces faced by the small island grid systems of Hawaii when 40% renewable energy penetrations levels are present.
“Where the Wind Blows” by Thomas Ackermann, et al. This article investigates how the power systems of Denmark, Spain, Ireland, and New Zealand (four of the highest wind penetration areas in the world) market wind power integration, and the experiences of curtailment and the use of wind forecasting. Additionally, the foremost wind forecasting methodologies and challenges are overviewed.
“The View from Top” by John Lawhorn, et al. This article presents the perspectives on value-based transmission planning processes for delivering renewable energy. Several different leading organizations, including regional transmission organizations, investor-owned utilities, and regional organizations, illustrate the changes needed to be made to the traditional transmission planning process in order to meet current challenges.
“Wind Power Myths Debunked” by Michael Milligan, et al. This article presents answers to commonly asked questions regarding the variability of wind, capacity credit of wind, uncertainty of forecasting, costs associated with wind integration,
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new transmission needs, and storage options. A final discussion is made on system flexibility, value of coal over wind, and the limits to wind on the electrical grid system.
International Council on Large Electrical Systems, (2006). “Electrical Power System Planning with the Uncertainty of Wind Generation”, April.
This report addresses the variability and uncertainty in wind output and in high penetration levels that system developers and grid operators face resulting from the rapid increase in wind power plants. Some of the results conclude that: penetration of Wind Energy Converters (WECs) implemented onto grid systems will increase, which are driven by policies designated to deliver cleaner energy; high wind penetration systems (islands) will likely feature energy storage and will need improved weather forecasting and tools to efficiently dispatch existing plant generation to deal with the variability; there will be a greater need for participation in ancillary services; and wind power plants will need to be tested to ensure compliance with standards. Available at http://www.cigre.org
Kiviluoma, J., Meibom, P., Holittinen, H., (2006). “Modelling of hydro and wind power in the regulation market”, proceedings of the Nordic Wind Power Conference 2006, Espoo, Finland, May.
The Nordic electricity market is organized around a day-ahead market where customers and producers buy and sell electricity for delivery for the following day. As increasing amounts of wind energy is added to the system, wind power prediction errors will have a large impact on regulation reserves and costs. This study investigates a model methodology developed to evaluate the economic effects of regulation costs from wind power prediction errors. Problems and issues related to developing a realistic model of the regulating power market are addressed, including the interaction between the spot market and regulating power market. Results show that wind integration onto a hydropower-dominated system with flexible hourly levels should not encounter any major challenges with regulation, even with large wind penetration levels.
Kiviluoma, J., Holttinen, H., (2006). “Impacts of Wind Power on Energy Balance of a Hydro Dominated Power System”, proceedings of the European Wind Energy Conference and Exhibition 2006, Athens, Greece, March.
This study looks at the Nordic electric system where hydropower is used to compensate for the uncertainty and variability of wind. Although there are no present issues involved with regulation of wind power in a hydro-dominated system, indirect issues arise due to the low marginal costs of hydropower offsetting other forms of generation out of the market. To assess the dependencies between wind and hydro power, a detailed energy system market model (WILMAR) of the Nordic countries and Germany is implemented, using an hourly operating time-scale along with wind penetration levels of Baseline (no wind), 10%, 20%, and 30%. Results from the 30% wind penetration levels show the cost duration curve falling significantly. Generally, nuclear or CHP can be accounted as marginal power, but during wind periods, the price may even go down to zero. Such a case would result in existing or
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potentially planned generators and investments to not be profitable or feasible. Techniques to mitigate these issues included new transmission capacity to the continental grid or additional energy consumption in the form of heat pumps, plug in electric vehicles or hydrogen production. Available at http://www.ewec2006proceedings.info/allfiles2/113_Ewec2006fullpaper.pdf
Luickx, P.J., Delarue, E.D., D’haeseleer, W.D., (2009). “The Examination of Different Energy Storage Methods for Wind Power Integration,” KULeuven Energy Institute, 2009.
This study explores pumped hydroelectric systems and heat pumps as two energy storage options based on current technologies. Using a Mixed Integer Linear Programming model for dispatch and unit commitment, evaluation of storage options are evaluated in terms of cost effectiveness and emission savings. Results show that pumped storage hydro systems can offer balancing and peak shaving services to the system, thus assisting in loss of load expectancy and cost savings. Storage of wind energy as heat through heat pumps remains economical as long as the heat produced is valuable and the high coefficient of performance of the heat pumps leads to significant emission savings. Available at http://www.mech.kuleuven.be/tme/research.
Loutan, C., Hawkins, D., Blatchford, J., et al., (2007). “Integration of Renewable Resources: Transmission and operating issues and recommendations for integrating renewable resources on the California ISO-controlled Grid,” California Independent System Operator.
This comprehensive report conducted by the California Independent System Operator (CAISO) focused on operational and transmission topics associated with the addition of substantial amounts of renewable energy sources to the California grid system. California adopted an aggressive Renewable Portfolio Standard (RPS) to incorporate 20% renewable generation by the end of 2010. The operations component of this study concluded that these goals are possible; however, a list of twelve recommended changes to operating practices needed in order to accomplish the RPS levels was presented. The transmission component of the study focused on the feasibility analysis for the proposed Tehachapi Transmission Project. A series of transmission system recommendations were presented, including suggested wind generator types and power systems requirements. Available at http://www.caiso.com/1ca5/1ca5a7a026270.pdf.
Maddaloni, J.D., Rowe, A.M., Kooten, G.C., (2008) “Network constrained wind integration on Vancouver Island,” Energy Policy, Vol. 36, pgs. 591-602, 2008.1
This study examined the operational changes and costs to the existing power system on Vancouver Island that would occur with increasing levels of wind power penetration. Vancouver Island’s current generator mix is dominated by hydropower (66% of total capacity) with a smaller amount of gas turbines (34%). Lacking any actual wind power data for the area, the authors used 30 m wind speed data from a two-week period and extrapolated that data to the 113 m hub height for an Enercon 70 wind turbine (a 2 MW machine). They also lacked empirical data to calculate the site specific wind shear factor, so
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they used a factor of 0.14 based on the local vegetation. The estimated wind speed at hub height from a single location was then run through the appropriate manufacturer’s power curve and multiplied to simulate increasing levels of wind power penetration (defined in this study as the nameplate capacity of wind divided by the peak historical demand). Such analysis ignores smoothing of the wind’s variability due to spatial diversity. The power flow model employed assumed perfect knowledge of the wind (i.e., it neglected the uncertainty of the wind).
The study concluded that operational costs declined steeply at penetrations up to 20%, and then more gradually to maximum system operating cost savings of 15% at a wind penetration of 50%, at which point the operational costs began to rise again. Not considered were tax credits, excess wind generation revenue potentially sold to the mainland, or any attempt to quantify the capacity value of wind. A comparison of the wind farm’s utilization factor (capacity factor of energy actually realized after curtailments) with and without transmission constraints shows that adding 100 MW of transmission capacity between two critical busses would allow wind penetration levels of 15% before curtailment would occur, versus 10% in the constrained case. Finally, the hydropower findings are based on Canadian water license rental rates for 2006 (hydro is charged $1.086/MWh and $0.006/1000m3 of throughput water). This allowed the authors to give hydropower a “fuel” charge. Hydro- generation costs vary between $1.092/MWh when operating at full capacity and $1.133/MWh near minimal capacity.
Maddaloni, J.D., Rowe, A.M., Kooten, G.C., (2009). “Wind integration into various generation mixtures,” Renewable Energy, Vol. 34, pp. 807-814, 2009.
This study used the same assumptions as the previous study [Maddaloni et al. 2008] by the same authors in a sensitivity analysis of different generation mixes. The existing generation mix on Vancouver Island was thus replaced with a generation mix simulating the Canadian national aggregate, the US national aggregate, and the Northwest (US) power pool’s generation mixes. The wind farm capital cost assumption was tripled in this study to $1800/kW. At this level, system operating costs were shown to rise at all wind penetration levels. The system operating costs increased the most (up to $35/MWh at 90% wind penetration) for the Canadian (hydro dominated) scenario, as wind capital and fixed operations and maintenance (O&M) costs overcame savings in fuel and variable O&M costs.
CO2 emissions savings ranged from 17, 70, and 85 kg/MWh for the Canadian, NWPP, and US generation mixtures, respectively.
Matevosyan, J. (2006). “On the Coordination of Wind and Hydropower,” Proceedings of 6th International Workshop on Large-Scale Wind Power Integration, October 2006.
This is a review of international literature that classifies existing wind and hydropower integration reports into four more specific categories: maximization of combined wind and hydro generator profits, optimized use of available transfer capability (ATC), investigations into planning methods that minimize imbalance costs, and coordination with pumped storage to produce piecewise firm blocks of aggregated energy. With regard to common profit maximization, the reviewed studies found that optimized coordination led to reduced
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water spillage, and this effect is greater in regions where wind and demand are correlated (winter peaking regions). With regard to ATC, coordination and geographic diversity reduce curtailments; however, wind is an additional constraint on hydropower that can reduce efficiency and increase maintenance costs. Finally, the last two categories of studies discuss the role of hybrid systems, point value versus probabilistic forecasting, and the role of transmission congestions in determining storage size.
Meibom, P., Kiviluoma, J., Barth, R., Brand, H., Weber, C., Larsen, H.V., (2007). “Value of electric heat boilers and heat pumps for wind power integration,” Risoe National Laboratory, 2007.
This study analyzes the economic value of implementing electric heat boilers and heat pumps in combined heat and power plants in the Northern European power system. The value of electric heat boilers and pumps result from the reduction in curtailment of wind and in the savings of various fuels used in the combined heat and power plants. Several benefits are concluded in the report, including the reduction in curtailment of wind power production, reduction of price for regulation power, and an added value to wind power resulting from the reduction of the hours with very low power prices.
Milligan, M., Porter, K., (2005). “Determining the Capacity Value of Wind: A Survey of Methods and Implementation,” Presented at WINDPOWER 2005, NREL/CP-500-38062.
This paper provides a summary of several methodologies for determining the capacity value of wind. The methods came from several wind integration studies and system operation practices from regions of the U.S. with different levels of wind variability and different views on the status of wind as a capacity resource. Discussion was provided on such metrics as Effective Load Carrying Capability (ELCC), Forced Outage Rate (FOR), and Loss of Load Probability (LOLP), and how the implications of these metrics differ when applied to intermittent generating resources, such as wind, as opposed to conventional generating units. Results are presented that show wind capacity value calculations throughout the U.S.
North American Electric Reliability Corporation, (2009). “Special Report: Accommodating High Levels of Variable Generation”, NERC, April.
This report builds on current experiences with variable generation to propose new practices from the traditional planning and operating methods in the North American Bulk power system. A summary is given for the primary reliability concerns associated with integrating large amounts of variable resources. A recommendation is proposed for study and coordination efforts needed to build a foundation for integration efforts and techniques. Other recommendations cited in the report for the purpose of easing variable integration include using different types of variable sources (e.g. wind, solar, oceanic etc.), geographic diversity, and advanced control systems. Transmission upgrades, flexible generator additions, new planning approaches, wind and solar technologies, and access to wider balancing areas are all discussed.
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Pete, C., (2010). “Implications on hydropower from large-scale integration of wind and solar power in the West: results from the Western Wind and Solar Integration Study,” Thesis Report, Northern Arizona University Mechanical Engineering Department, 2010.
This study follows on the Western Wind and Solar Integration Study with an in-depth analysis of hydropower operations in the study footprint. The estimated 2017 load being served is 60 GW, with up to 30 GW of wind power and 4 GW of existing hydropower. The inherent flexibility in hydropower facilities, often combined with reservoir storage, play a significant role in balancing the load with variable generation. Hydropower operations are statistically analyzed while comparing differences between scenarios and renewable energy penetration levels. Eight hydropower facilities, including Glen Canyon Dam, Hoover Dam, and one pumped hydro storage facility, were analyzed in depth since their capacities were large enough to make a difference as a balancing resource. Several case comparisons were performed demonstrating the value and change in hydro operations, including the degree and nature of change in generation schedules. Results from the study focus on benefits of hydropower as a balancing resource in the WECC, the added value that hydropower provides to renewable generation, and reductions in system operating costs (by nearly one billion dollars) when offsetting more expensive generation systems. Available from the cline library at http://www.nau.edu/library/
Piwko, R., Clark, K., Freeman, L., Jordan, G., Miller, N., (2010). “Western Wind and Solar Integration Study,” NREL Subcontract Report, 2010.
This study presents insight into the cost and operational impacts due to the variability and uncertainty of high levels of renewable generation, including distributed photovoltaic systems, concentrated solar power systems with six hours of thermal storage, and wind power serving up to 35% of the load energy in the WestConnect region (5% from solar and 35% from wind). This study focuses on the overall operational costs and savings due to fuel and emissions, and not on the capital cost to develop wind and solar sites. It was assumed up to 23% renewable generation penetration levels would be supplied in the rest of the WECC to address concerns of export variability between the study footprint and neighbouring regions.
For the study year of 2017, the estimated peak load being served is 60 GW, with levels up to 30 GW of wind power and 4 GW of existing hydropower. Wind data was developed for the western United States at 2-km and 10-minute resolution by 3TIER group. The State University of New York/Albany developed the solar data set for the United States at 10-km and hourly resolution. Analysis was conducted using General Electric’s Multi-Area Production Simulation Model for the load years 2004, 2005, 2006, examining the inter- annual variability. Three different study scenarios were conducted using several penetration levels, including: In-Area Scenario – each state meets its renewable energy requirements with best resources within its boundaries; Mega Project Scenario – the best available renewable energy resources were utilized in order to meet the renewable energy requirements within the entire study footprint with no preference for location due to state boundaries (i.e., most wind was located in Wyoming with high quality of wind resource, thus requiring new high voltage transmission); and the Local Priority Scenario – similar to the Mega Project but with the added benefit of a 10% capital cost reduction for using in-state resources. Statistical and
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operational analyses were conducted for these scenarios and under numerous operational sensitivities. Major findings from the report conclude it is feasible from a technical standpoint to accommodate up to 30% wind and 5% solar penetration assuming that extensive control area cooperation and/or consolidation would be implemented. Significant savings in operating costs can be gained from wind and solar of up to $20 billion per year and emission levels could be reduced by 120 million tons per year at the 30% wind penetration level. Lastly, integration of state-of-the-art forecasts for wind and solar is crucial in the unit commitment process resulting in a reduction of WECC operating costs by nearly $5 billion per year. Available at http://wind.nrel.gov/public/WWSIS/.
Piwko, R., Xinggang, B., Clark, K., et al. (2004). “The Effects of Integrating Wind Power On Transmission System Planning, Reliability, and Operations, Report on Phase 1: Preliminary Overall Reliability Assessment,” Prepared for the New York State Energy Research and Development Authority, by General Electric’s Power Systems Energy Consulting, Schenectady, NY.
The New York Independent System Operator (NYISO) and the New York State Energy Research and Development Authority (NYSERDA) conducted a two-part study with GE Energy Consulting to investigate the impacts of integrating large amounts of wind into the NYISO. Phase 1 of this report considered the impacts of wind integration on system reliability. The reliability concerns were addressed on the basis of fatal flaw transmission constraints, Loss of Load Expectation (LOLE) estimates, and contemporary operating protocols of the NYISO. A total capacity of 10,026 MW from 101 hypothetical wind sites was analyzed, which represented the estimated level needed to meet future Renewable Portfolio Standard (RPS) goals. Conclusions of the study indicated that few changes would be needed to the existing system operations procedures to accommodate wind levels up to 10% of peak load. The study also concluded that the most significant impacts of the wind integration would relate to load following reserve levels and unit commitment concerns, with only modest effects on regulation. Available at http://www.uwig.org/phase%20_1_feb_02_04.pdf.
Piwko, R., Xinggang, B., Clark, K., et al. (2005). “The Effects of Integrating Wind Power On Transmission System Planning, Reliability, and Operations, Report on Phase 2: System Performance Evaluation,” Prepared for the New York State Energy Research and Development Authority, by General Electric’s Power Systems Energy Consulting, Schenectady, NY.
Phase 2 of this study focused on evaluating the system performance impacts of large-scale wind integration into the New York State Bulk Power System (NYSBPS). This phase provided a more in-depth analysis of the 10% peak load wind scenario (3,300 MW) from a number of performance perspectives. Day- and hour-ahead markets, economic dispatch, forecast performance, and ancillary service concerns were addressed in detail. The outcome was to establish a list of recommended changes or lack of changes to the existing operating procedures that would be necessary to accommodate large amounts of wind. The study found that the existing market structure in the New York system was sufficient to incorporate the proposed wind penetration levels, the investment in forecasting was advantageous, and the imbalance penalties for wind should be eliminated. Several other recommendations regarding transmission and ancillary service matters are provided.
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Available at http://www.nyserda.org/publications/wind_integration_report.pdf Appendices available at http://www.nyserda.org/publications/wind_integration_apps.pdf
Princeton Energy Resources International (PERI), Vermont Environmental Research Associates, (2002). “Wind and Biomass Integration Scenarios in Vermont, Summary of First Phase Research: Wind Energy Resource Analysis,” Prepared under DOE project, number DE-FG01-00EE10762, March.
Technical and economic impacts were assessed for installations of various penetration levels of wind power in Vermont for the year 2010. The study also evaluated potential gains in value by integrating the Vermont wind with hydro generation in the Hydro-Québec system. The authors found no technical or economic barriers to absorbing large amounts of wind generation into the Vermont grid system. Overall system costs were found to increase during the scenario of integrating 810 MW into the New England Power Pool (NEPOOL), yet the wind integration was found to be up to 22% more valuable with the ability to export wind power to Hydro-Québec during favourable hours.
Söder, L., (1994). “Integration study of small amounts of wind power in the power system,” Royal Institute of Technology, Department of Electrical Power Technology, March.
The purpose of this report was to assess the impacts on hydro efficiency when integrating wind power into the Swedish power system using an hourly load and forecast model. It was assumed that wind penetration levels were adequately small, such that all balancing could be done using hydro resources. A portion of the Swedish hydro system was simulated for daily operation with hypothetical wind power. Results are included that discuss maximum wind levels that could be integrated without any major impacts to hydro system efficiencies. At larger levels of annual wind energy penetration, overall production levels increase given that it is necessary to accommodate for hydro efficiency losses. Available at http://www.eps.ee.kth.se/personal/lennart/lennart_report_mars94.html
Suul, J.A., Uhlen, K., Undeland, T., (2008). “Wind Power Integration in Isolated Grids enabled by Variable Speed Pumped Storage Hydropower Plant,” in Proc. of IEEE International Conference on Sustainable Energy Technologies, Singapore, Nov., 2008
This study simulated the power system operation of an isolated grid located on the Faroe Islands (Denmark). The peak demand of this system is 70 MW; however, the greatest challenge with integrating wind into this system will be during periods of high wind power production (up to 10 MW) and low load (minimum loads of 14 MW). The power system was simulated for 80 seconds with a 4 MW hydropower unit tripping after 40 seconds. The contribution of up to 12 MW of variable speed pumped storage hydropower was considered. The pumped storage was capable of providing load-following and frequency response whether generating as a turbine or pumping. With the remaining power system operating at a limited range, less diesel generator capacity would be required and remaining units can be operated more efficiently, thus reducing fuel consumption. Furthermore, the pumped storage’s voltage source converter was also capable of providing control of grid voltage or
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reactive power independently of the active power flow. An overview of the configuration details for such a variable speed pumped storage hydropower control system is provided. Such a configuration will allow for greater penetration of wind power and reduced fuel consumption for the production of electricity.
Tande, J., Uhlen, K., (2004). “Cost Analysis Case Study of Grid Integration of Large Wind Farms”, Wind Engineering, Volume 28, pp. 265-273.
This paper investigates the challenges presented in a weak grid system with comparably large amounts of wind and hydro. Automatic generation control (AGC) schemes are evaluated, allowing for the feasibility of wind power production. The case study is based on an actual system with slight modifications considering the connection in Norway between a 200 MW wind power plant, a 150 MW hydropower system, and a typical distribution grid with a 200 MW thermal capacity limit. Results from the simulations show a wind power plant with rated capacity of up to 200 MW maybe connected assuming there is sufficient reactive control (e.g., using the reactive control capabilities of modern wind turbines with frequency converters) and AGC must be implemented to avoid overloading the system.
Tande, J., (2006). “Impact of integrating wind power in the Norwegian power system”, SINTEF Energy Research, April.
This report summarizes the facts about the impacts of wind power in the Norwegian power system and demonstrates options and benefits for large-scale wind integration. Results primarily from a literature study show that high penetration levels of wind power seem feasible. As wind penetration levels increase, operational challenges with respect to operating reserves, frequency control and transmission capacity are becoming notably important. Sufficient transmission capacity is suggested to be a key factor for improving efficiency in the Norwegian and European power systems that incorporate large amounts of wind. Several items and topic areas are highlighted for further investigation.
Troscher, T., Korpas, M., (2008). “A Power Market Model for studying the Impact of Wind Power on Spot Prices,” Proc. of 16th PSCC, Glasgow, Scotland, July 2008.
In this study, various levels of wind power, network constraints, and chronologies of combined heat and power, wind power production, hydro inflows, and load were modeled stochastically to estimate the (day-ahead) spot market energy prices under different scenarios. There were several simplifying assumptions made based on aggregating production: thermal units’ stop and start costs were neglected (an aggregate marginal cost curve for each zone was used), and hydro reservoir capacities were summed by zone. Additionally, to consider increasing levels of wind power production, between 100-500% of current production, the current production was multiplied, thereby linearly increasing variability and neglecting any of the benefits of spatial diversity. This was justified by recent data (not cited in report) indicating that Western Denmark may be nearing spatial diversity saturation with new additions coming from re-power installations. Levels of wind power production 300% or greater than current levels of production began to drive down energy
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prices significantly, suggesting an economic limit to wind power in the region of 50% of total electrical generation. Perhaps most relevant to the subject of wind and hydro integration was the finding that without Norwegian hydro power (Norway is a very strongly hydro dominated market), income to wind power producers dropped by 13.7%. This was attributed to hydro’s balancing benefits. Furthermore, increasing transmission to Norway by 1000 MW to relieve network constraints and allow for more balancing with hydro resources resulted in income increases of 9.3% to wind turbine owners. However, the net effect on consumer expenditure on electricity is small.
Ummels, B.C., Pelgrum, E., Kling, W.L., (2008). “Integration of large-scale wind power and use of energy storage in the Netherlands’ electricity supply,” IET Renewable Power Generation, Vol. 2, No. 1, pp. 34-46, 2008.
This study explores the opportunities for implementing energy storage with large-scale wind power into the future layout of the Dutch electrical system as a direct result from high wind power penetration during low-load hours. Using a central unit commitment and economic dispatch model, three large-scale energy storage technologies, including pumped hydro accumulation storage, underground pumped hydro accumulation storage, and compressed air energy storage, are investigated using several wind power penetrations and scenarios. Results show that the operational cost savings from storage increase with wind penetration, but due the large investment costs, energy storage units are unlikely to have a profitable exploration. Additionally, an alternative solution is investigated using the installation of heat boilers to increase operational flexibility at selected combined heat and power units. Results from the installation of heat boilers is found to be considerably more efficient and is a likely solution for the integration of large-scale wind power in the Netherlands.
Ummels, B.C., Pelgrum, E., Kling, W.L., Droog, H., (2007). “Energy Storage Options for System Integration of Offshore Wind Power in the Netherlands,” 2007.
This study investigates the opportunities of energy storage in the Netherlands’ power supply in 2020 as large amounts of wind power are planned to be integrated into the system. Using a chronological production cost simulation area, the operational cost savings and total emission reductions are determined using four types of energy storage systems: pumped accumulation storage, underground pumped accumulation storage, compressed air energy storage, and tripling the interconnection capacity between the Netherlands and the hydropower systems of Norway. Results from this study show that up to 10 GW of wind power does not require the addition of energy storage from a technical point of view. Results from the simulation have shown that the compressed air energy storage and the expansion of the interconnection capacity have the highest potential for implementation since they both have positive revenue values in all scenarios. Alternatively, it was discovered that the
addition of energy storage systems leads to additional CO2 emissions at the system level due to increased operating hours of base-load coal-fired plants at the expense of peak-load gas- fired plants.
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U.S. Department of Energy, (2008). “20% Wind Energy by 2030: Increasing Wind Energy’s Contribution to U.S. Electrical Supply”, Produced for the U.S. Department of Energy by NREL, DOE/GO – 102008-2567, July.
This comprehensive report details the feasibility of generating 20% of the U.S. electricity demand (e.g. 20% penetration by energy) with wind power by the year 2030, representing a broad-range synopsis of U.S. wind integration efforts. Wind turbine technology, manufacturing capability, and transmission concerns were thoroughly addressed, as well as wind integration issues pertaining to electric system operations and market structure. The study found that the installed wind capacity would have to increase to about 300,000 megawatts (MW), roughly ten times the amount installed during the study release time. The report concluded that significant changes would be needed in the American energy market, along with transmission and manufacturing upgrades. The projected impacts of 20% wind
generation include: reductions on the order of 825 million metric tons of CO2 annually, 4 trillion gallons of water savings, increased energy security through a diversified energy portfolio, and domestic job creations. The DOE study found that cost increases for the 20% wind scenario would be as little as 0.06 cents (in 2006 U.S. dollars) per kilowatt-hour of total generation. Initial capital costs would be high, but long-term energy costs would be lower due to decreases in operations, maintenance, and fuel costs. Available at http://www1.eere.energy.gov/windandhydro/pdfs/41869.pdf
Vogstad, K.-O., (2000). “Utilising the complementary characteristics of wind power and hydropower through coordinated hydro production scheduling using the EMPS model”, a SINTEF Technical Report A5187, Proc. of the Nordic Wind Energy Conference, Trondheim, Norway, March, 2000.
Since the Norwegian electrical generation mix in 2000 was almost entirely hydropower, one cannot expect production cost savings with a fuel that is replenished naturally. So this paper is a departure from a cost/benefit analysis of adding wind power to the electrical generation mix and comparing production cost savings from reduced fossil fuel costs to the integration costs of managing a variable resource. The short-term variability of wind is outside the scope of this paper, which models wind energy as run-of-the-river hydro for 30 years of weekly averaged data. This paper found a very strong inverse seasonal correlation between wind and hydro inflows, and a strong correlation between wind power production (high in winter) and the winter peaking demand of this cold country. Thus, when the nation’s hydro production scheduling model (EMPS) was run with increasing levels of wind power, there was less hydro spillage. Therefore, even though wind power reduced spot prices, the aggregated value of combined wind and hydro energy increased with increasing wind power due to less hydro spillage. This benefit decreased with increasing levels of wind power penetration. Such an analysis would benefit hydro dominated utilities that are considering an investment in wind. Available at http://folk.ntnu.no/klausv/publications/Trondheim2000.pdf
Wang, R. and Baker, D., (2005). “Alberta Wind Power Variability Study,” prepared by Phoenix Engineering Inc., submitted to Alberta Electric System Operator.
This study investigated the 1-minute and 10-minute wind power variability levels for simulated wind power output from hypothetical wind development scenarios in Alberta. A
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model was created to simulate wind power variability on these short-term timescales by using a multi-turbine power curve approach. Simulated values were validated against actual measured wind power data. The effects of geographic diversity on short-term wind variability levels were also considered. Several tables and plots were presented, summarizing the normalized wind power fluctuation values for existing wind power facilities (WPF) and simulation scenarios. It was concluded that the wind power variability as a percentage of installed capacity was reduced when the aggregate fluctuations of multiple spatially diverse WPFs were compared to any single facility. The results were intended to aid the Alberta Electric System Operator (AESO) in understanding the reliability impacts of wind variability on the Alberta Interconnected Electric System (AIES).
Wiser, R., Bolinger, M., (2009). “2008 Wind Technologies Market Report”, produced for the U.S. Department of Energy by NREL, DOE/GO-102009-2868, July.
This report analyzes an assortment of developments in the wind market centered on the United States, including trends in wind project installations, turbine technology and prices, project costs and performance, and overall wind power prices. Additionally, the report details trends in project cost financing, a key issue in current economic conditions, as well as trends in project ownership, public policy, and wind integration. Available at http://www.windpoweringamerica.gov/pdfs/2008_annual_wind_market_report.pdf
Zavadil, R. (2006). “WAPA Wind Integration Study,” EnerNex Corporation, Knoxville, TN.
EnerNex conducted a wind integration feasibility study to determine the level of wind generation that could be integrated into the Upper Great Plains Region control area of the Western Area Power Authority (WAPA). Correlation between wind trends in the Dakotas and water runoff in the Missouri River Valley Basin were investigated. Daily and seasonal profiles were made for different capacity factors for five wind penetration levels. A small inverse correlation between wind velocity and hydro runoff was found for 2- and 3-year running averages. A statistical correlation was established linking years of low wind speed by preceding years of average hydro runoff.
Zavadil, R., (2007). “Avista Corporation Wind Integration Study,” Enernex Corporation, Final Report.
This study estimated the incremental costs of integrating various levels of wind generation into the Avista control area. Penetration levels ranged from 5-30% of the control area peak load, with respective integration costs ranging from $2.75-$8.84 per MWh. Avista’s LP model was used to optimize operations for lowest cost, both including and excluding wind generation. Hydro generation scheduling was modeled differently in four scenarios. The report concluded that short-term markets can reduce the costs associated with wind variability, and shared operational planning between wind facilities and system operators can reduce integration costs. The report also concluded that forecasting errors increase integration costs and geographic diversity of wind installations will influence integration costs.
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APPENDIX B. Bibliography of Wind Integration Reports
This appendix presents an extensive list of reports regarding wind integration. This list includes all reports cited in the body of this report plus others that may be of interest. The reports are organized alphabetically by country of origin (Source: Northern Arizona University).
Table B-1: Comprehensive list of wind integration reports. Country/ continent (leading author) Topic Reference Di Marzio G, Fosso O, Uhlen K, Pálsson M P, Large-scale wind power Wind integration - voltage stability limits and modal analysis, 15th Power System Belgium Integration Computation Conference, PSCC 2005, Liege Distributed Luther, M. Grid operation and management with large scale wind generation, Generation, European Conference on Integration of Renewable Energy Sources Wind and Distributed Generation in Energy Systems, Brussels 25- Belgium Integration 26.9.2001 Wind Integration, Energy AESO, 2006. Wind Integration Impact Studies. Phase 2: Assessing the Canada Markets impacts of increased wind power on AIES operations and mitigating measures. Bélanger, Camille and Gagnon, Luc 2002. Adding Wind Energy to Wind- Hydropower, Energy Policy, 30, pp. 1279-1284. Available at: Canada Hydro http://www.elsevier.com/locate/enpol Wind Benitez, Liliana E.; Benitez, Pablo C.; and van Kooten, G. Cornelius, Integration, 2006. The economics of wind power with energy storage, Energy Economics Wind- 2007, doi:10.1016/j.eneco.2007.01.017. Available at Canada Hydro www.elsevier.com or at www.sciencedirect.com Denault, M., Dupuis. D., Couture-Cardinal. S., (2009). Complementarily Wind- of hydro and wind power: Improving the risk profile of energy inflows, Energy Canada Hydro Policy, 37, pp. 5376-5384. Available at www.sciencedirect.com Hurdowar, Diana; Lafreniere, Marc; Welt, Francois; Bridgeman, Wind Stuart G. 2005; Girling, Bill; Gawne, Kevin; and Hunter, Kelly. Integration, Studying Short-Term Effects of Integrating Wind in a Hydro System: Manitoba Wind- Hydro Case Study. Proceedings of the Waterpower XIV Conference, Canada Hydro Austin, TX, July, 2005. Wind Integration, Power Kehler, John et al. (AESO) 2005. Incremental Impact on System Operations Canada Systems with Increased Wind Power Penetration. Phase 1: Final. Krau, S., Lafrance, G., Saulnier, B., Cohen, J., 2003. Integrating the Energy Markets in North America: Conditions Helping Large-scale Integration Wind- of Wind Power. 23rd Annual North America Conference of the Canada Hydro AMEE/USAEE/IAEE Mexico, Oct. 19-21 2003.
B-1 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Wind Integration, Lafrance, G, et al. 2002, Assessment of the Impact of Wind Power Power Penetration on the Vermont Electricity Grid, Hydro Quebec Institut de Canada Systems Recherche Maddaloni, J.D., Rowe, A.M., Kooten, G.C., (2008) Network Wind constrained wind integration on Vancouver Island, Energy Policy, Vol. 36, pgs. Canada Integration 591-602, 2008. Maddaloni, J.D., Rowe, A.M., Kooten, G.C., (2009). Wind integration Wind into various generation mixtures, Renewable Energy, Vol. 34, pp. 807-814, Canada Integration 2009. Wind Integration, Pourbeik, Pouyan, 2004. Integration of Wind Energy into the Alberta Power Electric System - Stage 1: Voltage Regulation Study. Prepared for AESO by Canada Systems Electric Systems Consulting. Pourbeik, Pouyan, 2004. Integration of Wind Energy into the Alberta Wind Electric System - Stage 2 and 3: Planning and Interconnection Criteria. Canada Integration Prepared for AESO by Electric Systems Consulting. Wind Integration, Energy Markets, Wind Pourbeik, Pouyan, 2004. Integration of Wind Energy into the Alberta Power Electric System - 4: Operations Impact. Prepared for AESO by Electric Canada Variability Systems Consulting. Wind Integration, Wang, Rui and Baker, David 2005. Alberta Wind Power Variability Wind Study, Alberta Electric System Operator, Calgary Place 2500, 330 – Power 5th Ave. SW Calgary, AB T2P 0L4, July. Available at Canada Variability http://www.aeso.ca/files/WindVariabilityFinalReport.pdf Wind Maritimes Area Wind Power Integration Study Summary Report, 2007, Canada Integration NBSO Wind Project Wind- Yanfang, F., Yibo, W., Qin, C. Wind-Hydro Hybrid Power System China Hydro Stability Analysis. Xinjiang University Danielian, Regis, et al. 2007, Surface-Layer Wind and Turbulence Profiling Wind from LIDAR: Theory and Measurements. Vestas Wind Systems. Available Denmark Forecasts at www.risoe.dk/rispubl/art/2007_86_paper.pdf Systems Energinet.DK, Recent Energinet.dk Papers (3 & 4 quarter 2005) on: Denmark Analysis System Analysis and Model Tools, December 2005 Systems Energinet.DK, Recent Energinet.dk Publications (4 quarter 2007, 1 quarter Denmark Analysis 2008) on: System analysis and model tools, March 2008 Energinet.dk, 2004. Regulation TF3.2.5 Wind turbines connected to grids Wind with voltages above 100kV, Dec 2004. Available at Denmark Integration http://www.energinet.dk/en/servicemenu/Library/Library.htm#
B-2 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Kristoffersen, J.R. The Horns Rev Wind Farm and the Operational Wind Experience with the Wind Farm Main Controller, Proceedings of Copenhagen Denmark Integration Offshore Wind, October 2005, Copenhagen, Denmark. Lund, H, 2005. Large-scale integration of wind power into different energy Wind systems, ENERGY 30 (13): 2402-2412 OCT 2005 Available at Denmark Integration www.sciencedirect.com Lund, H. Large-scale integration of optimal combinations of PV, wind, and wave power into the electricity supply, Renewable Energy Vol. 21(4), pp 503-515, April 2006 Available at Wind http://www.elsevier.com/wps/find/journaldescription.cws_home/9 Denmark Integration 69/description Wind Lund, H. and Münster, E., 2006. Integrated energy systems and local energy Integration, markets, Energy Policy, Volume 34, Issue 10, July 2006, Pages 1152- Energy 1160, Elsevier. Available at www.elsevier.com or at Denmark Markets www.sciencedirect.com Meibom, P., Kiviluoma, J., Barth, R., Brand, H., Weber, C., Larsen, Wind H., Value of electrical heat boilers and heat pumps for wind power integration, Integration, European Wind Energy Conference (EWEC), 27 February – 2 Heat March, 2006, Athens, Greece. Available at Denmark Pumps http://www.risoe.dk/rispubl/art/2007_76.pdf Wind Integration, Meibom, P., Kiviluoma, J., Barth, R., Brand, H., Weber, C., Larsen, Heat H.V., (2007). Value of electric heat boilers and heat pumps for wind power Denmark Pumps integration, Risoe National Laboratory, 2007. Meibom, P., Weber, C., Barth, R., Brand, H., Operational costs induced Wind by fluctuating wind power production in Germany and Scandinavia, pp 133- Power 154, In: Swider, D., Voss, A. (Eds), Deliverable D5b – Disaggregated Variability, system operation cost and grid extension cost caused by intermittent RES-E grid Wind integration, GreenNet-EU27, 2006. Available at Denmark Integration http://www.risoe.dk/rispubl/reports/ris-r-1608_196-205.pdf Wind Integration, Pedersen, J.; Eriksen, P.B.; Orths, A., 2006. Market Impacts of Large- Energy Scale System Integration of Wind Power, European Wind Energy Denmark Markets Conference EWEC 2006, Athens, Greece.
See risoe.dk wind energy publications list at http://risoe.dk/Risoe_dk/Home/Knowledge_base/publications/V Denmark EA.aspx Wind Ackermann, T.; Centeno-Lopez, E.; and Söder, L. Grid Issues for Integration, Electricity Production Based on Renewable Energy Sources in Spain, Portugal, Systems Germany, and United Kingdom. Fritzes - Statens offentliga utredningar, Europe Analysis 2008, Appendix to SOU 2008:13
B-3 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Eriksen, P B, Ackermann, T, Abildgaard, H, Smith, P, Winter, W, Garcia, J R, 2005. System operation with high wind penetration. The Wind transmission challenges of Denmark, Germany, Spain and Ireland. IEEE Integration, power & energy magazine, nov/dec 2005. Available at Systems http://ieeexplore.ieee.org/iel5/8014/32593/01524622.pdf?tp=&arn Europe Analysis umber=1524622&isnumber=32593 Wind ETSO, 2007. Balance management harmonisation and integration. 4th Europe Integration report, January, 2007. EWEA, 2005. Large scale integration of wind energy in the European power Wind supply: analysis, issues and recommendations. A report by EWEA Europe Integration (December 2005). Available at http://www.ewea.org/ EWEA, 2005. Large scale integration of wind energy in the European power supply: analysis, issues and recommendations. Electrical Grids and Wind Wind Power: the present situation in Europe. Available at Europe Integration http://www.ewea.org/ EWIS, 2007. European Wind Integration Study final report phase I, 2007. Wind Available at http://www.ucte.org/_library/otherreports/2007-01-15- Europe Integration Final-report-EWIS-phase-I-approved.pdf DeMeo E A, Grant W, Milligan M, Schuerger M J, Wind plant Wind integration: costs, status and issues, IEEE power & energy magazine, Europe Integration nov/dec 2005. Luickx, P.J., Delarue, E.D., D’haeseleer, W.D., (2009). The Examination of Different Energy Storage Methods For Wind Power Wind- Integration, KULeuven Energy Institute, 2009. Available at Hydro http://www.mech.kuleuven.be/energy/resources/docs/papers/pdf/ Europe Systems WP%20EN2008-007.pdf Wind Integration, Wind- Hydro, Systems Nordel Wind Group, 2008. Wind Power in Nordel - system impact for the Europe Analysis year 2008. Systems Europe Analysis UCTE 2005: UCTE System Adequacy Forecast 2006 - 2016, Dec. 2005 Holttinen, H, 2004. The impact of large scale wind power production on the Nordic electricity system. VTT Publications 554. Espoo, VTT Processes, Wind 2004. 82 p. + app. 111 p. Available at Finland Integration http://www.vtt.fi/inf/pdf/publications/2004/P554.pdf Wind Holttinen, H, 2005. Impact of hourly wind power variations on the system Finland Integration operation in the Nordic countries. Wind Energy, vol. 8, 2, ss. 197 – 218.
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Country/ continent (leading author) Topic Reference Wind Integration, Energy Holttinen, H, 2004 Optimal Electricity Market for Wind Power, Energy Finland Markets Policy 33 Wind Integration, Holttinen, Hannele et. al. 2006. Prediction Errors and Balancing Costs for Wind Wind Power Production in Finland, Global Wind Power Conference, Finland Forecasts Adelaide, Australia, September. Holttinen, Hannele; Koreneff, Göran. 2007. Imbalance costs of wind power for a hydro power producer in Finland. Proceedings. European Wind Wind Energy Conference EWEC2007. Milan, Italy, 7 - 10 May, 2007. Integration, European Wind Energy Association, EWEA. Available at Wind- http://www.ewec2007proceedings.info/allfiles2/699_Ewec2007fullp Finland Hydro aper.pdf Holttinen, H, Vogstad, K-O, Botterud, A, Hirvonen, R, 2001. Effects of Large-Scale Wind Production on the Nordic Electricity Market. Proceedings of European Wind Energy Conference, EWEC'01. Wind Copenhagen, DK, 2 - 6 July 2001. CD-ROM. European Wind Finland Integration Energy Association Wind Kiviluoma, Juha and Holttinen, Hannele. Impacts of Wind Power on Integration, Energy Balance of a Hydro Dominated Power System, VTT Technical Wind- Research Centre of Finland, VTT, Finland. Available at Finland Hydro http://www.vtt.fi/publications/index.jsp Kiviluoma, Juha; Meibom, Peter; Holttinen, Hannele. 2006. The operation of a regulation power market with large wind power penetration. Nordic Wind Power Conference – NWPC’2006. Grid Integration Wind and Electrical Systems of Wind Turbines and Wind Farms. Finland Integration Hanasaari, Espoo, Finland, 22 - 23 May 2006 Wind Kiviluoma, Juha and Meibom, Peter and Holttien, Hannele 2006. Integration, Modelling of Hydro and Wind Power In The Regulation Market, VTT Wind- Technical Research Centre of Finland, VTT, Finland, May. Available at Finland Hydro http://www.vtt.fi/publications/index.jsp Wind Integration, Nordel, 2005. Enhancing Efficient Functioning of the Nordic Electricity Energy market, NORDEL, February 2005. Available at Finland Markets http://www.Nordel.org Wind Integration, Soder, L. and Holttinen, H. (2008). On methodology for modeling wind Power power impact on power systems, Int. J. Global Energy Issues, Vol. 29, No. Finland Systems 1&2, pp. 181-198
B-5 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Soder, L. et al. 2007, Experience from Wind Integration in Some High Penetration Areas, IEEE Transactions on Energy Conversion, Vol. 22, No. 1. Available at Wind http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?isnumber=4105991&a Finland Integration rnumber=4106017&count=29&index=1 Wind Integration, Burges, K., De Broe, A. M. & Feijoo, A. Advanced wind farm control Systems according to Transmission System Operator requirements. European Wind Germany Analysis Energy Conference, EWEC’03 Madrid, Spain, 16.–20.6.2003. DENA, 2005. Planning of the Grid Integration of Wind Energy in Germany, Onshore and Offshore up to the year 2020 (dena Grid study). Deutsche Wind Energie-Agentur Dena, March 2005. Available at Germany Integration http://www.dena.de/themen/thema-reg/projektarchiv/ Ensslin, C. 2006: The Influence of Modeling Accuracy on the Determination of Wind Wind Power Capacity Effects and Balancing Needs, PhD Thesis, Kassel Integration, University Press 2006. Available at http://www.uni- Wind kassel.de/upress/publi/schriftenreihe.php?erneuerbare_energien.htm Germany Forecasts l Ensslin, C., Ernst, B., Rohrig, K., Schlogl, F., 2003. Online-Monitoring and Prediction of Wind Power in German Transmission System Operation Centres. WWEC 2003 - World Wind Energy Conference, Cape Town, Wind South Africa, 2003. Available at http://www.regie- Integration, energie.qc.ca/audiences/3526- Wind 04/MemoiresParticip3526/Memoire_CCVK_14_EWEC_03_Be_En Germany Forecasts _HK_Ro.pdf Wind Erlich, I., Winter, W., Dittrich, A., 2006. Advanced Grid Requirements for Integration, the Integration of Wind Turbines into the German Transmission System. IEEE Systems PES, Montreal, 2006. Available at http://ieeexplore.ieee.org Germany Analysis (subscription required.) Ernst, B. 1999. Analysis of wind power ancillary services characteristics with Wind German 250 MW wind data. NREL Report No. TP-500-26969. 38 p. Germany Integration Available at http://www.nrel.gov/publications/ Focken, U., Lange, M., Waldl, H.-P. 2001. Previento – A Wind Power Wind Prediction System with an Innovative Upscaling Algorithm, In: Proceedings Germany Forecasts of EWEC’01, 2nd–6th July, 2001, Copenhagen. pp. 826–829. Focken, Ulrich, 2007. Optimal combination of European weather models for improved wind power predictions. In: Proceedings of EWEC’07, 7–10th May, 2007, Milan, Italy. Available at Wind http://www.energymeteo.de/de/media/paper34_forecastcombinatio Germany Forecasts n_pub.pdf
B-6 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Distributed Generation, Giebel, G., 2000: On the Benefits of Distributed Generation of Wind Energy Wind in Europe; PhD Thesis, Carl von Ossietzky Universität, Oldenburg, Germany Integration 2000. Available at http://www.drgiebel.de/thesis.htm Giebel, G, Brownsword, R, Kariniotakis, G, 2003. The State-of-the-art in Short-term prediction of wind power. A literature overview. EU project ANEMOS (ENK5-CT-2002-00665). Available at Wind http://anemos.cma.fr/download/publications/pub_2003_paper_E Germany Forecasts WEC03_SOTAGiebel.pdf Giebel, G, 2007. A Variance Analysis of the Capacity Displaced by Wind Wind Energy in Europe. Wind Energy 2007; 10:69-79. Available at Germany Integration www.interscience.wiley.com Wind Krauss, C., Graeber, B., M. Lange, 2006. Integration of 18 GW Wind Integration, Energy into the Energy Market - Practical Experiences in Germany, Energy Workshop on Best Practice in the Use of Short-term Forecasting of Germany Markets Wind Power, Delft 2006. Wind Germany Integration ISET, 2005. Wind Energy Report Germany 2005, ISET, Kassel, 2005. ISET, 2006. Private communication with Cornel Ensslin for the standard Wind deviation of variations time series. Available at www.renknow.net (search Germany Forecasts keyword “time series”) Rohrig, K. and Lange, B., 2006. Application of Wind Power Prediction Tools for Power System Operations, presented at the 2006 IEEE Power Wind Engineering Society General Meeting, Montreal, Canada, 2006. Germany Forecasts Available at http://ieeexplore.ieee.org Wind Rohrig, K. and Lange, B., 2007. Improvement of the Power System Integration, Reliability by Prediction of Wind Power Generation, IEEE PES general Wind Meeting 2007, Tagungsband, Tampa, FL USA 06/2007. Available at Germany Forecasts http://ieeexplore.ieee.org Rohrig, K., Sassnick, Y., Styczynski, Z., Völzke, R., 2006. Experiences Wind with operation of wind farms using wind forecasting tools, CIGRE 2006, Germany Forecasts Tagungsband, Palais de Congres, Paris 08/2006 Rohrig, K. et al., 2005. Advanced Control Strategies to Integrate German Offshore Wind Potential into Electrical Energy Supply, 5th International Workshop on Large-Scale Integration of Wind Power and Wind Transmission Networks for Offshore Wind Farms, Tagungsband, Germany Integration Glasgow 04/2005 Bakos, George, 2002. Feasibility study of a hybrid wind/hydro power-system Wind- for low-cost electricity production. Applied Energy 72 pp.599-608, 2002. Greece Hydro Available at http://www.elsevier.com/locate/apenergy
B-7 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Kaldellis, J.K., Kavadias, K.A., Vlachou, D.S., Electricity Load Management of APS Using Wind-Hydro Solution. Lab of Soft Energy Wind- Applications and Environmental Protection. Available at Greece Hydro www.theiet.org Kaldellis, J.K., 2001, Parametrical Investigation of the Wind-Hydro Wind- Electricity Production Solution Aegean Archipelago, Energy and Greece Hydro Conservation Management Wind Bryans, Leslie et al., 2006. Electric Power System Planning with the International Integration Uncertainty of Wind Generation, CIGRE Working Group. April, 2006. Ensslin, C., Milligan, M., Holttinen, H., O’Malley, M.J. and Keane, A. Wind Current Methods to Calculate Capacity Credit of Wind Power, IEA International Integration Collaboration, IEEE PES General Meeting, Pittsburgh, July 2008. Ernst, Bernhard et al. Predicting the Wind: Models and Methods of Wind Forecasting for Utility Operations Planning, IEEE Power and Energy Magazine, Vol. 5, Num. 6, Nov./Dec. 2007. Available at Wind http://ieeexplore.ieee.org/iel5/8014/4382976/04383126.pdf?tp=&a International Forecasts rnumber=4383126&isnumber=4382976 Wind GWEC, 2005. Wind Force 12, A blueprint to achieve 12% of the world's International Integration electricity from wind power by 2020. Available at http://www.ewea.org Holttinen, Hannele et al., 2006. Design and Operation of Power Systems with large Amounts of Wind Power, first results of IEA collaboration. Global Wind Wind Power Conference, Adelaide, Australia. September 18-21, International Integration 2006. IEA. 2007. State of the Art Task 25 Report: Design and operation of power Wind systems with large amounts of wind power. Available at International Integration http://www.ieawind.org/AnnexXXV/Publications/W82.pdf IEA: Variability of wind power and other renewables. Management options and strategies. 2005. Available at Wind http://www.iea.org/Textbase/publications/free_new_Desc.asp?PU International Integration BS_ID=1572 Wind Integration, IEC 61400-21, 2001. Wind turbine generator systems - Part 21: Power Measurement and assessment of power quality characteristics of grid connected International Char. wind turbines, Ed. 1.0, International Standard, 2001. Sims, Ralph E. H. et al., 2003. Carbon emission and mitigation cost comparisons between fossil fuel, nuclear and renewable energy resources for electricity generation. Energy Policy 31 (2003), pp. 1315-1326. Available International Emissions at www.elsevier.com/locate/enpol Sørensen, P.; Norheim, I.; Meibom, P.; Uhlen, K., Simulations of wind Wind power integration with complementary power system planning tools. Electric International Integration Power Syst., Volume 78, Issue 6, June 2008, Pages 1069-1079.
B-8 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Tande J O, Muljadi E, Carlson O, Pierik J, Estanqueiro A, Sørensen P, O'Malley M, Mullane A, Anaya-Lara O, Lemstrom B (2004) Dynamic models of wind farms for power system studies - status by IEA Wind Wind R&D Annex 21, European Wind Energy Conference (EWEC’2004), Integration, 22-25 November, London, UK. Available at Power http://www.energy.sintef.no/wind/iea_dynamic_models_EWEC'04 International Systems _paper.pdf Wind Bazilian, M., Denny, E. and O’Malley, M.J., Challenges of Increased Wind Ireland Integration Energy Penetration in Ireland, Wind Engineering, vol. 28, pp. 43-56, 2004. Bryans, L., J. McCann, Smith, P. and O’Malley, M.J., All island Wind Renewable Grid Study, IEEE PES, General Meeting, Tampa, June 2007. Ireland Integration Available at http://ieeexplore.ieee.org Wind Integration, Burke, D.J. and O’Malley, M.J., Optimal Wind Power Location on Power Transmission Systems – A Probabilistic Load Flow Approach, IEEE Ireland Systems PMAPS, Puerto Rico, May, 2008. Denny, E., Bryans, G., Fitzgerald, J. and O’Malley, M.J., 2006. A Quantitative Analysis of the Net Benefits of Grid Integrated Wind, IEEE Wind PES, General Meeting, Montreal, June 2006. Available at Ireland Integration http://ieeexplore.ieee.org Denny, E and O’Malley, M. J., 2005. Impact of increasing levels of wind generation in electricity markets on emissions reduction, Proceedings of the 7th IAEE European Energy Conference - European Energy Markets Wind in Transition, Bergen, Norway, Aug, 2005. Available at Integration, http://www.snf.no/iaee2005/7th%20IAEE%20European%20Energ Energy y%20Conference/Monday%20August%2029TH/Concurrent%20Ses Markets, sions%20I/Wind%20Power/E.%20Denny%20and%20M.%20O'Mal Ireland Emissions ley.pdf Wind Integration, Power Denny, E. and O’Malley, M.J., Impact of wind generation on emissions under Systems, alternative power system operation approaches, Proceedings of the University Ireland Emissions Power Engineering Conference, Cork, Sept, 2005. Denny, E. and O’Malley, M.J. Quantifying the Total Net Benefits of Grid Integrated Wind, IEEE Transactions on Power Systems, Vol. 22, no. 2, pp. 605 -615, 2007. Also presented at the IEEE Power Engineering Wind Society, General Meeting, Tampa, June, 2007. Available at Ireland Integration http://ieeexplore.ieee.org Wind Integration, Power Denny, E., and O’Malley, M.J., Wind Generation, Power System Operation Systems, and Emissions Reduction IEEE Transactions on Power Systems, Vol. Ireland Emissions 21, pp. 341 – 347, 2006. Available at http://ieeexplore.ieee.org
B-9 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Wind Department of Communications, Energy and Natural Resources, Ireland Integration 2008. All Island Grid Study. Available at www.dcenr.gov.ie Wind Integration, Doherty, R., Denny, E. and O’Malley, M.J., System operation with a Power significant wind power penetration, IEEE PES General Meeting, Denver Ireland Systems 2004. Available at http://ieeexplore.ieee.org Doherty, R, Bryans, L., Gardner, P., O’Malley, M.J., Wind penetration Wind studies on the Island of Ireland, Wind Engineering, vol. 28, pp. 27-42, Ireland Integration 2004. Doherty, R. and O’Malley, M.J., Establishing the role that wind generation may have in future generation portfolios, IEEE Transactions on Power Wind Systems, Vol. 21, pp. 1415 – 1422, 2006. Available at Ireland Integration http://ieeexplore.ieee.org Wind Doherty, R., Lalor, G. and O’Malley, M.J., Frequency Control in Integration, Competitive Electricity Market Dispatch, IEEE Transactions on Power Power Systems, Vol. 20, pp. 1588 - 1596, 2005. Available at Ireland Systems http://ieeexplore.ieee.org Doherty, R. and O'Malley, M.J. 2005. “Generation portfolio analysis Wind for a carbon constrained and uncertain future”, Proceedings of Integration, International Conference on Future Electricity Networks, Ireland Emissions Amsterdam, Nov. 2005. Available at http://ieeexplore.ieee.org Doherty, R., O’Malley, M.J., 2005. New approach to quantify reserve demand in systems with significant installed wind capacity, IEEE Wind Transactions on Power Systems, Vol. 20, pp. 587 -595, 2005. Ireland Integration Available at http://ieeexplore.ieee.org Doherty, R. and O’Malley, M., Quantifying Reserve Demands due to Wind Increasing Wind Power Penetration, IEEE Power Tech, Bologna, Italy, Ireland Integration June, 2003. Wind ESBI, 2004. Renewable Energy Resources for Ireland 2010 & 2020. Ireland Integration Sustainable Energy Ireland, 2004. ESBNG, ESB National Grid, 2004. Impact of wind power generation in Ireland on the operation of conventional plant and the economic implications, Wind February 2004. Available at Ireland Integration http://www.sei.ie/index.asp?locID=1030&docID=-1 Feeley, C., Bryans, A.G., Nyamdash, B., Denny, E., O’Malley, M.J., Wind The Viability of Balancing Wind Generation with Storage, IEEE PES Ireland Integration General Meeting, Pittsburgh, July 2008. Fox, B. et al. 2007. Managing the variability of wind energy with heating load Wind control, IET Intl. Conf. on Information and Communication Ireland Integration Technology in Electrical Sciences, Chennai, India, December 2007 Fox, B., Littler, T. and Flynn, D., 2005 Measurement-based estimation of Wind wind farm inertia, PowerTech 2005, St. Petersburg, Russia, 27-30 June Ireland Integration 2005
B-10 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Fox, B. and Flynn, D., 2005. Wind intermittency – mitigation measures and Wind load management, PowerTech 2005, St. Petersburg, Russia, 27-30 June Ireland Integration 2005 Fox, B., Bryans, L., Flynn, D., Jenkins, N., Millborrow, D., O’Malley, Wind M., Watson, R. and Anaya-Lara, Wind power integration; Connection and Ireland Integration system operational aspects, IET Power and Energy Series, 2007. Wind Integration, Gardner, P., et al., 2003. The Impacts of Increased Levels of Wind Power Penetration on the Electricity Systems of the Republic of Ireland and Northern Ireland Systems Ireland. Commission for Energy Regulation Wind Horne, J., Flynn, D., and Littler, T., Frequency stability issues for island Integration, power systems, IEEE PES Power Systems Conference & Exposition, Power October 2004. Available at Ireland Systems http://www.ucc.ie/academic/civil/staff/brian/CER03024.pdf Ilex, UMIST, UCD and QUB, 2004. Operating reserve requirements as wind power penetration increases in the Irish electricity system. Sustainable Energy Ireland, 2004. Available at Wind http://www.sei.ie/uploadedfiles/InfoCentre/IlexWindReserrev2FSF Ireland Integration inal.pdf Ilex Energy, Strbac, G, 2002. Quantifying the system costs of additional Wind renewables in 2020. DTI, 2002. Available at Ireland Integration http://www.dti.gov.uk/energy/developep/080scar_report_v2_0.pdf Kennedy, J. et al. 2007 Distributed diesel generation to facilitate wind power integration, IEEE PowerTech, Switzerland 2007.Denny, E., Malaguzzi Distributed Valeri, L., Fitz Gerald, J. and O’Malley, M.J. “Carbon prices and asset Generation, degradation – a costly combination for electric power systems,” Wind Proceedings of 30th International Association for Energy Economics, Ireland Integration Wellington, New Zealand, 18-21, February, 2007. Distributed Generation, Wind Kennedy, J. et al. Distributed generation as a balancing tool for wind Ireland Integration generation, IET Renew, Power Gener., Vol. 1(3), 2007, pp. 167-174. Smith, P., O’Malley, M.J., Mullane, A., Bryans, L., Denic, D.P., Bell, Wind K.R.W., Meibom, P., Barth, R., Hasche, B., Brand, H., Swider, D.J., Integration, Burges, K. and Nabe, C., Technical and Economic Impact of High Power Penetration of Renewables in an Island Power System, CIGRE, C6-102, Ireland Systems Paris, 2008. Wind Integration, Tuohy, A., Denny, E. and M.J. O’Malley, Allocation of System Reserve Wind Based on Standard Deviation of Wind Forecast Error, Nordic Wind Power Ireland Forecasts Conference, Denmark, November, 2007.
B-11 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Wind Integration, Tuohy, A., Denny, E., and O’Malley, M.J., Rolling unit commitment for Power systems with significant installed wind capacities, IEEE Power Tech, Ireland Systems Lausanne, Switzerland, July, 2007. Wind Integration, Tuohy, A., Meibom, P. and O’Malley, M.J., Benefits of Stochastic Power Scheduling for Power Systems with Significant Installed Wind Power, IEEE Ireland Systems PMAPS, Puerto Rico, May, 2008. Wind Integration, Tuohy, A., Denny, E., Meibom, P., Barth, R., O’Malley, M.J., Power Operating the Irish Power System with Increased Levels of Wind Power, IEEE Ireland Systems PES General Meeting, Pittsburgh, July 2008. Twohig, S., Burges, K., Nabe, C., Polaski K., and O’Malley, M.J., Wind Ultra High Wind Energy Penetration in an Isolated Market, IEEE PES Ireland Integration General Meeting, Pittsburgh, July 2008. Jaramillo, O.A. and Borja, M.A. and Huacuz, J.M. 2004. Using Hydropower to Complement Wind Energy: A Hybrid System to Provide Firm Wind- Power, Renewable Energy, 29, pp. 1887-1909. February. Available at Mexico Hydro http://www.elsevier.com/locate/renene Eleveld, H.F., Enslin, J.H.R., Groeman, J.F., van Oeveren, K.J., van Schaik, M.A.W., 2005: Connect 6000 MW-II: Elektrische infrastructuur op Netherlands zee. Kema 40510025-TDC 05-485000, September 2005. Jansen, C.P.J. de Groot R.A.C.T.: Connect 6000 MW: Aansluiting van 6000 MW offshore windvermogen op het Nederlandse elektriciteitsnet. Deel 2: Netherlands Net op land. Kema 40330050-TDC 03-37074B. oktober 2003. Hagstrøm E, Norheim I, Uhlen K, Large-scale wind power integration in Wind Norway and impact on damping in the Nordic grid, Wind Energy 2005; 8(3) Netherlands Integration pp 375-384. Wind Kling, W.L., et al., 2007. Transmission and System Integration of Wind Integration, Power in the Netherlands, Proceedings of the IEEE PES General Power Meeting, Tampa, 24-28 June, 2007, pp 6. Available at Netherlands Systems http://ieeeexplore.ieee.org Palsson M T, Toftevaag T, Uhlen K, Tande J O, Large-scale Wind Wind Power Integration and Voltage Stability Limits in Regional Networks, Netherlands Integration Proceedings of 2002 IEEE-PES Summer Meeting Palsson M T, Toftevaag T, Uhlen K, Tande J O, Control Concepts to Wind Enable Increased Wind Power Penetration. Proceedings of IEEE-PES Netherlands Integration Meeting, Toronto 13-18 July 2003 Wind Integration, Slootweg, J.G., Kling, W.L. 2003, The Impact of Large Scale Wind Power Power Generation on Power System Oscillations, Electric Power Systems Research Netherlands Systems 67
B-12 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Wind Integration, Ummels, B.C., et al., 2008. Energy Storage Options for System Integration of Power Offshore Wind Power in the Netherlands, Proceedings of European Wind Netherlands Systems Energy Conference, Brussels, 3-7 April 2008, 10 pp. Ummels, B.C., et al., 2007. Impacts of Wind Power on Thermal Generation Unit Commitment and Dispatch, IEEE Transactions on Energy Wind Conversion, vol. 22, issue 1, March 2007, pp. 44-51. Available at Netherlands Integration http://ieeeexplore.ieee.org Ummels, B.C., et al., 2008. Integration of Large-Scale Wind Power and Use Wind of Energy Storage in the Netherlands’ Electricity Supply, IET Renewable Netherlands Integration Power Generation, vol. 2, issue 1, March 2008, pp. 34-46 Wind Integration, Ummels, B.C., et al., 2006. Integration of Wind Power in the Liberalized Energy Dutch Electricity Market, Wind Energy, Issue 9, no. 6, November- Netherlands Markets December 2006, pp. 579-590 Ummels, B.C., et al., 2006. System Integration of Large-Scale Wind Power Wind in the Netherlands, Proc. of IEEE PES General Meeting, Montreal, Netherlands Integration June 18-22, 2006, 8 pp. Available at http://ieeeexplore.ieee.org Wind- Pritchard, G.; Philpott, A. B.; and Neame, P.J. Hydroelectric reservoir Hydro, optimization in a pool market. December, 2004. Available at Energy http://www.springerlink.com/content/3am5a6g8cg2qpudj/fulltext.p New Zealand Markets df Berge, Erik, et al. Wind in Complex Terrain, A Comparison of WASP and two CFD models. Available at Wind www.windsim.com/documentation/papers_presentations/0602_ewe Norway Forecasts c/ewec_berge.pdf Wind Integration, Di Marzio G, Fosso O, Uhlen K, Pálsson M P, Large-scale wind power Power integration - voltage stability limits and modal analysis, 15th Power System Norway Systems Computation Conference, PSCC 2005, Liege Wind Integration, Power Gjengedal, T, 2003, Integration of Wind Power and the Impact on Power Norway Systems System Operation, IEEE Conference on Power Engineering. Systems Analysis, Gjengedal, T. 2003, System Control of Large Scale Wind Power by use of Automatic Automatic Generation Control, CIGRE/IEEE PES International Generation Symposium on Quality of Electric Power Delivery Systems, Norway Control Montreal, October 2003 Wind Gjengedal, T, 2005. Large scale wind power farms as power plants. Wind Norway Integration Energy, Vol. 8, Issue 3, pp. 361-373
B-13 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Hagstrøm E, Norheim I, Uhlen K, 2005. Large-scale wind power Wind integration in Norway and impact on damping in the Nordic grid, Wind Norway Integration Energy 2005; 8(3) pp 375-384. Wind Integration, Wind- Korpaas, Magnus; Holen, Arne T.; and Hildrum, Ragne, 2003. Hydro, Operation and sizing of energy storage for wind power plants in a market system. Energy International Journal of Electrical Power and Energy Systems, v25, Norway Markets n8, p599-606, October, 2003. Korpås M, Tande J O, Uhlen K, Gjengedal T, 2006. Planning and operation of large wind farms in areas with limited power transfer capacity. Wind European Wind Energy Conference (EWEC), Athens, Greece, 27 Integration, February - 2 March 2006. Available at Wind- http://www.ewec2006proceedings.info/allfiles2/188_Ewec2006fullp Norway Hydro aper.pdf Wind Palsson M T, Toftevaag T, Uhlen K, Tande J O, 2003. Control Integration, Concepts to Enable Increased Wind Power Penetration. Proceedings of Power IEEE-PES Meeting, Toronto 13-18 July 2003. Available at Norway Systems http://ieeeexplore.ieee.org Wind Integration, Palsson M T, Toftevaag T, Uhlen K, Tande J O, 2002. Large-scale Power Wind Power Integration and Voltage Stability Limits in Regional Networks, Norway Systems Proceedings of 2002 IEEE-PES Summer Meeting Suul, J.A., Uhlen, K., Undeland, T., (2008). Wind Power Integration in Wind- Isolated Grids enabled by Variable Speed Pumped Storage Hydropower Plant, Hydro in Proc. of IEEE International Conference on Sustainable Energy Norway Integration Technologies, Singapore, Nov. 2008. Tande J O, Uhlen K, 2004.Cost analysis case study of grid integration of Wind larger wind farms, Wind engineering, volume 28, No3, 2004, pp 265- Norway Integration 273 Tande, J.O., 2006. Impact of integrating wind power in the Norwegian power system. SINTEF report. Available at http://www.ebl.no/getfile.php/Filer/Presentasjoner/Impact_of_int Wind egrating_wind_power_in_the_Norwegian_power_system_- Norway Integration _Sintef_2006.pdf Wind Tande, John Olav and Korpas, Magnus 2006. Impact of Large Scale Integration, Wind Power on System Adequacy in a Regional Hydro-Based Power System Wind- With Weak Interconnections, Nordic Wind Power Conference, SINTEF Norway Hydro Energy Research, Espoo, Norway, May. Wind Integration, Tande, J.O. and Vogstad, Klaus-Ole, Operational Implications of Wind Wind- Power in a Hydro Based Power System, EWEC, Nice, France, March, Norway Hydro 1999. Available at www.stud.ntnu.no/~klausv
B-14 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Wind- Troscher, T., Korpas, M., (2008). A Power Market Model for studying the Hydro Impact of Wind Power on Spot Prices, Proc. of 16th PSCC, Glasgow, Norway Integration Scotland, July 2008. Vogstad, Klaus-Ole, Utilizing the complementary characteristics of wind power and hydropower through coordinated hydro production scheduling using the Wind- EMPS model, in Proc. 2000 Nordic Wind Energy Conference. Norway Hydro Available at www.stud.ntnu.no/~klausv Wind- Hydro, Vogstad, Klaus-Ole et al., System Benefits of Coordinating Wind Power and Energy Hydropower in a Deregulated Market, in Proc. 2000 Nordic Wind Energy Norway Markets Conference. Available at www.stud.ntnu.no/~klausv Wind de Almeida, R.G.; Castronuovo, E.D.; Lopes, J.A.P.; Optimum Integration, generation control in wind parks when carrying out system operator requests, Power IEEE Transactions on Power Systems, Volume 21, Issue 2, May Portugal Systems 2006 Page(s):718 – 725. Available at http://ieeeexplore.ieee.org de Almeida, R.G.; Pecas Lopes, J.A.; Barreiros, J.A.L.; Improving power Wind system dynamic behavior through doubly fed induction machines controlled by Integration, static converter using fuzzy control, IEEE Transactions on Power Systems, Power Volume 19, Issue 4, Nov. 2004 Page(s):1942 – 1950. Available at Portugal Systems http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1350834 Wind de Almeida, R.G.; Pecas Lopes, J.A.; Participation of Doubly Fed Integration, Induction Wind Generators in System Frequency Regulation, IEEE Power Transactions on Power Systems, Volume 22, Issue 3, Aug. 2007 Portugal Systems Page(s):944 – 950. Available at http://ieeeexplore.ieee.org de Almeida, R.G, Pecas Lopes, J.A., Primary frequency control Power participation provided by doubly fed induction wind generators. Proceedings do Portugal Systems 16th PSCC em Liége, Bélgica, August 2005. de Andrade, Mário C. J. and Pinto, Medeiros. Portuguese TSO strategy to Wind integrate 3750 MW of Wind Power by 2010 - Power System Operation with Portugal Integration large Wind Capacity Integrated, INETI, Lisbon, 2005. Baptist, F., 2006. - Plan of Specific Reinforcement of the RNT up to 2010 for Wind Reception of Production in Special Regimen, VI Days of Electrotécnica Portugal Integration Engineering and Computers - IST, Lisbon, 2006. Brown, P. D.; PeÇas Lopes, J. A.; Matos, M. A.; Optimization of Wind Pumped Storage Capacity in an Isolated Power System With Large Renewable Integration, Penetration, IEEE Transactions on Power Systems, Volume 23, Issue Wind- 2, May 2008 Page(s):523 – 531. Available at Portugal Hydro http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4476156 Castronuovo, E.D., J.A. Peças Lopes. Bounding Active Power Generation of a Wind-Hydro Power Plant, Proceedings of the PMAPS-2004 (8th. Wind- International Conference on Probabilistic Methods Applied to Power Portugal Hydro Systems). September 13-16, 2004, Ames, Iowa, USA.
B-15 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Castronuovo, E.D. and J.A. Pecas Lopes, On the Optimization of the Daily Operation of Wind-Hydro Power Plant, IEEE Transactions on Power Systems, vol. 19, pp. 1599-1606, Aug. 2004. Available at Wind- http://ieeexplore.ieee.org/iel5/59/29221/01318699.pdf?arnumber= Portugal Hydro 1318699 Castronuovo, E.D., J.A. Peças Lopes. Optimal Operation and Hydro Storage Sizing of a Wind-Hydro Power Plant, International Journal of Wind- Electrical Power and Energy Systems, vol. 26/10, pp 771-778, Portugal Hydro December, 2004. Power Systems, Power Estanqueiro, A. I., Tande, J.O., and Lopes, J.A. Pecas. Assessment of Characterist Power Quality Characteristics of Wind Farms, Proc. IEEE PES meeting, Portugal ics Tampa, Florida. June, 2007. Available at http://ieeeexplore.ieee.org Estanqueiro, A.I. et al. Barriers (and Solutions...) to Very High Wind Wind Penetration in Power Systems, Proc. IEEE PES meeting, Tampa, Florida, Portugal Integration Junho, 2007. Available at http://ieeeexplore.ieee.org Estanqueiro, A., 2006. Study on the Portuguese spatial correlation and Wind smoothing effect of fast wind power fluctuations. INETI, Private Portugal Integration communication, December, 2006. Estanqueiro, A., R. Castro, P. Flores, J. Ricardo, M. Pinto, R. Rodrigues, J. Peças Lopes. How to prepare a power system for 15% wind Wind energy penetration: the Portuguese case study. Wind Energy, Vol. 11, Portugal Integration Number 1,Jan. 2008 Page(s) 75 – 84 Fidalgo, J.N.; Pecas Lopes, J.A.; Miranda, V.; Neural networks applied to preventive control measures for the dynamic security of isolated power systems with renewables, IEEE Transactions on Power Systems, Volume 11, Issue Wind 4, Nov. 1996 Page(s):1811 – 1816. Available at Portugal Integration http://ieeeexplore.ieee.org Franco Marques, P.J., Pecas Lopes, J.A., Impact of the Use of FACTS to Power Increase Robustness of Operation in Grids with Large Scale Wind Generation, Portugal Systems in Nordic Wind Power Conference, Espoo, Finland, May, 2006. Franco Marques, P.J., Pecas Lopes, J.A., Improving power system dynamical behavior through dimensioning and location of STATCOMs in Power systems with large scale wind generation, in Power Tech, Lausanne, Portugal Systems Switserland, July, 2007. Franco Marques, P.J., Pecas Lopes, J.A., Use of Simulated Annealing for Power optimizing capacity and location of STATCOM in Grids with Large Scale Portugal Systems Wind Generation, in POWERENG, Setubal, Portugal, April, 2007. Wind INEGI, 2002. Wind Resource Variability Patterns in Continental Portugal, Integration, INEGI – Instituto de Engenharia Mecânica e Gestão Industrial – Wind University of Oporto, commissioned by REN, Rede Eléctrica Portugal Forecasts Nacional, SA
B-16 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Wind Imaz, Luíz et al., 2006. Admisible wind generation in the Iberian peninsular Portugal Integration electric system by 2011 (in Spanish or Portuguese) – MIBEL, July 2006. Mendonca, A, Pecas Lopes, J.A., A Multicriteria Approach to Identify the Wind Adequate Wind Power Penetration in Isolated Grids, Proceedings of Integration, MedPower'04 - 4th Mediterranean IEE Conference and Exhibition Power on Power Generation, Transmission and Distribution, Lemesos, Portugal Systems Cyprus, Novembro de 2004. Mendonça, Â., Peças Lopes, J.A.. Impact of Large Scale Wind Power Integration on Small Signal Stability, Proceedings of FPS 2005, Wind International Conference on Future Power Systems, November Portugal Integration 2005. Wind Integration, Moyano, Carlos Fabian, Pecas Lopes, J.A, A Unit Commitment and Power Dispatch for a Wind Park Considering Wind Power Forecast, Proceedings of Systems, ICREPQ'07 – International Conference on Renewable Energies and Wind Power Quality (ICREPQ'07) , vol.1, no.1, pp.1-6, Sevilha, Espanha, Portugal Forecasts Março, 2007. Wind Moyano, Carlos Fabian, Pecas Lopes, J.A, Unit Commitment and Integration, Dispatch Strategies for a Wind Park, Proceedings of POWERENG 2007 Power - International Conference on Power Engineering, Energy and Portugal Systems Electrical Drives, vol.1, no.1, pp.1-6, Setubal, Portugal, Abril, 2007. Wind Moyano, Carlos Fabian, Pecas Lopes, J.A, , Using an OPF like Integration, Approach to Define the Operational Strategy of a Wind Park under a System Power Operator Control, IEEE Lausanne Power Tech 2007, Lausanne, Portugal Systems Switzerland, Julho, 2007. Wind Paiva, Sucena et al., 2004. Limits of wind generation to connect to the public Portugal Integration networks under the stability point of view (in Portuguese), October, 2004. Pecas Lopes, J.A, New Technical and Conceptual Solutions to Allow a Larger Increase of the Integration of Intermittent Energy Sources in Power Power Systems, X Symposium of Specialists in Electric Operational and Portugal Systems Expansion Planning, X SEPOPE, Florianopolis, May, 2006. Pecas Lopes, J.A, Vasconcelos, H., Security Assessment of Interconnected Systems Having Large Wind Power Production, CIGRE SYMPOSIUM: Power Power Systems with Dispersed Generation, Athens, Greece, April, Portugal Systems 2005. Wind Pecas Lopes, J.A, Technical and Commercial Impacts of the Integration of Integration, Wind Power in the Portuguese System Having in Mind the Iberian Electricity Power Market, Proceedings do IEEE PowerTech2005 - St. Petersburg Portugal Systems Power Tech 2005, St. Petersburg, Russia, June, 2005. Ricardo, João et al., 2006. National Goals For Renewable Generation In Wind Portugal An Organizational And Technical Challenge From The Point Of Portugal Integration View Of The Transmission System Operator - CIGRÉ SESSION, 2006.
B-17 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Ricardo, João et al., 2005. First Phase-Shifting Autotransformers (PSAT) Wind for the 400 kV Portuguese Network – 1st International Conference on Portugal Integration Electrical Power Transmission, Algéria, 2005 Ricardo, João et al., 2005. Study of Transitory Stability of the Portuguese net Wind of transport of electric energy with raised volumes of aeolian production - XI Portugal Integration Encuentro Regional IberoAmericano del CIGRÉ-XI ERIAC, 2005. Wind Rodrigues, A., et al. EPREV - A wind power forecasting tool for Portugal, Portugal Forecasts EWEC 2007, Milan, Italy. May, 2007. Rodriguez-Bobada, F.; Reis Rodriguez, A.; Ceña, A.; and Giraut, E., Study of wind energy penetration in the Iberian peninsula. European Wind Energy Conference (EWEC), 27 February – 2 March, 2006, Athens, Greece. Available at Wind http://www.ewec2006proceedings.info/allfiles2/743_Ewec2006fullp Portugal Integration aper.pdf da Silva, A. M. Leite, et al. Application of Monte Carlo Simulation to Generating System Well-Being Analysis Considering Renewable Sources, Systems Proceedings of PMAPS'2004 - 8th International Conference on Portugal Analysis PMAPS 2004. Ames, USA, September, 2004. Wind Forecasts, Trancoso, Ana Rosa, et al. Comparative evaluation of wind power forecasts Power for Portuguese transmission system operator, EWEC 2008, Brussels Expo, Portugal Systems Belgium, March 31 - April 3 Wind Integration, Wind Forecasts, Trancoso, Ana Rosa, et al. REN Online Monitoring and Prediction of Power Wind Power: Portuguese Transmission System Operator’s Methodology. Portugal Systems ENER’06, 28. September, 2006. Figueira da Foz. Wind Trancoso, Ana Rosa, et al, Wind power predictability: comparative study of Forecasts, forecasts with MM5 and WRF for Portuguese transmission system operator. Power EMS7/ECAM8 Abstracts, Vol. 4, EMS2007-A-00260, 20077th EMS Portugal Systems Annual Meeting / 8th ECAM, Madrid, Oct 1-5, 2007. Vasconcelos, H., Pecas Lopes, J.A., ANN Design for Fast Security Power Evaluation of Interconnected Systems with Large Wind Power Production, Portugal Systems Proceedings of PMAPS 2006, Stockholm, Sweden, June, 2006. AEE (Spanish Wind Energy Association). Procedure for verification Wind validation and certification of the requirements of the PO 12.3 on the response of Integration, wind farms in the event of voltage dips, (in Spanish and English) AEE. Power 2008. Available at Spain Systems http://www.aeeolica.org/doc/privado/pvvc_v3_english.pdf
B-18 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Wind- Angarita, Jorge Marquez and Usaola, Julio Garcia, 2007. Combining Hydro, hydro-generation and wind energy. Biddings and operation on electricity spot Energy markets, Electric Power Systems Research, Vol. 77, Issues 5-6, pp. Spain Markets 393-400, April, 2007. Available at www.sciencedirect.com Wind Integration, Criado, R., Soto, J., Rodríguez, J. M., Martin, L. Fernández, J.L., Power Molina, J.L., Tapia, A., Saez, J.R. Analysis and control strategies of wind Spain Systems energy in the Spanish power system. Proc. 2000 CIGRE (Paris). Wind Integration, Wind Fabbri, A.; Roman, T.G.S.; Abbad, J.R.; Quezada, V.H.M. Assessment Forecasts, of the Cost Associated With Wind Generation Prediction Errors in a Energy Liberalized Electricity Market. IEEE Transactions on Power Systems. Spain Markets Vol. 20 (3), Aug. 2005. Available at http://ieeeexplore.ieee.org Wind Feijoo, A.E.; Cidras, J.; Dornelas, J.L.G. Wind speed simulation in wind Integration, farms for steady-state security assessment of electrical power systems. IEEE Power Transaction on Energy Conversion, Vol. 14 (4), Dec. 1999. Available Spain Systems at http://ieeeexplore.ieee.org Wind Gómez-Lázaro, E., Cañas, M., Fuentes, J.A., Molina A. Discussion on Integration, the Grid Disturbance on 4 November 2006 and its effects in a Spanish Wind Power Farm, Nordic Wind Power Conference – NWPC’2007, Roskilde Spain Systems (Denmark), November 2007. Wind Integration, Reactive Gómez, E., Fuentes, J. A., Molina, A., Ruz, F., Jiménez, F., 2006. Power, Results using Different Reactive Power Definitions for Wind Turbines Submitted Power to Voltage Dips: Application to the Spanish Grid Code, Power Systems Spain Systems Conference, October-November 2006, Atlanta, USA. Gómez-Lázaro, E., Cañas, M., Fuentes, J.A., Molina, A., Ruz, F., Wind Jiménez, F. Field Measurements on Wind Turbines: a Voltage Dip Integration, Characterization under the Spanish Grid Code. 9th International Power Conference on Electrical Power Quality and Utilisation. Barcelona Spain Systems (Spain), October 2007. Wind Gómez, E., Fuentes, J. A., Molina-García, A., Ruz, F., Jiménez, F., Integration, 2007. Field Tests of Wind Turbines Submitted to Real Voltage Dips under the Power New Spanish Grid Code Requirements. Wind Energy, Vol. 10, Issue 5, pp Spain Systems 483-295, 2007. Gómez, E., Fuentes, J. A., Molina-García, A., Ruz, F., Jiménez, F., 2007b. Wind Turbine Modeling: Comparison of Advanced Tools for Transient Wind Analysis, PES General Meeting, June 2007, Tampa, USA. Available at Spain Integration http://ieeeexplore.ieee.org
B-19 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Wind Integration, Ledesma, P.; Usaola, J. Doubly fed induction generator model for transient Power stability analysis. IEEE Transaction on Energy Conversion, Vol. 20 Spain Systems (2), pp. 388-397, June 2005. Available at http://ieeeexplore.ieee.org Morales, A.; Robe, X.; Sala, M.; Prats, P.; Aguerri, C.; Torres, E. Wind Advanced grid requirements for the integration of wind farms into the Spanish Integration, transmission system. IET Renewable Power Generation, Vol. 2 (1), Spain Regulation March 2008. Available at http://ieeeexplore.ieee.org Wind REE 1995, General criteria of Protection of the Electrical System Peninsular Spain Integration Spanish, REE and Power Companies. 1995. Rodríguez, J.M., Alvira, D., Bañares, S. The Spanish Experience of the Wind grid integration of wind energy sources. IEEE Power Tech 2005. Available Spain Integration at http://ieeeexplore.ieee.org Rodriguez, J.M.; Fernandez, J.L.; Beato, D.; Iturbe, R.; Usaola, J.; Wind Ledesma, P.; Wilhelmi, J.R. Incidence on power system dynamics of high Integration, penetration of fixed speed and doubly fed wind energy systems: study of the Power Spanish case. IEEE Transactions on Power Systems, Vol. 17(4). Nov. Spain Systems 2002. Available at http://ieeeexplore.ieee.org Rodriguez-Bobada, F, Reis Rodriguez, A, Ceña, A, Giraut, E, Study of wind energy penetration in the Iberian peninsula. European Wind Energy Conference (EWEC), 27 February – 2 March, 2006, Athens, Greece. Available at Wind http://www.ewec2006proceedings.info/allfiles2/743_Ewec2006fullp Spain Integration aper.pdf Rodriguez-Garcia, J.M.; Dominguez, T.; Alonso, J. F.; Imaz, L. Large integration of wind power: the Spanish experience. IEEE Power Engineering Wind Society General Meeting, 24-28 June 2007. Available at Spain Integration http://ieeeexplore.ieee.org Usaola, J.; Ledesma, P. Dynamic incidence of wind turbines in networks with high wind penetration. IEEE Power Engineering Society Summer Wind Meeting, Vol. 2, pp. 15-19, July 2001. Available at Spain Integration http://ieeeexplore.ieee.org Usaola, J.; Ledesma, P.; Rodriguez, J.M.; Fernandez, J.L.; Beato, D.; Iturbe, R.; Wilhelmi, J.R. Transient stability studies in grids with great wind power penetration. Modeling issues and operation requirements. IEEE Power Wind Engineering Society General Meeting, 2003. Available at Spain Integration http://ieeeexplore.ieee.org Wind Integration, Usaola, Julio, et al. SIPREOLICO, A Wind Power Prediction Tool for the Wind Spanish Peninsular Power System Operation, in Proceedings from CIGRE Spain Forecasts 40th General Session and Exhibition, 2004. Wind Ackermann, Thomas, 2005. European Wind Power Integration Experience, Sweden Integration Solar 05 ANZSES, Dunedin, New Zealand, 2005.
B-20 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Wind Axelsson U, Murray R, Neimane V, 4000 MW wind power in Sweden - Integration, Impact on regulation and reserve requirements. Elforsk Report 05:19, Sweden Regulation Stockholm, 2005. Available at http://www.elforsk.se Jäderström, Anna; Matevosyan, Julija; and Söder, Lennart. Coordinated Wind- regulation of wind power and hydro power with separate ownership, IEWT 05, Sweden Hydro Vienna, Austria, 2005 Kariniotakis, G., et al, 2006. Next generation forecasting tools for the optimal management of wind generation, Proceedings PMAPS Conference, Wind 'Probabilistic Methods Applied to Power Systems', KTH, Stockholm, Sweden Forecasts Sweden, June 2006. Wind Integration, Lindgren, Elin and Söder, Lennart, 2006. Minimizing regulation costs in Wind multi-area systems with uncertain wind power forecasts, Nordic Wind Power Sweden Forecasts Conference NWPC'2006, Espoo, Finland, 2006. Lindgren, Elin and Söder, Lennart, 2005. Wind Power Impact on Costs Wind for Regulating Power in Multi-Area Markets, Fifth International Integration, Workshop on Large-Scale Integration of Wind Power and Energy Transmission Networks for Offshore Wind Farms, Glasgow, Sweden Markets Scotland, 2005. Matevosyan, J., 2006. Wind power integration in power system with Wind transmission bottlenecks, PhD study, KTH, Sweden, 2006. Available at Sweden Integration http://www.diva-portal.org/kth/theses/abstract.xsql?dbid=4108 Matevosyan, Julija, 2006. On the Coordination of Wind and Hydro Power. Wind- 6th International Workshop on Large-Scale Wind Power Integration, Sweden Hydro October, 2006. Wind Matevosyan, Julija, 2005. Wind Power in Areas with Limited Transmission Sweden Integration Capacity, Wind Power in Power Systems, Wiley & Sons, 2005 Matevosyan, Julija et al., Hydro Power Planning Coordinated with Wind Wind- Power in Areas with Congestion Problems for Trading on the Spot and the Sweden Hydro Regulating Market. Wind Matevosyan, Julija and Söder, Lennart, 2006. Minimization of imbalance Integration, costs trading wind power on the short-term power market, IEEE Transactions Energy on Power Systems, (no. 3,) pp. 1396-1404, August, 2006. Available at Sweden Markets http://ieeeexplore.ieee.org Matevosyan, Julija, Söder, Lennart, Optimal daily planning for hydro power system coordinated with wind power in areas with limited export capability, Wind- Proceedings Probabilistic Methods Applied to Power Systems Sweden Hydro Conference, 2006. Matevosyan, Julija and Soder, Lennart, 2007. Short-term Hydropower Planning Coordinated with Wind Power in Areas with Congestion Problems, Wind Energy, February 2007; 10:195-208. Available at Wind- http://www3.interscience.wiley.com/cgi- Sweden Hydro bin/fulltext/114113010/PDFSTART
B-21 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Wind Neij, L. 1999, Cost Dynamics of Wind Power, Energy, Sweden Integration Volume 24, Issue 5, May 1999, Pages 375-389. Ohrvall, F., 2008. Samkorning av vindkraft och vattenkraft I Skellefrealven, Wind- Elforsk report V-107, 2008. (Summary in English) Available at Sweden Hydro http://www.vindenergi.org Wind Söder, L. 1994. Integration study of small amounts of wind power in the power Sweden Integration system. Royal Institute of Technology KTH report TRITA-EES-9401 Wind Söder, Lennart. 2005. Modelling Approach impact on estimation of Sweden Integration integration cost of wind power, 7th IAEE, Bergen, Norway, 2005 Söder, Lennart, 2004. On limits for Wind Power Generation, Published in Wind International Journal of Global Energy Issues, Vol. 21, Issue 3, pp. Sweden Integration 243-254, March 2004 Wind Söder, Lennart, 2005. The Value of Wind Power, Wind Power in Power Sweden Integration Systems, (pp. 169-195,) John Wiley & Sons, Ltd, 2005. Söder, L.; Ekwue, A.; and Douglas, J. 2006. Study on the technical security Wind rules of the European electricity network. Royal Institute of Technology Sweden Integration (KTH) report TRITA-EE 2006:003. Wind Integration, Power Söder, L, Holttinen, H, 2007. On methodology for modeling power system Characterist impact of wind power. Int. J. of Global Energy Issues, Vol. 25, 2007 (in Sweden ics print). Söder, L, Hofmann, L, Nielsen, C S, Holttinen, H, 2006. Experience Wind from wind integration in some high penetration areas. Nordic Wind Power Sweden Integration Conference, 22-23 May, 2006, Espoo, Finland. VTT, Espoo, 2006. Wind Bathurst, G.N. and Strbac, G. 2003. Value of Combining Energy Storage Integration, and Wind in Short-Term Energy and Balancing Markets, Electric Power United Wind- Systems Research, 67, pp. 1-8. January. Available at Kingdom Hydro http://www.elsevier.com/locate/epsr Dale, Milborrow D, Slark, & Strbac G, 2003. A shift to wind is not unfeasible (Total Cost Estimates for Large-scale Wind Scenarios in UK). United Wind Power UK Journal Issue 109, 17-25. Available at Kingdom Integration http://www.bwea.com/pdf/PowerUK-March2003-page17-25.pdf Wind Integration, DTI Centre for Distributed Generation and Sustainable Electrical Power Energy, Influence of wind farms on power system dynamic and transient United Characterist stability, Summary Report to ESTISG (www.dti.gov.uk), February Kingdom ics 2005. Gross, Robert et al. 2006. The Costs and Impacts of Intermittency: An United Wind assessment of the evidence on the costs and impacts of intermittent generation on Kingdom Integration the British electricity network. UKERC
B-22 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference MacDonald M, 2003. The Carbon Trust & DTI Renewables Network Impact Study Annex 4: Intermittency Literature Survey & Roadmap. 2003. The Carbon Trust & DTI. 2003. Available at United Literature http://www.uwig.org/Intermittency_literature_analysis_file25924.pd Kingdom Survey f United Wind Milborrow D, 2005. Capacity credit of renewable energy sources in the UK, Kingdom Integration Report to ESTISG, Feb. 2005. Royal Academy of Engineering & PB Power. The Cost of Generating Electricity. 2004. Available at United Wind http://www.raeng.org.uk/news/publications/list/reports/Cost_of_ Kingdom Integration Generating_Electricity.pdf Wind Integration, United Wind- Strbac G, Black M, Value of storage in managing intermittency, Report to Kingdom Hydro DTI (www.sedg.ac.uk), May 2004. Wind Integration, Power Strbac G, Bopp T, Value of fault ride through capability for wind farms, United Characterist Report to Ofgem (www.sedg.ac.uk), July 2004. Available at Kingdom ics http://www.sedg.ac.uk/ Strbac, Goran, Shakoor, Anser, Black, Mary, Pudjianto, David, Bopp, Thomas, 2007. Impact of wind generation on the operation and development of the UK electricity systems, Electrical Power Systems Research, Volume 77, Issue 9, Pages 1143-1238, Elsevier 2007. Available at http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6 V30-4M4KK9Y- 1&_user=10&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_ United Wind acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5 Kingdom Integration =45ff1a312ff87c918f895d13daa7249c Acker, T., 2007, Final Report: Arizona Public Service Wind Integration Cost Wind Impact Study, Northern Arizona University, October 2007. Available United States Integration at: http://wind.nau.edu/APSWindIntegrationsStudy.shtml Wind Acker, T., Buechler, J., Knitter, K., and Conway, K., 2007, Impacts Of Integration, Integrating Wind Power Into The Grant County PUD Balancing Area, Wind- Proceedings of the AWEA Windpower 2007 Conference, Los United States Hydro Angeles, CA, June. Wind Integration, Acker, T., 2007, IEA Task 24: Integration Wind and Hydropower Systems, Wind- Proceedings of the 2006 Global Wind Power Conference, Adelaide, United States Hydro Australia, September.
B-23 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Wind Acker, T., Knitter, K., Conway, K., and Buechler, J., 2006, Integrating Integration, Wind and Hydropower on the Mid-Columbia River in Grant County, Wind- Washington, Proceedings of the AWEA Windpower 2006 Conference, United States Hydro Pittsburgh, PA, June. Wind Acker, T., Knitter, K., Conway, K., and Buechler, J., 2006, Wind and Integration, Hydropower Integration in the Grant County Public Utility District, Wind- Washington, Proceedings of the Hydrovision 2006 Conference, United States Hydro Portland, OR, August. Wind Integration, Acker, T., 2005, Synthesizing Wind and Hydropower: Opportunities and Wind- Challenges, Proceedings of the Waterpower XIV Conference, Austin, United States Hydro TX, July. Wind Integration, Acker, T., 2005, Characterization of Wind and Hydropower Integration in the Wind- USA, Proceedings of the AWEA Windpower 2005 Conference, United States Hydro Denver, CO, May. Wind Acker, T. and Parson, B., 2004, Opportunities to Optimize Hydropower and Integration, Wind Energy Systems Through Coordination, Cooperation, or Integration, Wind- Proceedings of the Global Windpower Conference, Chicago, IL, United States Hydro March. Ancona, Daniel and Krau, Stéphane et. al. 2003. Operational Constraints and Economic Benefits of Wind-Hydro Hybrid Systems – Analysis of Systems in the U.S./Canada and Russia, Princeton Energy Resources Wind- International, LLC, European Wind Energy Conference, Madrid, United States Hydro Spain, June. Available at http://www.perihq.com/archives.htm AWS Scientific and Truewind Solutions, 2003. Overview of Wind Energy Wind Generation Forecasting. Submitted to NYSERDA and NYISO. United States Forecasts Available at www.uwig.org/forecst_overview_report_dec_2003.pdf Bai, Xiggang, 2007. Intermittency Analysis Project, Appendix B: Impact of Intermittent Generation on Operation of California Power Grid, California Energy Commission. Available at Wind http://www.energy.ca.gov/pier/final_project_reports/CEC-500- United States Integration 2007-081.html Bailey, Bruce, 2007. PIER Project Task Report: California Wind Energy Resource Modeling and Measurement, Measurement Program Final Report. Available at Wind http://www.energy.ca.gov/pier/final_project_reports/CEC-500- United States Forecasts 2006-066.html Banta, R.M., 2003, Analysis of Cases-99, LIDAR and Turbulence Data Wind in Support of Wind Turbine Effects, NREL. Available at United States Forecasts http://www.osti.gov/bridge/
B-24 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Bielecki, M., et al. (2010). Characterization of Errors in Wind Power Wind Forecasting, Master’s Thesis, Northern Arizona University, 2010. United States Forecasts Available at http://www.nau.edu/library Wind Bird, L., Parsons, B., Gagliano, T., and Brown, M., Wiser R., Integration, Bolinger, M., 2003. Policies and Market Factors Driving Wind Power Energy Development in the United States. NREL/TP-620-34599, National United States Markets Renewable Energy Laboratory, Colorado, US. Wind- Bonneville Power Administration- Integration of Wind with Hydro-electric United States Hydro Generation Brooks, Daniel et al. Assessing the Impact of Wind Generation at System Wind Operations at XCEL Energy - North and Bonneville Power Administration. United States Integration Available at http://www.uwig.org/operatingimpacts.html Brooks, Daniel et al. 2003 Characterizing the Impacts of Significant Wind Generation Facilities on Bulk Power System Operations Planning, XCEL Wind Energy - North Case Study. Available at United States Integration http://www.uwig.org/operatingimpacts.html Brower, Michael, 2007, Intermittency Analysis Project: Characterizing New Wind Resources in California, California Energy Commission. Available Wind at www.energy.ca.gov/pier/notices/2007-02- United States Integration 13_workshop/presentations/05_2007-02-13_YEN+AWS.PDF Wind Integration, Wind- Buechler, Jason and Acker, Tom, 2008. Grant County Public Utility United States Hydro District Wind Integration Study. (still in edit) Cadogan, J. and Milligan, M. et. al. 2000. Short-Term Output Variations in Wind Farms—Implications for Ancillary Services in the United States, NREL/CP-500-29155, National Renewable Energy Laboratory, Wind Golden, CO, September. Available at United States Integration http://www.nrel.gov/publications/ California Independent System Operator. Integration of Renewable Resources: Transmission and operating issues and recommendations for Wind integrating renewable resources on the California ISO-controlled grid. United States Integration November, 2007 California Wind Energy Collaborative, 2006, Impact of Past, Present and Future Wind Turbine Technologies on Transmission System Operation and Performance, California Energy Commission. Available at Wind http://www.energy.ca.gov/pier/final_project_reports/CEC-500- United States Integration 2006-050.html Cardinal and Miller, 2006. Grid Friendly Wind Plant Controls: Wind WindCONTROL – Field Test Results, WindPower 2006, Pittsburgh, United States Integration PA, US Wind- Cheng, Edmond 1989. An Investigation of a Pumped Storage Hydropower United States Hydro System. Waterpower, 1989.
B-25 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Davis, Ronald, 2007 Intermittency Analysis Project, Appendix A: Intermittency Impacts of Wind and Solar Resources on Transmission Reliability, California Energy Commission. Available at Wind http://www.energy.ca.gov/pier/final_project_reports/CEC-500- United States Integration 2007-081.html DeMeo E A, Grant W, Milligan M, Schuerger M J, Wind plant Wind integration: costs, status and issues, IEEE power & energy magazine, United States Integration nov/dec 2005. Department of Energy, 2008. 20% Wind Energy by 2030. Increasing Wind Energy's Contribution to the US Electric Supply. Available at Wind http://www.20percentwind.org/20percent_wind_energy_report_rev United States Integration Oct08.pdf Dragoon, K. and Dvortsov, V. 2006. Z-Method for Power System Power Resource Adequacy Applications. IEEE Transactions on Power Systems, United States Systems Vol. 21, No.2, May 2006. Available at http://ieeeexplore.ieee.org Dragoon, K. and Milligan, M. 2003. Assessing Wind Integration Costs Wind with Dispatch Models: A Case Study of PacifiCorp, NREL/CP-500-34022, United States Integration National Renewable Energy Laboratory, Golden, CO. May. Wind EnerNex Corporation, 2007. Avista Corporation Wind Integration Study Integration, Final Report. March, 2007. Available at Wind- http://www.avistautilities.com/inside/resources/irp/electric/Docu United States Hydro ments/AvistaWindIntegrationStudy.pdf Wind Integration, Electrotek Concepts, Systems Operations Impacts of Wind Generation Systems Integration Study. Prepared for We Energies, June 2003. Available at United States Analysis http://www.uwig.org/WeEnergiesWindImpacts_FinalReport.pdf EnerNex Corporation and Wind Logics, Inc. 2004. Characterization of Wind the Wind Resource in the Upper Midwest Wind Integration Study – Task 1, Integration, Xcel Energy and the Minnesota Department of Commerce, Wind Knoxville, TN, September. Available at United States Forecasts http://www.enernex.com/staff/publications.htm EnerNex Corporation and Wind Logics, 2004. Wind Integration Study – Final Report. Xcel Energy and the Minnesota Department of Wind Commerce, Knoxville, TN, September. Available at Integration, http://www.enernex.com/staff/downreports.htm or at Wind- http://www.state.mn.us/cgi- United States Hydro bin/portal/mn/jsp/content.do?contentid=536904447 EnerNex Corporation and Wind Logics, 2006. Minnesota Wind Wind Integration Study, Volumes I and II. Available at United States Integration http://www.puc.state.mn.us/docs EnerNex Corporation and Idaho Power Company, 2007. Operational Wind Impacts of Integrating Wind Generation into Idaho Power's Existing Resource United States Integration Portfolio. Available at www.enernex.com
B-26 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference ERCOT, 2007. ERCOT Operations Report on the EECP event on February 8, 2007. Available at Wind http://www.ercot.com/meetings/ros/keydocs/2007/0315/07._ER United States Integration COT_OPERATIONS_REPORT_EECP020807_rev3.doc GE Energy, 2004. The Effects of Integrating Wind Power On Transmission System Planning, Reliability, and Operations, Report on Phase 1: Preliminary Overall Reliability Assessment, Prepared for the New York State Energy Research and Development Authority, by General Electric’s Power Wind Systems Energy Consulting, Schenectady, NY. Available at United States Integration http://www.uwig.org/phase%20_1_feb_02_04.pdf GE Energy, 2005. The Effects of Integrating Wind Power on Transmission System Planning, Reliability, and Operations: Report on Phase 2, Prepared for The New York State Energy Research and Development Wind Authority, City, State, Mar. 2005. Available at United States Integration http://www.nyserda.org/publications/wind_integration_report.pdf Wind Hand, N.M., Kelly, N.D., Balas, M.J. 2003, Identification of Wind United States Forecasts Turbine Response to Turbulent Inflow Structures, NREL. Hand, N.M., Maureen, M. 2003, Mitigation of Wind Turbine/Vortex Wind Interaction Using Disturbance Accommodating Control, NREL. Available at United States Forecasts http://www.osti.gov/bridge/ Hanson, R.J., Millham, C.B., Estimating the Costs in Lost Power of Wind- Alternative Snake-Columbia Basin Management Policies. Water Resources United States Hydro Research, Vol. 17, No. 5, pp. 1295-1303, October 1981. Wind Harris, M., Hand, M, and Wright, M. 2005, LIDAR for Turbine United States Forecasts Control, NREL. Available at http://www.osti.gov/bridge/ Wind Hirst, Eric 2002. Integrating Wind Energy With The BPA Power System: Integration, Preliminary Study, Consultant, Oak Ridge, TN, September. Available at Wind- http://www.bpa.gov/Power/pgc/wind/Wind_Integration_Study_09 United States Hydro -2002.pdf Wind- Hirst, Eric 2003. The Value of Regulation and Spinning Reserves for United States Hydro Hydroelectric Resources. Hirst, Eric and Kirby, Brendan 2003. Allocating Costs of Ancillary Services: Contingency Reserves and Regulation, ORNL/TM-2003/152, Oak Ridge National Laboratory, Oak Ridge, TN, June. Available at Wind http://lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/fqma/tpsext United States Integration /SF Hirst, Eric and Kirby, Brendan. Defining Intra-And Interhour Load Swings, Oak Ridge National Laboratory, Oak Ridge, TN. Available at Load http://lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/fqma/tpsext United States Analysis /SF
B-27 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Hirst, Eric and Kirby, Brendan 2001. Measuring Generator Performance In Providing Regulation And Load-Following Ancillary Services, ORNL/TM-2000/383, Oak Ridge National Laboratory, Oak Ridge, TN, January. Available at Wind http://lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/fqma/tpsext United States Integration /SF Hirst, Eric and Kirby, Brendan 2000. What Is The Correct Time- Averaging Period For The Regulation Ancillary Service?, Oak Ridge National Laboratory, Oak Ridge, TN, April. Available at Wind http://lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/fqma/tpsext United States Integration /SF Hirst, Eric and Kirby, Brendan 2001. Measuring Generator Performance In Providing Regulation And Load-Following Ancillary Services, ORNL/TM-2000/383, Oak Ridge National Laboratory, Oak Ridge, TN, January. Available at Wind http://lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/fqma/tpsext United States Integration /SF Hirst, Eric and Kirby, Brendan 1996. Electric-Power Ancillary Services, ORNL/CON-426, Oak Ridge National Laboratory, Oak Ridge, TN, February. Available at Wind http://lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/fqma/tpsext United States Integration /SF Hudson, Randy and Kirby, Brendan and Wan, Yih-Huei. Regulation Requirements For Wind Generation Facilities, Oak Ridge National Laboratory, Oak Ridge, TN and National Renewable Energy Laboratory, Golden, CO. Available at Wind http://lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/fqma/tpsext United States Integration /SF Wind Integration, Ihle, J, Owens, B. 2004, Integrated Coal and Wind Power Development in United States Coal the U.S. Upper Great Plains. Wind Jaynes, Daniel et al. 2007, MTC Final Progress Report: LIDAR, NREL. United States Forecasts Available at http://www.osti.gov/bridge/ Kelley, N.D., et al. 2007, Comparing Pulsed Doppler LIDAR with Wind SODAR and Direct Measurements for Wind Assessment, NREL. Available United States Forecasts at http://www.osti.gov/bridge/ Kirby, Brendan 2003. Spinning Reserve From Responsive Loads, Wind ORNL/TM-2003/19, Oak Ridge National Laboratory, Oak Ridge, United States Integration TN, March. Available at http://www.osti.gov/bridge/
B-28 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Kirby, Brendan and Hirst, Eric 2000. Customer-Specific Metrics For The Regulation And Load-Following Ancillary Services, ORNL/CON-474, Oak Ridge National Laboratory, Oak Ridge, TN, January. Available at Wind http://lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/fqma/tpsext United States Integration /SF Kirby, Brendan and Hirst, Eric 2000. Pricing Ancillary Services So Customers Pay For What They Use, Oak Ridge National Laboratory, Oak Ridge, TN. Available at Wind http://lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/fqma/tpsext United States Integration /SF Kirby, Brendan and Hirst, Eric 2001. Using Five-Minute Data To Allocate Load-Following And Regulation Requirements Among Individual Customers, ORNL/TM-2001/13, Oak Ridge National Laboratory, Oak Ridge, TN, January. Available at Wind http://lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/fqma/tpsext United States Integration /SF Kirby, Brendan and Milligan, Michael. A Method and Case Study for Estimating The Ramping Capability of a Control Area or Balancing Authority and Implications for Moderate or High Wind Penetration, Oak Ridge National Laboratory, Oak Ridge, TN. Available at Wind http://lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/fqma/tpsext United States Integration /SF or at www.nrel.gov/publications Wind Komer, P. Wind Power: Opportunity or Albatross, Platts Research and United States Integration Consulting. Krich, A. and Milligan, M. 2005. The Impact of Wind Energy on Hourly Load Following Requirements: An Hourly and Seasonal Analysis, Wind NREL/CP-500-38061, National Renewable Energy Laboratory, United States Integration Golden, CO, May. Available at http://www.nrel.gov/publications/ Lackner, M.A. et al. 2007. The Round Robin Site Assessment Method: A New Approach to Wind Energy Site Assessment. Renewable Energy, Vol. Wind 33 (2008), pp. 2019-2026. Available at www.sciencedirect.com or United States Forecasts www.elsevier.com McGill, Chris. 2005, Wind Energy and Natural Gas: Balancing Price and Wind Supply Volatility, National Wind Coordinating Committee. Available at United States Integration http://www.aceny.org/pdfs/wind_facts/aga_on_wind.pdf Millham, C.B. 1985. Using Hydropower to Smooth Intermittent and Unreliable Sources of Generation, Washington State University, Pullman, Wind- WA. May. Applied Mathematical Modelling. Vol. 9, no. 5, pp. 314- United States Hydro 320. 1985 Milligan, M. and Porter, K. 2005. Determining the Capacity Value of Wind: A Survey of Methods and Implementation, NREL/CP-500-38062, Wind National Renewable Energy Laboratory, Golden, CO, May. Available United States Integration at http://www.nrel.gov/publications/
B-29 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Milligan, Michael 2002. Modeling Utility-Scale Wind Power Plants Part 2: Capacity Credit, NREL/TP-500-29701, National Renewable Energy Wind Laboratory, Golden, CO, March. Available at United States Integration http://www.nrel.gov/publications/ Milligan, Michael and Parsons, Brian 1997. A Comparison and Case Study of Capacity Credit Algorithms for Intermittent Generators, NREL/CP- Wind 440-22591, National Renewable Energy Laboratory, Golden, CO, United States Integration April. Available at http://www.nrel.gov/publications/ Milligan, M, 2003. Wind power plants and system operation in the hourly time domain. Proceedings of Windpower 2003 conference, May 18–21, Wind 2003 Austin, Texas, USA. NREL/CP-500-33955. Available at United States Integration http://www.nrel.gov/publications/ Milligan, M. and Schwartz, M.N. et. al. 2003. Statistical Wind Power Forecasting for U.S. Wind Farms, NREL/CP-500-35087, National Wind Renewable Energy Laboratory, Golden, CO, November. Available at United States Forecasts http://www.nrel.gov/publications/ Milligan, M. Measuring Wind Plant Capacity Value. National Renewable Wind Energy Laboratory. 1996. Available at United States Integration http://www.nrel.gov/docs/legosti/fy96/20493.pdf Milligan, M, Porter, K, 2005. The Capacity Value of Wind in the United Wind States: Methods and Implementation. Electricity Journal, Vol. 19, Issue 2, United States Integration March 2006. pp 91-99. Elsevier, Inc. Wind Moore, Kathleen and Bailey, Bruce, 2002. SODAR for Wind Energy United States Forecasts Resource Assessment. American Wind Energy Association Reactive Mulijadi, E. and Butterfield, C.P. and Yinger, R. and Romanowitz, H. Power, 2004. Energy Storage and Reactive Power Compensator in a Large Wind Wind Farm, National Renewable Energy Laboratory, Golden, CO. January. United States Integration Available at http://www.nrel.gov/publications/ Wind Northwest Wind Integration Action Plan, 2007. Available at United States Integration http://www.nwcouncil.org/energy/Wind/Default.asp New York - General Electric, NYSERDA Phase 2 Appendices Wind Available at United States Integration http://www.nyserda.org/publications/wind_integration_apps.pdf Wind Pacificorp, 2007. Integrated Resource Plan. Available at United States Integration http://www.pacificorp.com/Navigation/Navigation23807.html Wind Integration, Parsons, B. et al. 2003, Grid Impacts of Wind Power: A Summary of Grid Recent Studies in the United States. Available at United States System http://www.neo.ne.gov/reports/grid-integration-studies-draft.pdf
B-30 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Pete, C., (2010). Implications on hydropower from large-scale integration of wind and solar power in the West: results from the Western Wind and Solar Wind- Integration Study, Thesis Report, Northern Arizona University Hydro Mechanical Engineering Department, 2010. Available from the cline United States Integration library at http://www.nau.edu/library/ Piwko, R., Clark, K., Freeman, L., Jordan, G., Miller, N., (2010). Wind Western Wind and Solar Integration Study, NREL Subcontract Report, 2010. United States Integration Available at http://wind.nrel.gov/public/WWSIS/ Porter, Kevin. 2007. PIER Project Report: Review of International Experience Integrating Variable Renewable Energy Generation, California Energy Commission. Available at Wind http://www.energy.ca.gov/pier/final_project_reports/CEC-500- United States Integration 2007-029.html Porter, Kevin. 2007. PIER Project Report: Review of International Experience Integrating Variable Renewable Energy Generation: Appendix A Denmark, California Energy Commission. Available at Wind http://www.energy.ca.gov/pier/final_project_reports/CEC-500- United States Integration 2007-029.html Porter, Kevin. 2007. PIER Project Report: Review of International Experience Integrating Variable Renewable Energy Generation: Appendix B Germany, California Energy Commission. Available at Wind http://www.energy.ca.gov/pier/final_project_reports/CEC-500- United States Integration 2007-029.html Porter, Kevin. 2007. PIER Project Report: Review of International Experience Integrating Variable Renewable Energy Generation: Appendix C India, California Energy Commission. Available at Wind http://www.energy.ca.gov/pier/final_project_reports/CEC-500- United States Integration 2007-029.html Porter, Kevin. 2007. PIER Project Report: Review of International Experience Integrating Variable Renewable Energy Generation: Appendix D Spain, California Energy Commission. Available at Wind http://www.energy.ca.gov/pier/final_project_reports/CEC-500- United States Integration 2007-029.html Porter, Kevin. 2007. Intermittency Analysis Project: Final Report. California Energy Commission, Public Interest Energy Research Program. July, 2007. Available at Wind http://www.energy.ca.gov/pier/final_project_reports/CEC-500- United States Integration 2007-081.html Wind Potter, Cameron et al. 2008. Creating the Dataset for the Western Wind Integration, and Solar Integration Study (U.S.A.). 7th International Workshop on Wind Large Scale Integration of Wind Power and Transmission Networks United States Forecasts for Offshore Wind Farms.
B-31 Hydroelectric Industry’s Role in Integrating Wind Energy
Country/ continent (leading author) Topic Reference Ray, M.L. et al. 2006, Analysis of Wind Shear Models and Trends in Different Terrains, University of Massachusetts. Available at Wind www.ceere.org/rerl/publications/published/2006/AWEA%202006 United States Forecasts %20Wind%20Shear.pdf Princeton Energy Resources International (PERI), Vermont Environmental Research Associates, (2002). Wind and Biomass Integration Scenarios in Vermont, Summary of First Phase Research: Wind Wind- Energy Resource Analysis Prepared under DOE project, number DE- United States Hydro FG01-00EE10762, March. Shiu, H., Milligan, M., Kirby, B. Jackson, K., 2006. California Renewables Portfolio Standard Renewable Generation Integration Cost Analysis. California Energy Commission, PIER Public Interest Energy Research Program. Available at Wind http://www.energy.ca.gov/pier/final_project_reports/CEC-500- United States Integration 2006-064.html Short, W., and Sullivan, P. 2007, Modeling the National Potential for Offshore Wind, Preprint, NREL. Available at Wind http://cc.msnscache.com/cache.aspx?q=73373285619372&mkt=en- United States Integration US&lang=en-US&w=f6da4623,ac70722f&FORM=CVRE Smith, Charles and DeMeo, Edgar et. al. 2004. Wind Power Impacts On Electric Power System Operating Costs: Summary And Perspective On Work Wind To Date, American Wind Energy Association Global WindPower United States Integration Conference, Chicago, IL, March. Available at http://www.uwig.org Smith, J. C., Milligan, M.R., DeMeo, E.A., Parsons, B. Utility Wind Wind Integration and Operating Impact State of the Art. IEEE Transactions on United States Integration Power Systems, Vol. 22, No. 3, August 2007. Smith, J.C, Parsons, B., Acker, T., Milligan, M., Zavadil, R., Schuerger, M., and DeMeo, E., 2007, Best Practices in Grid Integration of Variable Wind Power: Summary of Recent US Case Study Results and Wind Mitigation Measures, Proceedings of the 2007 European Wind Energy United States Integration Conference, Milan, Italy, May. TrueWind Solutions and AWS Scientific, 2003. Overview of Wind Wind- Energy Generation Forecasting. Draft Report. New York State Energy and United States Hydro Research Development Authority. Walling, Reigh. Analysis of Wind Generation Impact on ERCOT Ancillary Services Requirements; GE, March, 2008. Available at Wind http://www.ercot.com/news/presentations/2008/Wind_Generatio United States Integration n_Impact_on_Ancillary_Services_-_GE_Study.zip Wan, Y, 2005. Fluctuation and Ramping Characteristics of Large Wind Power Plants. Windpower 2005 (Windpower 05) Conference and Exhibition (CD-ROM), 15-18 May 2005, Denver, Colorado. Wind Washington, DC: American Wind Energy Association; Content United States Integration Management Corp. 13 pp.; NREL Report No. CP-500-38057.
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Country/ continent (leading author) Topic Reference Wind Wan, Y. and Liao, J.R. 2005. Analyses of Wind Energy Impact on WFEC Integration, System Operations, NREL/TP-500-37851, National Renewable Energy Systems Laboratory, Golden, CO, August. Available at United States Analysis http://www.nrel.gov/publications/ Wan, Y. 2005. Primer on Wind Power for Utility Applications. NREL Wind Report No. TP-500-36230. Available at United States Integration http://www.nrel.gov/publications/ Wind Wan, Y. 2004, Wind Power Plant Behaviors: Analyses of Long-Term Wind United States Integration Power Data, NREL. Available at http://www.osti.gov/bridge Westrick, Kenneth and Storck, Pascal and Froese, Gerry. Reliance on Renewables - The Synergistic Relationship between Wind and Hydro Power, Wind- American Wind Energy Association, 2002. Available at United States Hydro http://www.awea.org/publications/ Wiser, Ryan and Bolinger, Mark, Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2006, U.S. DOE Energy Wind Efficiency and Renewable Energy. Available at United States Integration http://www1.eere.energy.gov/windandhydro/pdfs/41435.pdf Wind Wolf, K. Wind Integration Study Introduction, Minnesota Department of United States Integration Commerce. Zack, J. 2003, Overview of Wind Energy Generation Forecasting, Wind NYSERDA, TrueWind Solutions. Available at Integration, http://www.nyiso.com/public/webdocs/services/planning/special_ United States Forecasting studies/forecst_overview_report_dec_2003.pdf Zavadil, R.M. 2003. Wind Generation Technical Characteristics for the Wind NYSERDA Wind Impacts Study, EnerNex Corporation, Knoxville, United States Integration TN, November. Zavadil, R, 2006. Wind Integration Study for Public Service Company of Colorado, May 22, 2006. Available at Wind http://www.xcelenergy.com/XLWEB/CDA/0,3080,1-1- United States Integration 1_1875_15056_15473-13518-2_171_258-0,00.html Wind Integration, Zavadil, R.M. 2006. WAPA Wind Integration Study, EnerNex Wind- Corporation, Knoxville, TN. August. Available at United States Hydro http://www.enernex.com/staff/publications.htm
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B-34 Hydroelectric Industry’s Role in Integrating Wind Energy
APPENDIX C. Overview of Wind Power: Technology, Costs, Penetration, and Policies
People throughout the world have been using energy at an unprecedented level over the past century, ultimately leading to conditions that have impacted the costs of energy and related environmental concerns. These conditions in addition to an ever increasing demand have resulted in wind energy becoming the world’s fastest growing renewable power source. Over the last 20 years, the costs of utility-scale wind systems have dropped by over 80% as a direct result of advancements in technology and policies that enable wind to be competitive with new gas or coal-fired power systems. With over 120 GW of global wind capacity installed by the end of 2008, 260 TWh of 19 electricity will be generated annually, avoiding 158 million tons of CO2 emissions. Government agencies, such as the National Renewable Energy Laboratory (NREL) in the United States and Risø, the National Laboratory for Sustainable Energy at the Technical University of Denmark, have been formed to proactively develop and improve the next generation of renewable energy technology, thus helping drive down costs. This appendix presents an overview of wind power technologies, costs, penetration levels, and policies related to wind energy development.
C.1 Wind Technology
Wind technology has drastically improved over the past 40 years, reducing capital costs, increasing efficiency, and improving reliability. Drag-based and simple lift-based designs (that were once used primarily for grinding grain or pumping water) have given way to analytically and experimentally designed and tested high-lift rotors. Blades that were once made of sail or sheet metal have been replaced with state-of-the-art composite material blades. The induction generator (variable-speed utilizing advanced power electronics) have become grid synchronized, overriding the DC alternator. Mechanical linkages that once furled a machine have been replaced with high-speed digital controls. Models such as finite element analysis and structural dynamics codes make the turbine of today stronger yet less expensive than the forerunners of years past. Sizes considered large in the 1980’s (50 kW) are now dwarfed by common 1.5 MW and larger turbines of today [U.S. Department of Energy 2008].
C.1.1 The Commercial Wind Turbine
Today’s modern wind turbines have a three-bladed rotor system with diameters anywhere from 70 to 80 meters. The towers supporting the nacelle are typically on the order of 60 m to 80 m in height. Figure C-1 illustrates how the commercial wind turbine has grown in size and power over time.
19 GWEC’s Global Wind Energy Report available at http://www.gwec.net/fileadmin/documents/Global%20Wind%202008%20Report.pdf accessed April 2010.
C-1 Hydroelectric Industry’s Role in Integrating Wind Energy
Figure C-1: Evolution of wind turbine size over time. (Source: EWEA20)
Typical array sizes range from 30 to 150 turbines in a wind power plant. In the United States in 2008, the average turbine could output 1.68 MW of electrical power. The amount of power available in the wind can be defined as: 1 Power WindinAvailable AV 3 2 Where ρ is the mass density of the air, A is the swept area of the rotor blades, and V is the wind speed. Thus, the amount of power available is highly dependent on the wind speed due to the cubic relationship between the two [Manwell et al. 2008]. For example, a 20% increase in wind speed creates a 73% increase in wind power. Of this available energy, the maximum power that can be extracted is 1 Maximum extractedbecanthatpower AVCwindthefrom 3 p max 2
In this expression, Cpmax is the maximum value of the power coefficient possible for a wind turbine, known as the Betz Limit (theoretically equal to 59%; the best Cp achievable on a commercial turbine is usually in excess of 40%). As the height above the ground increases, the wind speed also increases. The shape of this increase, known as the vertical wind shear, can be thought of as increasing logarithmically. For this reason, and due to the cubic relationship between power and wind speed, turbines are continually becoming taller. As the turbine hub heights increase, the rotor diameters also grow, increasing the swept area and further improving the energy capture.
An illustration of the common components in a wind turbine is shown in Figure C-2.21 The energy in the wind is extracted as the air flows past the rotor blades, generating lift and causing the blades to apply a torque to the low-speed shaft, thus spinning the rotor. Most modern wind turbines have rotor blades that can pitch along their long axis, which changes the angle of attack of the wind approaching the blades. Modifying the pitch permits optimization of the aerodynamics and control of turbine power output. For the rotor blades to operate effectively, the nose of the turbine should be pointed directly into the oncoming wind, positioning the blades in front of the tower. This configuration is typical of most utility-scale, megawatt-sized turbines, which are consequently referred to as “upwind turbines” (indicating the position of the blades relative to the tower). Pointing the turbine into the wind is achieved by adjusting the “yaw” of the turbine and rotating the
20 See AWEA’s Wind Energy and Research at http://www.ewea.org/fileadmin/ewea_documents/documents/publications/factsheets/EWEA_FS_Research.pdf accessed April 2010. 21 Available at http://windeis.anl.gov/guide/basics/turbine.html accessed April 2010.
C-2 Hydroelectric Industry’s Role in Integrating Wind Energy
nacelle around the tower into the direction of the wind through use of a yaw motor. Downwind rotors are far less common in commercial technology, though small wind applications do employ downwind systems. Wind sensors, such as wind vanes (measuring wind direction) and anemometers (measuring wind speeds), give inputs to the yaw controller. Additionally, these wind sensors, along with the drivetrain (gearbox, generator, and power converter) sensors, are used to inform the blade pitch controller how to regulate power and rotor speed to optimize power output and avoid overloading individual components.
Figure C-2: Illustration of wind turbine components. (Source: Wind Energy Development Programmatic EIS)
Generally, the cut-in wind speed, or speed at which the turbine will start producing power, occurs in wind speeds of about 4 to 5 m/s. Rated power or maximum power output is at about 12 to 13 m/s. The cut-out wind speed (when blades begin to feather to stop power production and avoid over loading) occurs for sustained winds at about 22 m/s. Advanced braking systems stop production at these speeds to avoid mechanical damage to the unit [U.S. Department of Energy 2008]. Overall, the variation of a wind turbine’s power output with the incoming wind speed is called the turbine’s “power curve.” Figure C-3 illustrates an example power curve, including actual field observations. Depending on the technology implemented into a turbine’s design and control systems, each wind turbine will have a different power curve.
C-3 Hydroelectric Industry’s Role in Integrating Wind Energy
Figure C-3: Example of a wind turbine power curve with observed data. (Source: Acker 2007a; power curve provided by 3TIER)
As for the eventual scale of land-based wind turbines, many designers don’t expect these turbines to become larger than 100-meters in rotor diameter with power output greater than 5 MW (assuming current technology) due to the logistics of transportation and construction constraints from suppliers to the customers. Another primary argument for limiting turbine size is based on the “square-cube law”. This law explains that as a rotor diameter grows in size, its energy output increases roughly as the diameter squared (i.e. rotor swept area), while the volume of the material (e.g. mass and cost) increases as the cube of the diameter, thus at some rotor diameter, the cost will grow faster than the corresponding energy output revenue [U.S. Department of Energy 2008].
C.1.2 Turbine Components
Rotors
Turbine blades have increased in length from about 8-m in the eighties to currently over 70-m, while improving in strength and fatigue resistance. Using specially designed airfoils for different turbine applications and wind regimes, multiple airfoil designs are currently used along a single blade, thus optimizing low-speed wind aerodynamic efficiency, minimizing sensitivity to blade fouling due to dirt and bugs accumulating along the leading edge of the blade, and limiting aerodynamic loads in high winds. The ability to control pitch independently on each blade has significant improvements over the first generation (fixed-pitch or collective-pitch linkages) by enabling the blades to feather or rotate out of the wind, reducing maximum loads when parked and even during operation.
Controls
Current control systems used in wind turbine applications integrate the signals from various sensors to control rotor speed, blade pitch angle, generator torque, power conversion voltage, and phase angle. The control system is also responsible for safety precautions, such as shut down during
C-4 Hydroelectric Industry’s Role in Integrating Wind Energy extreme events. Additionally, the control system sets the rotor speed in variable speed turbines to obtain peak efficiency in varying wind speeds by constantly updating the rotor speed and generator loading to maximize power and reduce momentary drivetrain torque loads. Power converters are also used in variable speed systems, allowing for the ability to deliver fault ride-through protection, voltage control, and volt-ampere-reactive (VAR) support to the grid system.
Drive train
Historically, converting torque to electrical power has been accomplished using a speed-increasing gearbox and an induction generator (such as the one shown in Figure C-2). Today’s turbines typically use a three-stage gearbox consisting of planetary gears and parallel shafts. Generators can either be squirrel-cage induction or wound-rotor induction, with the latest systems using the doubly fed induction design for variable speed (rotor’s variable frequency electrical output is fed into the collection system through a solid-state power converter). It now has become standard practice to perform extensive dynamometer testing of new gearboxes to prove reliability and robustness due to maintenance issues and related failures of the past.
Tower
Tower configurations used exclusively today consist of a steel monopole on a concrete foundation, varying slightly with location and site conditions. The main variable in tower design is considerations related to height. This is due to the optimization of energy capture with respect to cost. Depending on the wind regime and site characteristics, a turbine may be placed on a 60-m to 80-m tower, but 100-m towers are now being implemented and used more frequently. Various foundation designs are being tested and are in use to minimize material usage and costs.
Balance of Station
The balance of station (BOS) of the wind farm consists of turbine foundations, the electrical collection system, power-conditioning and service equipment, supervisory control and data acquisition (SCADA) systems, service/access roads, maintenance and control/observatory buildings, and engineering permits.
C.1.3 Offshore Wind Technology
Many of the costal shores around the U.S. and other countries possess an abundant and broadly dispersed wind energy resource. Often, these wind resources are near some of the highest load areas. The U.S. DOE’s Energy Information Agency shows that the 28 states in the lower 48 states with a costal boundary use 78% of the nation’s electricity [EIA 2006]. The shallow-water offshore wind turbine is essentially an upgraded version of the land-based wind turbine, with some changes incorporated into the system to account for the marine environment. These modifications include: structural/tower reinforcement (accounting for wave loads), pressurized nacelles, environmental controls (preventing corrosive effects of salt water from degrading drive train and electrical components), and access platforms. Additionally, to minimize servicing expenses, turbines may be equipped with enhanced condition monitoring systems, automatic bearing lubrication systems, on- board service cranes, and oil temperature regulation systems. Typically, rated power is higher than land-based turbines, in the range of 2 to 5 MW, and rotor diameters are increased to 80-m to 125- m. Current foundation technology is a limiting factor for deployment of large turbines in deep
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water. Baseline technology uses monopiles at depths of up to 30-m. Monopiles are large steel tubes with wall thicknesses of up to 60-mm and diameters of 6-m. Embedded depth depends on soil conditions, but a typical North Sea installation must be embedded 25-m to 30-m below mud line. Once set in place, the monopile extends from the sea bottom to just above the sea surface where a tower is connected to the top of the monopile. These foundations require specialized equipment for driving the pile into the seabed and lifting the turbine structure into place. As water depths increase beyond 30-m, at transitional depths (between 30-60 m deep), towers will use some sort of substructure, possibly similar to that of current oil and gas practices. In deep water (60-m to 900- m), floating technology will have to be employed. Power is exported through grid connections aggregated from each turbine via high-voltage subsea cables. Various interconnection points might be used to step-up the voltage before connecting to the power grid. In any case, offshore technology would open up major wind resource areas along coastal cities to wind development [U.S. Department of Energy 2008]. Currently, there are no offshore wind developments in the U.S., but there are some in Europe.
C.2 Costs of Wind Energy
The costs of wind energy have changed dramatically over the past 30 years as the cost of wind power has fallen by nearly 80 percent during that period. This can be seen from Figure C-4, illustrating wind project installed costs in 2008 dollars. However, due to recent increases in material costs, the weak U.S. dollar, and with turbine/component shortages, the cost has risen slightly over the past couple of years. Although costs are predicted to rise slightly over the next few years, costs will continue to decline overall as the industry progresses and matures [Wiser 2009].
Figure C-4: U.S. Installed wind power project costs. (Source: Wiser 2009)
Despite the recent cost increases, the wind industry is still growing. Several key factors affecting the economics of wind energy and its competitiveness in today’s energy marketplace are listed below.22
22 See AWEA website on Wind Energy Costs at http://www.awea.org/faq/wwt_costs.html accessed April 2010.
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Wind Speed – As mentioned before, the power available in the wind is proportional to the cube of wind speed, thus higher wind speed regimes result in more energy captured, driving down the cost of electricity. Wind resource evaluation is a critical criterion to estimating a turbine’s performance at a potential site. Normally, wind speeds have diurnal and seasonal patterns. Areas that are considered a good wind resource will have consistent winds throughout the year, and especially be productive during the peak load times of the day and year. Generally, average wind speeds greater than 5 m/s are required for grid-connected applications to be economically viable.23 Table C-1 lists the different wind power classes with corresponding wind power densities and wind speeds.
Table C-1: Wind power resource table at 10 m and 50 m heights. (Source: AWEA)
Turbine Design – Improvements in turbine technology and design, economy of scale, increases in height, and larger rotor diameter has enabled wind turbines to capture and produce more energy than less efficient designs of the past. For example, consider the turbine data for two typical turbines shown in Table C-2 – one turbine from 1981 and another from 2000.
Table C-2: Cost and performance difference between turbines from two generations with differing technologies (Source: AWEA) Year – Rated Output 1981 – 25 kW 2000 – 1.65 MW Diameter 10 m 71 m Total Cost $65,000 $1,300,000 Cost per kW $2,600 $790 Annual Output (MWh) 45 MWh 5,600 MWh
23 See AWEA website on Wind Resource Evaluation at http://www.awea.org/faq/basicwr.html accessed April 2010.
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Wind Plant Size – Larger wind power plants typically have a lower cost of energy than smaller turbines due to economies of scale. For example, consider two wind power plants using the same wind turbines located in similar wind regimes: a wind power plant of 51 MW delivers electricity at a cost of $0.036 per kWh while a smaller power plant of 3 MW delivers its cost of electricity at $0.056 per kWh, a 40% decrease.24 Financing Costs – Because wind energy systems are capital-intensive, financing wind projects is typically more expensive than financing conventional generators. In the U.S., wind projects are typically financed by independent power producers (IPPs) (on a stand-alone basis). These projects are typically more expensive to finance when compared to utility- owned financing due to the fact that large electric utilities (investor-owned utilities) have access to lower-cost financing options which may reduce levelized costs by up to 30%. Additionally, wind turbine technology is still regarded as novel by many members of the U.S. financial community and lenders, and therefore, they offer less favourable financing terms and demand higher rates of return on their investments. 25 Integration Costs – Recent studies have shown that wind integration costs will continue to rise as wind penetration levels increase. These costs are typically well below $10/MWh and are often less than $5/MWh, up to wind penetration levels as high as 30% of the peak load. Operating strategies to reduce these costs are being considered, such as larger balancing areas, using a regional wind power forecast for informed operational decisions, and intra- hour generation scheduling [Wiser 2009]. Transmission Costs – Market access and transmission constraints can impact the cost of wind energy. Traditional penalties may be applied to deviations from scheduled wind generation. Interconnection procedures can occasionally be difficult to acquire, and transmission is regularly built from the wind site to the interconnection bus (several miles). Additionally, due to the remoteness of the wind plant, transmission access rates to deliver the power may differ from line to line26. Government Incentives – Depending on the country, there may be financial incentives to employ wind power, such as feed-in tariffs or tax incentives. For example, the incentive that the U.S. government has set in place for utility-scale wind plants is the production tax credit (PTC), an income tax credit set at 2.1 cents/kWh of electricity produced for the first 10 years of the project. Offshore Costs – Worldwide, offshore wind capacity increased to 1,400 MW in 2008. This technology is still immature (resulting in high costs), and it is estimated that a current project’s installed cost will be in the range be of $2,400 - $5,000 per kW of installed capacity [Wiser 2009]. O&M costs – Costs have decreased significantly since the 1980’s as a result of improved turbine design and quality. Looking at a capacity-weighted average for historical U.S. wind projects, those constructed in the 1980’s have an equivalent O&M cost equal to $32/MWh, decreasing to $22/MWh for projects installed in the 1990’s and dropping to $8/MWh for projects brought online in the 2000’s. Figure C-5 illustrates the averaged O&M costs over
24 See AWEA website on Economics of Wind Power at http://www.awea.org/pubs/factsheets/EconomicsOfWind-Feb2005.pdf accessed April 2010. 25 See RenewableUK (formally known as BWEA) website on Economics of Wind Energy at http://www.bwea.com/ref/econ.html accessed April 2010. 26 See AWEA website on Fair Transmission Access to Wind: A Brief Description of Priority Issues at http://www.awea.org/policy/documents/transmission.PDF accessed April 2010.
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2000-2008 with the O&M costs trend line decreasing. Two key conclusions can be drawn about O&M costs: generally, they will increase as the project’s timeline increases due to aging components and manufacturers’ warranties expiring; and secondly, recent projects brought online with larger and more sophisticated designs will have lower overall O&M costs when compared on an energy-produced basis [Wiser 2009].
Figure C-5: Average O&M costs for U.S. wind projects. (Source: Wiser 2009)
C.3 Wind Energy Penetration
Over the past 10 years, global capacity levels of wind power have increased to unprecedented levels. With many of the driving factors described in the previous sections, wind energy has and will continue to grow for years to come. Figure C-6 illustrates the cumulative wind capacity levels as of December 2009. On an annual basis, in 2008, the U.S. installed 8,558 MW of wind capacity, followed by China with 6,246 MW [Wiser 2009].
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Figure C-6: The top 10 countries in terms of cumulative installed wind power capacity. (Source: EWEA)
As global capacity levels of wind power continue to rise, annual energy generation levels continue to climb. Several countries have begun to reach high penetration levels (see Figure C-7), the most notable being Demark at 20%, Spain at 13% and Portugal at 12%. U.S. penetration levels are at 1.9%, although individual states are now beginning to achieve higher levels, such as Iowa at 13.3%, Minnesota at 10.4%, and some individual utilities seeing excess of 10% on their individual systems [Wiser 2009].
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Figure C-7: International wind power penetration levels. (Source Wiser 2009)
C.4 Policies
Several policies have been imperative to the acceptance and expansion of the wind power market. European countries often set predefined feed-in tariffs for wind energy to encourage development. In the U.S., the PTC has sustained industry growth since it was first established in 1992 by the Energy Policy Act and has currently been extended through December 2012. Other federal policies have also helped support wind development, such as allowing property used for wind power to be depreciated for tax purposes. For entities unable to take advantage of tax incentives, the Energy Policy Act of 2005 created the Clean Renewable Energy Bond program (CREB). This program allows eligible renewable energy projects interest-free debt. In 2007, 102 wind projects received over 170 million dollars27. The United States Department of Agriculture (USDA) also provides loan guarantees and grants to eligible renewable energy and energy efficiency projects and programs. On a state level, Renewable Portfolio Standards policies are helping to spur wind development levels in rural areas in need of economic development. State renewable energy funds and state tax incentives are also providing support. Utility resource planning requirements, such as integrated resource planning (IRP) in the Western half of the U.S., have also helped establish opportunities to serve loads through energy efficiency and demand reduction programs. Ultimately, environmental impacts of global climate change are driving awareness and concern on a state, regional, and federal level to mitigate greenhouse gas reductions. These policies will certainly strengthen wind growth and other forms of renewables. These policies have made the wind industry more robust and stronger than any time over the last decade, and the support will only continue to grow. Below are a few websites with links attached for additional information on wind policies:
EWEA – Policy Overview available at: http://www.ewea.org/index.php?id=1446 AWEA – Policy Resources available at: http://www.awea.org/policy/ and Policy Issues available at: http://www.awea.org/faq/wwt_policy.html
27 See AWEA website on Wind Energy for a New Era at http://www.newwindagenda.org/ accessed April 2010.
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GWEA - A study of pricing policy of wind power in China available at: http://www.gwec.net/index.php?id=156&L=0 IEA – Policy and measures database addressing energy efficiency available at: http://www.iea.org/textbase/pm/?mode=pm and policy and measures addressing climate change database available at http://www.iea.org/textbase/pm/?mode=cc Windustry – U.S. Federal and State policies available at: http://www.windustry.com/federal- policy-descriptions DSIRE – Database of U.S. incentives for renewable energy available at: http://www.dsireusa.org/ DOE – Wind Powering America policy information available at: http://www.windpoweringamerica.gov/policy/index.asp NREL – Technical report on policies and market factors driving wind power development in the U.S. available at: http://eetd.lbl.gov/ea/emp/reports/53554.pdf RenewableUK – Planning Policy available at http://www.bwea.com/planning/uk_planning_legislation.html
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APPENDIX D. Methods to Quantify Wind Integration Impacts and Costs
The methods used to estimate wind integration impacts, costs, and benefits may differ somewhat based upon the information sought, the tools used to conduct the study, the organization(s) conducting the study and resources at its/their disposal, and the nature of the electrical system into which the wind power is being incorporated. An illustration showing the variety of potential integration study topics, varying from the very short time-scale electrical system studies to the long- term capacity expansion studies, is provided in Figure D-1. This figure has been drawn from the final report of International Energy Agency (IEA) Wind Implementing Agreement (IA) Task 25 [Holttinen et al. 2008]. The red oval labeled “Task 25” encapsulates many impact study topics (shown in the blue bubbles and corresponds to the studies of interest in Task 25). Generally speaking, these topics are also the topics of interest in wind and hydropower integration, focusing on system planning, operation, and optimal use of resources, but are not necessarily on the short- term electrical modeling of voltage and frequency (though these studies are of importance, they are exceedingly system dependent and handled through the electrical design and interconnection). The IEA Wind IA has also sponsored Task 24 on the “Integration of Wind and Hydropower Systems.” Task 24 focused on specific case studies addressing wind integration into systems with hydropower, ranging across the topics suggested in Figure D-1, and performed by organizations in the US, Canada, Europe, and Australia. The final report of this task is expected to be released in 2010, and will complement and extend the information provided in this report. Regarding wind integration studies, ideally all aspects of the power system could be modeled for all the appropriate time frames and projected to any desired future point. However, a study’s available finances, deadlines, and human and computational resources dictate that trade-offs must be made to meet study goals. To help the reader interpret the results presented in this report and other wind integration studies, a broad description of some of the methods that have been used will be presented, followed by a brief list of specialized wind integration study terms not presented elsewhere in this report.
Figure D-1: Range of time- and geographic-scales that may be of interest in wind integration studies. (Source: Holttinen et al. 2008)
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With regard to overall scope, wind integration studies can range from simple to a highly detailed model using of sophisticated methodologies, and may strive to simulate the effect of wind power in the current electrical system as operated, or attempt to simulate some future power system operating under different circumstances and constraints (different resources, operational practices, transmission interconnections, policies, etc.). Furthermore, wind integration can be considered from a holistic point of view (the “overall value” of wind power in the system; refer to the blue bar on the right side of Figure 1-2 in the main body of this report) or from an “integration cost” point-of-view where the impacts and costs of the uncertainty and variability of wind power are analyzed (refer to the bottom section of the red bar in Figure 1-2). Naturally, there are studies that are a combination of the two; for example, developing a new wind integration product using dedicated hydropower resources (e.g., firming and shaping, energy redelivery, provision of short term reserves, etc.) where the integration costs must be covered by the revenues produced through sale of the product. Regardless of the perspective adopted, the fact is that wind integration studies should always be considered in the context of the entire system with its load, generation resources, and interconnections. Just as the load is served at the time of its demand, wind power is absorbed into a power system as it is generated, effectively showing up as negative load. Consequently, the impact of wind power should always be contemplated in terms of its impact on the overall system’s load net wind (i.e., the system load with the wind power subtracted), often referred to as “net load.” The resources of the remaining power system are then required to balance the net load via its available mechanisms (on-line resources, market transactions, etc.).
With respect to the level of detail of an integration study, a simple study typically looks only at the effect of wind power on system load, and in particular the change in the variability and forecast uncertainty of the load net wind. A simple study may use a statistical approach, with detailed histograms, but temporal correlations between actual load events and wind production are not captured. In essence, a simple study provides an indicator of how much additional flexibility may be required to accommodate the additional variability and uncertainty that wind power adds to the load’s variability and uncertainty. This type of study is conducted most frequently to determine impacts on time scales for the operational reserves: seconds, minutes, and hourly.
In addition to the information provided by a simple study, wind integration studies often employ a chronological simulation of system operation. Thus, a detailed study simulates the system operation in order to deduce the impacts and costs of wind integration. System operations are simulated at some fine time resolution (e.g., 1 hour) using coincident wind and load data. In such a simulation, unit commitment and dispatch are simulated using a production cost model28 that includes interactions with neighbouring systems, yielding an adjusted production cost (APC). The load data in these studies are typically historical, often scaled to some future load level, and the wind power data are typically created using a meso-scale, numerical weather prediction model to retroactively estimate what a hypothetical set of wind power plants would have generated during the same year(s) as the load data. With this method, some of the weather-driven correlation between the load and the wind is preserved. The data, along with synchronized load and wind power forecast data (or simplifying assumptions to approximate them) are then used to determine the APC. The simulation proceeds to compute the cost to operate the system over some time frame (at least 1-year) by mimicking the decision processes made day-ahead and hour–ahead, and then deducing the impact of wind integration by comparing some base case scenario (e.g., no renewables in the system) to cases that
28 For example, modeling tools such as GE’s MAPS, Ventyx’s PROMOD, Riso’s Wilmar, ABB’s GridView, Argonne’s GTMax, to name a few.
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include increased levels of wind penetration and energy. In performing the simulation, the modeling platform (e.g., production cost simulation software) is constrained to realize some system reliability requirements, and possibly include transmission limitations, while optimizing some performance criteria, usually the production costs. Beyond determining wind integration costs due to uncertainty and variability, detailed simulations that employ cost production models are also capable of determining the overall value of the wind energy, thus permitting evaluation of changes in the system composition, constraints, and operation, in search of more efficient ways to incorporate wind power and to evolve the power system.
Söder and Holttinen (2008) published an article describing approaches taken when setting up and performing a wind integration study. Adapted from their paper, Figure D-2 provides an illustration of two similar-balancing areas with the exceptions that System 2 is incorporating some amount of wind power while System 1 includes some “other” power generation resources that would be “replaced” by the wind power. The other power sources could be any type of generation, existing or new. The “remaining system” shown represents the remaining power system and is the same in both systems. Depending on how the replaced system is defined, and the assumptions employed in modeling, the study could be classified as either simple or detailed, as mentioned previously. Söder proposes that the “integration cost” is the difference in operating costs (O) for the two systems, assuming each is run optimally given its technical and economical specifications, including any investments (I) that might be made that reduce the overall operating cost (in essence, the integration cost is the difference between the APC for the two systems). Written in equation form:
Integration cost = (Owind – Oreplaced) – (Iwind – Ireplaced)
This simple equation applies for any type of integration cost study. If one is interested in determining the integration costs as defined in Figure 1-2, then the two systems are set-up such that the only difference between the two is the variability and uncertainty of the wind energy (at least to a close approximation). If, on the other hand, one is interested in finding optimal ways to evolve the power system, or how it will perform under various different circumstances (policies, generation resources, etc.), then there may be numerous differences between the two systems that are compared. For example, one may consider different transmission elements or constraints, different generation resources, market rules, scheduling intervals, etc.
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Figure D-2: Determining the impact and costs of wind integration by comparing the costs of operating two variations of an electrical system, one with wind and one with some other set of generation resources. (Source: Söder and Holttinen 2008)
A block diagram illustrating a variant of the methodology employed in detailed wind integration studies is shown in Figure D-3, taken from the final report of the wind integration study conducted for Xcel Energy and the Minnesota Department of Commerce in 2004 [EnerNex 2004]. The results of this type of study provide, among other things, wind integration cost estimates caused by an increased need for reserves and balancing resources due to the additional variability and forecast uncertainty in net load caused by wind energy. Often, this deduction of the integration cost is made through a comparison in which the wind power is replaced by some other generation resource. In some cases, this replaced resource is defined as an ideal generation resource, possessing none of the variability and uncertainty of wind energy, but available at the same cost as wind energy and in the same quantities. This is the comparison suggested by the “flat” profile in the block diagram of Figure D-3. The “actual” system production cost will incorporate day-ahead wind hind-casts and load forecasts in committing units and then simulate dispatch decisions in the intra-hour time frame. This can then be compared to a reference system production cost generated with only load forecasts to make dispatch decisions and simulating the non-wind portion of the power system’s dispatch decisions in the intra-hour time frame (not shown in Figure D-3).
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Figure D-3: Block Diagram Representation of one method used in detailed wind integration studies. (Source: EnerNex 2004)
The level of realism and complexity in a power system model is a function of the time-varying data inputs. The models are very data-intensive and require detailed, time-dependent information on a number of parameters. Some of the data inputs for these models include:
Generators: Capabilities, heat rates, variable costs, fixed costs, minimum up-time, minimum down-time, emissions Fuel: Costs, transportation, emissions Load: Load shape, peak load, energy, hourly load profiles, load forecasts Transmission: Topology, flowgates, transfer limits Regional: Reserve requirements, spinning reserves, hurdle rates
A number of these data inputs serve as constraints that must be honoured at all times. There are generally four types of constraints that may be modeled in a power system model: transmission, generator, area, and balance. Transmission constraints are limited by the available transfer capability (e.g., flowgates, nomograms). Generator constraints are capacity limits, ramp rates, and minimum up- or down-times. Area constraints include reserve and spinning reserve requirements. Balance constraints are the limitation that generation plus energy exchanges must equal the load plus losses at whatever timeframe that is being considered. Balance constraints may be imposed across several levels (e.g., intra-zone, across a power pool). When considering the range of power system models, it is possible to categorize them into two basic classes: power flow models and cost production models. The main characteristics of these models are described in Table D-1.
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Table D-1: Characteristics of two major classes of models used in wind integration studies. Power Flow Models Production Cost Models Simulates a limited period of time (e.g., summer Simulates grid operations for at least a full year peak demand) AC model DC model Unit commitment and dispatch fixed Unit commitment and dispatch dynamically optimized All transmission constraints and flowgates Transmission constraints limited (or ignored) considered Shorter run times (although shorter period Longer run times studied) Used for wind generator interconnection, Used for wind integration and economically transmission planning, and reliability studies focused studies
The purpose of this appendix was to provide an introductory overview to the methods used in determining wind integration impacts and costs. The basic idea in any integration study, whether it is determining the more limited “integration cost” or the more expansive “value of wind energy,” is to analyze the effect of wind power on the net load of the entire system. Some studies are purely statistical and are used to provide approximate results, whereas others are quite detailed and attempt to simulate the operation of the power system at an hourly level, taking into account the decision processes and market transactions that occur in system operation. In deducing the impact of wind energy on system operation, a comparison is made between the system that is operated with wind power versus the system that is operated with some other reference set of generation resources.
Some terminology related to power system models:
Adjusted Production Cost is the production cost plus energy import costs (MW imported * load weighted zonal LMP) minus sales revenue (MW exported * generator weighted zonal LMP) Economic Dispatch refers to the decision to dispatch (cycle up or down) previously committed generation units in the most economically efficient manner. Hurdle Rate is the charge for transferring energy between regions and is intended to simulate the effect of various tariffs. Locational Marginal Price (LMP) is the cost to serve one additional MW at a specified node and is composed of three components: energy, loss, and congestion. Nodal refers to a market structure in which energy prices are settled (e.g., by an ISO) on a nodal basis, where a region will have several (in the order of hundreds) nodes. Shadow Price is the production cost reduction that would result by raising the limit on a constraint by 1 MW. Unit Commitment is the process of scheduling generating units to be available for dispatch in real-time operations. This is a binary on or off decision process; both decisions can subject the system to subsequent constraints (i.e., minimum up or down times) and the former incurs start-up costs. Zonal refers to a market structure where prices are settled across many bus-bars. An ISO may have only a few such zones.
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