DOCSLIB.ORG

Capacity Planning and Power Management to Exploit Sustainable Energy

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Capacity Planning and Power Management to Exploit Sustainable Energy Capacity Planning and Power Management to Exploit Sustainable Energy Daniel Gmach, Jerry Rolia, Cullen Bash, Yuan Chen, Tom Christian, Amip Shah, Ratnesh Sharma, Zhikui Wang HP Labs Palo Alto, CA, USA e-mail: {firstname.lastname}@hp.com Abstract—This paper describes an approach for designing a On the supply side, power may come from a primary power management plan that matches the supply of power power source such as the power grid, from local renewable with the demand for power in data centers. Power may come sources, and from energy storage subsystems. The supply of from the grid, from local renewable sources, and possibly from renewable power is often time-varying in a manner that energy storage subsystems. The supply of renewable power is depends on the source that provides the power, the location often time-varying in a manner that depends on the source that of power generators, and the local weather conditions. provides the power, the location of power generators, and the On the demand side, data center power consumption is weather conditions. The demand for power is mainly mainly determined by the time-varying workloads hosted in determined by the time-varying workloads hosted in the data the data center and its power management policies. We center and the power management policies implemented by the assume that the data center has pools of servers that execute data center. A case study demonstrates how our approach can be used to design a plan for realistic and complex data center consolidated workloads, and that these servers support power workloads. The study considers a data center’s deployment in management policies such as capping the amount of power two geographic locations with different supplies of power. Our used by the servers. Power may be capped if the demand for approach offers greater precision than other planning methods power from the grid exceeds the choice for available peak that do not take into account time-varying power supply and grid power. We consider two types of power capping demand and data center power management policies. policies in this work: server power capping and pool power capping. Server power capping exploits dynamic processor Keywords-component; Capacity Planning, Energy Supply frequency scaling to adjust power used by servers. Pool Management, Energy Demand Management, Power Capping power capping dynamically varies the number of running servers based on the availability of power and the demand of I. INTRODUCTION the workloads. The capping methods are complementary. Significant research is underway to develop technologies We describe a trace-driven, simulation based capacity that improve the energy efficiency of data centers and reduce planning tool that is able to simulate power management their dependence on the power grid. On the demand side, activities in data centers and estimate the impact of power virtualization technology is being used to consolidate management plans on application performance and power workloads and improve IT utilization [1]; cutting-edge usage. Traces provide the detailed information needed to: cooling technologies such as dynamic smart cooling [2] and effectively consolidate workloads onto servers; report on air-side economizers further help improve data center energy metrics that express how often demands are satisfied; and, to efficiency. On the supply side, distributed generation and estimate the impact of consolidation on workload renewable energy sources are increasingly being deployed. performance and power consumption. A chosen plan can However, the joint behavior of these technologies in an then be used during the operation of the data center to integrated supplyņdemand context is hard to predict. achieve the desired behavior. The goal of this work is to support the design of a power A case study involving three months of data for 138 SAP management plan that matches the supply of power with the applications in a real data center is used to evaluate the demand for power in data centers. We define a power effectiveness of a set of power management plans. Our management plan as a choice for the peak grid power, a mix approach gives greater precision than other methods that do of renewable energy sources, energy storage, and data center not take into account the time-varying resource usage of the server power management policies. We assume the data data center, the location specific weather data for renewable center also has a backup plan that may require the use of power sources, the time-varying supply of power, the power more grid power or diesel generators when necessary. A management policies, and the impact of energy storage sensitivity analysis using our approach can determine how technologies. often such a backup plan is expected to be employed. The paper is organized as follows. Section II gives an Although this work focuses on design time, the resulting overview of our overall approach. Section III documents the plan and its policies can be used to optimize the real time implementation of server and pool power management and management of the data center. data center energy storage in the simulator. Section IV Peak grid power usage is often a concern for data centers provides characterizations of workload demand variability as it can affect the power infrastructure of grid power and renewable power supply variability. The case study is providers. Contracts are often heavily influenced by peak presented in Section V. Related work is described in Section usage [3] and can impose penalties for exceeding an agreed VI. Section VII offers a summary and the concluding upon peak. remarks along with a description of future research. 978-1-4244-8909-1/$26.00 c 2010 IEEE 96 This paper was peer reviewed at the direction of IEEE Communications Society by subject matter experts for publication in the CNSM 2010 proceedings. Figure 1: Capacity planning to exploit sustainable energy II. APPROACH power supply traces. In our case study, we use traces of Figure 1 shows our approach for design and evaluation of measurements made every 5 minutes for sunshine (global capacity planning and power management processes. The irradiance) and wind data (average wind speed) for two first step uses historical workload demand traces and IT different locations in the US: New Mexico and Colorado. equipment descriptions to compute time-varying IT power The traces cover six weeks, three weeks of June in 1998 and demands for given data center workload on a particular IT three weeks of June in 1999. infrastructure. The time-varying IT power demands are used The global irradiance and average wind speed impact to characterize the total data center power demand assuming power supply for sources, such as PV panels or wind no constraints on power supply. turbines. To determine how much power they provide, we Next, the power supply infrastructure and its location are consider the nature of the power source (e.g., efficiency, size, selected based on the estimated power demand. This allows operational profile) and time-varying geographic data. us to use historical information to produce representative C. Simulate Power Management Plan and Report traces of power for each of the power supplies. In general, To evaluate which workloads can be consolidated to we want to consider many traces so that the impact of which servers, we employ a trace-based approach [4][5][10] representative set of behaviors can be observed for a that assesses permutations and combinations of workloads in sensitivity analysis. order to determine a near-optimal workload placement that In the third step, we simulate data center operation with provides specific qualities of service for applications. After both power supply and demand management. Various plans consolidation, the simulation based capacity planning tool can be evaluated using the tool and compared with walks forward over additional traces of workload demands to performance criteria using standardized metrics. Acceptable simulate workload placement policy. A migration controller plans are finally reported to data center designers and [8] recognizes over and under-utilized resources, causes operators to support the design of the data center and the migrations to improve application QoS, and shuts down as implementation of power management policies. well as starts up servers as needed. We have explored the The following sections describe each step in more detail. impact of various data center management policies using the A. Characterize Power Demand simulation environment [5]. The work presented in this paper We estimate each server’s power consumption within the enhances the simulation environment to implement server trace driven approach as follows. As we simulate the power capping and pool power capping policies and to take workload placement and server utilization over time, we into account the time-varying supply of power. employ the following simple linear power model: The simulator reports metrics including the CPU violation penalty for the workloads and power deficit—the , ൫ܲ௙௨௟௟ െܲ௜ௗ௟௘൯ difference between required and available power. Thoughכ௦௘௥௩௘௥ ൌܲ௜ௗ௟௘ ൅ݑܲ where ܲ௜ௗ௟௘ is the idle power of the server and ܲ௙௨௟௟ is the the impact of aggressive consolidation and power deficits power consumption of the server when it’s fully utilized. The upon application performance cannot be modeled precisely term ݑ represents the CPU utilization of the server. This using the information available to us, we rely upon the CPU simple model has been shown to be a good estimator for violation penalty metric presented in [5] to estimate the power usage [3]. Other formulas could be used as well. sustained impact of resource deficits: The total IT power demand is the sum of the power per ௞ server. Finally, the power demand for the whole data center ଶ ூ ͳെݑ௔ǡ௜ ௜ୀଵ൫ݓ௣௘௡ǡ௜൯ǡݓ௣௘௡ǡ௜ ൌͳെ ௞ ܫ ݌݁݊ ൌ is calculated through a Power Usage Effectiveness (PUE) ͳെݑௗǡ௜ value [6], which is the ratio of the total power demand over ݑ and ݑ are the actual and desired CPU utilizations the IT power demand of the data center.
Load more

Recommended publications
  • Energy Management and Switching Control of PHEV Charging Stations in a Hybrid Smart Micro-Grid System
    electronics Article Energy Management and Switching Control of PHEV Charging Stations in a Hybrid Smart Micro-Grid System Tariq Kamal 1,2,* ID , Murat Karabacak 2, Syed Zulqadar Hassan 3 ID , Luis M. Fernández-Ramírez 1 ID , Muhammad Hussnain Riaz 4 ID , Muhammad Tanveer Riaz 3, Muhammad Abbas Khan 5 and Laiq Khan 6 1 Research Group in Electrical Technologies for Sustainable and Renewable Energy (PAIDI-TEP-023), Department of Electrical Engineering, University of Cadiz, Higher Polytechnic School of Algeciras, 11202 Algeciras (Cadiz), Spain; [email protected] 2 Department of Electrical and Electronics Engineering, Sakarya University, 54050 Sakarya, Turkey; [email protected] 3 State Key Laboratory of Power Transmission Equipment and System Security and New Technology, School of Electrical Engineering, Chongqing University, 400044 Chongqing, China; [email protected] (S.Z.H.); [email protected] (M.T.R.) 4 Department of Electrical Engineering, Lahore University of Management Sciences (LUMS), 54792 Lahore, Pakistan; [email protected] 5 School of Electronics and Information Engineering, Changchun University of Science and Technology, Jilin 130022, China; [email protected] 6 Department of Electrical Engineering, COMSATS Institute of Information Technology, 22060 Abbottabad, Pakistan; [email protected] * Correspondence: [email protected]; Tel.: +90-536-6375731 Received: 30 June 2018; Accepted: 20 August 2018; Published: 22 August 2018 Abstract: In this study, the energy management and switching control of plug-in hybrid electric vehicles (PHEVs) in a hybrid smart micro-grid system was designed. The charging station in this research consists of real market PHEVs of different companies with different sizes.
    [Show full text]
  • Alliant Energy Corporation Profile
    Alliant Energy Corporation Profile Corporate Overview Alliant Energy Corporation (Alliant Energy) is an electric Alliant Energy is a member of the NASDAQ CRD Global and gas utility holding company headquartered in Madison, Sustainability Index – chosen for its leadership role in Wisconsin. Alliant Energy is a component of the S&P 500. sustainability reporting. The company is committed The company is dedicated to delivering on its Purpose to voluntarily sharing its sustainability strategy and – to serve customers and build stronger communities. governance, environmental footprint and emissions Business efforts are focused on building a cleaner energy reductions, social metrics and community investments. future, keeping costs affordable and creating a simple, personalized experience for customers across Wisconsin Highlights and Iowa. Expanding rate base provides catalyst for long-term Through its utility earnings growth – Modernization of the electric and gas subsidiaries Interstate distribution systems and investment in up to 1,400 MW of Power and Light Company solar for our Wisconsin and Iowa customers are expected (IPL) and Wisconsin Power to drive growth in revenues and earnings. and Light Company (WPL), Alliant Energy provides Strong balance sheet and cash flows reduce need regulated electric and natural for equity – Alliant Energy’s 2021 financing plan includes gas service to approximately issuance of up to $25 million of new common equity 975,000 electric and through the Shareowner Direct Plan. WPL plans to issue approximately 420,000 up to $300 million of long-term debt. natural gas customers in the Attractive Midwest. common dividend The company also owns 16% of American Transmission yield – Alliant Energy Company LLC (ATC), a transmission-only utility operating has a targeted in the Midwest, and a 50% cash equity interest in the 225 dividend payout megawatt (MW) Great Western Wind Project.
    [Show full text]
  • Energy's Water Demand
    Energy’s Water Demand: Trends, Vulnerabilities, and Management Nicole T. Carter Specialist in Natural Resources Policy November 24, 2010 Congressional Research Service 7-5700 www.crs.gov R41507 CRS Report for Congress Prepared for Members and Committees of Congress Energy’s Water Demand: Trends, Vulnerabilities, and Management Summary The nation’s energy choices embody many tradeoffs. Water use is one of those tradeoffs. The energy choices before Congress represent vastly different demands on domestic freshwater. The energy sector is the fastest-growing water consumer in the United States, in part because of federal policies. Much of this growth is concentrated in regions that already have intense competition among water uses. Whether the energy sector may exacerbate or alleviate future water tensions is influenced by near-term policy and investment decisions. These decisions also may determine whether water will limit U.S. capacity to reliably meet the nation’s energy demand. Part of the energy-water policy issue for Congress is identifying the extent of the federal role in responding to energy’s growing water demand. Currently, the energy industry and states have the most responsibility for managing and meeting energy’s water demand. The energy sector’s water consumption is projected to rise 50% from 2005 to 2030. This rising water demand derives from both an increase in the amount of energy demanded and shifts to more water-intense energy sources and technologies. The more water used by the energy sector, the more vulnerable energy production and reliability is to competition with other water uses and water constraints. Climate change impacts that alter water patterns may exacerbate this vulnerability in some regions.
    [Show full text]
  • Phd Dissertation Lvdm
    Advancing resilience assessments: the social dimensions of electricity supply in South Africa by Susara Elizabeth van der Merwe Dissertation presented for the degree of Doctor of Philosophy in the Faculty of Economic and Management Sciences at Stellenbosch University Supervisor: Prof Reinette Biggs Co-supervisor: Dr Rika Preiser April 2019 Stellenbosch University https://scholar.sun.ac.za Declaration By submitting this dissertation electronically, I declare that the entirety of the work contained therein is my own, original work, that I am the sole author thereof (save to the extent explicitly otherwise stated), that reproduction and publication thereof by Stellenbosch University will not infringe any third party rights and that I have not previously in its entirety or in part submitted it for obtaining any qualification. This dissertation includes four original papers (two has been published, two submitted for review) in peer-reviewed journals. The development and writing of the papers (published and unpublished) were the principal responsibility of myself and, for each of the cases where this is not the case, a declaration is included in the dissertation indicating the nature and extent of the contributions of co-authors. April 2019 Copyright © 2019 Stellenbosch University All rights reserved ii Stellenbosch University https://scholar.sun.ac.za Abstract Electricity supply serves as a lifeline, is foundational to the effective functioning of modern society, and powers multiple layers of other critical infrastructure systems. In South Africa, Eskom, the national state-owned electrical utility, generates 95% of the country’s electricity, making the South African economy highly dependent on the utility. Eskom has been caught up in socio-political, technical and financial challenges, including corruption and state capture allegations.
    [Show full text]
  • Energy Demand Models for Policy Formulation
    WPS4866 POLICY RESEARCH WORKING PAPER 4866 Energy Demand Models for Policy Formulation A Comparative Study of Energy Demand Models Subhes C. Bhattacharyya Govinda R. Timilsina The World Bank Development Research Group Environment and Energy Team March 2009 POLICY RESEARCH WORKING PAPER 4866 Abstract This paper critically reviews existing energy commodities are often poorly reflected in these models. demand forecasting methodologies highlighting the While the end-use energy accounting models with methodological diversities and developments over detailed sector representations produce more realistic the past four decades in order to investigate whether projections compared with the econometric models, the existing energy demand models are appropriate they still suffer from huge data deficiencies especially in for capturing the specific features of developing developing countries. Development and maintenance of countries. The study finds that two types of approaches, more detailed energy databases, further development of econometric and end-use accounting, are used in the models to better reflect developing country context, and existing energy demand models. Although energy institutionalizing the modeling capacity in developing demand models have greatly evolved since the early countries are the key requirements for energy demand 1970s, key issues such as the poor-rich and urban-rural modeling to deliver richer and more reliable input to divides, traditional energy resources, and differentiation policy formulation in developing countries. between commercial and non-commercial energy This paper—a product of the Environment and Energy Team, Development Research Group—is part of a larger effort in the department to study climate change and clean energy issues. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org.
    [Show full text]
  • Questionnaire
    Application of Big Data for Energy Management: Questionnaire Stantec is leading a research project for The Water Research Foundation entitled: "Application of Big Data for Energy Management in Water Utilities" (WRF #4798). Progress has been made over the last decades in data technologies for improved data analysis and management, which have been incorporated into water and wastewater facility operation and planning. The tools for data processing in the water industry have evolved from sensor-based knowledge to more recent optimization-based data mining techniques and to new approaches based on big data including predictive analytics that allow for actionable real-time system control. This contemporary research project aims to provide utilities with guidance on advanced big data analytics for automated data collection and achieving energy efficiency and cost-effective operations. This questionnaire, as one of the tasks for this project, will collect information on the current practice, opportunities and challenges related to data acquisition, data analytics, display and other data management strategies for energy optimization and management. Please complete the following questionnaire by April 15, 2020. Your input is extremely valuable for the project as the information collected will highlight the critical needs in advancing big data and data management practices at water and wastewater utilities. If you have any questions about the project or the questionnaire, please contact Dr. Carla Cherchi at [email protected] or at (626)-568-6009. All information information received will be used strictly for academic research purposes and under no circumstances will your organization be identified with any of the information provided, unless permission is given at the end of the questionnaire.
    [Show full text]
  • Pathways to Sustainable Energy Accelerating Energy Transition in the UNECE Region
    UNEC E Pathways to Sustainable Energy Accelerating Energy Transition in the UNECE Region Energy underpins economic development and the 2030 Agenda for Sustainable Development and has a critical role to play in climate change mitigation. The recognition of the role that energy plays in modern society is highly signicant, however, there remains an important disconnection between agreed energy and climate targets and the Pathways to Sustainable Energy • Accelerating Transition in the UNECE Region approaches in place today to achieve them. Only international cooperation and innovation can deliver the accelerated and more ambitious strategies. Policies will be needed to ll the persistent gaps to achieve the 2030 Agenda. If the gaps are not addressed urgently, progressively more drastic and expensive measures will be required to avoid extreme and potentially unrecoverable social impacts as countries try to cope with climate change. This report uniquely focuses on sustainable energy in the UNECE region up to 2050 as regional economic cooperation is an important factor in achieving sustainable energy. Arriving at a state of attaining sustainable energy is a complex social, political, economic and technological challenge. The UNECE countries have not agreed on how collectively they will achieve energy for sustainable development. Given the role of the UNECE to promote economic cooperation it is important to explore the implications of dierent sustainable energy pathways and for countries to work together on developing and deploying policies and measures. Pathways to Sustainable Energy Accelerating Energy Transition in the UNECE Region 67UNECE Energy Series UNIT Palais des Nations CH - 1211 Geneva 10, Switzerland E Telephone: +41(0)22 917 12 34 D E-mail: [email protected] N A Website: www.unece.org TION S UNITED NATIONS ECONOMIC COMMISSION FOR EUROPE Pathways to Sustainable Energy - Accelerating Energy Transition in the UNECE Region ECE ENERGY SERIES No.
    [Show full text]
  • Can We Finance the Energy Transition?*
    CADMUS, Volume 2, No.4, April-May 2015, 162-183 Can we Finance the Energy Transition?* Ian Johnson Former Secretary General, Club of Rome; Member, Board of Trustees, World Academy of Art & Science Abstract The energy sector is pivotal to our aspirations for a sustainable planet and yet two major challenges face policymakers worldwide. The first is to decide what set of technical choices provide the best solution to meet social, economic and environmental agendas; and the second is to decide how these choices can be financed. The bulk of new energy demand will come from the emerging economies where energy demand is expected to increase by 40% over the coming three decades and to have doubled by the middle of the century. However for a number of reasons the investment needs of the energy sector are likely to rise even faster than overall energy demand. This is due to a number of factors over and above the increase in demand and described in the paper, including, inter alia, subsidized prices; the substitution of traditional energy for modern energy; the growth in peak demand in the electricity sector; the rising costs of securing primary energy resources; and the urgent need to replace vintage capital stock (including the decommissioning of nuclear power plants), especially in the developed countries. Clean energy investment will also incur high upfront investment costs in order to reduce long-term recurrent costs (fuel and maintenance). High priority must be given to energy demand management (both to reduce energy use and to reduce energy capital) and investment in upgrading of existing capital stock can provide strong and quick returns.
    [Show full text]
  • Strategies for Saving Energy at Public Water Systems (EPA 816-F-13-004)
    STRATEGIES FOR SAVING ENERGY AT PUBLIC WATER SYSTEMS This document discusses energy issues facing public drinking water systems, steps that systems can take to understand and reduce their energy use and costs, and funding resources for energy efficiency. This document is intended for small to medium‐sized water systems as well as technical assistance providers and state programs that support or regulate these systems. How much energy do drinking water systems use? Providing safe drinking water is a highly energy‐intensive activity. At the national level, drinking water and wastewater systems account for three to four percent of U.S. energy use.i This is equivalent to 56 billion kilowatt hours (kWh) annually, and the generation of almost 45 million tons of greenhouse gases (GHG). At the community level, drinking water and wastewater systems are typically the largest energy consumers accounting for 25 to 40 percent of a municipality’s total energy bill.ii Approximately 80 percent of municipal water processing and distribution costs are for electricity.iii For drinking water systems, energy is needed for raw water extraction and conveyance, treatment, water storage and distribution. Energy usage can vary based on water source, facility age, treatment type, storage capacity, topography, and system size, which encompasses volume produced and service area. As illustrated in Figure 1, energy usage for a typical surface water drinking water system is 1,500 kWh/million gallons (MG), broken down as follows: 100 kWh/MG for conveyance; 250 kWh/MG
    [Show full text]
  • Transitions in Energy Efficiency and Demand Provides an Important Contri- Bution to the Energy Transition Literature, Correcting the Usual Bias Towards Energy Supply
    ‘Transitions in Energy Efficiency and Demand provides an important contri- bution to the energy transition literature, correcting the usual bias towards energy supply. Drawing on case studies of innovation, it highlights demand- side innovations in system change; and by using sociotechnical approaches, the case studies avoid the trap of thinking of innovation simply in terms of technical fixes.’ Nick Eyre, Professor, University of Oxford, UK ‘Transitions in Energy Efficiency and Demand is at the forefront of research on energy innovation and energy demand, providing new and in- depth insights into both technological and social change across a range of domains. Essential reading for scholars, policy makers, business leaders, stu- dents, and anyone else interested in a low-carbon, energy- efficient and low- demand energy transition.’ Marilyn Brown, Professor, Georgia Tech, USA Transitions in Energy Efficiency and Demand Meeting the goals enshrined in the Paris Agreement and limiting global temper- ature increases to less than 2°C above pre- industrial levels demands rapid reduc- tions in global carbon dioxide emissions. Reducing energy demand has a central role in achieving this goal, but existing policy initiatives have been largely incremental in terms of the technological and behavioural changes they encour- age. Against this background, this book develops a sociotechnical approach to the challenge of reducing energy demand and illustrates this with a number of empirical case studies from the United Kingdom. In doing so, it explores the emergence, diffusion and impact of low- energy innovations, including electric vehicles and smart meters. The book has the dual aim of improving the aca- demic understanding of sociotechnical transitions and energy demand and pro- viding practical recommendations for public policy.
    [Show full text]
  • Integrating Renewables Economic Dispatch with Demand Side Management in Micro-Grids: a Genetic Algorithm-Based Approach
    Energy Efficiency (2014) 7:271–284 DOI 10.1007/s12053-013-9223-9 ORIGINAL ARTICLE Integrating renewables economic dispatch with demand side management in micro-grids: a genetic algorithm-based approach Ahmer Arif · Fahad Javed · Naveed Arshad Received: 14 February 2012 / Accepted: 6 August 2013 / Published online: 8 September 2013 © Springer Science+Business Media Dordrecht 2013 Abstract Economic dispatch and demand side Keywords Demand side management · management are two of the most important tools Economic dispatch · Smart grids · Micro-grids · for efficient energy management in the grid. It Intelligent energy management is a casual observation that both these processes are intertwined and thus complement each other. Nomenclature Strategies aiming to optimize economic dispatch have implications for demand side management VC Cut-in speed of wind generator techniques and vice versa. In this paper, we VR Rated speed of wind generator present a genetic algorithm-based solution which VF Cutoff speed of wind generator combines economic dispatch and demand side C The set of consumers under the micro-grid management for residential loads in a micro-grid. S The set of currently available energy Our system collects preferences of demand data suppliers to the micro-grid from consumers and costs of energy of various μx Total energy demand by consumer x sources. It then finds the optimal demand schedul- μx,h Total energy demanded by consumer x at ing and energy generation mix for the given time hour h window. Our evaluations show that the given ap- αy,h Total energy available from supplier y at proach can effectively reduce operating costs in a hour h single- and multiple-facility micro-grids for both λy,h Price of energy from supplier y at hour h suppliers and consumers alike.
    [Show full text]
  • Energy Demand Management
    University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Supervised Undergraduate Student Research Chancellor’s Honors Program Projects and Creative Work 5-2016 Energy Demand Management Doug W. Bouler III [email protected] Alex Wortham Asanga Bandara Alex Chaloux Follow this and additional works at: https://trace.tennessee.edu/utk_chanhonoproj Part of the Power and Energy Commons Recommended Citation Bouler, Doug W. III; Wortham, Alex; Bandara, Asanga; and Chaloux, Alex, "Energy Demand Management" (2016). Chancellor’s Honors Program Projects. https://trace.tennessee.edu/utk_chanhonoproj/1903 This Dissertation/Thesis is brought to you for free and open access by the Supervised Undergraduate Student Research and Creative Work at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Chancellor’s Honors Program Projects by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. Control and Monitoring of Residential Loads 11/15/15 Team SP15-01 Doug Bouler, Alex Wortham, Asanga Bandara, Alex Chaloux, & Chauncey Meade Customer Harshal Upadhye – EPRI Table of Contents I. Executive summary II. Requirements a. Change log III. Design process IV. Lessons learned V. Team contributions VI. Team and customer approval Executive Summary As modern civilization becomes increasingly saturated by electronic devices, an issue of infrastructure stability has arisen. The electrical distribution network, known as “the grid” has become burdened by demand driven by the rise in electronic usage. In East Tennessee power is often developed through the use of hydroelectric dams, coal-burning steam plants, or nuclear reactors. Our current electrical distribution system is based on demand response.
    [Show full text]