America's Electricity Generation Capacity
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A Review of Energy Storage Technologies' Application
sustainability Review A Review of Energy Storage Technologies’ Application Potentials in Renewable Energy Sources Grid Integration Henok Ayele Behabtu 1,2,* , Maarten Messagie 1, Thierry Coosemans 1, Maitane Berecibar 1, Kinde Anlay Fante 2 , Abraham Alem Kebede 1,2 and Joeri Van Mierlo 1 1 Mobility, Logistics, and Automotive Technology Research Centre, Vrije Universiteit Brussels, Pleinlaan 2, 1050 Brussels, Belgium; [email protected] (M.M.); [email protected] (T.C.); [email protected] (M.B.); [email protected] (A.A.K.); [email protected] (J.V.M.) 2 Faculty of Electrical and Computer Engineering, Jimma Institute of Technology, Jimma University, Jimma P.O. Box 378, Ethiopia; [email protected] * Correspondence: [email protected]; Tel.: +32-485659951 or +251-926434658 Received: 12 November 2020; Accepted: 11 December 2020; Published: 15 December 2020 Abstract: Renewable energy sources (RESs) such as wind and solar are frequently hit by fluctuations due to, for example, insufficient wind or sunshine. Energy storage technologies (ESTs) mitigate the problem by storing excess energy generated and then making it accessible on demand. While there are various EST studies, the literature remains isolated and dated. The comparison of the characteristics of ESTs and their potential applications is also short. This paper fills this gap. Using selected criteria, it identifies key ESTs and provides an updated review of the literature on ESTs and their application potential to the renewable energy sector. The critical review shows a high potential application for Li-ion batteries and most fit to mitigate the fluctuation of RESs in utility grid integration sector. -
A Simple and Fast Algorithm for Estimating the Capacity Credit of Solar and Storage
Electricity Markets & Policy Energy Analysis & Environmental Impacts Division Lawrence Berkeley National Laboratory A Simple and Fast Algorithm for Estimating the Capacity Credit of Solar and Storage Andrew D. Mills and Pía Rodriguez July 2020 This is a pre-print version of an article published in Energy. DOI: https://doi.org/10.1016/j.energy.2020.118587 This work was supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Solar Energy Technology Office under Lawrence Berkeley National Laboratory Contract No. DE-AC02-05CH11231. DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or The Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof, or The Regents of the University of California. Ernest Orlando Lawrence Berkeley National Laboratory is an equal opportunity employer. -
Wind Energy Technology Data Update: 2020 Edition
Wind Energy Technology Data Update: 2020 Edition Ryan Wiser1, Mark Bolinger1, Ben Hoen, Dev Millstein, Joe Rand, Galen Barbose, Naïm Darghouth, Will Gorman, Seongeun Jeong, Andrew Mills, Ben Paulos Lawrence Berkeley National Laboratory 1 Corresponding authors August 2020 This work was funded by the U.S. Department of Energy’s Wind Energy Technologies Office, under Contract No. DE-AC02-05CH11231. The views and opinions of the authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof, or The Regents of the University of California. Photo source: National Renewable Energy Laboratory ENERGY T ECHNOLOGIES AREA ENERGY ANALYSISAND ENVIRONMENTAL I MPACTS DIVISION ELECTRICITY M ARKETS & POLICY Disclaimer This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or The Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof, or The Regents of the University of California. -
Renewable Energy Generator Output – Sample Calculations
Net Metering Program Highlights Net metering will be available to new customers until the size of the program reaches 1% of the electric provider’s previous year system peak in MW. The 1% will be measured against the total of the generator nameplate capacities for all participating customer’s generators and is split into the following tiers: (1) 0.5% for ≤ 20 kW True Net Metering This tier will include almost all residential customers. • Billing is based on net usage. • Customer receives the full retail rate for all excess kWh. • Utility shall use the customer’s existing meter if it is capable of reverse registration (spinning backwards) or install an upgraded meter at no additional cost to the net metering customer. • Utilities with fewer than 1,000,000 customers shall charge net metering customers at cost for an upgraded meter if the customer’s existing meter is not capable of reverse registration (spinning backwards). • A generator meter shall be provided at cost, if requested by the customer. (The generator meter is for the customer’s benefit. Utilities are not obligated to read a customer’s generator meter.) • No interconnection costs (beyond the combined $100 interconnection/net metering application fees), study fees, testing or inspection charges. • Net metering credits carry forward indefinitely. (2) 0.25% for >20 kW up to 150 kW Modified Net Metering • Customers pay full retail rate for electricity deliveries from the utility and receive the generation portion of the retail rate or a wholesale rate for deliveries to the grid. • No charge for the engineering review. • Customers pay all interconnection costs, distribution study fees and any network upgrade costs. -
What Is US Electricity Generation by Energy Source
What is U.S. electricity generation by energy source? - FAQ - U.S. Energy Information Administration (EIA) U.S. Energy Information Administration - EIA - Independent Statistics and Analysis Li FREQUENTLY ASKED QUESTIONS What is U.S. electricity generation by energy source? On This Page: In 2012, the United States generated about 4,054 billion kilowatthours of electricity. About 68% of the electricity Coal generated was from fossil fuel (coal, natural gas, and petroleum), with 37% attributed from coal. Conversion & Equivalents Energy sources and percent share of total electricity generation in 2012 were: Crude Oil Coal 37% Natural Gas 30% Diesel Nuclear 19% Hydropower 7% Electricity Other Renewable 5% Biomass 1.42% Environment Geothermal 0.41% Solar 0.11% Gasoline Wind 3.46% Petroleum 1% General Energy Other Gases < 1% Natural Gas Learn more: Nuclear Monthly Energy Review Prices Last updated: May 9, 2013 Renewables OTHER FAQS ABOUT ELECTRICITY Can I choose the electricity supplier where I live? Can I generate and sell electricity to an electric utility? Full list of upcoming reports Does EIA have city or county-level energy consumption and price data? Sign up for email notifications Does EIA have county-level energy production data? Does EIA have data on each power plant in the United States? Get the What's New RSS feed Does EIA have data on the costs for electricity transmission and distribution? Does EIA have electricity prices by state? Does EIA have information on the service territories of U.S. electric utilities? Does EIA have maps or information on the location of electric power plants and transmission lines in the United States? Didn't find the answer to your Does EIA have projections for energy production, consumption, and prices for individual states? question? Ask an energy expert! Does EIA publish data on peak or hourly electricity generation, demand, and prices? Does EIA publish electric utility rate, tariff, and demand charge data? How is electricity used in U.S. -
Electric Transmission and Distribution Equipment Use
Electric Transmission and Distribution Equipment Use Final Rule: Mandatory Reporting of Greenhouse Gases (40 CFR 98, Subpart DD) Under the final Mandatory Reporting Rule for Additional Sources of Fluorinated Greenhouse Gases (GHGs), owners and operators of electric power system facilities with a total nameplate capacity that exceeds 17,820 lbs (7,838 kg) of sulfur hexafluoride (SF6) and/or perfluorocarbons (PFCs) must report emissions of SF6 and/or PFCs from the use of electrical transmission and distribution equipment. Owners or operators must collect emissions data, calculate GHG emissions, and follow the specified procedures for quality assurance, missing data, recordkeeping, and reporting. How Is This Source Category Defined? The electrical transmission and distribution equipment use source category consists of all electric transmission and distribution equipment and servicing inventory insulated with or containing SF6 or PFCs used within an electric power system. This equipment includes but is not limited to gas-insulated substations; circuit breakers; switchgear, including closed-pressure and hermatically sealed-pressure switchgear; gas-insulated lines containing SF6 or PFCs; gas containers such as pressurized cylinders; gas carts; electric power transformers; and other containers of SF6 or PFC. For the purposes of this subpart, facility is defined as the electric power system, comprising all electric transmission and distribution equipment insulated with or containing SF6 or PFCs that is linked through electric power transmission -
Understanding Technology, Fuel, Market and Policy Drivers for New York State’S Power Sector Transformation
sustainability Article Understanding Technology, Fuel, Market and Policy Drivers for New York State’s Power Sector Transformation Mine Isik * and P. Ozge Kaplan Office of Research and Development, U.S. Environmental Protection Agency, 109 TW Alexander Dr., Durham, NC 27709, USA; [email protected] * Correspondence: [email protected]; Tel.: +1-919-541-4965 Abstract: A thorough understanding of the drivers that affect the emission levels from electricity generation, support sound design and the implementation of further emission reduction goals are presented here. For instance, New York State has already committed a transition to 100% clean energy by 2040. This paper identifies the relationships among driving factors and the changes in emissions levels between 1990 and 2050 using the logarithmic mean divisia index analysis. The analysis relies on historical data and outputs from techno-economic-energy system modeling to elucidate future power sector pathways. Three scenarios, including a business-as-usual scenario and two policy scenarios, explore the changes in utility structure, efficiency, fuel type, generation, and emission factors, considering the non-fossil-based technology options and air regulations. We present retrospective and prospective analysis of carbon dioxide, sulfur dioxide, nitrogen oxide emissions for the New York State’s power sector. Based on our findings, although the intensity varies by period and emission type, in aggregate, fossil fuel mix change can be defined as the main contributor to reduce emissions. Electricity generation level variations and technical efficiency have relatively smaller impacts. We also observe that increased emissions due to nuclear phase-out will be avoided by the onshore and offshore wind with a lower fraction met by solar until 2050. -
Demand Side Management Effects on Substation Transformer Capacity
applied sciences Article Demand Side Management Effects on Substation Transformer Capacity Limits Kerry D. McBee, Jacquelyn Chong and Prasanth Rudraraju * Department of Electrical and Computer Engineering, California State University, Fresno, CA 93740, USA * Correspondence: [email protected] Received: 24 June 2019; Accepted: 7 August 2019; Published: 9 August 2019 Featured Application: The research provides insight into the effects that high penetrations of photovoltaic (PV) systems, energy storage (ES) applications, and electric vehicle (EV) charging systems will have on substation transformer capacity ratings. The manuscript identifies how these applications change the operational conditions of a transformer to the point where capacity ratings (normal and emergency) should be adjusted to account for the additional internal heating in the windings and oil. The research also identifies how harmonic distortion induced by PV, ES, and EV charging equipment affects capacity ratings. The results of the analysis are utilized to describe mitigating approaches for existing units and new units being designed. The approaches are applied to the design attributes of a 50 MVA SPX Waukesha transformer. Abstract: In high penetrations, demand side management (DMS) applications augment a substation power transformer’s load profile, which can ultimately affect the unit’s capacity limits. Energy storage (ES) applications reduce the evening peaking demand, while time-of-use rates incentivize end-users to charge electric vehicles overnight. The daily load profile is further augmented by high penetrations of photovoltaic (PV) systems, which reduce the midday demand. The resulting load profile exhibits a more flattened characteristic when compared to the historical cyclic profile. Although the initial impact of PV and ES applications may reduce a unit’s peak demand, long-term system planning and emergency conditions may require operation near or above the nameplate rating. -
Economics of Power Generation Prepared by the Legislative Finance Committee July 2017 Understanding Electric Power Generation
Economics of Power Generation Prepared by the Legislative Finance Committee July 2017 Understanding Electric Power Generation Following the Great Recession, electricity demand in the United States contracted, and energy efficiency improvements in buildings, lighting, and appliances stunted its recovery. Globally, a slowdown in Chinese coal demand depressed coal prices worldwide and reduced the market for U.S. exports, and coal demand in emerging markets is unlikely to make up for the slowdown in Chinese coal consumption. According to Columbia University’s Center on Global Energy Policy (CGEP), over half of the decline in coal company revenue between 2011 and 2015 is due to international factors.i Given current technological constraints, electricity cannot be stored on a large scale at a reasonable cost. Therefore, entities operating the transmission grid must keep supply and demand matched in “real-time” – from minute to minute. Imbalances in supply and demand can destroy machinery, cause power outages, and become very costly over time. The need to continually balance supply and demand plays a key role in how electricity generation sources are dispatched. In the 1980s, electricity supply was relatively straightforward, with less flexible coal and nuclear plants supplying base load power needs, and more flexible gas turbines and hydroelectric plants supplying peak load power needs. Developments over the last decade challenged this traditional mix of power generation. Natural gas, wind, and solar now meet 40 percent of U.S. power needs, up from 22 percent a decade ago. Early July 2017, The Wall Street Journal reported three of every 10 coal generators has closed permanently in the last five years. -
SDRC 4 Learning Generated from the Openlv Project Trials by Method 1
SDRC 4 Learning Generated from the OpenLV Project trials by Method 1. SDRC 4 LEARNING GENERATED FROM THE OPENLV PROJECT TRIALS Report Title : SDRC 4 - Learning Generated from the OpenLV Project trials by all Method 1.. Report Status : Final Draft for Review Project Ref : WPD/EN/NIC/02 - OpenLV Date : 31.01.20 Document Control Name Date Prepared by: T. Butler, K. Platt, P. 24.01.20 Morris & R. Burns Reviewed by: D. Russell & S Rossi 24.01.20 Ashton Recommended by: D. Roberts & J. Berry 27.01.20 Approved (WPD): A. Sleightholm WPD 31.01.20 Resources and External Affairs Director Revision History Date Issue Status 24.01.20 3 Draft for Review 31.01.20 3.1 For Issue Page 2 of 76 SDRC 4 LEARNING GENERATED FROM THE OPENLV PROJECT TRIALS Contents Executive Summary ....................................................................................................................... 7 Key Findings .................................................................................................................................. 8 1 Introduction ........................................................................................................................... 9 1.1 Project Background...................................................................................................... 9 1.1.1 Method 1: Network Capacity Uplift .................................................................. 9 1.1.2 Method 2: Community Engagement ................................................................. 10 1.1.3 Method 3: OpenLV Extensibility ....................................................................... -
2015 Renewable Energy Data Book Acknowledgments
2015 Renewable Energy Data Book Acknowledgments This report was produced by Philipp Beiter and Tian Tian, edited by Mike Meshek, and designed by Alfred Hicks of the U.S. Department of Energy's National Renewable Energy Laboratory (NREL). We greatly appreciate the input, review, and support of Assistant Secretary David Friedman, Ookie Ma, Steve Capanna, Paul Basore, Hoyt Battey, Charlie Gay, Susan Hamm, Ian Hamos, Fred Joseck, Benjamin King, Tien Nguyen, Sunita Satyapal, Paul Spitsen, Rich Tusing, Timothy Welch, and Jeff Winick of the U.S. Department of Energy (DOE), as well as Chad Augustine, Jerry Davis, Judi Deitchel, David Feldman, Ran Fu, Bryan Hannegan, Caley Johnson, Henry Johnston, Eric Lantz, Al LiVecchi, Jeff Logan, David Mooney, Robin Newmark, Gian Porro, and Paul Schwabe of NREL. Notes Capacity data are reported in watts of alternating current (AC) unless indicated otherwise. The primary data represented and synthesized in the 2015 Renewable Energy Data Book come from the publicly available data sources identified on page 122. Front page inset photos (left to right): iStock/754519; iStock/4393369; iStock/354309; iStock/2101722; iStock/2574180; iStock/5080552; Leslie Eudy, NREL 17854; iStock/11265066 Page 2: iStock/721000; page 6: iStock/5751076; page 17: photo from Invenergy LLC, NREL 14369; page 41: iStock/750178; page 53: iStock/ 754519; page 63: iStock/4393369; page 71: iStock/354309; page 77: iStock/2101722; page 83: iStock/2574180; page 87: iStock/5080552; page 91: photo by Leslie Eudy, NREL 17854; page 99: iStock/11265066; page 109: iStock/330791; page 119: iStock/3459287 Key Findings • The overall U.S. energy consumption decreased to 97.7 quadrillion British thermal units (Btu) in 2015—a 0.6% decline from 2014. -
Electricity Storage and Renewables: Costs and Markets to 2030
ELECTRICITY STORAGE AND RENEWABLES: COSTS AND MARKETS TO 2030 October 2017 www.irena.org ELECTRICITY STORAGE AND RENEWABLES: COSTS AND MARKETS TO 2030 © IRENA 2017 Unless otherwise stated, material in this publication may be freely used, shared, copied, reproduced, printed and/or stored, provided that appropriate acknowledgement is given of IRENA as the source and copyright holder. Material in this publication that is attributed to third parties may be subject to separate terms of use and restrictions, and appropriate permissions from these third parties may need to be secured before any use of such material. ISBN 978-92-9260-038-9 Citation: IRENA (2017), Electricity Storage and Renewables: Costs and Markets to 2030, International Renewable Energy Agency, Abu Dhabi. About IRENA The International Renewable Energy Agency (IRENA) is an intergovernmental organisation that supports countries in their transition to a sustainable energy future, and it serves as the principal platform for international co-operation, a centre of excellence, and a repository of policy, technology, resource and financial knowledge on renewable energy. IRENA promotes the widespread adoption and sustainable use of all forms of renewable energy, including bioenergy, geothermal, hydropower, ocean, solar and wind energy, in the pursuit of sustainable development, energy access, energy security and low-carbon economic growth and prosperity. www.irena.org Acknowledgements IRENA is grateful for the the reviews and comments of numerous experts, including Mark Higgins (Strategen Consulting), Akari Nagoshi (NEDO), Jens Noack (Fraunhofer Institute for Chemical Technology ICT), Kai-Philipp Kairies (Institute for Power Electronics and Electrical Drives, RWTH Aachen University), Samuel Portebos (Clean Horizon), Keith Pullen (City, University of London), Oliver Schmidt (Imperial College London, Grantham Institute - Climate Change and the Environment), Sayaka Shishido (METI) and Maria Skyllas-Kazacos (University of New South Wales).