Framework for the Introduction of Vehicle-To-Grid Technology Into the Polish Electricity Market
Total Page:16
File Type:pdf, Size:1020Kb

Load more
Recommended publications
-
Thermal Management of Lithium-Ion Batteries Using Supercapacitors
University of South Florida Scholar Commons Graduate Theses and Dissertations Graduate School March 2021 Thermal Management of Lithium-ion Batteries Using Supercapacitors Sanskruta Dhotre University of South Florida Follow this and additional works at: https://scholarcommons.usf.edu/etd Part of the Electrical and Computer Engineering Commons Scholar Commons Citation Dhotre, Sanskruta, "Thermal Management of Lithium-ion Batteries Using Supercapacitors" (2021). Graduate Theses and Dissertations. https://scholarcommons.usf.edu/etd/8759 This Thesis is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. Thermal Management of Lithium-ion Batteries Using Supercapacitors by Sanskruta Dhotre A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering Department of Electrical Engineering College of Engineering University of South Florida Major Professor: Arash Takshi, Ph.D. Ismail Uysal, Ph.D. Wilfrido Moreno, Ph.D. Date of Approval: March 10, 2021 Keywords: Thermal Runaway, Hybrid Battery-Supercapacitor Architecture, Battery Management Systems, Internal heat Generation Copyright © 2021, Sanskruta Dhotre Dedication I wish to dedicate this thesis to my late grandfather, Gurunath Dhotre, who has always inspired me to be the best version of myself, my parents, without whose continuous love and support my academic journey would not have been the same and my brother for encouraging me to soldier on forward no matter what the obstacle. Acknowledgments First and foremost, I would like to express my gratitude to my guide Dr. -
Distributed Wind Competitiveness Improvement Project
Distributed Wind Competitiveness Improvement Project The Competitiveness Improvement Project (CIP) is a periodic solicitation through the U.S. Department of Energy (DOE) and its National Renewable Energy Laboratory (NREL). Manufacturers of small and medium wind turbines are awarded cost-shared subcontracts via a competitive process to optimize their designs, develop advanced manufacturing processes, and perform turbine testing. The goals of the CIP are to make wind energy cost competitive with other distributed generation technology and increase the number of wind turbine Photo from Northern Power Systems, NREL 36193 Increased Energy Reduced Hardware Production Costs Performance & Safety CIP component innovations and CIP manufacturing process CIP awardee Primus system optimization awardee innovation awardee Pika Energy Windpower of Lakewood, Colorado, achieved Bergey Windpower of Norman, of Westbrook, Maine, reduced Oklahoma, achieved a 110% blade costs by approximately for safety, function, performance, and durability— energy production increase for the 90% by developing an innovative to international standards on two of their turbine Excel 15 turbine over the Excel 10 tooling and cooling strategy to models. Northern Power Systems also recently turbine by increasing blade length produce blades using injection- and improving blade aerodynamics molded plastic. Two additional CIP awardees are currently and system controls. Through six funding cycles, DOE and NREL have awarded 28 subcontracts to 15 companies, totaling $6.3 million of investment -
Optimum Sizing of Distributed Generation and Storage Capacity in Smart Households Salman Kahrobaee University of Nebraska-Lincoln, [email protected]
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Faculty Publications from the Department of Electrical & Computer Engineering, Department of Electrical and Computer Engineering 2013 Optimum Sizing of Distributed Generation and Storage Capacity in Smart Households Salman Kahrobaee University of Nebraska-Lincoln, [email protected] Sohrab Asgarpoor University of Nebraska-Lincoln, [email protected] Wei Qiao University of Nebraska-Lincoln, [email protected] Follow this and additional works at: http://digitalcommons.unl.edu/electricalengineeringfacpub Part of the Computer Engineering Commons, and the Electrical and Computer Engineering Commons Kahrobaee, Salman; Asgarpoor, Sohrab; and Qiao, Wei, "Optimum Sizing of Distributed Generation and Storage Capacity in Smart Households" (2013). Faculty Publications from the Department of Electrical and Computer Engineering. 280. http://digitalcommons.unl.edu/electricalengineeringfacpub/280 This Article is brought to you for free and open access by the Electrical & Computer Engineering, Department of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Faculty Publications from the Department of Electrical and Computer Engineering by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. IEEE TRANSACTIONS ON SMART GRID, VOL. 4, NO. 4, DECEMBER 2013 1791 Optimum Sizing of Distributed Generation and Storage Capacity in Smart Households Salman Kahrobaee, Student Member, IEEE, Sohrab Asgarpoor, Senior Member, IEEE,and Wei Qiao, Senior Member, IEEE Abstract—In the near future, a smart grid will accommodate DI Decision interval in h. customers who are prepared to invest in generation-battery sys- tems and employ energy management systems in order to cut down Time-step of the simulation in h. on their electricity bills. -
Advances of 2Nd Life Applications for Lithium Ion Batteries from Electric Vehicles Based on Energy Demand
sustainability Article Advances of 2nd Life Applications for Lithium Ion Batteries from Electric Vehicles Based on Energy Demand Aleksandra Wewer, Pinar Bilge * and Franz Dietrich Institute for Machine Tools and Factory Management (IWF), Technische Universität Berlin, 10587 Berlin, Germany; [email protected] (A.W.); [email protected] (F.D.) * Correspondence: [email protected]; Tel.: +49-(30)-314-27091 Abstract: Electromobility is a new approach to the reduction of CO2 emissions and the deceleration of global warming. Its environmental impacts are often compared to traditional mobility solutions based on gasoline or diesel engines. The comparison pertains mostly to the single life cycle of a battery. The impact of multiple life cycles remains an important, and yet unanswered, question. The aim of this paper is to demonstrate advances of 2nd life applications for lithium ion batteries from electric vehicles based on their energy demand. Therefore, it highlights the limitations of a conventional life cycle analysis (LCA) and presents a supplementary method of analysis by providing the design and results of a meta study on the environmental impact of lithium ion batteries. The study focuses on energy demand, and investigates its total impact for different cases considering 2nd life applications such as (C1) material recycling, (C2) repurposing and (C3) reuse. Required reprocessing methods such as remanufacturing of batteries lie at the basis of these 2nd life applications. Batteries are used in their 2nd lives for stationary energy storage (C2, repurpose) and electric vehicles (C3, Citation: Wewer, A.; Bilge, P.; reuse). The study results confirm that both of these 2nd life applications require less energy than Dietrich, F. -
Microgen & DG Report June 2020
Small Distribution-Connected Generation Resources in Alberta Within Alberta, electric distribution systems are operated by utility companies and are the portion of the electric system that operates at 25 kilovolts or less. These distribution systems are used to deliver electricity from the Alberta interconnected electric system to an end-use customer. A Distributed Energy Resource is any resource that is connected to and can supply energy to an electric distribution system. This includes distribution-connected generation resources and energy storage. This report focuses on distribution-connected generation resources, which are typically connected to a distribution system at customer locations. Distribution-connected generation, if it qualifies, can be designated as micro-generation. For the purposes of this report, resources that are not designated as micro-generation will be referred to simply as distributed generation. This report has a section containing a brief description of each class of generation. In addition, there is data on the number of sites and total installed capacity broken out by energy source. Micro-Generation Distributed generation may qualify as micro-generation under the Micro-generation Regulation. To qualify as micro-generation, a generating unit must use renewable or alternative energy sources, be intended to offset consumer load, and have a nameplate capacity that does not exceed 5,000 kW. Electricity may be generated from solar, wind, hydro, fuel cells or biomass. Other sources may be permitted if they have current EcoLogo certification or their greenhouse gas intensity is lower then the regulated limit. Micro-generators producing electricity in excess of on-site load receive credits for what they feed to the electricity grid. -
Distributed Generation: a Brighter Future?
DISTRIBUTED GENERATION: A BRIGHTER FUTURE? Sponsored by DISTRIBUTED GENERATION A BRIGHTER FUTURE? CONTENTS 2 About this report 3 Executive summary 5 Part one: The shift to decentralised power production 9 Part two: Early movers 14 Part three: Looking ahead 17 Conclusion © The Economist Intelligence Unit Limited 2018 1 DISTRIBUTED GENERATION A BRIGHTER FUTURE? ABOUT THIS REPORT Distributed generation: a brighter future? is an Economist Intelligence Unit report, sponsored by E.ON. In this paper, The Economist Intelligence Unit examines the growth in distributed generation, as an increasing number of UK businesses are meeting a greater proportion of their energy needs through electricity generated themselves, on-site. This report seeks to examine the impact that distributed generation could have on UK businesses. To do so, we surveyed 450 senior executives with familiarity of their companies’ energy strategies in April-May 2018. The survey focused exclusively on executives from energy-intensive industries: manufacturing, transport and logistics, hospitality and retail. Half of the respondents are either members of their companies’ boards or hold C-level positions; the remainder are other senior managers and executives. All are from UK businesses with annual revenue exceeding £100m. The Economist Intelligence Unit supplemented the survey results with in-depth interviews with executives and industry experts. We would like to thank all survey respondents, as well as the following executives (listed alphabetically by company), for their time and insights: l Richard Carter, head of finance and sustainability, Adnams l Ilesh Patel, partner—energy and resources, Baringa l Simon Virley, partner and UK head of power and natural resources, KPMG l Caroline Hill, head of sustainability and public affairs, Landsec l Tom Byrne, sustainability manager, Landsec l Stuart Ravens, principal research analyst, Navigant Research l James Pitcher, director of sustainability, Whitbread This paper was written by Jessica Twentyman and edited by Jeremy Kingsley. -
Grid Energy Storage
Grid Energy Storage U.S. Department of Energy December 2013 Acknowledgements We would like to acknowledge the members of the core team dedicated to developing this report on grid energy storage: Imre Gyuk (OE), Mark Johnson (ARPA-E), John Vetrano (Office of Science), Kevin Lynn (EERE), William Parks (OE), Rachna Handa (OE), Landis Kannberg (PNNL), Sean Hearne & Karen Waldrip (SNL), Ralph Braccio (Booz Allen Hamilton). Table of Contents Acknowledgements ....................................................................................................................................... 1 Executive Summary ....................................................................................................................................... 4 1.0 Introduction .......................................................................................................................................... 7 2.0 State of Energy Storage in US and Abroad .......................................................................................... 11 3.0 Grid Scale Energy Storage Applications .............................................................................................. 20 4.0 Summary of Key Barriers ..................................................................................................................... 30 5.0Energy Storage Strategic Goals .......................................................................................................... 32 6.0 Implementation of its Goals ............................................................................................................... -
USAID Energy Storage Decision Guide for Policymakers
USAID ENERGY STORAGE FOR DECISION GUIDE POLICYMAKERS www.greeningthegrid.org | www.nrel.gov/usaid-partnership USAID ENERGY STORAGE FO R DECISION GUIDE P OLICYMAKERS Authors Ilya Chernyakhovskiy, Thomas Bowen, Carishma Gokhale-Welch, Owen Zinaman National Renewable Energy Laboratory July 2021 View the companion report: USAID Grid-Scale Energy Storage Technologies Primer www.greeningthegrid.org | www.nrel.gov/usaid-partnership Prepared by NOTICE This work was authored, in part, by the National Renewable Energy Laboratory (NREL), operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the United States Agency for International Development (USAID) under Contract No. IAG-17-2050. The views expressed in this report do not necessarily represent the views of the DOE or the U.S. Government, or any agency thereof, including USAID. This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. U.S. Department of Energy (DOE) reports produced after 1991 and a growing number of pre-1991 documents are available free via www.OSTI.gov. Front cover: photo from iStock 506609532; Back cover: photo from iStock 506611252 NREL prints on paper that contains recycled content. Acknowledgments The authors are greatly indebted to several individuals for their support and guidance. We wish to thank Sarah Lawson, Andrew Fang, and Sarah Dimson at the U.S. Agency for International Development (USAID) for their thoughtful reviews. We also wish to thank Peerapat Vithayasrichareon, Jacques Warichet, Enrique Gutierrez Tavarez, and Luis Lopez at the International Energy Agency, and Dr. -
Hydroelectric Power Generation and Distribution Planning Under Supply Uncertainty
Hydroelectric Power Generation and Distribution Planning Under Supply Uncertainty by Govind R. Joshi A Thesis Submitted to The Department of Engineering Colorado State University-Pueblo In partial fulfillment of requirements for the degree of Master of Science Completed on December 16th, 2016 ABSTRACT Govind Raj Joshi for the degree of Master of Science in Industrial and Systems Engineering presented on December 16th, 2016. Hydroelectric Power Generation and Distribution Planning Under Supply Uncertainty Abstract approved: ------------------------------------------- Ebisa D. Wollega, Ph.D. Hydroelectric power system is a renewable energy type that generates electrical energy from water flow. An integrated hydroelectric power system may consist of water storage dams and run-of-river (ROR) hydroelectric power projects. Storage dams store water and regulate water flow so that power from the storage projects dispatch can follow a pre-planned schedule. Power supply from ROR projects is uncertain because water flow in the river, and hence power production capacity, is largely determined by uncertain weather factors. Hydroelectric generator dispatch problem has been widely studied in the literature; however, very little work is available to address the dispatch and distribution planning of an integrated ROR and storage hydroelectric projects. This thesis combines both ROR projects and storage dam projects and formulate the problem as a stochastic program to minimize the cost of energy generation and distribution under ROR projects supply uncertainty. Input data from the Integrated Nepal Power System are used to solve the problem and run experiments. Numerical comparisons of stochastic solution (SS), expected value (EEV), and wait and see (W&S) solutions are made. These solution approaches give economic dispatch of generators and optimal distribution plan that the power system operators (PSO) can use to coordinate, control, and monitor the power generation and distribution system. -
The Supply Chain for Electric Vehicle Batteries
United States International Trade Commission Journal of International Commerce and Economics December 2018 The Supply Chain for Electric Vehicle Batteries David Coffin and Jeff Horowitz Abstract Electric vehicles (EVs) are a growing part of the passenger vehicle industry due to improved technology, customer interest in reducing carbon footprints, and policy incentives. EV batteries are the key determinant of both the range and cost of the vehicle. This paper explains the importance of EV batteries, describes the structure of the EV battery supply chain, examines current limitations in trade data for EV batteries, and estimates the value added to EV batteries for EVs sold in the United States. Keywords: motor vehicles, cars, passenger vehicles, electric vehicles, vehicle batteries, lithium- ion batteries, supply chain, value chain. Suggested citation: Coffin, David, and Jeff Horowitz. “The Supply Chain for Electric Vehicle Batteries.” Journal of International Commerce and Economics, December 2018. https://www.usitc.gov/journals. This article is the result of the ongoing professional research of USITC staff and is solely meant to represent the opinions and professional research of the authors. It is not meant to represent in any way the views of the U.S. International Trade Commission, any of its individual Commissioners, or the United States Government. Please direct all correspondence to David Coffin and Jeff Horowitz, Office of Industries, U.S. International Trade Commission, 500 E Street SW, Washington, DC 20436, or by email to [email protected] and [email protected]. The Supply Chain for Electric Vehicle Batteries Introduction Supply chains spreading across countries have added complexity to tracking international trade flows and calculating the value each country receives from a particular good. -
Electric Vehicles As Distributed Energy Resources
ELECTRIC VEHICLES AS DISTRIBUTED ENERGY RESOURCES BY GARRETT FITZGERALD, CHRIS NELDER, AND JAMES NEWCOMB O Y M UN ARBON K T C C A I O N R I W N E A M STIT U T R R O O AUTHORS & ACKNOWLEDGMENTS AUTHORS ACKNOWLEDGMENTS Garrett Fitzgerald, Chris Nelder, and James Newcomb The authors thank the following individuals and e-Lab * Authors listed alphabetically. All authors are from member organizations for offering their insights and Rocky Mountain Institute unless otherwise noted. perspectives on this work, which does not necessarily reflect their views. ADDITIONAL CONTRIBUTORS Jim Lazar, Regulatory Assistance Project Rich Sedano, Regulatory Assistance Project Riley Allen, Regulatory Assistance Project Sarah Keay-Bright, Regulatory Assistance Project Jim Avery, San Diego Gas & Electric CONTACTS Greg Haddow, San Diego Gas & Electric Chris Nelder ([email protected]) San Diego Gas & Electric Load Analysis Group James Newcomb ([email protected]) Noel Crisostomo, California Public Utilities Commission Jonathan Walker, Rocky Mountain Institute SUGGESTED CITATION Chris Nelder, James Newcomb, and Garrett Fitzgerald, The authors also thank the following additional Electric Vehicles as Distributed Energy Resources individuals and organizations for offering their insights (Rocky Mountain Institute, 2016), and perspectives on this work: http://www.rmi.org/pdf_evs_as_DERs. Joel R. Pointon, JRP Charge Joyce McLaren, National Renewable Energy Laboratory DISCLAIMER e-Lab is a joint collaboration, convened by RMI, with participationfrom stakeholders across the electricity Editorial Director: Cindie Baker industry. e-Lab is not a consensus organization, and Editor: David Labrador the views expressed in this document are not intended Art Director: Romy Purshouse to represent those of any individual e-Lab member or Images courtesy of iStock unless otherwise noted. -
An Improved SOC Control Strategy for Electric Vehicle Hybrid Energy Storage Systems
energies Article An Improved SOC Control Strategy for Electric Vehicle Hybrid Energy Storage Systems Kai Wang 1,* , Wanli Wang 1, Licheng Wang 2 and Liwei Li 1,* 1 School of Electrical Engineering, Qingdao University, Qingdao 266071, China; [email protected] 2 College of Information Engineering, Zhejiang University of Technology, Hangzhou 310014, China; [email protected] * Correspondence: [email protected] or [email protected] (K.W.); [email protected] (L.L.) Received: 27 July 2020; Accepted: 2 October 2020; Published: 12 October 2020 Abstract: In this paper, we propose an optimized power distribution method for hybrid electric energy storage systems for electric vehicles (EVs). The hybrid energy storage system (HESS) uses two isolated soft-switching symmetrical half-bridge bidirectional converters connected to the battery and supercapacitor (SC) as a composite structure of the protection structure. The bidirectional converter can precisely control the charge and discharge of the SC and battery. Spiral wound SCs with mesoporous carbon electrodes are used as the energy storage units of EVs. Under the 1050 operating conditions of the EV driving cycle, the SC acts as a “peak load transfer” with a charge and discharge current of 2isc~3ibat. An improved energy allocation strategy under state of charge (SOC) control is proposed, that enables SC to charge and discharge with a peak current of approximately 4ibat. Compared with the pure battery mode, the acceleration performance of the EV is improved by approximately 50%, and the energy loss is reduced by approximately 69%. This strategy accommodates different types of load curves, and helps improve the energy utilization rate and reduce the battery aging effect.