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The Potential of Grid Integration of Electric Vehicles in Shanghai

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The Potential of Grid Integration of Electric Vehicles in Shanghai © Wilson Hui The Potential of Grid Integration of Electric Vehicles in Shanghai September 2016 Contact us Natural Resources Defense Council Taikang Financial Tower, Suite 1706 No. 38 Dongsanhuan Bei Road, Chaoyang District Beijing, China 100026 Tel: +86-10-5927 0688 www.nrdc.cn 4 The Potential of Grid Integration of Electric Vehicles in Shanghai ACKNOWLEDGEMENTS The Potential of Grid Integration This report is the result of a collaborative effort by the Energy Research Institute of the National Reform and Development Commission, the China National Renewable Energy Centre, and the Natural Resources Defense Council. During the research process, data and information were generously made available by the Shanghai of Electric Vehicles in Shanghai Municipal Commission of Economy and Informatization, Shanghai Municipal Reform and Development Commis- sion, Shanghai He Huang Energy Technologies Co., Ltd., BMW China Services Ltd., Shanghai Anyo Charging Technologies Co., Ltd., Shanghai Electric Vehicle Public Data Collecting, Monitoring and Research Center and Shanghai Municipal Electric Power Company of the State Grid. We would like to express special gratitude to Professor Ruan Yudong of Shanghai Electrical Apparatus Research Institute (Group) Co., Ltd., Professor Han Yanmin of Shanghai Jiao Tong University, Frederich Kahrl of Energy and Environmental Economics, Zhang Hao of Shanghai Twenty-First Energy Services Company, and Roland Hwang, Vignesh Gowrishankar, and Dr. Chris- tina Swanson at the NRDC, for their review and invaluable comments and suggestions. Research Team Liu Jian | Energy Research Institute, National Development and Reform Commission China National Renewable Energy Centre Hyoungmi Kim | Natural Resources Defense Council Tang Li | Shanghai He Huang Energy Technologies Co., Ltd. Project Team at the Natural Resources Defense Council Mona Yew Li Yuqi Liu Mingming Zhou Xiaozhu Gao Tianjian Qin Siyan Mi Siyi Noah Lerner Vera Lummis We would like to thank the ClimateWorks Foundation for the sponsorship of this study. Table of Contents 4.5 Case study: An EV Battery Storage Grid Integration Project by 1.Executive Summary 2 BMW ConnectedDrive Lab in Shanghai 35 2.Background on the Development of Electric Vehicles 7 5.Market Mechanisms and Business Models 37 2.1 The Development of Electric Vehicles and the Impact on the Power System 7 5.1 Power Sector Reform and Electric Vehicles 37 2.2 Electric Vehicle Technologies 9 5.2 A Comparison of EV Commercial Operation Model 38 2.2.1 Plug-in Hybrids 9 5.3 EV Charging Rates 39 2.2.2 Battery Electric Vehicles 10 2.3 Electric Vehicles and Demand Response 11 6.Conclusions and Suggestions for Further Research 41 6.1 Strengthening Research on Managed Charging Technology 42 3.The Impact of Electric Vehicle Charging Load on 6.2 The Implementation of Managed Charging for Load Adjustment 42 Shanghai’s Electrical Grid 12 6.3 Establishing a Market that Values Flexible Resources 42 6.4 Accelerating Residential and Office Charging Facilities 43 3.1 The Scale of Shanghai Electric Vehicle Stock 13 6.5 Formulation of the Vehicle Charging Pricing System 43 3.2 Charging Infrastructure 14 6.6 Research Limitations and Next Steps 43 3.3 Shanghai’s Electricity Sector 16 3.3.1 Electricity Generation and Consumption Mix 16 Appendices 44 3.3.2 Forecasting Electricity Demand 17 3.4 Electric Vehicle Charging Demand 19 References 49 3.5 Electric Vehicle Charging Load Profiles 21 3.6 The Impact of EV Charging on the Transmission and Distribution(T&D) Networks 23 4.The Potential and Economics of EV Demand Response in Shanghai 26 4.1 Demand Response in Shanghai 26 4.2 The Potential of Electric Vehicles as a Demand Response Resource 27 4.3 The Economics of EV as a Demand Response Resource 30 4.4 V2G 33 List of Figures Table of Abbreviations Figure 2-1: 2006-2016 China Electric Car Sales and Market Share 8 Abbreviation Full Name Figure 3-1. Planned Growth of Shanghai’s Electric Vehicles 14 Figure 3-2. Typical Daily Load Curves in Shanghai in Winter and Summer in 2015 16 AC Alternating Current BEV Battery Electric Vehicle Figure 3-3. Shanghai Power Generation Mix in 2015 17 C&I Commercial and Industrial Figure 3-4. 2020 Projections of Shanghai’s Total Electrical Consumption 18 CD Charge Depleting (Mode) Figure 3-5. 2020 Estimates of Shanghai’s Electricity Grid’s Maximum Load 18 CS Charge Sustaining (Mode) DC Direct Current Figure 3-6. Sales Volume and Total EVs in Shanghai 2020-2030: Two Scenarios 20 DR Demand Response Figure 3-7. Factors Influencing Electric Vehicle Charging Load 21 EV Electric Vehicle FCV Fuel Cell Vehicle Figure 3-8. Probabilistic Distribution of Charging Time among Different EV Types in Shanghai 22 FYP Five Year Plan Figure 3-9. 2030 Summer EV Charging Load in Shanghai Under Two Scenarios 23 FR Frequency Reductions HEV Hybrid Electric Vehicle Figure 4-1. Probability Distribution of Charging and Parking Hours of Private and ICE Internal Combustion Engine Government-Owned EVs 28 ISO Independent System Operator Figure 4-2. Grid Impacts of Managed Charging in Two Growth Scenarios 29 NERC North American Electric Reliability Corporation Figure 4-3. Charging Loads of Private and Government EVs under Two Scenarios 29 NOx Mono-Nitrogen Oxides PCS Power Conversion System Figure 4-4. Costs and Benefits of EV Providing Demand Response 30 PHEV Plug-in Hybrid Electric Vehicle Figure 4-5. Conventional DR Resources and Managed EV Charging Cost Comparisons 31 RMB Renminbi (Yuan) SDG&E San Diego Gas and Electric Figure 4-6. Cost Reduction Potential of V2G 34 SOC State of Charge Figure 4-7. Framework for BMW ConnectedDrive Lab’s EV and Energy Storage Project in SHEIC Shanghai Municipal Commission of Economic and Informatization Shanghai 35 TOU Time of Use T&D Transmission and Distribution V Volt VA Voltage Amps V2G Vehicle-to-Grid W Watt List of Tables Wh Watt Hour XLPE Cross-Linked Polyethylene Table 2-1. Key Parameters for Domestic Plug-in Hybrid Vehicles 10 Table 2-2. Key Parameters for Domestic Battery Electric Vehicles 11 Table 3-1. EV Charging Modes 15 Table 4-1. Projections of Shanghai’s Load Profiles in 2030 with and without Managed Charging 28 T a b l e 4 - 2 . B e n e fi t s t o t h e G r i d o f O f f - P e a k C h a r g i n g u n d e r T h r e e R a t e S c e n a r i o s ( R M B / k W h ) 3 1 Table 5-1. Charging Capacities and Prices of Selected Chinese Domestic Brands 40 2 The Potential of Grid Integration of Executive Summary 3 Electric Vehicles in Shanghai 1. EXECUTIVE SUMMARY with the number of electric vehicle users reaching 2.45 million. In terms of charging The development of electric vehicles is essential to improving energy efficiency capacity, in the baseline growth scenario the annual charging demand for electric and reducing emissions in China’s transportation sector, as well as accelerating the vehicles will reach 12.4TWh in the year 2030, comprising 7.4 percent of Shanghai’s structural transformation of China’s industrial sectors. The government has recently total electricity consumption; in the high-growth scenario, the charging demand will enacted a series of policies supporting the development of the electric vehicle sector, reach 19.6TWh, comprising 11.2% of total electricity consumption. In terms of charg- focusing on increasing investment in related research and industry support, develop- ing load profiles, this study bases its findings on the projected growth in Shanghai’s ing regulatory measures, and promoting the widespread adoption of electric vehicles. electric vehicle users, as well as on research on the driving patterns of electric vehi- The government has also set a nationwide target of producing and selling five million cle users, in order to estimate the impact of charging on the load curve. The results electric vehicles and plug-in hybrid vehicles by 2020. These policies have promoted demonstrate that unmanaged charging will significantly increase evening peak load rapid growth in China’s electric vehicle market. In 2015, more than 330,000 electric and widen the difference between daytime peak load and off-peak load, thus putting vehicles were sold in China, representing 1.34 percent of total annual vehicle sales pressure on the safety and stability of the power grid. in China and making China the world’s largest market for electric vehicles. The widespread adoption of electric vehicles will affect the electric power system in multiple ways. First, the growing number of electric vehicles will increase electric- POTENTIAL OF Compared to traditional demand side resources, electric vehicles have higher capaci- ity demand. Peak power load, in particular, will be significantly increased as a large ties to adjust their charge and discharge of electricity. In fact, when the integration of MANAGED EV number of vehicles charge during peak hours. This will require improvements in the electric vehicles becomes more widespread, the impact of electric vehicles on load system capacity and stability of the power system. On the other hand, if power man- CHARGING ON distribution may become one of the most important methods of load management in agement and two-way technologies are promoted, electric vehicles can be viewed LOAD SHIFTING the power system. Therefore, appropriate management of the electric vehicle charg- as both demand response resources and distributed energy resources. Therefore, ing load is necessary for improving grid flexibility and for reducing the destabilizing large-scale electric vehicle integration can increase the efficiency of distribution infra- impacts that large-scale electric vehicle integration may have on the grid. In order to structure and also bring about additional benefits such as peak load shaving and the evaluate the driving patterns of electric vehicle users in Shanghai, this study analyz- provision of ancillary services.
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