An Analysis of the Electric Vehicle Charging Demand in Lanzhou (China)
Keywords:
electric vehicle, charging of electric vehiclescharging of electric vehicles, analysis of charging demand, additional load on power grids, assessment of electricity consumption nonuniformity
Abstract
The article proposes an approach to analyzing the demand for electricity required for charging electric vehicles. The approach is based on the sociological data on electric vehicle owners and their schedule of using electric vehicles. The approach is aimed at obtaining a reasonable estimate of the electrical grid load produced by electric vehicles. The approach is applied to the conditions of the Lanzhou city (China). The entire population of the city was divided into nine groups, and for each of them, a model of electric vehicle use for a week was proposed. The total number of electric vehicles was around 20500 units, and each owner had his or her own individual schedule of using the electric vehicle within the assumption’s characteristic of their group. This made it possible to predict the electric vehicle charging time for each individual in the group and, accordingly, obtain a schedule of electricity consumption at charging stations for the entire city of Lanzhou. An important result was the confirmation of a highly nonuniform consumption of electricity by electric vehicles: the peak power consumed by charging stations is eight times higher than its average value. With the high growth rates in the number of electric vehicles that are typical for China, this can create essential problems for the power grid.
References
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#
1. Global EV. Outlook 2023: Catching up with Climate Ambitions. IEA, 2023, 142 p.
2. Butyrin P.A., Halyutin S.P. Elektrichestvo – in Russ. (Electri-city), 2023, No. 2, pp. 13–26.
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4. Sinitsyn М. EKO – in Russ. (ECO), 2020, 50(10), pp. 65–87.
5. Fang Y., Hu J., Ma W. Optimal Dispatch Strategy for Electric Vehicle Aggregators Based on Stackelberg Game Theory Considering User Intention. – Transactions of China Electrotechnical Society, 2023, pp. 1–13.
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8. Wu S., Yang Z. Availability of Public Electric Vehicle Charging Pile and Development of Electric Vehicle: Evidence from China. – Sustainability, 2020, No 12(16), DOI:10.3390/su12166369.
9. Liu C.H., Chau K.T., Wu D.Y. Opportunities and Challenges of Vehicle-to-Home, Vehicle-to-Vehicle, and Vehicle-to-Grid Technologies. – Proceedings of the IEEE, 2013, 101(11), pp. 2409–2427, DOI:10.1109/JPROC.2013.2271951.
10. Ma K. et al. Voltage Regulation with Electric Taxi Based on Dynamic Game Strategy. – IEEE Transactions on Vehicular Technology, 2022, 71(3), pp. 2413–2426, DOI: 10.1109/TVT.2022.3141954.
11. Li Z.H., Khajepour A., Song J. A Comprehensive Review of the Key Technologies for Pure Electric Vehicles. – Energy, 2019, No 182, pp. 824–839, DOI:10.1016/j.energy.2019.06.077.
12. Yan H.D. et al. Multi-Time Scale Stochastic Optimal Dispatch of Electric Vehicle Charging Station Considering Demand Response. – Power System Protection and Control, 2020, No 10, pp. 71–80.
13. Zhou Y.T. et al. Demand Forecasting and Planning Layout of Urban Electric Vehicle Charging Facilities. – Power System Protection and Control, 2021, No 24, pp. 177–187.
14. Tian L., Shi S., Jia Z. A Statistical Model for Charging Power Demand of Electric Vehicles. – Power System Technology, 2010, 34(11), pp. 126–130.
15. Fan J. et al. Using Big GPS Trajectory Data Analytics for Vehicle Miles Traveled Estimation. – Transportation Research Part C Emerging Technologies, 2019, 103(05), pp. 298–307, DOI:10.1016/j.trc.2019.04.019
2. Бутырин П.А., Халютин С.П. Производство систем электроснабжения автономных электромобилей в России. – Электричество, 2023, № 2, с. 13–26.
3. Комарова М.В. Анализ рынка электромобилей в России. – Инновации. Наука. Образование, 2020, № 21, с. 276–281.
4. Синицын М. Влияние продвижения легковых электромобилей на потребление нефти. – ЭКO, 2020, т. 50, № 10, с. 65–87.
5. Fang Y., Hu J., Ma W. Optimal Dispatch Strategy for Electric Vehicle Aggregators Based on Stackelberg Game Theory Considering User Intention. – Transactions of China Electrotechnical Society, 2023, pp. 1–13.
6. Rauma K. et al. Electric Vehicles as a Flexibility Provider: Optimal Charging Schedules to Improve the Quality of Charging Service. – Electricity, 2021, 2(3), pp. 225–243, DOI:10.3390/electricity2030014.
7. Wang H. et al. Review and Prospect of Key Techniques for Vehicle-Station-Network Integrated Operation in Smart City. – Transactions of China Electrotechnical Society, 2022, 37(1), pp. 112–132, DOI:10.19595/j.cnki.1000-6753.tces.211285.
8. Wu S., Yang Z. Availability of Public Electric Vehicle Charging Pile and Development of Electric Vehicle: Evidence from China. – Sustainability, 2020, No 12(16), DOI:10.3390/su12166369.
9. Liu C.H., Chau K.T., Wu D.Y. Opportunities and Challenges of Vehicle-to-Home, Vehicle-to-Vehicle, and Vehicle-to-Grid Techno-logies. – Proceedings of the IEEE, 2013, 101(11), pp. 2409–2427, DOI:10.1109/JPROC.2013.2271951.
10. Ma K. et al. Voltage Regulation with Electric Taxi Based on Dynamic Game Strategy. – IEEE Transactions on Vehicular Technology, 2022, 71(3), pp. 2413–2426, DOI: 10.1109/TVT.2022.3141954.
11. Li Z.H., Khajepour A., Song J.A Comprehensive Review of the Key Technologies for Pure Electric Vehicles. – Energy, 2019, No 182, pp. 824–839, DOI:10.1016/j.energy.2019.06.077.
12. Yan H.D. et al. Multi-Time Scale Stochastic Optimal Dispatch of Electric Vehicle Charging Station Considering Demand Response. – Power System Protection and Control, 2020, No 10, pp. 71–80.
13. Zhou Y.T. et al. Demand Forecasting and Planning Layout of Urban Electric Vehicle Charging Facilities. – Power System Protection and Control, 2021, No 24, pp. 177–187.
14. Tian L., Shi S., Jia Z. A Statistical Model for Charging Power Demand of Electric Vehicles. – Power System Technology, 2010, 34(11), pp. 126–130.
15. Fan J. et al. Using Big GPS Trajectory Data Analytics for Vehicle Miles Traveled Estimation. – Transportation Research Part C Emerging Technologies, 2019, 103(05), pp. 298–307, DOI:10.1016/j.trc.2019.04.019.
#
1. Global EV. Outlook 2023: Catching up with Climate Ambitions. IEA, 2023, 142 p.
2. Butyrin P.A., Halyutin S.P. Elektrichestvo – in Russ. (Electri-city), 2023, No. 2, pp. 13–26.
3. Komarova M.V. Innovatsii. Nauka. Obrazovanie – in Russ. (Innovation. Science. Education), 2020, No. 21, pp. 276–281.
4. Sinitsyn М. EKO – in Russ. (ECO), 2020, 50(10), pp. 65–87.
5. Fang Y., Hu J., Ma W. Optimal Dispatch Strategy for Electric Vehicle Aggregators Based on Stackelberg Game Theory Considering User Intention. – Transactions of China Electrotechnical Society, 2023, pp. 1–13.
6. Rauma K. et al. Electric Vehicles as a Flexibility Provider: Optimal Charging Schedules to Improve the Quality of Charging Service. – Electricity, 2021, 2(3), pp. 225–243, DOI:10.3390/electricity2030014.
7. Wang H. et al. Review and Prospect of Key Techniques for Vehicle-Station-Network Integrated Operation in Smart City. – Transactions of China Electrotechnical Society, 2022, 37(1), pp. 112–132, DOI:10.19595/j.cnki.1000-6753.tces.211285.
8. Wu S., Yang Z. Availability of Public Electric Vehicle Charging Pile and Development of Electric Vehicle: Evidence from China. – Sustainability, 2020, No 12(16), DOI:10.3390/su12166369.
9. Liu C.H., Chau K.T., Wu D.Y. Opportunities and Challenges of Vehicle-to-Home, Vehicle-to-Vehicle, and Vehicle-to-Grid Technologies. – Proceedings of the IEEE, 2013, 101(11), pp. 2409–2427, DOI:10.1109/JPROC.2013.2271951.
10. Ma K. et al. Voltage Regulation with Electric Taxi Based on Dynamic Game Strategy. – IEEE Transactions on Vehicular Technology, 2022, 71(3), pp. 2413–2426, DOI: 10.1109/TVT.2022.3141954.
11. Li Z.H., Khajepour A., Song J. A Comprehensive Review of the Key Technologies for Pure Electric Vehicles. – Energy, 2019, No 182, pp. 824–839, DOI:10.1016/j.energy.2019.06.077.
12. Yan H.D. et al. Multi-Time Scale Stochastic Optimal Dispatch of Electric Vehicle Charging Station Considering Demand Response. – Power System Protection and Control, 2020, No 10, pp. 71–80.
13. Zhou Y.T. et al. Demand Forecasting and Planning Layout of Urban Electric Vehicle Charging Facilities. – Power System Protection and Control, 2021, No 24, pp. 177–187.
14. Tian L., Shi S., Jia Z. A Statistical Model for Charging Power Demand of Electric Vehicles. – Power System Technology, 2010, 34(11), pp. 126–130.
15. Fan J. et al. Using Big GPS Trajectory Data Analytics for Vehicle Miles Traveled Estimation. – Transportation Research Part C Emerging Technologies, 2019, 103(05), pp. 298–307, DOI:10.1016/j.trc.2019.04.019
Published
2024-07-31
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