Анализ спроса на зарядку электромобилей в Ланьчжоу (Китай)
Ключевые слова:
электромобиль, зарядка электромобилей, анализ спроса на зарядку, дополнительная нагрузка на сети, оценка неравномерности потребления электроэнергии
Аннотация
В статье предложен подход к анализу спроса на электроэнергию, необходимую для зарядки электромобилей. Основой подхода являются социологические данные о владельцах электромобилей и графике использования ими электромобилей. Цель исследований – получить обоснованную оценку нагрузки на электрическую сеть, создаваемую электромобилями. Подход применен к условиям города Ланьчжоу (Китай). Население города разделено на девять групп, для каждой из которых предложена модель использования электромобиля в течение недели. Общее число электроавтомобилей составило около 20500 шт. Каждый владелец имел свой индивидуальный график пользования электромобилем в рамках допущений, характерных для его группы. Это позволило спрогнозировать время зарядки электромобиля каждым представителем группы и, соответственно, получить график потребления электроэнергии на зарядных станциях для всего города Ланьчжоу. Важным результатом явилось подтверждение резко неравномерного потребления электроэнергии электромобилями: пиковое значение мощности, потребляемой зарядными станциями, в восемь раз превосходит ее среднее значение. При высоких темпах роста числа электромобилей, характерного для Китая, это может создавать существенные проблемы для энергетической сети.
Литература
1. Global EV. Outlook 2023: Catching up with Climate Ambitions. IEA, 2023, 142 p.
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
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
