Frequency Regulation Incentive Mechanism and Control Strategy for Electric Vehicles Under Elastic Charging Demand

doi:10.11930/j.issn.1004-9649.202407004

Abstract

Abstract:

The high proportion of new energy penetration in the power system poses a serious challenge to frequency stability. With the development of vehicle to grid, electric vehicles as a flexible energy storage system can provide stable frequency regulation services for the power system. In order to enable electric vehicles to provide greater frequency regulation capacity for the power grid and increase users' willingness to participate in frequency regulation, the behavioral characteristics, state of charge, and power constraints of electric vehicles were analyzed. The travel chain and transportation network of electric vehicles were modeled, and a method for optimizing the expected SOC state constraint of electric vehicles was proposed, and the elastic frequency regulation capacity space, incentive mechanism, and frequency regulation control strategy of electric vehicles were constructed. Simulation has verified that compared with traditional control strategies that do not consider elastic charging demand, the proposed control strategy that considers elastic charging demand has advantages in providing frequency regulation capacity for the power grid and increasing user frequency regulation revenue. The proposed control strategy can provide a larger frequency regulation capacity for the power grid, increase users' frequency regulation revenue, and maintain the stability of the power grid frequency.

Key words: electric vehicle, frequency response, traffic demand, incentive mechanism, SOC

LI Xiaohan, CAO Wei. Frequency Regulation Incentive Mechanism and Control Strategy for Electric Vehicles Under Elastic Charging Demand[J]. Electric Power, 2025, 58(4): 148-158.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202407004

https://www.electricpower.com.cn/EN/Y2025/V58/I4/148

Figures/Tables 15

Fig.1 Zoning of EV driving areas

Fig.2 Elastic frequency regulation capacity space of EV batteries

Fig.3 Ladder pricing under different charging cycles

Fig.4 Structure of EVs participating in grid frequency regulation control

Fig.5 Flow chart of EVs participating in grid frequency regulation

Fig.6 Block diagram of frequency support model for EVs in single area

Table 1 Simulation system parameters

参数类型	数值	参数类型	数值
调速器时间常数 T_G/s	0.2	调差系数 R_g(p.u.)	0.05
汽轮机时间常数 T_CH/s	0.3	惯性时间常数 H_g/s	5
再热时间常数 T_RH/s	7.0	阻尼系数 D(p.u.)	1.0
再热系数 F_HP(p.u.)	0.3	额定频率 f/Hz	50

Fig.7 Regional transportation network simulation

Table 2 Probability of EV regional transfer

类型		H⇆W		H⇆B		H⇆W⇆B
数值		0.73		0.15		0.12

Table 3 Simulation parameters

参数类型	数值	参数类型	数值
EV电池容量/(kW·h)	30	期望SOC分布	N（0.75, 0.85）
最大充电功率/kW	6	容量补偿系数	1.02
充电效率	0.95	弹性激励系数	1.2
最大放电功率/kW	6	电价置信度	0.95
放电效率	0.95

Fig.8 Distribution of EVA power capacity in the workspace

Fig.9 Distribution of EVA power capacity in the residential area

Fig.10 Frequency regulation power scheduling curve and incentive price

Fig.11 Revenue from EV frequency regulation

Fig.12 Grid frequency fluctuations

References 33

1	张俊成, 黎敏, 刘志文, 等. 配电网用户侧多类型柔性资源调节能力评估方法[J]. 中国电力, 2023, 56 (9): 96- 103, 119.
	ZHANG Juncheng, LI Min, LIU Zhiwen, et al. An evaluation method for multi-type flexible resource regulation capability on the user side of distribution networks[J]. Electric Power, 2023, 56 (9): 96- 103, 119.
2	于凤娇, 王典, 李润宇. 计及需求侧响应的分布式电源并网优化策略[J]. 东北电力大学学报, 2022, 42 (2): 92- 103.
	YU Fengjiao, WANG Dian, LI Runyu. Optimization strategy for grid connection of distributed generation considering demand side response[J]. Journal of Northeast Electric Power University, 2022, 42 (2): 92- 103.
3	中华人民共和国中央人民政府. 国务院办公厅关于印发新能源汽车产业发展规划(2021—2035年)的通知[EB/OL]. (2020-11-02) [2024-06-18]. https://www.gov.cn/gongbao/content/2020/content_5560291.htm.
4	马艳红, 张炜函. 考虑充放电成本的V2G参与用户细分及激励机制研究[J]. 智慧电力, 2024, 52 (5): 31- 36, 51. DOI
	MA Yanhong, ZHANG Weihan. V2G participating in user segmentation & incentive mechanism considering charging and discharging cost[J]. Smart Power, 2024, 52 (5): 31- 36, 51. DOI
5	夏晖, 张敏, 刘志强, 等. 新能源项目运营技术经济分析及其对发展的影响[J]. 电力科技与环保, 2023, 39 (6): 543- 552.
	XIA Hui, ZHANG Min, LIU Zhiqiang, et al. Investigate on the impact factors of operational capability for new energy projects[J]. Electric Power Technology and Environmental Protection, 2023, 39 (6): 543- 552.
6	安佳坤, 杨书强, 王涛, 等. 电动汽车聚合下的微能源互联网优化调度策略[J]. 中国电力, 2023, 56 (5): 80- 88.
	AN Jiakun, YANG Shuqiang, WANG Tao, et al. Optimal scheduling strategy for micro energy Internet under electric vehicles aggregation[J]. Electric Power, 2023, 56 (5): 80- 88.
7	陈浩, 胡俊杰, 袁海峰, 等. 计及配电网拥塞的集群电动汽车参与二次调频方法研究[J]. 中国电力, 2021, 54 (12): 162- 169.
	CHEN Hao, HU Junjie, YUAN Haifeng, et al. Research on supplementary frequency regulation with aggregated electric vehicles considering distribution network congestion[J]. Electric Power, 2021, 54 (12): 162- 169.
8	吴盛军, 曹路, 陈浩, 等. 基于充放电裕度的电动汽车集群一次调频控制策略[J]. 电力工程技术, 2024, 43 (2): 154- 162, 188. DOI
	WU Shengjun, CAO Lu, CHEN Hao, et al. Primary frequency regulation control strategy for electric vehicle aggregation based on charging and discharging margin[J]. Electric Power Engineering Technology, 2024, 43 (2): 154- 162, 188. DOI
9	赵梓潼, 顾兵. 需求响应下基于电动汽车负荷聚合商的充放电电价与时段研究[J]. 东北电力大学学报, 2023, 43 (6): 79- 86.
	ZHAO Zitong, GU Bing. Research on charging and discharging price and time period basedon electric vehicle load aggregator under demand response[J]. Journal of Northeast Electric Power University, 2023, 43 (6): 79- 86.
10	LIU H, QI J J, WANG J H, et al. EV dispatch control for supplementary frequency regulation considering the expectation of EV owners[J]. IEEE Transactions on Smart Grid, 2018, 9 (4): 3763- 3772. DOI
11	IQBAL S, XIN A, JAN M U, et al. Aggregation of evs for primary frequency control of an industrial microgrid by implementing grid regulation & charger controller[J]. IEEE Access, 2020, 8, 141977- 141989. DOI
12	WANG M, MU Y, SHI Q, et al. Electric vehicle aggregator modeling and control for frequency regulation considering progressive state recovery[J]. IEEE Transactions on Smart Grid, 2020, 11 (5): 4176- 4189. DOI
13	高爽, 戴如鑫. 电动汽车集群参与调频辅助服务市场的充电调控策略[J]. 电力系统自动化, 2023, 47 (18): 60- 67. DOI
	GAO Shuang, DAI Ruxin. Charging control strategy for electric vehicle aggregation participating in frequency regulation ancillary service market[J]. Automation of Electric Power Systems, 2023, 47 (18): 60- 67. DOI
14	葛乐, 王庆园, 王明深, 等. 考虑充放电激励机制的电动汽车聚合商参与能量-调频市场多阶段运营策略[J]. 电力自动化设备, 2024, 44 (6): 176- 184.
	GE Le, WANG Qingyuan, WANG Mingshen, et al. Multi-stage operation strategy of electric vehicle aggregator participating in energy and frequency regulation markets considering charging and discharging incentive mechanisms[J]. Electric Power Automation Equipment, 2024, 44 (6): 176- 184.
15	侯慧, 唐俊一, 王逸凡, 等. 价格与激励联合需求响应下电动汽车长时间尺度充放电调度[J]. 电力系统自动化, 2022, 46 (15): 46- 55. DOI
	HOU Hui, TANG Junyi, WANG Yifan, et al. Long-time-scale charging and discharging scheduling of electric vehicles under joint price and incentive demand response[J]. Automation of Electric Power Systems, 2022, 46 (15): 46- 55. DOI
16	TAO Y C, QIU J, LAI S Y. Deep reinforcement learning based bidding strategy for EVAs in local energy market considering information asymmetry[J]. IEEE Transactions on Industrial Informatics, 2022, 18 (6): 3831- 3842. DOI
17	崔岩, 胡泽春, 段小宇. 考虑充电需求空间灵活性的电动汽车运行优化研究综述[J]. 电网技术, 2022, 46 (3): 981- 994.
	CUI Yan, HU Zechun, DUAN Xiaoyu. Review on the electric vehicles operation optimization considering the spatial flexibility of electric vehicles charging demands[J]. Power System Technology, 2022, 46 (3): 981- 994.
18	陈丽丹, 张尧, Antonio Figueiredo. 融合多源信息的电动汽车充电负荷预测及其对配电网的影响[J]. 电力自动化设备, 2018, 38 (12): 1- 10.
	CHEN Lidan, ZHANG Yao, FIGUEIREDO A. Charging load forecasting of electric vehicles based on multi-source information fusion and its influence on distribution network[J]. Electric Power Automation Equipment, 2018, 38 (12): 1- 10.
19	IVERSEN E B, MØLLER J K, MORALES J M, et al. Inhomogeneous Markov models for describing driving patterns[J]. IEEE Transactions on Smart Grid, 2017, 8 (2): 581- 588.
20	邢强, 陈中, 冷钊莹, 等. 基于实时交通信息的电动汽车路径规划和充电导航策略[J]. 中国电机工程学报, 2020, 40 (2): 534- 550.
	XING Qiang, CHEN Zhong, LENG Zhaoying, et al. Route planning and charging navigation strategy for electric vehicles based on real-time traffic information[J]. Proceedings of the CSEE, 2020, 40 (2): 534- 550.
21	新能源汽车国家大数据联盟. 中国小型纯电动乘用车出行大数据报告[R]. 北京: 新能源汽车国家大数据联盟, 2020.
	National Big Data Alliance of New Energy Vehicles. Big data report on China's small pure electric passenger vehicle travel[R]. Beijing: National Big Data Alliance of New Energy Vehicles, 2020.
22	禤宗衡, 荆朝霞, 叶文圣, 等. 考虑储能灵活能量状态的新型电能量市场机制[J]. 电网技术, 2022, 46 (10): 3810- 3823.
	XUAN Zongheng, JING Zhaoxia, YE Wensheng, et al. New energy market mechanism considering flexible state of energy in energy storage[J]. Power System Technology, 2022, 46 (10): 3810- 3823.
23	徐俊俊, 程奕凌, 张腾飞, 等. 计及充电行为特征与可调性的电动汽车集群优化调度[J]. 电力系统自动化, 2023, 47 (23): 23- 32. DOI
	XU Junjun, CHENG Yiling, ZHANG Tengfei, et al. Optimal scheduling of electric vehicle clusters considering characteristics and adjustability of charging behavior[J]. Automation of Electric Power Systems, 2023, 47 (23): 23- 32. DOI
24	王秀茹, 黄小庆, 段建焱, 等. 电池健康状态对电动汽车充电负荷计算的影响[J]. 南方电网技术, 2023, 17 (7): 65- 73.
	WANG Xiuru, HUANG Xiaoqing, DUAN Jianyan, et al. Influence of state of health of battery on EV charging load calculation[J]. Southern Power System Technology, 2023, 17 (7): 65- 73.
25	SAXENA S, HENDRICKS C, PECHT M. Cycle life testing and modeling of graphite/LiCoO₂ cells under different state of charge ranges[J]. Journal of Power Sources, 2016, 327, 394- 400. DOI
26	周椿奇, 向月, 童话, 等. 轨迹数据驱动的电动汽车充电需求及V2G可调控容量估计[J]. 电力系统自动化, 2022, 46 (12): 46- 55. DOI
	ZHOU Chunqi, XIANG Yue, TONG Hua, et al. Trajectory-data-driven estimation of electric vehicle charging demand and vechicle-to-grid regulable capacity[J]. Automation of Electric Power Systems, 2022, 46 (12): 46- 55. DOI
27	祁兵, 陈淑娇, 李彬, 等. 计及用户满意度的可调节负荷资源需求响应优化策略研究[J]. 内蒙古电力技术, 2023, 41 (3): 43- 50.
	QI Bing, CHEN Shujiao, LI Bin, et al. Research on demand response optimization strategy of adjustable load resource considering user satisfaction[J]. Inner Mongolia Electric Power, 2023, 41 (3): 43- 50.
28	YANG W, XIANG Y, LIU J Y, et al. Agent-based modeling for scale evolution of plug-in electric vehicles and charging demand[J]. IEEE Transactions on Power Systems, 2018, 33 (2): 1915- 1925. DOI
29	KUNDUR P. Power system stability and control[M]. McGraw-Hill, Companies, Inc, 1994.
30	RAUTIAINEN A, REPO S, JARVENTAUSTA P, et al. Statistical charging load modeling of PHEVs in electricity distribution networks using national travel survey data[J]. IEEE Transactions on Smart Grid, 2012, 3 (4): 1650- 1659. DOI
31	DENG X S, ZHANG Q, LI Y, et al. Hierarchical distributed frequency regulation strategy of electric vehicle cluster considering demand charging load optimization[C]//2020 IEEE 3rd Student Conference on Electrical Machines and Systems (SCEMS). Jinan, China. IEEE, 2020: 959–969.
32	潘振宁, 余涛, 王克英. 考虑多方主体利益的大规模电动汽车分布式实时协同优化[J]. 中国电机工程学报, 2019, 39 (12): 3528- 3541.
	PAN Zhenning, YU Tao, WANG Keying. Decentralized coordinated dispatch for real-time optimization of massive electric vehicles considering various interests[J]. Proceedings of the CSEE, 2019, 39 (12): 3528- 3541.
33	SONG M, AMELIN M. Purchase bidding strategy for a retailer with flexible demands in day-ahead electricity market[C]//2017 IEEE Manchester PowerTech. Manchester, UK. IEEE, 2017: 1.

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