Game-based Operation Optimization for Photovoltaic Storage Charging Station Considering Photovoltaic Uncertainty and Carbon Trading

YAN Qingyou; YU Pengshuo; ZHANG Meijuan; LIN Hongyu

doi:10.19725/j.cnki.1007-2322.2023.0363

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Game-based Operation Optimization for Photovoltaic Storage Charging Station Considering Photovoltaic Uncertainty and Carbon Trading

更新时间：2025-10-22

- Game-based Operation Optimization for Photovoltaic Storage Charging Station Considering Photovoltaic Uncertainty and Carbon Trading
- Vol. 42, Issue 5, Pages: 1012-1025(2025)
- 作者机构：
  
  华北电力大学经济与管理学院, 北京市昌平区,102206
- 作者简介：
- 基金信息：
- DOI：10.19725/j.cnki.1007-2322.2023.0363
  CLC： 5
- Published：2025
- 稿件说明：
移动端阅览
YAN Qingyou, YU Pengshuo, ZHANG Meijuan, et al. Game-based Operation Optimization for Photovoltaic Storage Charging Station Considering Photovoltaic Uncertainty and Carbon Trading[J]. 2025, 42(5): 1012-1025.
DOI：

YAN Qingyou, YU Pengshuo, ZHANG Meijuan, et al. Game-based Operation Optimization for Photovoltaic Storage Charging Station Considering Photovoltaic Uncertainty and Carbon Trading[J]. 2025, 42(5): 1012-1025. DOI： 10.19725/j.cnki.1007-2322.2023.0363.

摘要

随着双碳目标的推进，光储充电站成为利用清洁能源，满足电动汽车用电需求，并减少碳排放的重要设施。如何在兼顾经济性和低碳性的前提下，确定各主体的交易策略，实现利益双方互利共赢，成为亟待解决的课题。基于此，在考虑光伏出力不确定性和电动汽车充电随机性的前提下，构建计及碳交易的光储充电站博弈运行优化模型。首先，通过场景生成和削减技术处理光伏不确定性，随后根据用户行驶习惯建立电动汽车(electric vehicles，EV)随机充电模型。其次，引入阶梯型碳交易机制约束充电站的碳排放。最后，构建充电站-电动汽车主从博弈模型。上层制定充电运营商的定价策略，以保证其运行经济性和低碳性；下层模型通过制定电动汽车用户的充电策略，以最大化车主满意度，并采用遗传算法与混合整数线性规划相结合的算法进行求解。仿真结果表明，所提策略能够在有效兼顾各主体利益的同时，减少系统的碳排放量。

Abstract

The determination of the trading strategies for each participant

under the premise of considering the economy and low carbon and realizing mutual benefits and win-win situation

have emerged as an urgent research topic. Based on this

considering the uncertainty of photovoltaic output and the stochastic nature of electric vehicle charging

in this paper we construct a game-based operation optimization model for PVCS

taking into account the carbon trading. Firstly

we deal with photovoltaic uncertainty through scenario generation and reduction techniques. Subsequently

the EV stochastic charging model is established based on users’ driving habits. Secondly

a stepwise carbon trading mechanism is introduced to constrain the carbon emissions of charging stations. Finally

we construct a PVCS-EV Stackelberg game model. The upper layer formulates the pricing strategy for charging operators to ensure its operation economy and low carbon

while the lower one develops the charging strategy for EV users to maximize owners' satisfaction. The model is solved using an algorithm that integrates intelligent algorithms with mixed integer linear programming. The simulation results demonstrate the efficacy of the proposed strategy in reducing the system’s carbon emissions while effectively balancing the interests of all stakeholders.

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Keywords

references

WANG Youran. The energy crisis will bring multiple impacts to the world [N]. China Social Science Journal, 2023-02-13(008) (in Chinese).

王悠然. 能源危机将给世界带来多重影响[N]. 中国社会科学报, 2023-02-13(008).

ZHANG Panzhao, XIE Lirong, MA Ruizhen, et al. Multi-player two-stage low carbon optimal operation strategy considering electric vehicle cluster schedule ability[J]. Power System Technology, 2022, 46(12): 4809-4821(in Chinese).

章攀钊, 谢丽蓉, 马瑞真, 等. 考虑电动汽车集群可调度能力的多主体两阶段低碳优化运行策略[J]. 电网技术, 2022, 46 (12): 4809-4821.

DONG Houqi, WANG Liying, CAO Yuwei, et al. Research on capacity allocation and pricing method of light-storage charging station considering user price demand response[J]. Acta Energiae Solaris Sinica, 2021, 42(06): 79−86 (in Chinese).

董厚琦, 王俐英, 曹雨微, 等. 考虑用户价格需求响应的光-储充电站容量配置与定价方法研究[J]. 太阳能学报, 2021, 42(06): 79−86.

GUI Qiang, SHI Yiwei, ZHOU Yun , et al. Optimal allocation model of optical storage capacity for charging stations considering dynamic operating characteristics of energy storage[J]. Electric Power Construction, 2021, 42(05): 90-99 (in Chinese).

桂强, 史一炜, 周云, 等. 考虑储能动态运行特性的充电站光储容量优化配置模型[J]. 电力建设, 2021, 42(05): 90-99.

LI Jingli, SHI Yongkai, ZHANG Linjuan, et al. Energy storage capacity optimization strategy for optical storage charging stations considering orderly charging of electric vehicles[J]. Power System Protection and Control, 2021, 49(07): 94−102 (in Chinese).

李景丽, 时永凯, 张琳娟, 等. 考虑电动汽车有序充电的光储充电站储能容量优化策略[J]. 电力系统保护与控制, 2021, 49(07): 94−102.

GU Xiu, ZHAO Zhiyong, LI Handong. Comprehensive evaluation of environmental benefits of photovoltaic charging station[J]. Environment and Development, 2016, 28(04): 32−38 (in Chinese).

谷秀, 赵志勇, 李捍东. 光伏充电站环境效益综合评价[J]. 环境与发展, 2016, 28(04): 32−38.

YANG Meng. Research on capacity configuration and comprehensive benefit of electric vehicle charging station with integrated solar storage and charging[D]. Beijing: North China Electric Power University (Beijing), 2020 (in Chinese).

杨猛. 光储充一体化电动汽车充电站容量配置及综合效益研究[D]. 北京: 华北电力大学(北京), 2020.

ZHENG Jianfeng, LI Tianlun, MAO Shuren, et al. Optimal control strategy of user-side optical storage system under time-of-use electricity price[J]. Computer Measurement and Control, 2021, 29(07): 106−110(in Chinese).

郑剑锋, 李天伦, 毛树人, 等. 分时电价下用户侧光储系统优化控制策略[J]. 计算机测量与控制, 2021, 29(07): 106−110.

LU Xinyi, LIU Nian, CHEN Zheng, et al. Multi-objective optimal scheduling method for photovoltaic charging station for electric vehicle[J]. Transactions of China Electrotechnical Society, 2014, 29(08): 46−56 (in Chinese).

路欣怡, 刘念, 陈征, 等. 电动汽车光伏充电站的多目标优化调度方法[J]. 电工技术学报, 2014, 29(08): 46−56.

CHEN Tingxuan, XU Xiaoyuan, YAN Zheng, et al. Optimal operation based on deep reinforcement learning for energy storage system in photovoltaic-storage charging station[J]. Electric Power Automation Equipment, 2021, 41(10): 90−98 (in Chinese).

陈亭轩, 徐潇源, 严正, 等. 基于深度强化学习的光储充电站储能系统优化运行[J]. 电力自动化设备, 2021, 41(10): 90−98.

XUE Guiting, WANG Liujun, LIU Zhe, et al. Photovoltaic storage and charging integrated station considering carbon emissions[J]. Power System Protection and Control, 2022, 50(07): 103−110 (in Chinese).

薛贵挺, 汪柳君, 刘哲, 等. 考虑碳排放的光储充一体站日前运行策略[J]. 电力系统保护与控制, 2022, 50(07): 103−110.

HE Chenke, ZHU Jizhong, LIU Yun, et al. Coordination planning of electric vehicle charging and storage integrated station and active distribution network considering carbon emission reduction[J]. Transactions of China Electrotechnical Society, 2022, 37(01): 92−111 (in Chinese).

何晨可, 朱继忠, 刘云, 等. 计及碳减排的电动汽车充换储一体站与主动配电网协调规划[J]. 电工技术学报, 2022, 37(01): 92−111.

LIU Guoming, YU Hui, KANG Kai, et al. Capacity configuration of photovoltaic storage charging station considering demand response and carbon emissions[J]. Proceedings of the CSU-EPSA, 2021, 33(07): 106−112 (in Chinese).

刘国明, 于晖, 康凯, 等. 考虑需求响应与碳排放的光储充电站容量配置[J]. 电力系统及其自动化学报, 2021, 33(07): 106−112.

LIU Chang, LIU Hong, LI Xianglong, et al. Multi-objective planning of electric vehicle charging station considering the reliability of road network and distribution network[J]. Electric Power Automation Equipment, 2017, 37(08): 28−34 (in Chinese).

刘畅, 刘洪, 李香龙, 等. 考虑路网与配电网可靠性的电动汽车充电站多目标规划[J]. 电力自动化设备, 2017, 37(08): 28−34.

XU Wenfa, WANG Yufei, XUE Hua, et al. Research on real-time pricing strategy of electric vehicle charging based on game theory[J]. Electrical Measurement and Instrumentation, 2021, 58(07): 36−43 (in Chinese).

徐文法, 王育飞, 薛花, 等. 基于博弈论的电动汽车充电实时定价策略研究[J]. 电测与仪表, 2021, 58(07): 36−43.

FENG Xiao, ZHANG Chuanlin, CUI Chenggang, et al. Scheduling optimization of islanded photovoltaic storage charging station based on Stackelberg game[J]. Power System Technology, 2022, 46(10): 3989−4001 (in Chinese).

冯小, 张传林, 崔承刚, 等. 基于Stackelberg博弈的孤岛式光储充电站调度优化[J]. 电网技术, 2022, 46(10): 3989−4001.

XIE Zhenxue, LIN Fan, WANG Ruogu, et al. Ultra-short-term photovoltaic power prediction method based on time series dynamic regression[J]. Smart Power, 2022, 50(07): 45−51 (in Chinese).

解振学, 林帆, 王若谷, 等. 基于时序动态回归的超短期光伏发电功率预测方法[J]. 智慧电力, 2022, 50(07): 45−51.

SALAMEH Z M, BOROWY B S, AMIN A R A. Photovoltaic module-site matching based on the capacity factors[J]. IEEE Transactions on Energy Conversion, 1995, 10(2): 326−332.

WANG Shouxiang, CHEN Haiwen, LI Xiaoping. Conditional variational autoencoder method for random scene generation of wind power and photovoltaics[J]. Power System Technology, 2018, 42(06): 1860−1869 (in Chinese).

王守相, 陈海文, 李小平, 等. 风电和光伏随机场景生成的条件变分自动编码器方法[J]. 电网技术, 2018, 42(06): 1860−1869.

JIANG Cheng, WANG Shuo, WANG Baoqing, et al. Probabilistic reliability evaluation of wind power system based on Latin hypercube sampling[J]. Transactions of China Electrotechnical Society, 2016, 31(10): 193−206 (in Chinese).

蒋程, 王硕, 王宝庆, 等. 基于拉丁超立方采样的含风电电力系统的概率可靠性评估[J]. 电工技术学报, 2016, 31(10): 193−206.

FU Wenjie, WANG Yuxi, SHEN Hongtao, et al. Baseline load estimation method of residential users based on Latin hypercube sampling and scenario reduction[J]. Power System Technology, 2022, 46(06): 2298−2307 (in Chinese).

付文杰, 王喻玺, 申洪涛, 等. 基于拉丁超立方抽样和场景消减的居民用户基线负荷估计方法[J]. 电网技术, 2022, 46(06): 2298−2307.

JIANG Chengcheng, ZHU Jian’an, ZHU Chengming, et al. EV modeling in V2G mode[J]. Electronic Science and Technology, 2022, 35(2): 74−78(in Chinese).

蒋成成, 朱健安, 朱成名, 等. V2G模式下的EV建模研究[J]. 电子科技, 2022, 35(2): 74−78.

ZHOU Jianli, WU Yunna, DONG Haoxin, et al. Optimal planning of wind-solar-hydrogen integrated energy system considering random charging of electric vehicles[J]. Automation of Electric Power Systems, 2021, 45(24): 30−40(in Chinese).

周建力, 乌云娜, 董昊鑫, 等. 计及电动汽车随机充电的风-光-氢综合能源系统优化规划[J]. 电力系统自动化, 2021, 45(24): 30−40.

CHEN Jinpeng, HU Zhijian, CHEN Jiabin, et al. Optimal dispatch of integrated energy system considering stepped carbon trading and flexible response of supply and demand[J]. High Voltage Engineering, 2021, 47(09): 3094−3106(in Chinese).

陈锦鹏, 胡志坚, 陈嘉滨, 等. 考虑阶梯式碳交易与供需灵活双响应的综合能源系统优化调度[J]. 高电压技术, 2021, 47(09): 3094−3106.

WANG Lingyun, XU Jianzhe, LI Shichun, et al. Low-carbon economic dispatch of integrated energy system considering electricity-gas-heat demand response and stepped carbon trading[J]. Smart Power, 2022, 50(09): 45−52(in Chinese).

王凌云, 徐健哲, 李世春, 等. 考虑电-气-热需求响应和阶梯式碳交易的综合能源系统低碳经济调度[J]. 智慧电力, 2022, 50(09): 45−52.

LIU Dongyang. Research on optimal dispatching strategy of photovoltaic auxiliary charging station for electric vehicle[D]. Jilin: Northeast Electric Power University, 2022(in Chinese).

刘东洋. 电动汽车光伏辅助充电站优化调度策略研究[D]. 吉林: 东北电力大学, 2022.

GUO Ziyao. Research on real-time energy management strategy of photovoltaic electric vehicle charging station[D]. Harbin: Harbin Institute of Technology, 2021(in Chinese).

郭子瑶. 光伏型电动汽车充电站实时能量管理策略研究[D]. 哈尔滨: 哈尔滨工业大学, 2021.

FAN Libo. Research on pricing strategy and energy consumption optimization of load aggregator based on Stackelberg game[D]. Zhengzhou: Zhongyuan University of Technology, 2022(in Chinese).

范力搏. 基于主从博弈的负荷聚合商定价策略及用能优化研究[D]. 郑州: 中原工学院, 2022.

LIN Kaijun. Research on energy management optimization of micro-energy grid based on game theory[D]. Beijing: Beijing Jiaotong University, 2020(in Chinese).

林凯骏. 基于博弈论的微能源网能量管理优化研究[D]. 北京: 北京交通大学, 2020.

GONG Chengjiarui, LIN Shunfu, BIAN Xiaoyan, et al. Economic optimization model of load aggregator based on multi-agent Stackelberg game[J]. Power System Protection and Control, 2022, 50(02): 30−40(in Chinese).

龚诚嘉锐, 林顺富, 边晓燕, 等. 基于多主体主从博弈的负荷聚合商经济优化模型[J]. 电力系统保护与控制, 2022, 50(02): 30−40.

WANG Xingxing, ZHAO Jinquan, WANG Ke, et al. Multi-objective double-layer charging optimization of electric vehicles considering user satisfaction and distribution network safety[J]. Power System Technology, 2017, 41(07): 2165−2172(in Chinese).

王行行, 赵晋泉, 王珂, 等. 考虑用户满意度和配网安全的电动汽车多目标双层充电优化[J]. 电网技术, 2017, 41(07): 2165−2172.

WEI Wei, CHEN Yue, LIU Feng, et al. Intelligent community agent pricing strategy and electric vehicle charging management based on Stackelberg game[J]. Power System Technology, 2015, 39(04): 939−945(in Chinese).

魏韡, 陈玥, 刘锋, 等. 基于主从博弈的智能小区代理商定价策略及电动汽车充电管理[J]. 电网技术, 2015, 39(04): 939−945.

SHI Yiwei, FENG Donghan, ZHOU Ella, et al. Charging guidance method and pricing strategy of charging service provider based on Stackelberg game[J]. Transactions of China Electrotechnical Society, 2019, 34(S2): 742−751(in Chinese) .

史一炜, 冯冬涵, ZHOU Ella, 等. 基于主从博弈的充电服务商充电引导方法及其定价策略[J]. 电工技术学报, 2019, 34(S2): 742−751.

LIU Jun, WANG Chao, CHEN Jinjing, et al. Multi-market main revenue model of urban energy Internet based on game theory[J]. Automation of Electric Power Systems, 2019, 43(14): 90−96(in Chinese).

刘俊, 王超, 陈津莼, 等. 基于博弈论的城镇能源互联网多市场主体收益模型[J]. 电力系统自动化, 2019, 43(14): 90−96.

PAN Zhenning, YU Tao, WANG Keying. Distributed real-time collaborative optimization of large-scale electric vehicles considering the interests of multiple parties[J]. Proceedings of the CSEE, 2019, 39(12): 3528−3540(in Chinese).

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): 3528−3540.

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