摘要
【目的】随着规模化电动汽车(electric vehicle,EV)的发展,其大规模接入对电网运行带来新的挑战,亟待充分挖掘电动汽车的灵活调节能力,以提升电网运行的安全性与经济性。虚拟电厂(virtual power plant,VPP)作为聚合多类分布式资源的高效模式,为EV参与电网运行提供了新的解决方案,文章提出了基于条件风险价值(conditional value at risk,CVaR)的虚拟电厂与电动汽车主从博弈优化策略。【方法】文章构建包含VPP与EV两层决策主体的Stackelberg博弈模型。上层以VPP收益最大化为目标,引入CVaR理论,量化并规避由EV充放电不确定性引发的风险,制定风险感知的充放电服务价格;下层以EV用户充放电成本最小为目标,引入包含成本满意度与体验满意度的效用函数,刻画EV用户响应行为。【结果】通过设置含光伏、风电、储能和300辆EV的VPP系统,开展数值仿真与多场景对比分析,验证了所提策略在降低负荷峰谷差、降低EV用户平均充放电成本以及提升VPP收益稳定性方面的有效性,具备较强的工程适用性。【结论】所提基于CVaR的VPP与EV主从博弈策略能够兼顾电网调控需求与用户行为偏好,在复杂不确定环境下实现多方利益协调,提升系统的经济性与稳定性。研究结果为电动汽车参与电力市场交易与虚拟电厂风险管理提供了可行的方法参考。
[Objective]The large-scale integration of electric vehicles(EVs)presents potential flexibility and operational uncertainty in power systems.Virtual power plants(VPPs),as efficient paradigms for aggregating distributed energy resources,offer a feasible approach for coordinating EV participation in grid operations.This study proposed a bi-level optimization strategy based on a Stackelberg game to manage the interaction between VPPs and EV users under uncertainty.[Methods]A bi-level Stackelberg game model was developed in which the VPP acts as the leader and the EV users as followers.The upper-level model maximized the VPP profit while managing EV-related uncertainties via the conditional value at risk(CVaR).It sets risk-aware charging and discharging prices.The lower-level model minimized user costs by responding to these prices using a utility function that captures both cost satisfaction and charging experience.A particle swarm optimization algorithm was employed to solve the coupled model and identify the equilibrium strategies.[Results]A case study of a VPP system with wind,solar,storage,and 300 EVs demonstrated the effectiveness of the proposed approach.Compared to benchmark strategies,the model reduced the peak-valley load gap by up to 36.9%,lowered the average user cost by 28.79%,and enhanced profit stability under uncertainty.[Conclusions]The CVaR-based bi-level game framework effectively balances the VPP profit,EV user satisfaction,and system stability.It provides a risk-aware,market-oriented approach for flexible resource management and offers practical insights into future EV-grid integration strategies.
作者
马乾鑫
加鹤萍
郭宇辰
李培军
杨烨
刘敦楠
赵振宇
MA Qianxin;JIA Heping;GUO Yuchen;LI Peijun;YANG Ye;LIU Dunnan;ZHAO Zhenyu(School of Economics and Management,North China Electric Power University,Beijing 102206,China;State Grid Smart Internet of Vehicles Co.,Ltd.,Beijing 100032,China)
出处
《电力建设》
北大核心
2025年第7期53-66,共14页
Electric Power Construction
基金
国家电网有限公司科技项目(5400-202427221A-1-1-ZN)。
