电力系统保护与控制2024，Vol.52Issue(3)：1-11,11.DOI:10.19783/j.cnki.pspc.230925
考虑路网和用户满意度的集群电动汽车主从博弈优化调度策略
Stackelberg game optimization scheduling strategy for aggregated electric vehicles considering customer satisfaction and the road network
摘要
Abstract
Traditional centralized optimization methods for electric vehicles(EVs)are faced with problems such as scheduling difficulty,a large amount of computation and lack of real data support in practical application,and they cannot accurately reveal the interaction behavior among various entities.Therefore,a Stackelberg game optimization scheduling strategy for aggregated EVs considering user satisfaction and the road network is proposed.First,it simulates user travel behavior based on real travel data and road network data.Second,the load aggregator(LA)integrates EV load resources to cluster EVs with similar travel characteristics.In the two-level Stackelberg game model,the LA is the leader of the upper level,and the clustered EV subgroups are the followers of the lower level.Considering the different consumption preferences of EV users,Nash equilibrium is achieved by optimizing the pricing strategy of the LA,the output plan of new energy and energy storage systems,and the charging and discharging strategies of EV clusters.The solution is achieved by an improved genetic algorithm.Finally,simulation is used to verify that the proposed model can effectively improve revenue of the LA and consumer surplus of EV users,increase consumption of new energy,and provide differentiated services for users with different consumption preferences.关键词
集群电动汽车/主从博弈/负荷聚合商/需求响应/K-means++聚类算法/用户满意度Key words
aggregated electric vehicle/Stackelberg game/load aggregator/demand response/K-means++ clustering algorithm/customer satisfaction引用本文复制引用
张美霞,王晓晴,杨秀,张安,付御临..考虑路网和用户满意度的集群电动汽车主从博弈优化调度策略[J].电力系统保护与控制,2024,52(3):1-11,11.基金项目
This work is supported by the National Natural Science Foundation of China(No.51725701). 国家自然科学基金项目资助(51725701) （No.51725701）
上海电力人工智能工程技术研究中心项目资助(19DZ2252800) （19DZ2252800）
