摘要
随着电力系统转型的不断推进,区域综合能源服务商(regional integrated energy service provider,RIESP)由传统的自上而下无竞争的垄断模式向多方竞争模式转变。文章综合考虑了RIESP自身发电成本及用户购能满意度,提出了一种基于主从博弈的RIESP运行策略模型。首先,介绍了RIESP的基本架构及两步式决策机制,建立了以RIESP运行利润最大为领导者目标函数和用户消费剩余最大为跟随者目标函数的主从博弈模型。然后,证明了模型Stackelberg均衡解的存在性和唯一性,并采用基于差分进化和粒子群(differential evolution-particle swarm optimization,DE-PSO)的混合算法进行求解。最后,通过仿真算例验证了所提策略的有效性,结果证明,RIESP收益及用户消费剩余均有所提升。
With the continuous advancement of power system transformation,the regional integrated energy service provider(RIESP) has changed from a traditional top-down monopoly model without competition to a multi-party competition model.This paper comprehensively considers power generation cost of RIESP and user purchase satisfaction,and proposes a RIESP operation strategy model based on master-slave game.Firstly,the basic structure of RIESP and the two-step decision-making mechanism are introduced,and a master-slave game model is established,in which the maximum profit of RIESP is the leader objective function and the maximum user consumption surplus is the follower objective function.Then,the existence and uniqueness of the Stackelberg equilibrium solution of the model are proved,and the DE-PSO hybrid algorithm is used to solve it.Finally,through simulation examples,the effectiveness of the strategy proposed in this paper is verified,and both the revenue of RIESP and the surplus of user consumption are improved.
作者
李东东
周冠廷
李宽宏
林顺富
段维伊
沈运帷
LI Dongdong;ZHOU Guanting;LI Kuanhong;LIN Shunfu;DUAN Weiyi;SHEN Yunwei(College of Electrical Engineering,Shanghai University of Electric Power,Shanghai 200090,China;State Grid Fuzhou Electric Power Supply Company,Fuzhou 350009,China;Shanghai Higher Institution Engineering Research Center of High Efficiency Application,Shanghai 200090,China)
出处
《电力建设》
CSCD
北大核心
2021年第1期10-19,共10页
Electric Power Construction
基金
国家自然科学基金项目(51977127)
上海市教育委员会和上海市教育发展基金会“晨光计划”(17CG56)
上海市科学技术委员会地方院校能力建设项目(19020500800)。
关键词
区域综合能源服务商(RIESP)
运行策略
两步式决策
主从博弈
regional integrated energy service provider(RIESP)
operation strategy
two-step decision-making
master-slave game
