基于VaR理论的综合能源零售市场最优策略  

Optimal Strategy of Integrated Energy Retail Market Based on VaR Theory

作　　者：郭祚刚 徐敏 李睿智 袁智勇 谈赢杰 陈柏沅 雷金勇 刘念 GUO Zuogang;XU Min;LI Ruizhi;YUAN Zhiyong;TAN Yingjie;CHEN Baiyuan;LEI Jinyong;LIU Nian(Electric Power Research Institute,CSG,Guangzhou 510663,China;State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(North China Electric Power University),Beijing 102206,China)

机构地区：[1]南方电网科学研究院,广州市510663 [2]新能源电力系统国家重点实验室(华北电力大学),北京市102206

出　　处：《电力建设》2021年第6期9-16,共8页Electric Power Construction

基　　金：南方电网公司科技项目(ZBKJXM20180209)。

摘　　要：随着综合能源系统推广,多能源供给-传输-使用耦合程度加深,用户用能形式逐渐多样化,能源市场改革形成的零售市场内涵不断丰富。传统单一能源独立供给-定价的零售市场不能有效引导用户用能、提高系统经济性,综合能源系统零售市场的定价策略亟待研究。计及用户多能负荷、现货价格的随机性和用户需求响应提出基于风险价值(value at risk, VaR)理论的综合能源园区零售最优定价方法,并建立了静态零售定价-日前优化调度两阶段模型,研究了综合能源服务商的静态零售定价最优策略。第一阶段为计及日前阶段用户负荷、现货价格随机性的零售定价优化模型。第二阶段为第一阶段最优零售价格下的日前优化调度模型。最后采用粒子群-线性规划算法对所提两阶段模型进行迭代求解。算例结果表明,基于VaR的零售定价方法可以有效降低综合能源服务商参与零售市场的风险。With the promotion of integrated energy system, the coupling of multiple energies in terms of supply, transmission and use increases, the forms of energy use are gradually diversified, and the connotation of retail market is constantly enriched under the reform of energy market. Under the traditional retail market of single energy, independent supply and pricing method cannot effectively guide users to use energy and improve the economic efficiency. Therefore, it is urgent to study the pricing strategy for retail market of integrated energy system. In this paper, optimal retail pricing method for the comprehensive energy park on the basis of value at risk(VaR) theory is proposed considering multi-energy load, randomness of spot price and demand response. A two-stage model of static retail pricing and day-ahead optimal scheduling is established to study the optimal static retail pricing strategy of integrated energy service providers. The first stage is a retail pricing optimization model that takes into account day-ahead energy load and spot price randomness. The second stage is the day-ahead optimal scheduling model under the optimal retail price in the first stage. The particle swarm optimization(PSO) linear programming algorithm is used to solve the two-stage model iteratively. The results show that VaR-based retail pricing can effectively reduce the risk of integrated energy service providers participating in the retail market.

关 键 词：综合能源零售市场 综合能源服务商 需求响应 风险价值 

分 类 号：TM-9[电气工程]