摘要
区域综合能源系统是以可再生能源为核心,多能源网络耦合、多利益主体协同的未来能源网络,多方主体间的制约平衡是实现系统优化运行的关键。构建了包含产能基地、系统管理商和综合能源用户三方主体的典型区域IES模型;并建立综合能源用户的热电负荷耦合特性模型,完善综合需求响应机制。基于综合需求响应和博弈方法,提出了一种两阶段优化调度策略,实现区域IES内三方主体利益诉求的制约平衡和日内联合优化。一阶段为系统管理商的经济收益优化,利用Stackelberg博弈和电价型IDR策略实现用户对系统管理商经济优化的制约;二阶段为产能基地与用户利益的联合优化,采用激励型IDR策略建立用户与产能基地的互利关系,利用联盟博弈实现用户间制约平衡,从而实现三方主体利益相互制约和联合优化。最后,通过仿真算例验证了所提调度策略的优越性。
Integrated energy system (IES) is a future energy system focusing on renewable energy, containing multi-energy systems and multiple players. Equilibrium among players is the key point of system optimization. Firstly, an IES model is built, composed of a system manager, a generation base and integrated energy consumers. Then a coupling model between different loads is proposed. On this basis, a complete integrated demand response (IDR) strategy is proposed. Based on IDR and game method, a two-stage optimal dispatch is proposed to realize equilibrium and multi-player intraday optimization. The first-stage dispatch focuses on optimization of system manager profit. The optimization is restricted by consumers through Stackelberg game and price-based IDR. The second-stage dispatch is optimization of consumers and generation base. The proposed reward-based IDR gains the mutual benefit between the consumers and the generation base. The coalition game is used to gain equilibrium among consumers in the reward-based IDR, realizing the multi-player equilibrium and intraday optimization. Finally, simulation results verify advantages of the proposed strategy.
作者
徐业琰
廖清芬
刘涤尘
彭思成
杨铮
邹宏亮
张黎明
XU Yeyan;LIAO Qingfen;LIU Dichen;PENG Sicheng;YANG Zheng;ZOU Hongliang;ZHANG Liming(School of Electrical Engineering, Wuhan University, Wuhan 430072, Hubei Province, China;Taizhou Power Supply Branch, State Grid Zhejiang Electric Power Company, Taizhou 318000, Zhejiang Province, China)
出处
《电网技术》
EI
CSCD
北大核心
2019年第7期2506-2516,共11页
Power System Technology
基金
国家自然科学基金项目(51777142)
国家电网公司科技项目(5211TZ170005)~~
关键词
区域综合能源系统
综合需求响应
博弈
多主体联合优化
integrated energy system
integrated demand response
games
multi-players optimal dispatch