摘要
用户侧分布式储能具备优化用户电力负荷曲线和协调消纳系统侧可再生能源发电的能力。提出一种基于动态电价机制的配电系统用户侧分布式储能电能交易策略。首先,该策略在充分考虑新能源出力和用户电能需求不确定性的基础上,构建用户侧分布式储能和配电系统的日前电能调度模型;然后,根据动态电价机制对用户侧分布式储能调度计划和系统侧可再生能源消纳水平的影响,建立基于主从博弈的配电网运营商和用户侧储能运营商的电能交易模型,并采用启发式算法获取博弈模型的均衡解;最后,通过算例验证了所提电能交易策略可有效提升配电网运营商的经济效益与新能源消纳水平,并降低用户侧的运行成本。
User-side distributed energy storage has the ability to optimize user power load curve and coordinate renewable energy generation at the consumption system side. In this paper, a user-side distributed energy storage trading strategy is proposed based on dynamic electricity price mechanism. Firstly, a day-ahead power dispatching model is constructed for the user-side distributed energy storage and distribution system with full consideration of the uncertainty of new energy output and user’s power demand. Secondly,according to the impact of dynamic electricity price mechanism on the user-side distributed energy storage scheduling plan and the system-side renewable energy consumption level, a power trading model is established for distribution network operators(DNOs)and user-side distributed energy storage owners(DEOs) based on master-slave game, and the metaheuristic algorithm is used to obtain the equilibrium solution of the game model. Finally, it is verified through a case study that the proposed power trading strategy can effectively improve the DNO’s economic benefits and renewable energy accommodation level and reduce the user-side operating costs.
作者
郭之栋
胡存刚
芮涛
罗魁
林振锋
GUO Zhidong;HU Cungang;RUI Tao;LUO Kui;LIN Zhenfeng(School of Electrical Engineering and Automation,Anhui University,Hefei 230601,China;Engineering Research Center of Power Quality,Ministry of Education(Anhui University),Hefei 230601,China;China Electric Power Research Institute,Beijing 100192,China)
出处
《中国电力》
CSCD
北大核心
2023年第1期28-37,共10页
Electric Power
基金
安徽省高校自然科学基金资助项目(KJ2020A0038)
新能源与储能运行控制国家重点实验室(中国电力科学研究院有限公司)开放基金项目(NYB51202001734)。
关键词
用户侧
分布式储能
动态电价机制
主从博弈
电能交易
user side
distributed energy storage system
dynamic electricity price mechanism
Stackelberg game
energy trading
