摘要
储能的高投资成本是限制其商业化发展的主要障碍,通过储能聚合商协调储能设备运行,提高储能的利用率并降低成本。首先,综合考虑了微电网中的火电机组、充电站、可中断负荷等可调节灵活性资源的成本以及共享储能的费用分摊,以各方效益最大化为目标,构建了各微电网与共享储能聚合商的博弈优化运行模型。其次,采用了多智能体强化学习方法求解多主体下博弈问题,引入KL散度优化智能体的学习率,提高算法的收敛性。最后,以3个相邻微电网的算例分析,共享储能模式下提升了各主体的经济效益,验证了共享储能模式的优越性与算法改进的有效性。
The high investment cost of energy storage is the main obstacle to its commercial development.Through the energy storage aggregators to coordinate the operation of energy storage equipment, the utilization rate of energy storage is improved and the cost is reduced.Firstly, the cost of adjustable flexible resources such as thermal power units, charging stations and interruptible loads in microgrid and the cost sharing of shared energy storage are comprehensively considered.Aiming at maximizing the benefits of all parties, the game optimization operation model between microgrid and shared energy storage aggregator is constructed.Secondly, the Multi-Agent Reinforcement learning method is used to solve the multi-agent game problem, and KL divergence is introduced to optimize the agent learning rate and improve the convergence of the algorithm.Finally, taking three adjacent microgrids as examples, the economic benefits of each subject are improved under the shared energy storage mode, which verifies the superiority of the mode and the effectiveness of the algorithm improvement.
作者
郑海林
温步瀛
朱振山
翁智敏
ZHENG Hailin;WEN Buying;ZHU Zhenshan;WENG Zhimin(College of Electrical Engineering and Automation,Fuzhou University,Fuzhou 350108,China;Fujian Key Laboratory of New Energy Generation and Power Conversion,Fuzhou 350108,China;Fujian Province University Engineering Research Center of Smart Distribution Grid Equipment,Fuzhou 350108,China)
出处
《电器与能效管理技术》
2022年第2期12-20,共9页
Electrical & Energy Management Technology
基金
福建省教育厅中青年教师教育科研项目(JAT190043)
福州大学科研启动项目(510901)。
关键词
共享储能
多主体博弈
强化学习
KL散度
自适应学习率
shared energy storage
multi agent game
reinforcement learning
Kullback-Leibler divergence
adaptive learning rate
