Optimization of Multi Microgrid Game Method Under Shared Energy Storage Mode

doi:10.16628/j.cnki.2095-8188.2022.02.003

Abstract

Abstract:

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.

Key words: shared energy storage, multi agent game, reinforcement learning, Kullback-Leibler divergence, adaptive learning rate

CLC Number:

TM734

ZHENG Hailin, WEN Buying, ZHU Zhenshan, WENG Zhimin. Optimization of Multi Microgrid Game Method Under Shared Energy Storage Mode[J]. LOW VOLTAGE APPARATUS, 2022, 0(2): 12-20.

Figures/Tables 10

References 21

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运行主体	各微电网独立优化(天)
运行主体	总运行成本/元	储能全寿命周期费用/元	充放电损耗/元
微电网1	44 196.14	2 233.26	5 265.70
微电网2	52 075.55	1 488.84	5 264.35
微电网3	49 835.60	3 722.10	10 591.27

运行主体	共享储能模式(天)
运行主体	总运行成本/元	调度(租赁) 储能费用/元	充放电损耗/元
微电网1	38 506.74	2 070.05	9 560.71
微电网2	49 327.81	2 143.25	9 171.42
微电网3	48 081.44	1 924.89	7 197.04
储能聚合商	-1 441.70(盈利)	7 444.20	23 181.51