电力建设2024，Vol.45Issue(7)：100-112,13.DOI:10.12204/j.issn.1000-7229.2024.07.009
基于分布鲁棒和改进纳什谈判的多微网-共享储能运行优化策略
Multi-Microgrid and Shared Energy Storage Operation Optimization Strategy Based on Distributionally Robust and Improved Nash Bargaining
摘要
Abstract
To promote the consumption of renewable energy and improve energy efficiency has become an important development direction of power system.In this paper,an operation optimization strategy of multi-microgrids and shared energy storage system is proposed,which considers the uncertainty of energy output and the difference of cooperative contribution.A cost optimization model based on Nash bargaining is established and decomposed into two sub-problems to reduce the difficulty of solving.Subproblem 1 establishes a two-stage distributionally robust optimization model based on the comprehensive norm to determine the energy storage capacity configuration,interactive power,and integrated demand response plan with minimum overall cost under the worst scenario.Sub-problem 2 performs asymmetric bargaining based on improved Nash bargaining to complete transaction payment and distributes cooperation income based on energy contribution and charge state change.The two subproblems are solved iteratively by column and constraint generation(C&CG)algorithm and alternating direction method of multipliers(ADMM).The results of the example show that the distributionally robust optimization can achieve the balance between economy and robustness.The transaction payment based on the improved Nash bargaining can reasonably distribute the cooperation income and maintain the cooperation enthusiasm.关键词
多微电网/共享储能系统/两阶段分布鲁棒/非对称纳什议价/合作博弈Key words
multi-microgrids/shared energy storage system/two-stage distributionally robust/asymmetric Nash bargaining/cooperative game分类
信息技术与安全科学引用本文复制引用
胡亚春,窦震海,张志一,于润泽,陈佳佳,尹文良..基于分布鲁棒和改进纳什谈判的多微网-共享储能运行优化策略[J].电力建设,2024,45(7):100-112,13.基金项目
This work is supported by the National Natural Science Foundation of China(No.52005306)and the Natural Science Foundation of Shandong Province(No.ZR2020QE220). 国家自然科学基金项目(52005306) （No.52005306）
山东省自然科学基金项目(ZR2020QE220) （ZR2020QE220）
