南方电网技术2025，Vol.19Issue(3)：163-173,11.DOI:10.13648/j.cnki.issn1674-0629.2025.03.015
考虑置信间隙决策理论的多能微网群协同共赢优化研究
Collaborative Win-Win Optimization Study of Multi-Energy Microgrid Cluster Considering Confidence Gap Decision Theory
摘要
Abstract
In order to promote new energy consumption and low-carbon economic operation in microgrids,a multi-energy microgrid cluster model with shared energy storage power stations is constructed.Firstly,a multi-energy microgrid model with electricity,heat and gas is established,and multiple microgrids form a cooperative alliance to jointly establish shared energy storage.Secondly,acknowledging the intricate correlation and inherent unpredictability of wind and solar energy outputs,a refined multi-objective robust optimization scheduling model for the multi-energy microgrid cluster is formulated.This approach integrates Copula-multi-scenario confidence gap decision theory to attain the dual objectives of cost minimization and carbon emission reduction.Finally,considering the energy interaction contribution,risk level,and carbon reduction contribution of the members in the alliance,the benefit of the improved Shapely value method is used to quantify the contribution of each alliance subject and equitably distribute the cooperation surplus.The example results show that the proposed model reduces the total cost by 18.64%and carbon emission by 30.24%compared with the independent allocation of energy storage,and it realizes the precise matching between the comprehensive contribution of each subject to the alliance and the distribution of the cooperation surplus,so as to enhance the enthusiasm of the multi-energy microgrids to participate in the cooperation.关键词
共享储能/多能微网群/Copula/多场景置信间隙决策/改进Shapley值Key words
shared energy storage/multi-energy microgrid cluster/Copula/multi-scenario confidence gap decision/improved Shapley value分类
能源与动力引用本文复制引用
高建伟,王紫莹,孟琪琛,闫宇声..考虑置信间隙决策理论的多能微网群协同共赢优化研究[J].南方电网技术,2025,19(3):163-173,11.基金项目
国家自然科学基金资助项目(72071076).Supported by the National Natural Science Foundation of China(72071076). （72071076）
