Robust game-theoretic optimization for energy management in community-based energy system

被引：5
|
作者：
Liu, Xiaofeng [1 ]
Ji, Zhenya [1 ]
Sun, Wangqing [1 ]
He, Qinman [1 ]
机构：
[1] Nanjing Normal Univ, Sch Elect & Automation Engn, Nanjing 210046, Peoples R China
来源：
ELECTRIC POWER SYSTEMS RESEARCH | 2023年 / 214卷
基金：
中国国家自然科学基金;
关键词：
Community -based energy system; Robust game -theoretic optimization; Demand response; Uncertainty; GENERATION;
D O I：
10.1016/j.epsr.2022.108939
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
It is significant to schedule energy consumption in community-based energy system consisting of distributed generation, energy storage, multi-community. In this paper, a robust game-theoretic approach is proposed to optimize the storage capacity and energy consumption considering the uncertainty of distributed generation. Energy management with energy storage optimization is studied by considering the cost of distributed genera-tions, cost of energy storage, and bidirectional energy trading. In order to search the robust solution for Nash equilibrium and optimal storage capacity, a distributed algorithm combining column and constraint generation and particle swarm optimization is designed. Simulation results show that the proposed approach has a well performance in reducing operation cost of energy system and tackling the uncertainty of distributed generation.
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收藏
页数：13
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