Q-learning Algorithm Based Multi-Agent Coordinated Control Method for Microgrids

被引：0

作者：

Xi, Yuanyuan ^{[1
]}

Chang, Liuchen ^{[2
]}

Mao, Meiqin ^{[1
]}

Jin, Peng ^{[1
]}

Hatziargyriou, Nikos ^{[3
]}

Xu, Haibo ^{[4
]}

机构：

[1] Hefei Univ Technol, Res Ctr Photovolta Syst Engn, Hefei, Peoples R China

[2] Univ New Brunswick, Dept Elect & Comp Engn, Fredericton, NB, Canada

[3] Natl Tech Univ Athens, Dept Elect & Comp Engn, Zografos, Greece

[4] GuangDong EAST Power Co Ltd, Dongguan, Peoples R China

来源：

2015 9TH INTERNATIONAL CONFERENCE ON POWER ELECTRONICS AND ECCE ASIA (ICPE-ECCE ASIA) | 2015年

关键词：

coordinated control; microgrid; MultiAgent; Q-learning;

D O I：

暂无

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：

This paper proposes a Q-learning algorithm (Q-LA) based multi-agent coordinated control method for microgrids. By the method, Q-LA is adopted to calculate the power to be regulated, which is called the microgrid regulation error (MRE), in secondary control for real-time operation. And the generation schedule of distributed generators (DGs) as well as batteries is modified in real time with the MRE by the fuzzy theory and particle swarm optimization method, taking the economy and environmental benefits into consideration together. The simulation platform of Q-LA based multi-agent hybrid energy management system for microgrid (HEMS-MG) is established in C++ Builder. The simulation results verify the effectiveness and feasibility of the proposed method.

引用

页码：1497 / 1504

页数：8

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