Cooperative Reinforcement Learning Algorithm to Distributed Power System Based on Multi-Agent

被引：0

作者：

Gao, La-mei ^{[1
]}

Zeng, Jun ^{[1
]}

Wu, Jie ^{[1
]}

Li, Min ^{[1
]}

机构：

[1] S China Univ Technol, Coll Elect Power, Guangzhou 510640, Guangdong, Peoples R China

来源：

2009 3RD INTERNATIONAL CONFERENCE ON POWER ELECTRONICS SYSTEMS AND APPLICATIONS: ELECTRIC VEHICLE AND GREEN ENERGY | 2009年

关键词：

distributed power; multi-agent; reinforcement learning; Q-learning; joint action learning;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

With the development of renewable energy technology, the distributed wind-PV power system has a wider application. This paper proposes a distributed wind-PV power system based on Multi-Agent, whose main character is energy management, and describes the multi-agent cooperative reinforcement learning process using the joint action learning pattern as the cooperative strategy. The experiment of a distributed wind-PV power system shows the efficiency.

引用

页码：53 / 53

页数：1