Cooperative reinforcement learning algorithm to distributed power system based on Multi-Agent

Author

Gao, La-Mei ; Zeng, Jun ; Wu, Jie ; Li, Min

Author_Institution

Coll. of Electr. Power, South China Univ. of Technol., Guangzhou, China

fYear

2009

fDate

20-22 May 2009

Firstpage

1

Lastpage

4

Abstract

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.

Keywords

distributed power generation; energy management systems; learning (artificial intelligence); multi-agent systems; photovoltaic power systems; wind power plants; cooperative reinforcement learning algorithm; distributed power system; distributed wind-PV power system; energy management; multiagent systems; renewable energy technology; Educational institutions; Energy management; Learning; Medical services; Power electronics; Power system protection; Power system security; Power systems; Renewable energy resources; Wind; Q-learning; distributed power; joint action learning; multi-agent; reinforcement learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Electronics Systems and Applications, 2009. PESA 2009. 3rd International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-3845-7

Type

conf

Filename

5228583