Title :
Agent-based retail electricity market: modeling and analysis
Author :
Yu, Jing ; Zhou, Jian-zhong ; Yang, Junjie ; Wu, Wei ; Fu, Bo ; Liao, Rong-Tao
Author_Institution :
Dept. of Hydropower & Information Eng., Huazhong Univ. of Sci. & Technol., Hubei, China
Abstract :
In the past decades, power systems in the whole world have been facing pressure to be deregulated or restructured. This research has designed an agent-based retail electricity market to simulate the trading procedure in modern power systems, and utilize colored Petri nets technology to present the communications and cooperation of agents in the market. We design four kinds of participant agents: power exchanger agent (PXA), power user agents (PUAs), retail company agents (RCAs) and independent power plant agents (IPPAs). PXA is supervisor of the marketplace, in charge of opening and closing the market, and dealing with the trading request from the other agents, avoiding conflicts with constraints of power transmission grids. The other three kinds of agents could enter the marketplace arbitrary if it opens and freely select their satisfied consumers/providers, which are the chief distinctions of our design. The results of analysis show that the proposed retail electricity market could increase efficiency, reduce operational costs and give consumers more alternatives. Though it has more latently conflicts and concurrencies, which cause a little complication, we successfully deal with them by colored Petri nets.
Keywords :
Petri nets; mobile agents; power engineering computing; power markets; power transmission; retailing; agent-based retail electricity market; colored Petri nets; independent power plant agents; power exchanger agent; power systems; power transmission grids; power user agents; retail company agents; Concurrent computing; Costs; Electricity supply industry; Electricity supply industry deregulation; Petri nets; Power generation; Power system analysis computing; Power system modeling; Power system simulation; Power transmission;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1380618