IEEJ Transactions on Power and Energy
Online ISSN : 1348-8147
Print ISSN : 0385-4213
ISSN-L : 0385-4213
Paper
RPS Market Analysis Based on Reinforcement Learning in Power Systems
Takanori SuganoHiroyuki KitaEiichi TanakaJun Hasegawa
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JOURNAL FREE ACCESS

2006 Volume 126 Issue 2 Pages 217-224

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Abstract
Deregulation and restructuring of electric power supply business are proceeding all over the world. In many cases, a competitive environment is introduced, where a market to transact electric power is established, and various attempts are done to decrease the price. On the other hand, environmental problems are pointed out in recent years. However, there is a possibility of the environmental deterioration by cost reduction of electric power. In this paper, the RPS (Renewable Portfolio Standard) system is taken up as the solution method of environmental problem under the deregulation of electric power supply business. A RPS model is created by multi-agent theory, where Q-learning is used as a decision-making technique of agent. By using this model, the RPS system is verified for its effectiveness and influence.
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© 2006 by the Institute of Electrical Engineers of Japan
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