Modeling of suppliers' learning Behaviors in an electricity market environment

被引：0

作者：

Yu, Nanpeng ^{[1
]}

Liu, Chen-Ching ^{[1
]}

Tesfatsion, Leigh ^{[2
]}

机构：

[1] Iowa State Univ, Dept Elect & Comp Engn, Ames, IA 50010 USA

[2] Iowa State Univ, Dept Econ, Ames, IA 50010 USA

来源：

2007 INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS APPLICATIONS TO POWER SYSTEMS, VOLS 1 AND 2 | 2007年

关键词：

electricity market; supplier Modeling; competitive Markov decision process; Q-learning;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The Day-Ahead electricity market is modeled as a multi-agent system with interacting agents including supplier agents, Load Serving Entities, and a Market Operator. Simulation of the market clearing results under the scenario in which agents have learning capabilities is compared with the scenario where agents report true marginal costs. It is shown that, with Q-Learning, electricity suppliers are making more profits compared to the scenario without learning due to strategic gaming. As a result, the LMP at each bus is substantially higher.

引用

页码：24 / +

页数：2

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