An Agent-Based Computational Laboratory for Wholesale Power Market Design
Tesfatsion, Leigh S.
This study reports on the model development and open-source implementation (in Java) of an agent-based computational wholesale power market organized in accordance with core FERC-recommended design features and operating over a realistically rendered transmission grid subject to congestion effects. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Market power findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. Related work can be accessed at: http://www.econ.iastate.edu/tesfatsi/AMESMarketHome.htm
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