Agent-based Optimization to Estimate Nash Equilibrium in Power Markets
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Date
2013
Authors
Valenzuela, Jorge
Journal Title
Journal ISSN
Volume Title
Publisher
Taylor & Francis Inc
Open Access Color
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Abstract
In most deregulated power markets firms bid daily into a day-ahead power market. The auction mechanism supply and demand determine the equilibrium at each hour. In this environment firms aim to maximize their revenues by carefully determining their bids. This requires the development of effective computational methods that help them estimate their competitors' behaviors under incomplete information. In this article an agent-based method that uses particle swarm optimization is described to simulate the behavior of market participants. Particle swarm optimization is used in the bidding process and an agent-based model is applied to find a Nash equilibrium. Different stopping conditions are used to determine the equilibrium. Experimental results are presented for two power systems.
Description
Keywords
Agent-based modeling and simulation, Electricity price, Equilibrium, Particle swarm optimization (PSO), Power markets, Strategic bidding
Turkish CoHE Thesis Center URL
Fields of Science
Citation
4
WoS Q
N/A
Scopus Q
Q1
Source
Volume
8
Issue
2
Start Page
209
End Page
216