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Agent-Based Simulation of Power Markets under Uniform and Pay-as-Bid Pricing Rules using Reinforcement Learning

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2 Author(s)
Bakirtzis, A.G. ; Dept. of Electr. & Comput. Eng., Aristotelian Univ. of Thessaloniki ; Tellidou, A.C.

In this paper agent-based simulation is employed to study the power market operation under two alternative pricing systems: uniform and discriminatory (pay-as-bid). Power suppliers are modeled as adaptive agents capable of learning through the interaction with their environment, following a reinforcement learning algorithm. The SA-Q-learning algorithm, a slightly changed version of the popular Q-Learning, is used in this paper; it proposes a solution to the difficult problem of the balance between exploration and exploitation and it has been chosen for its quick convergence. A test system with five supplier-agents is used to study the suppliers' behavior under the uniform and the pay-as-bid pricing systems

Published in:

Power Systems Conference and Exposition, 2006. PSCE '06. 2006 IEEE PES

Date of Conference:

Oct. 29 2006-Nov. 1 2006