@inproceedings{da316b3ff7fa4f16bfa08b5308edd32a,
title = "Using Q-learning to model bidding behaviour in electricity market simulation",
abstract = "While the choice between two pricing rules, namely Uniform pricing rule and Pay-as-bid pricing rule, has led to a continuous debate in the electricity market establishment process, little attention has been paid to the Vickrey pricing rule. This paper presents an agent-based model to examine the employment of Uniform and Vickrey pricing rules in a deregulated electricity market. Using Q-learning in repetitive trading process, generator agents learn the market characteristics and seek to maximise their revenue by exploring bidding strategies. A look up table is utilised to memorise agents' bidding experience that help the agents improve their strategies. Supply quantity withholding and generators' collusion phenomenon have been observed in this study under certain market arrangements. The implication of these two pricing rules on the total dispatch costs and generators' profit are discussed in this paper.",
keywords = "agent-based model, auction market, bidding behaviour, pricing rules, Q-Learning, simulation",
author = "Zhigang Liao and Sugianto, \{Ly Fie\}",
year = "2011",
month = aug,
day = "10",
doi = "10.1109/SMDCM.2011.5949267",
language = "English",
isbn = "9781612840697",
series = "IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MCDM 2011: 2011 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making",
pages = "1--7",
booktitle = "IEEE SSCI 2011 - Symposium Series on Computational Intelligence - MCDM 2011",
note = "Symposium Series on Computational Intelligence, IEEE SSCI 2011 - 2011 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making, MCDM 2011 ; Conference date: 11-04-2011 Through 15-04-2011",
}