Title :
Implication of different pricing rules on generators´ bidding behaviour
Author :
Sugianto, Ly-Fie ; Liao, Zhigang
Author_Institution :
Fac. of Bus. & Econ., Monash Univ., Clayton, VIC, Australia
Abstract :
This paper presents an agent-based model to examine the employment of different pricing rules, namely the Uniform pricing rule and Pay-as-bid pricing rule. Using Q-learning in repetitive trading process, generator agents learn the market characteristics and seek to maximize their revenue by exploring bidding strategies. Supply quantity withholding and generators´ collusion phenomenon have been observed in this study under certain market arrangements. The implication of different pricing rules on the total dispatch costs and generators´ profit are discussed in this paper.
Keywords :
learning (artificial intelligence); power markets; power system simulation; pricing; Q-learning; agent-based model; dispatch costs; generator profit; generators bidding behaviour; generators collusion phenomenon; pay-as-bid pricing rule; supply quantity withholding; uniform pricing rule; Conferences; Economics; Electricity; Electricity supply industry; Generators; ISO; Pricing; Q-Learning; agent-based model; auction market; pricing rules;
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2011 6th IEEE Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-8754-7
Electronic_ISBN :
pending
DOI :
10.1109/ICIEA.2011.5975999