Title: Multi-objective bidding strategy for GenCo using non-dominated sorting particle swarm optimisation
Authors: Weerakorn Ongsakul; Apinat Saksinchai; Chanwit Boonchuay
Addresses: Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani, 12120, Thailand. ' Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani, 12120, Thailand. ' Department of Electrical Engineering Technology, Rajamangala University of Technology Rattanakosin, Petchkasem Rd., Nongkea, Hua Hin, Prachuap Khiri Khan, 77110, Thailand
Abstract: This paper proposes a multi-objective bidding strategy for a generation company (GenCo) in a day-ahead uniform price spot market using non-dominated sorting particle swarm optimisation (NSPSO). NSPSO is introduced to solve the multi-objective strategic bidding problem considering expected profit maximisation and risk (profit variation) minimisation. Monte Carlo (MC) simulation is employed to simulate rivals| bidding behaviour. Test results indicate that the proposed approach can provide an efficient non-dominated solution front. In addition, it can be efficiently used as a decision-making tool for a GenCo compromising between expected profit and the risk of profit variation in a spot market.
Keywords: optimal bidding strategies; NSPSO; non-dominated sorting particle swarm optimisation; Monte Carlo simulation; multi-objective strategies; generation companies; day-ahead prices; uniform prices; spot markets; profit maximisation; risk minimisation; profit variation; bidding behaviour; non-dominated solutions; decision-making; expected profits; electricity generation; applied decision sciences.
International Journal of Applied Decision Sciences, 2011 Vol.4 No.4, pp.305 - 323
Published online: 29 Sep 2014 *Full-text access for editors Access for subscribers Purchase this article Comment on this article