Abstract
The problem of building optimal bidding strategies for competitive suppliers in a day-ahead energy market is addressed in this paper. It is assumed that each supplier bids 24 linear energy supply functions, one for each hour, into the day-ahead energy market, and the market is cleared separately and simultaneously for all the delivery hours. Each supplier makes decisions on unit commitment and chooses the coefficients in the linear energy supply functions to maximize total benefits in the schedule day, subject to expectations about how rival suppliers will bid. Two different bidding schemes, namely ‘maximum hourly-benefit bidding strategies’ and ‘minimum stable output bidding strategies’, have been suggested for each hour, and based on these two schemes an overall bidding strategy in the day-ahead market can then be developed. Stochastic optimization models are first developed to describe these two different bidding schemes and a genetic algorithm based method is then presented to develop an overall bidding strategy for the day-ahead market. A numerical example is utilized to illustrate the essential features of the method.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.