In this paper, the problem of building optimally coordinated bidding strategies for competitive suppliers in day-ahead energy and spinning reserve markets is addressed. It is assumed that each supplier bids 24 linear energy supply functions and 24 linear spinning reserve supply functions, one for each hour, into the energy and spinning reserve markets, respectively, and each market is cleared separately and simultaneously for all the 24 delivery hours. Each supplier makes decisions on unit commitment and chooses the coefficients in the linear energy and spinning reserve supply functions to maximise total benefits, subject to expectations about how rival suppliers will bid in both markets. Two different bidding schemes have been suggested for each hour, and based on them an overall coordinated bidding strategy in the day-ahead energy and spinning reserve market is then developed. Stochastic optimisation models are first developed to describe these two different bidding schemes and a genetic algorithm (GA) is then used to build the optimally coordinated bidding strategies for each scheme and to develop an overall bidding strategy for the day-ahead energy and spinning reserve markets. A numerical example is utilised to illustrate the essential features of the method.
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