New bidding strategy formulation for day-ahead energy and reserve markets based on evolutionary programming

In this paper, a new bidding strategy for a day-ahead market is formulated. The proposed algorithm is developed from the viewpoint of a generation company wishing to maximize a profit as a participant in the deregulated power and reserve markets. Separate power and reserve markets are considered, both are operated by clearing price auction system. The optimal bidding parameters for both markets are determined by solving an optimization problem that takes unit commitment constraints such as generating limits and unit minimum up/down time constraints into account. This is a non-convex and non-differentiable which is difficult to solve by traditional optimization techniques. In this paper, evolutionary programming is used to solve the problem. The algorithm is applied to both single-sided and double-sided auctions, numerical simulations are carried out to demonstrate the performance of the proposed scheme compared with those obtained from a sequential quadratic programming.