Optimal Bidding Strategies Using New Aggregated Demand Model with Artificial Bee Colony (ABC) Technique

摘要

In this paper Artificial Bee Colony (ABC) algorithm is used to determine the optimal bidding strategy in competitive auction market implementation. The deregulated power industry meets the challenges of increase their profits and also minimizing the associadted risks of the system. The market includes generating companies (Gencos) and large Consumers. The demand prediction of the system is determined by the neural network, which is trained by using the previous day demand dataset, the training process is achieved by the back propagation algorithm. Test results indicate that the proposed algorithm converge much faster and more reliable than Genetic Algorithm (GA). The ABC technique could be implemented in the MATLAB Platform.