Optimal Bidding Strategies using New Aggregated Demand Model with Particle Swarm Optimization Technique

In this paper, Particle Swarm optimization(PSO) and Artificial Bee Colony (ABC) algorithms are 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 minimize the associadted risks of the system. Themarket includes generating companies(Gencos) and large Consumers. The demand prediction of the system has been 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. The fitness of the system compared with PSO and ABC technique, the maximized fitness is the optimal bidding strategy of the system . The results for two techniques will be analyzed in this paper. The implementation of the two techniques could be implemented in theMATLAB Platform.