Deregulated power system load forecasting using artificial intelligence

Electricity market demands to the power industry in de-regulated form in this paper. The proposed load forecasting using ANN shows the effective risk management plans. This power market is to maintain their effective cost in terms of energy generation, energy purchase and optimization of the switching losses. This creates the need of load forecasting. So in this paper the load forecasting using ANN is introduced to many applications in serial approach. Two types of ANN algorithms for training have been proposed explore the importance of each. The forecasting provides when the weather factors also represented in the training data. The simulation results shown that model is also of producing reasonable accurate power system load forecasting. The combination of RBFNN and BPNN is used as effective tools and shown that RBFNN method is good method than BPNN for STLF.