Comparison of day-ahead price forecasting in energy market using Neural Network and Genetic Algorithm

Abstract

Price prognostication has become progressively relevant to producers and shoppers within the new competitive wattage markets. Both for spot markets and long term contractors, value forecasts square measure necessary to develop bidding ways. In this paper, Genetic Algorithm based Neural network (GANN) approach is used to forecast short term hourly electricity price and the results are compared with Aritificial Neural Network(ANN). The recommended method is studied on the PJM electricity market. The results achieved through the simulation illustrates that the proposed model offers exact and improved results.