Aplicação da transformada wavelet discreta na previsão de carga a curto prazo via redes neurais.

Abstract

The importance of short-termload forecasting has been in-creasing lately. With deregulation and competition, energy price forecasting has become a big business. Bus-loadfore-castingis essential to feed analytical methods utilized for de- termining energy prices. The variability and non-stationarity of loads are be coming worse due to the dynamics of energy prices. Besides, the number of nodal loads to be predicted does notal low frequent interventions from load forecasting experts. More autonomous load predictors are needed in the new competitive scenario. This paper proposes novel wavelet transform-based technique for short-term load fore-casting via neural networks. Its main goal is to develop more robust load forecasters. Two whole years of load data from a North-American electric utility has been used in order to test The proposed methodology