Investigation of Weather Impact on Electric Load Power Forecasting based on Cascade Forward Neural Network Technique

Electric Load Power Load Forecasting (ELPF) is an important activity in any power distribution utilities. Most of the literatures debates that an Artificial Neural Network (ANN) based load forecasting technique always yields a higher accuracy as related to traditional statistical learning and regression techniques especially in short term load forecasting. Hence one such ANN i.e. cascade forward neural network (CFNN)-based technique is attempted here in this paper. This paper mainly deals with study the impact of weather in ELPF models developed using CFNN in a day-ahead time horizon.