Short Term Load Forecasting using Neural Network trained with Genetic Algorithm

Abstract

A computationally efficient artificial neural network for the purpose of short term load forecasting is proposed. The major drawback of feed forward neural networks such as a multilayer perceptron (MLP) or dynamic neural network such as Hopfield, Elman, MFLNN trained with back propagation algorithm is that it requires a large amount of computation for learning. We propose a three-layer multi layer neural network trained with genetic algorithm in which the need for computationally intensive back propagation is eliminated. The results of which are better than a MLP trained by back propagation algorithm, which require more number of hidden neurons. The whole project is carried out for Orissa Power Transmission Corporation Limited, taking into the load data of Orissa.