Automatic Integrated System Load Forecasting Using Mutual Information and Neural Networks

Abstract

This paper describes a novel application of ANNs for electrical load forecasting. The production of a forecast is divided into two phases: Self Organising Feature Maps are used to mine the available data, identifying measurements relevant to the forecast. These measurements are then used to train a Multi Layer Perceptron to provide load forecasts. The resultant non-linear forecaster is compared with a similar, but linear system employing multivariate linear regression and results are presented.