A Hybrid Modelling Technique for Load Forecasting

This paper presents a comparative study of soft computing models namely; multilayer perceptron networks, partial recurrent neural networks, radial basis function network, fuzzy inference system and hybrid fuzzy neural network for the hourly electricity demand forecast in Northern Ireland. The soft computing models were trained and tested using the actual hourly load data. A comparison of the proposed techniques is presented for predicting a 48 hour horizon demand for electricity. Simulation results indicate that hybrid fuzzy neural network and radial basis function networks are the best candidates for the analysis and forecasting of electricity demand.