A novel approach to electrical load forecasting based on a neural network
Dipti Srinivasan, A.C. Liew, J.S.P. Chen · 1991
The authors demonstrate how an artificial neural network can be used to forecast electrical load demand. This network is based on the nonstatistical neural paradigm, backpropagation, which is found to be effective for accurate forecasting of electrical load. The major advantage of using an artificial neural network as opposed to other techniques for electrical load forecasting is that the network produces an immediate decision with minimal computation for the given input data, whereas classical techniques require complex mathematical calculations to predict future load values. The performance of the proposed network has been compared to that of some traditional methods of load forecasting and the results have shown the superiority of this approach.>