Soft computing based techniques for short-tem load forecasting

摘要

Neural networks are currently finding practical applications, ranging form 'soft' regulatory control in consumer products to accurate modelling of non-linear systems. This paper presents the development of improved neural networks based short-term electric load forecasting models for the power system of the Greek Island of Crete. Several approaches including radial basis function networks, dynamic neural networks have been considered. In addition, a novel approach, based on neural-fuzzy approach has been proposed and discussed in this paper.