Dk. Ranaweera et al., APPLICATION OF RADIAL BASIS FUNCTION NEURAL-NETWORK MODEL FOR SHORT-TERM LOAD FORECASTING, IEE proceedings. Generation, transmission and distribution, 142(1), 1995, pp. 45-50
A description and original application of a type of neural network, ca
lled the radial basis function network (RBFN), to the short-term syste
m load forecasting (SLF) problem is presented. The predictive capabili
ty of the RBFN models and their ability to produce accurate measures t
hat can be used to estimate confidence intervals for the short-term fo
recasts are illustrated, and an indication of the reliability of the c
alculations is given. Performance results are given for daily peak and
total load forecasts for one year using data from a large-scale power
system. A comparison between results from the RBFN model and the Back
-propagation neural network are also presented.