Electric energy load forecasting using anfis and arma methods [Anfis ve arma modelleri• i•le elektri•k enerji•si• yük tahmi•ni•]

Abstract

Electricity power is one of the needs of people to be able to live a contemporary life and for his well-being. In order for this need to be met, it is vital that electricity is produced enough and in good quality. It is necessary to predict the need of electricity beforehand, and thereby deciding on the generation of it. In this study, of the prediction methods, Regression, ANFIS, and ARMA have been used to assess the results obtained and the most successful method in the prediction of electricity demand has been determined. Fuuzy Logic and Neural Networks toolboxes of Matlab 7.04 for ANFIS medel and SPSS 15 for ARMA model were used respectively. In this study, Gross National Product, Produced Energy, Consumed Energy, Population and I•nstalled Capacity data have been used in the prediction of the consumed electricity between the years 1970-2007. ANFIS and ARMA models have been used and thus the energy demands between 2006-2010 have been predicted. The results obtained by ANFIS and ARMA models were compared and some suggestions were presented.