Previsão da demanda de energia elétrica utilizando lógica fuzzy e função de autocorrelação estendida- um estudo de caso aplicado ao Estado de Rondônia

Abstract

The study of demand forecast correlated to time series of electric energy develops an optimization process for the supply of electricity, with the objective of improving the forecasting routine. In this study, it is presented a comparison of three autoregressive models used for the mentioned optimization, with the fuzzy logic model, dimensioned through the extended autocorrelation function. The electric energy consumption data presents a seasonal time series structure, provoking a historical cut with the electric power consumption characteristics of the State of Rondônia, and in this object was implemented a methodology of prediction by means of already sedimented models and in comparison to a new model, presented in Fuzzy Identification Methods for Autoregressive Models Using the Extended Autocorrelation Function. The performance of the models and application for short-term electricity demand forecasting, 5 (five) five business days of the week, was analyzed for the purpose of contracting electric energy packages with the electricity distribution concessionaires, in compliance with the legislation current agreement on auctions and purchase agreements. In the course of the work, we analyzed the results of electric energy prediction, by the models presented, the proposed model in Fuzzy System related to Extended Autocorrelation, being the most satisfactory one confirmed by errors of forecast in relation to the demand of electric power for the State of Rondônia, and complying with legislation on forecasting and demand of electric energy in Brazil.