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Electric load forecasting through a radial basis function (RBF) neural network using MATLAB toolboxes

Grant number: 07/01023-3
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): June 01, 2007
Effective date (End): May 31, 2008
Field of knowledge:Engineering - Electrical Engineering - Power Systems
Principal researcher:Anna Diva Plasencia Lotufo
Grantee:Jorge Luiz Yoshito Maeda
Home Institution: Faculdade de Engenharia (FEIS). Universidade Estadual Paulista (UNESP). Campus de Ilha Solteira. Ilha Solteira , SP, Brazil

Abstract

Load Forecasting is a very important function for power system planning. The traditional statistic methods like ARIMA of Box Jenkins no more are interesting since Neural networks applications can be very useful to predict load forecasting. This work is going to use a RBF (Radial Basis Function) using toolboxes of MATLAB with data of a Brazilian electrical company to predict load forecasting.

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