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

• Grant number: 07/01023-3
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: June 01, 2007
• End date: May 31, 2008
• Field of knowledge: Engineering - Electrical Engineering - Power Systems
• Principal Investigator: Anna Diva Plasencia Lotufo
• Grantee: Jorge Luiz Yoshito Maeda
• Host 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.