Short Term Load Forecasting using Neuro-Fuzzy Networks

M. Hoffman, A. Hasan, and D. Martinez (USA)

Keywords

Load forecasting, neurofuzzy network, intelligent control, power systems.

Abstract

: The paper presents the development of a neuro-fuzzy network based short-term load forecasting system for the power utility. The proposed method was designed and implemented using MATLAB software and tested using real utility data. The network forecasted day-ahead load with a Mean Absolute Percent Error (MAPE) of about 3% for no temperature forecast error and about 5% MAPE for 10% temperature forecast error.

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