JCC  Vol.3 No.11 , November 2015
Short-Term Load Forecasting Using Radial Basis Function Neural Network
Author(s) Wen-Yeau Chang
Abstract

An accurate short-term forecasting method for load of electric power system can help the electric power system’s operator to reduce the risk of unreliability of electricity supply. This paper proposed a radial basis function (RBF) neural network method to forecast the short-term load of electric power system. To demonstrate the effectiveness of the proposed method, the method is tested on the practical load data information of the Tai power system. The good agreements between the realistic values and forecasting values are obtained; the numerical results show that the proposed forecasting method is accurate and reliable.


Cite this paper
Chang, W. (2015) Short-Term Load Forecasting Using Radial Basis Function Neural Network. Journal of Computer and Communications, 3, 40-45. doi: 10.4236/jcc.2015.311007.
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