A Novel Short-Term Load Forecasting Technique Using Wavelet Transform Analysis

This paper proposes a novel wavelet transform-based technique for short-time load forecasting of weather-sensitive loads. In this paper, Daubechies D2, D4, and D10 wavelet transforms are adopted to predict short-term loads, and the numerical results reveal that certain wavelet components can effectively be used to identify the load characteristics in electric power systems. The wavelet coefficients associated with certain frequency and time localization are adjusted using the conventional multiple regression method and then reconstructed in order to forecast the final loads through a three-scale synthesis technique. The outcome of the study clearly indicates that the proposed wavelet transform approach can be used as an attractive and effective means for short-term load forecasting.