Study on Application of Fast Intrinsic Mode Decomposition to Short-Term Load Forecasting

Abstract

The forecasting technique is one of the key factors for load forecasting. According to analysis, the Fast Intrinsic Mode Decomposition (FIMD) method is applied to short-term load forecasting in this paper. The specific implementation process of the proposed short-term load forecasting method is in the following. The selected load sample data are decomposed into a number of stationary Intrinsic Mode Functions (IMFs) with respective single mode by the FIMD method firstly. Then, each obtained load component with different frequency band is forecasted according to the Gene Expression Programming (GEP) method by time-sharing. The final forecasting models are obtained by rebuilding the forecasting model of each IMF. Lots of virtual forecasting tests are done, and it proves that the proposed load forecasting method based on the FIMD method in this paper is more accurate than the method based on Empirical Mode Decomposition (EMD).