Price Forecast of Power Grid Equipment Based on EEMD-SVM Model

As the price of power grid equipment is nonlinear and non-stable, which leads to big difficulty and low accuracy of forecast, the model of ensemble empirical mode decomposition (EEMD) and support vector machine (SVM) has been built. The empirical mode decomposition (EMD) is improved by EEMD. The history price is divided into several smooth and periodically fluctuated components by EEMD, which is used to forecast with SVM as an input. Finally, the superposition value of forecasted components has been gained as the predictive value of price. Taking the history data of 220 kVA column circuit breaker as samples, the prediction results of EMD-SVM and EEMD-SVM are compared and the errors are analyzed. The results show that the prediction accuracy of EEMD-SVM is better than that of EMD-SVM, which can make references to project cost control and equipment bidding to some extent.