Application of Improved Gray Verhulst Model in Middle and Long Term Load Forecasting

According to such features in middle and long term load forecasting as small samples,poor information,uncertainty and nonlinearity,an improved Verhulst model based on least square-support vector machine (LS-SVM) algorithm and equal-dimension and new-information technique is built and applied to the middle and long term load forecasting for load growth in S-type or load growth being saturated. The parameters of the model are evalutated by LS- SVM algorithm and the load data is forecasted by equal- dimension and new-information addition prediction. Case study results show that the relative errors of forecasting results by the proposed modes are less than 3%,thus in comparison with traditional forecasting models,the proposed model can offer more accurate forecasting results.