ANN and SVM forecasting models need large sample data, and the traditional time series forecasting model cannot fit sufficiently the biggest load due to random factors. And in order to overcome the shortcomings as mentioned, this paper applied the season-multiplicative model in time series to forecast the monthly peak load of region, and adopted the GARCH model to modify the forecasting error. The application results of the proposed model in a regional power grid show that the forecasting is precise, because the error rate is only 2%. And compared with the unmodified model, the new model’s error rate decreased by 0.5%.