Medium\|and\|long\|term Forecasting of Beijing Electric Demand Based on Error Adjustment

Medium\|and\|long\|term forecasting of electric load is the essential to power systems planning. Based on the factor decomposition of GDP, a nonlinear forecasting model of electricity demand, which can describe the relationship between electricity demand and economical social development, is built based on population, urbanization, economical development and industrial structure adjustment. Due to the special concern on electricity demand in the next year, the GARCH model is adopted to reduce errors caused by regression forecasting technique, which shows its effectiveness on forecasting medium\|and\|long\|term electric demand in Beijing. Then the forecast model of relative self\|variable is built. By comparison of initial forecasting value with that of with corrected forecasting value, the proposed method is verified to have high accuracy. The proposed approach could also be extended to other research area related to energy systems planning.