季节划分下产业用电量关联分析及预测

产业用电需求预测对于实现精细化用电管理、降低电力企业运行与规划成本具有十分重要的意义。鉴于常见的预测方法在产业结构划分下的中短期用电量预测中效果不佳，分析了不同季节下产业用电量之间内在关联关系以及气温对其的外在影响，结合计量经济学思想，分季节构建了用于电量预测的误差修正模型，并利用该模型对华中某省网月度用电量进行了预测分析，结果表明，该模型具有较高的预测精度。

Correlation Analysis and Forecast on Industrial Electricity Demands Based on Seasonal Divisions

The forecasting of industrial electricity demand has a vital significance for realizing the refined power consumption management and reducing the cost of electric power enterprises operation and planning. However, the conventional forecasting methods, which forecast the electricity demands in the medium-term under the division of industrial structure, can’t provide satisfied results. In this paper, the correlative relationship between industrial electricity demands and forecasting methods is analyzed according to different seasons, and the external influence of temperature is discussed. In addition, on the basis of the aforementioned analysis and the econometrics theory, an error correction model is established in seasonal divisions for forecasting electricity demand. Finally, the monthly electricity demands of one province in the central China is forecasted and analyzed by using the correction model, and the results proves the feasibility of the method and shows the promised accuracy.