一种基于用电行业分类的中长期电量预测方法

针对传统中长期电量预测方法思路单一,忽视不同层次电量预测之间的内在联系而影响中长期电量预测精度的问题,提出了一种基于用电行业分类的新型中长期电量预测方法。首先,设计了适用于电量预测的用电行业分类原则和方法;然后,以8种特性互补的预测方法为基础,建立优选组合预测模型,对待预测区域整体以及各用电行业的电量需求分别进行年度和季度的预测;最后,运用多级预测协调理论建立了一个二维二级协调模型,对上一步的电量预测值进行修正,改善预测精度,得到上下级统一的区域整体以及各行业未来年度和季度的电量预测值。以实际的电量数据进行了算例分析,验证了该方法的有效性。

A Medium and Long-term Electricity Demand Forecasting Method Based on Industry Classification

As to the problem that the accuracy of medium and long-term electricity demand forecasting is affected by such factors as the singleness of traditional method and the weak inner link between different power prediction levels, a new medium and long-term electricity demand forecasting method is proposed based on industry classification. Firstly, electricity industry classification principles and methods are designed. Then, an appropriate optimized combination prediction model is built to forecast annual and quarterly electricity demand of the predicted district and its electricity consuming industries based on eight basic complementary predicting methods. Finally, a two-dimension and two-level coordinated model is designed based on multilevel forecasting and coordinated principle to correct the predicted value, to improve the predicting accuracy, and to obtain future annual and quarterly electricity demand of whole district and each industry. The actual data is used to test the effectiveness of the proposed method.