基于Hausdorff形状分类的配电网日最大负荷预测

日最大负荷及其出现时刻的准确预测是配电网经济调度与安全运行的重点关注对象。研究了各类型负荷日最大值及其出现时刻的内在规律,提出了一种联合Hausdorff负荷形状分类与去年同期节假日修正的日最大负荷及其出现时刻预测方法。首先,分析日负荷形状特性,通过Hausdorff距离算法对负荷类型进行分类。然后,分析去年同期节假日在日最大负荷及其出现时刻预测中的修正作用,并将其与近期日负荷、气温等数据一同作为预测输入。最后,基于ElasticNet线性回归算法对每类负荷单独构建日最大负荷及其出现时刻预测模型。以湖南某台区负荷数据为实例,预测该台区春节期间的日最大负荷及出现时刻,该方法的准确性与有效性在实例中得到验证。

Forecast of Daily Maximum Load of Distribution Network Based on Hausdorff Shape Classification

The accurate prediction of daily maximum load and its occurrence time are the focus of economic dispatch and safe operation of distribution network. This paper studies the internal law of daily maximum value and its occurrence time of various types of load, and proposes a forecasting method of daily maximum load and its occurrence time combined with Hausdorff load shape classification and holiday correction in the same period of last year. Firstly, the shape characteristics of daily load are analyzed, and the load types are classified by Hausdorff distance algorithm. Then, the correction effect of holidays in the same period of last year in the prediction of daily maximum load and its occurrence time are analyzed, and it is used as the forecast input together with the recent daily load, temperature and other data. Finally, based on ElasticNet regression algorithm, the daily maximum load and its occurrence time prediction model are constructed for each type of load. Taking the load data of a certain station area in Hunan province as an example, the daily maximum load and its occurrence time in the Spring Festival of the station area are predicted and the accuracy and effectiveness of the method are verified in an example.