计及气象因素时间累积效应的输电线路覆冰预测

现有基于机理的覆冰预测模型考虑因素众多,结构复杂,但仍存在预测误差。基于统计回归的覆冰预测模型则较少考虑时间累积效应,与实际情况亦有出入。因此提出了计及气象因素时间累积效应的输电线路覆冰预测模型。建立了气象因素下的覆冰厚度增长简易模型,分析了覆冰厚度随时间增长的关系。并进一步考虑不同气象因素对覆冰增长的影响,构建不同气象因素覆冰厚度增长程度指标。利用历史气象数据计算该指标并与覆冰厚度监测值组成训练集,采取SVM回归方法实现对覆冰情况的预测。通过算例对现有各方法与所提方法进行了对比,验证了该预测模型在精度等方面的优势。

Transmission line icing forecast considering the time cumulative effect of meteorological factors

Icing forecast theoretical models in existence consider so many factors and have very complicated structures, but they still have errors in forecasting. Meanwhile, icing forecast models based on regression methods think less about time cumulative effect, thus the forecasting results are still different with the real conditions. On the basis of the review of nowadays icing forecast models, a transmission line icing forecast model considering the time cumulative effect of meteorological factors is proposed in this paper. Based on the built icing thickness growth model, the relationship of icing thickness and time is analyzed. According to the analysis result and the influence of various meteorological factors on icing growth, the degree of icing growth under different meteorological factors is given. The degree can be calculated by historical meteorological data and together with historical icing thickness data, it can be used to train SVM regression forecasting model to forecast icing thickness. The proposed model is validated through a case analysis and demonstrated to have the forecasting precise advantage over typical icing forecast models in existence. This work is supported by National Natural Science Foundation of China (No. 51707018), China Postdoctoral Science Foundation (No. 2017M612907), and State Grid Xinjiang Electric Power Co., Ltd. (No. 5230DK16001P).