Prediction Method for Amount of 10 kV Damaged Poles Under Severe Typhoon Environment Based on Meshing and Support Vector Machine

ZHENG Lingming; SHU Shengwen; CHEN Bin; WU Han; HUANG Jianye; QIAN Jian

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Prediction Method for Amount of 10 kV Damaged Poles Under Severe Typhoon Environment Based on Meshing and Support Vector Machine

更新时间：2025-12-08

- Prediction Method for Amount of 10 kV Damaged Poles Under Severe Typhoon Environment Based on Meshing and Support Vector Machine
- Vol. 46, Issue 1, Pages: 42-51(2020)
- 作者机构：
  
  1. 福州大学电气工程与自动化学院
  2. 国网福建省电力有限公司电力科学研究院
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published Online：31 January 2020，
  
  Published：2020
- 稿件说明：
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ZHENG Lingming, SHU Shengwen, CHEN Bin, et al. Prediction Method for Amount of 10 kV Damaged Poles Under Severe Typhoon Environment Based on Meshing and Support Vector Machine[J]. 2020, 46(1): 42-51.
DOI：

ZHENG Lingming, SHU Shengwen, CHEN Bin, et al. Prediction Method for Amount of 10 kV Damaged Poles Under Severe Typhoon Environment Based on Meshing and Support Vector Machine[J]. 2020, 46(1): 42-51. DOI：

摘要

10kV杆塔因抗风等级较低而易遭受强台风影响发生受损事故

开展10kV杆塔受损量的预测对灾前防御措施部署和抢修资源调配具有重要意义。为此

提出了一种基于格点化和支持向量机的10 kV杆塔受损量预测方法。从区域自然灾害系统论出发

构建包含致灾因子、孕灾环境和承灾体的10 kV杆塔受损影响因子特征集

并进行3 km×3 km格点化单元处理

作为支持向量机回归（support vector machine regression

SVR）模型的输入量;以格点单元内10 kV杆塔受损量作为支持向量机回归模型的输出量

建立了强台风环境下10 kV杆塔受损量预测模型。采用该模型对1614台风"莫兰蒂"期间某地区电网的10 kV杆塔受损量进行了预测

得到预测值与实际受损量达到显著相关水平

验证了方法的有效性。所提方法可为强台风环境下10 kV杆塔受损量的预测提供一条可能的途径。

Abstract

The 10 kV poles are vulnerable to severe typhoons due to the low wind-resistance

and prediction for the amount of 10 kV damaged poles is important for the deployment of preparedness plans and the allocation of emergency resources before the disaster. Consequently

we proposed a prediction method for the amount of 10 kV damaged poles under severe typhoon environment based on meshing and support vector machine. Based on the theory of regional natural disaster system

a feature set representing the influence on the 10 kV poles

including disaster-causing factors

disaster-pregnant environment and disaster-affected body

was constructed and meshed to 3 km×3 km grid units as the input of support vector machine regression（SVR） model. Then

the amount of 10 kV damaged poles in each grid unit was taken as the output of the SVR model. Thereby

a prediction model for the amount of 10 kV damaged poles under severe typhoon environment was established. Meanwhile

the model was adopted to predict the amount of 10 kV damaged poles in a certain area during the Typhoon Meranti（no. 1614）

and the predicted value is significantly correlated with the actual damage

which validated the proposed model. This method provides a possible way to predict the amount of 10 kV damaged poles under severe typhoon environment.

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