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基于空间多源异构数据的台风下输电杆塔风险评估
作者:
作者单位:

1.武汉理工大学自动化学院,湖北省 武汉市 430070;2.广东电网有限责任公司电力科学研究院,广东省 广州市 510080

作者简介:

通讯作者:

基金项目:

中央高校基本科研业务费专项资金资助项目(191011005);中国南方电网有限责任公司科技项目(GDKJXM20198441);已申请国家发明专利(申请号:201811278469.6)。


Risk Assessment of Transmission Tower in Typhoon Based on Spatial Multi-source Heterogeneous Data
Author:
Affiliation:

1.School of Automation, Wuhan University of Technology, Wuhan 430070, China;2.Electric Power Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou 510080, China

Fund Project:

This work is supported by the Fundamental Research Funds for the Central Universities (No. 191011005) and Electric Power Research Institute of Guangdong Power Grid Co., Ltd. (No. GDKJXM20198441).

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    摘要:

    台风灾害下电力系统的风险评估及可视化对电力系统防灾减灾具有重要的科学意义和工程应用价值。为了预测高风险区域,优化抢修资源配置和潮流风险调度,文中分数据层、知识提取层和可视化处理层构建了台风灾害下输电杆塔风险评估体系。首先,基于设备运行信息、气象信息以及地理信息等构建空间多源异构信息数据库。再基于参数优化,应用6种机器学习算法建立了杆塔损毁风险预测智能模型,通过指标对比选择相对最优模型,同时,在此基础上提出基于不等权拟合优度法的组合模型。以1 km×1 km的尺度对台风“彩虹”下某中国沿海城市的杆塔损毁风险进行了评估及可视化,将相对最优模型与组合模型进行了详细的对比,测试结果显示:相对最优模型及组合模型均能够识别损毁最严重的区域,但相同风险阈值下组合模型的预测效果更好,验证了所提方法的可行性与合理性。最后,分析了模型通用性和样本数量级对预测效果的影响。

    Abstract:

    Risk assessment and visualization of power system under typhoon disasters has scientific significance and engineering application value for disaster prevention and mitigation of power systems. In order to predict high-risk areas and optimize the emergency material allocation and risk-based dispatch of power flow, the data layer, knowledge extraction layer and visualization layer are used to construct the risk assessment system for power transmission towers under typhoon disasters. Firstly, based on equipment operation information, meteorological information and geographic information, a spatial multi-source heterogeneous information database is built. Then, based on parameter optimization, six machine learning algorithms are used to establish intelligent models for tower damage risk prediction, and a relative optimal model is selected through index comparison. At the same time, a combined model based on goodness of fit method with unequal weight is proposed. The tower damage risk in a Chinese coastal city under the typhoon “Mujigae” is assessed and visualized with dimension of 1 km×1 km. The relative optimal model is compared with the combined model in detail. The results show that both relative optimal model and combined model can identify the most severely damaged area, but the combined model has better prediction with the same risk threshold, which verifies the feasibility and rationality of the proposed method. Finally, the model universality and the influence of sample magnitude on prediction effect are analyzed.

    表 2 Table 2
    表 3 Table 3
    图1 台风灾害下输电杆塔智能可视化风险评估总体框架Fig.1 Overall framework of intelligent visualization risk assessment of transmission tower under typhoon disaster
    图2 原始模型评估流程Fig.2 Evaluation process of original model
    图3 6种模型优化前后的评估结果Fig.3 Evaluation results of 6 models before and after optimization
    图 变量的平行坐标可视化Fig. Parallel coordinates visualization of variables
    图 变量相关性分析Fig. Correlation analysis of variables
    图 实际损毁情况Fig. Actual damage situation
    表 1 地面粗糙度系数Table 1 Ground roughness coefficient
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引用本文

侯慧,于士文,肖祥,等.基于空间多源异构数据的台风下输电杆塔风险评估[J/OL].电力系统自动化,http://doi.org/10.7500/AEPS20191113002.
HOU Hui,YU Shiwen,XIAO Xiang,et al.Risk Assessment of Transmission Tower in Typhoon Based on Spatial Multi-source Heterogeneous Data[J/OL].Automation of Electric Power Systems,http://doi.org/10.7500/AEPS20191113002.

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历史
  • 收稿日期:2019-11-13
  • 最后修改日期:2020-03-17
  • 录用日期:2019-12-29
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