谢桦, 陈俊星, 郭志星, 张沛. 基于随机森林算法的架空输电线路状态评价方法[J]. 现代电力, 2020, 37(6): 559-565. DOI: 10.19725/j.cnki.1007-2322.2019.1065
引用本文: 谢桦, 陈俊星, 郭志星, 张沛. 基于随机森林算法的架空输电线路状态评价方法[J]. 现代电力, 2020, 37(6): 559-565. DOI: 10.19725/j.cnki.1007-2322.2019.1065
XIE Hua, CHEN Junxing, GUO Zhixing, ZHANG Pei. Condition Evaluation Method of Overhead Transmission Line Based on Random Forest Algorithm[J]. Modern Electric Power, 2020, 37(6): 559-565. DOI: 10.19725/j.cnki.1007-2322.2019.1065
Citation: XIE Hua, CHEN Junxing, GUO Zhixing, ZHANG Pei. Condition Evaluation Method of Overhead Transmission Line Based on Random Forest Algorithm[J]. Modern Electric Power, 2020, 37(6): 559-565. DOI: 10.19725/j.cnki.1007-2322.2019.1065

基于随机森林算法的架空输电线路状态评价方法

Condition Evaluation Method of Overhead Transmission Line Based on Random Forest Algorithm

  • 摘要: 对电网中架空输电线路进行准确的状态评价可以有效降低故障率,提高系统的供电性能。该文提出一种基于随机森林算法的架空输电线路状态评价方法。首先,通过对架空输电线路状态的影响因素分析,以线路8个单元选取的状态量和特殊情况状态量构建了包含79个状态量的架空输电线路状态量体系。其次,基于随机森林算法,构建了架空输电线路状态评价的多棵子决策树组合分类模型。然后,通过优化决策树数目和随机特征变量,提高随机森林算法分类性能和计算效率。最后,以某市110 kV电压等级架空输电线路实际数据进行实例分析。结果表明,采用该方法可实现架空输电线路状态的准确评价,从而为区域电网的运行调控提供决策支持。

     

    Abstract: Carrying on accurate condition evaluation for overhead transmission lines in power grids can decrease failure rate and enhance power supply performance of power grid effectively. A random forest algorithm based condition evaluation method for overhead transmission lines was proposed. Firstly, the factors influencing the condition of overhead transmission lines were analyzed, and the state variables as well as those under special conditions selected from eight kinds of components in transmission lines were selected to construct a state variable system in which 79 state variables for overhead transmission lines were contained. Secondly, based on the random forest algorithm a multi sub-decision tree combinatorial classification model for condition evaluation of overhead transmission lines was proposed. And then, both numbers of sub-decision trees and random characteristic variables were optimized to improve the classification performance and the efficiency of random forest algorithm. Finally, an example analysis based on actual data from the 110 kV overhead transmission line in a certain city was carried out. Simulation results show that using the proposed method, an accurate condition evaluation for overhead transmission line can be obtained, thus it might provide decision support for overhead transmission lines in regional power grid.

     

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