首页 > 过刊浏览>2022年第41卷第3期 >202-208. DOI:10.12158/j.2096-3203.2022.03.024
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基于CSO-SVR的低压架空线路谐波损耗评估
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中图分类号:

TM726.2

基金项目:

国家自然科学基金资助项目(61876040);中国南方电网有限责任公司资助项目(GDKJXM20172877)


Harmonic loss evaluation of low voltage overhead lines based on CSO-SVR model
Author:
Fund Project:

National Natural Science Foundation of China (61876040); China Southern Power Grid science and technology project (gdkjxm20172877)

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    摘要:

    针对低压架空线路物理解析模型谐波损耗计算精度不高的问题，文中提出采用基于纵横交叉优化(CSO)算法的支持向量回归(SVR)模型对架空线路谐波损耗进行评估。首先，采用结构风险最小化设计的SVR模型，拟合线路特征与谐波损耗之间的关系。然后，利用CSO算法对SVR超参数进行全局搜索，以动态优化获取最优超参数组，建立CSO-SVR谐波损耗评估模型。文中依托国内某大型电能质量综合试验平台进行低压架空线路谐波试验，获得线路谐波损耗实测数据，并基于该数据对所提模型进行验证。结果表明，采用CSO算法对SVR超参数进行优化，可有效提升SVR模型的谐波损耗评估性能。与其他模型相比，所提模型的评估精度更高。

    Abstract:

    In view of the low calculation accuracy of physical analytical model of harmonic loss,a support vector regression (SVR) model based on crisscross optimization (CSO) algorithm is proposed to evaluate the harmonic loss of overhead lines. Firstly,the SVR model designed to minimize structural risk is used to fit the relationship between line characteristics and harmonic losses. Then,the SVR hyperparameters are globally searched by the CSO algorithm. The optimal hyperparameter group is obtained by dynamic optimization,and the CSO-SVR harmonic loss evaluation model is established. Based on a large power quality test platform,the harmonic test of low voltage overhead lines is carried out. And the proposed model is verified by the measured data of this test. The results show that using CSO algorithm to optimize hyperparameters of SVR can effectively improve the line loss evaluation performance of SVR model. Compared with other models,the proposed model presents higher accuracy.

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孟安波,蔡涌烽,符嘉晋,陈德,殷豪,陈子辉.基于CSO-SVR的低压架空线路谐波损耗评估[J].电力工程技术,2022,41(3):202-208

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  • 收稿日期:2022-01-12
  • 最后修改日期:2022-04-03
  • 录用日期:2021-10-13
  • 在线发布日期: 2022-05-24
  • 出版日期: 2022-05-28
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