A Valid Data Selection Method in Estimating Harmonic Impact of Individual Loads

被引：0

作者：

Meng S. ^{[1
]}

Xiao X. ^{[1
]}

Zhang Y. ^{[2
]}

Huang Y. ^{[1
]}

Chen F. ^{[1
]}

机构：

[1] College of Electrical Engineering and Information Technology, Sichuan University, Chengdu, 610065, Sichuan Province

[2] State Grid Fujian Electric Power Research Institute, Fuzhou, 350000, Fujian Province

来源：

Huang, Yong (951093608@qq.com) | 2006年 / Power System Technology Press卷 / 41期

关键词：

Clustering; Data selection; Improved k-means method; Multiple harmonic sources; Quantifying the harmonic impact;

D O I：

10.13335/j.1000-3673.pst.2016.2150

中图分类号：

学科分类号：

摘要：

Considering possibly existing problem of shortage of valid data sets when estimating impact of individual loads in multiple harmonic source system, a valid data selection method was proposed. In selected data, only one of harmonic loads changed. Firstly, improved k-means clustering method was adopted in a step-by-step way to obtain valid data sets with amplitude and phase angle as two properties of clustering objects. Then contribution of each harmonic source in every cluster was calculated with partial least-squares regression. Final harmonic contribution during the period was obtained by calculating weighted summation of harmonic contribution of every cluster. The proposed method overcomes difficulty of obtaining intersection of several valid data sets. Simulation in IEEE 14-bus system demonstrates accurate performance of the proposed method and its superiority over traditional data selection methods. © 2017, Power System Technology Press. All right reserved.

引用

页码：2006 / 2011

页数：5

共 23 条

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