Parameter Identification of Norton Equivalent Model from Harmonic Monitoring Data

被引：0

作者：

Shao, Zhenguo ^{[1
]}

Xu, Haobo ^{[1
]}

Jiang, Ruobin ^{[1
]}

机构：

[1] Fuzhou Univ, Coll Elect Engn & Automat, Fuzhou, Fujian, Peoples R China

来源：

PROCEEDINGS OF 2018 5TH IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND INTELLIGENCE SYSTEMS (CCIS) | 2018年

关键词：

PCA; typical harmonic operating conditions; group feature parameters;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A method of identifying the operating parameters of harmonic customers based on historical monitoring data is introduced in this paper. Firstly, PCA is used to reduce the original harmonic data dimensions and determine the appropriate number of clusters. Then k -means is used to partition harmonic mode on low dimensions. Lastly group feature parameters are calculated from the clustered typical harmonic operating conditions. Experimental results showed that the operating parameters of harmonic customers can be identified from a large number of high -dimensional historical statistic data by the proposed method, which will also contribute to the harmonic source location and optimal operation strategy.

引用

页码：101 / 106

页数：6

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