基于谐波特征与核Fisher判别分析的<br/>孤岛检测方法研究

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摘要提出一种基于谐波特征与核Fisher判别分析的孤岛检测方法,并对其进行研究。该方法首先从并网逆变器的输出电流和公共连接点(PCC)处电压信号中提取谐波幅值组成特征矢量,然后利用核Fisher判别分析(KFDA)对其进行类别划分,判断是否发生孤岛效应。实验结果表明,所提出的方法比传统的被动式孤岛检测方法检测速度更快,在功率平衡状态下依然能准确检测孤岛的发生,且不易受系统暂态过程的影响;同时,由于未向系统中加入扰动信号,不会对电能质量产生影响,克服了主动式孤岛检测方法的不足,具有较高的准确性与可靠性。

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	徐华电
	苏建徽
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	戴云霞

关键词 ：分布式发电, 孤岛检测, 特征矢量, 核Fisheri判别分析

Abstract：A novel islanding detecting method of distributed generation (DG) based on harmonic characteristics and kernel fisher discriminant analysis (KFDA) is proposed.The basic idea is to first extract the harmonic amplitudes to form the feature vectors from the voltage of the point of common coupling (PCC) and the output current of the inverter,and then classify them via KFDA to determine whether islanding occurs.The experiment results show that this method is faster than traditional passive methods in islanding detection,can still accurately detect islanding in the state of power equilibrium,and is not easily affected by system transient effect.At the same time,there is no negative impact on the power quality because of no-injected-disturbance to the electric power system in this method.The method overcomes the shortcomings of active methods and has high accuracy and reliability.

Key words： Distributed Generators islanding detection feature vectors kernel fisher discriminant analysis

收稿日期: 2015-01-25 出版日期: 2016-02-25

PACS:

TM712

基金资助:国家电网公司科技项目资助(NY71-13-036)。

作者简介: 徐华电男,1990年生,硕士研究生,研究方向为光伏发电技术。E-mail:xuhuadian@163.com

引用本文:

徐华电,苏建徽,张军军,刘宁,戴云霞. 基于谐波特征与核Fisher判别分析的
孤岛检测方法研究[J]. 电工技术学报, 2016, 31(3): 25-30. Xu Huadian, Su Jianhui, Zhang Junjun, Liu Ning ,Dai Yunxia. Research on Islanding Detection Based on Harmonic Characteristics and Kernel Fisher Discriminant Analysis. Transactions of China Electrotechnical Society, 2016, 31(3): 25-30.

链接本文:

https://dgjsxb.ces-transaction.com/CN/Y2016/V31/I3/25

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