基于S变换与SVM的电能质量复合扰动识别

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Abstract This paper presents a new approach based on S-transform and support vector machine (SVM) for identification of power quality complex disturbances. Firstly, original power quality signals are processed by S-transform and features were extracted from the result of S-transform at different frequency areas. Then, 2 types of most distinguished feature are selected by statistic feature selection. The selected features are used as the input vector of SVM and to train a SVM based classifier for power quality disturbances recognition. Furthermore, the SVM classifier is used to classify the short-time power quality disturbances. The proposed method reduces the computing costs of feature calculation, meanwhile saves the time of training and classification. 8 types of power quality disturbances including 2 types of complex disturbances are accurate identified. The simulation results show the validity of this method.

Key words： Power quality disturbances disturbance recognition S-transform support vector machine feature selection

Received: 22 October 2009 Published: 07 March 2014

PACS:

TM714.3

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	Articles by authors
	Huang Nantian
	Xu Dianguo
	Liu Xiaosheng

Cite this article:

Huang Nantian,Xu Dianguo,Liu Xiaosheng. Identification of Power Quality Complex Disturbances Based on S-Transform and SVM[J]. Transactions of China Electrotechnical Society, 2011, 26(10): 23-30.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2011/V26/I10/23

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