基于改进形态滤波器和弧长差分序列的微电网电能质量扰动定位与识别

doi:10.19595/j.cnki.1000-6753.tces.161483

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Abstract Aiming at the problem of location and identification of micro-grid power quality disturbances with strong noise,a novel method based on modified morphological filter and arc length difference sequence is proposed to locate and identify disturbances.Firstly,the dilation function and the erosion function are separately improved to the mean-dilation function and the mean-erosion function,and the improved alternating hybrid morphological filter is used to filter the power quality signal.Then,on the basis of the analysis of the disturbance waveform and the three typical disturbance examples,the arc length differential sequence of the filtered signal is defined and calculated.Finally,based on the arc length difference sequence,disturbance time is accurately located,the amplitude and peaks characteristics are extracted from the arc length difference sequence and filtered signal.These characteristics are input to the identifier defined by the disturbance identification rules to get the final identification results.The simulation and one practical micro-grid data test shown that the proposed method could accurately locate and identify 5 types of single disturbances and 3 types of complex disturbances mixed with different intensity of noise,and is suitable for the disturbances location and identification of actual micro-grid power quality.

Key words： Power quality disturbance location and identification modified morphological filter arc length differential sequence micro-grid

Received: 14 September 2016 Published: 14 September 2017

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TM714.3

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	Zhuo Jinbao
	Shi Weifeng
	Lan Ying
	Zhang Wei
	Lu Jie

Cite this article:

Zhuo Jinbao,Shi Weifeng,Lan Ying等. Location and Identification of Micro-Grid Power Quality Disturbances Based on Modified Morphological Filter and Arc Length Differential Sequence[J]. Transactions of China Electrotechnical Society, 2017, 32(17): 21-34.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.161483 OR https://dgjsxb.ces-transaction.com/EN/Y2017/V32/I17/21

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