Power Quality Transient Disturbance Detection Based on Improved QPSO Morphological Filter

doi:10.11930/j.issn.1004-9649.2017.06.095.06

Abstract

Abstract: A morphological filter based on improved quantum particle swarm optimization (QPSO) algorithm is proposed for power quality transient disturbance detection. Firstly, the quantum particle swarm optimization algorithm is improved. Particle position is initialized by chaos sequence to improve global optimization ability, and the mutation operator is introduced to avoid premature convergence. Then, the improved algorithm is applied to adaptive optimization of structural elements of morphological filter, which is combined with characteristics of structural elements to find out the best structural elements of the attributes to improve the filtering ability. Through simulation experiment of containing complex and changeful environment noise, voltage swell, voltage sag, voltage interruption phenomenon of transient interference constructed and performance of the improved filter is researched. Compared with the experimental results, it is proved that proposed method is fast and accurate. Compared with traditional filtering method, it also improves reliability of power quality disturbance detection.

Key words: mathematical morphology, quantum particle swarm optimization, power quality disturbance, structural element, wave filtering

CLC Number:

TM732

SHENG Siqing, WANG Jiaqi. Power Quality Transient Disturbance Detection Based on Improved QPSO Morphological Filter[J]. Electric Power, 2017, 50(6): 95-100.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.2017.06.095.06

https://www.electricpower.com.cn/EN/Y2017/V50/I6/95

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