Detection and classification of power quality disturbances in distribution networks based on VMD and DFA

Yanchun Xu; Yongkang Gao; Zhenhua Li; Mi Lu

doi:10.17775/CSEEJPES.2018.01340

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Detection and classification of power quality disturbances in distribution networks based on VMD and DFA

Regular Papers | 更新时间：2025-12-19

- Detection and classification of power quality disturbances in distribution networks based on VMD and DFA
- Detection and classification of power quality disturbances in distribution networks based on VMD and DFA
- 中国电机工程学会电力与能源系统学报(英文) 2020年6卷第1期页码：122-130
- 作者机构：
  
  1. College of Electrical Engineering and New Energy, China Three Gorges University,Yichang,China
  2. College of Electrical and Computer Engineering, Texas A&M University, College Station,TX,USA
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2018.01340
  中图分类号：
- 纸质出版：2020
- 稿件说明：
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Yanchun Xu, Yongkang Gao, Zhenhua Li, 等. Detection and classification of power quality disturbances in distribution networks based on VMD and DFA[J]. 中国电机工程学会电力与能源系统学报(英文), 2020,6(1):122-130.

Yanchun Xu, Yongkang Gao, Zhenhua Li, et al. Detection and classification of power quality disturbances in distribution networks based on VMD and DFA[J]. CSEE Journal of Power and Energy Systems, 2020, 6(1): 122-130.
Yanchun Xu, Yongkang Gao, Zhenhua Li, 等. Detection and classification of power quality disturbances in distribution networks based on VMD and DFA[J]. 中国电机工程学会电力与能源系统学报(英文), 2020,6(1):122-130. DOI： 10.17775/CSEEJPES.2018.01340.

Yanchun Xu, Yongkang Gao, Zhenhua Li, et al. Detection and classification of power quality disturbances in distribution networks based on VMD and DFA[J]. CSEE Journal of Power and Energy Systems, 2020, 6(1): 122-130. DOI： 10.17775/CSEEJPES.2018.01340.

摘要

Abstract

In this paper

a novel algorithm is proposed to detect and classify the power quality (PQ) disturbances for distribution networks with distributed generation. First

a distribution system with photovoltaic and wind power generation is built as a test platform. Then

nine types of power quality disturbances in the distribution network are decomposed by variational mode decomposition (VMD) and the noise is filtered. Meanwhile

the mode functions containing characteristic information are extracted as input signals of detrended fluctuation analysis (DFA). Power quality disturbances are classified from the view of their distributed energy operational status

and three types of windows are set up to deal with different frequency disturbances. The two-dimensional and three-dimensional scatter plots of each type under three windows are depicted

and the criteria are determined to distinguish the disturbances under the different operating conditions. The simulations show that the algorithm is simpler

more accurate and feasible. It provides an approach for online real-time detection of embedded systems.

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