Multiple Impact Factor Based Accuracy Analysis for Power Quality Disturbance Detection

Zijing Yang; Haochen Hua; Junwei Cao

doi:10.17775/CSEEJPES.2020.01270

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Multiple Impact Factor Based Accuracy Analysis for Power Quality Disturbance Detection

Regular Papers | 更新时间：2026-10-15

- Multiple Impact Factor Based Accuracy Analysis for Power Quality Disturbance Detection
- Multiple Impact Factor Based Accuracy Analysis for Power Quality Disturbance Detection
- 中国电机工程学会电力与能源系统学报(英文) 2023年9卷第1期页码：88-99
- 作者机构：
  
  1. College of Electromechanical Engineering, Beijing Institute of Graphic Communication,Beijing,China
  2. College of Energy and Electrical Engineering, Hohai University,Nanjing,China
  3. Beijing National Research Center for Information Science and Technology, Tsinghua University,Beijing,China
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2020.01270
  中图分类号：
- 纸质出版：2023-01-01
- 稿件说明：
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Zijing Yang, Haochen Hua, Junwei Cao. Multiple Impact Factor Based Accuracy Analysis for Power Quality Disturbance Detection[J]. 中国电机工程学会电力与能源系统学报(英文), 2023,9(1):88-99.

Zijing Yang, Haochen Hua, Junwei Cao. Multiple Impact Factor Based Accuracy Analysis for Power Quality Disturbance Detection[J]. CSEE Journal of Power and Energy Systems, 2023, 9(1): 88-99.
Zijing Yang, Haochen Hua, Junwei Cao. Multiple Impact Factor Based Accuracy Analysis for Power Quality Disturbance Detection[J]. 中国电机工程学会电力与能源系统学报(英文), 2023,9(1):88-99. DOI： 10.17775/CSEEJPES.2020.01270.

Zijing Yang, Haochen Hua, Junwei Cao. Multiple Impact Factor Based Accuracy Analysis for Power Quality Disturbance Detection[J]. CSEE Journal of Power and Energy Systems, 2023, 9(1): 88-99. DOI： 10.17775/CSEEJPES.2020.01270.

摘要

Abstract

Nowadays

power quality problems are affecting people's daily life and production activities. With an aim to improve disturbance detection accuracy

a novel analysis approach

based on multiple impact factors

is proposed in this paper. First

a multiple impact factors analysis is implemented in which two perspectives

i.e.

the wavelet analysis and disturbance features are simultaneously considered. Five key factors

including wavelet function

wavelet decomposition level

redundant algorithm

event type and disturbance intensity

and start and end moment of disturbance

have been considered. Next

an impact factor based accuracy analysis algorithm is proposed

through which each factor's potential impact on disturbance location accuracy is investigated. Three transforms

i.e.

the classic wavelet

lifting wavelet and redundant lifting wavelet are employed

and their superiority on disturbance location accuracy is investigated. Finally

simulations are conducted for verification. Through the proposed method

the wavelet based parameters can be validly selected in order to accurately detect power quality disturbance.

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