Research on Identification Method of Voltage Sag Cause Based on BiLSTM

SU Tingting; PENG Hexiang; WANG Can; LI Bo; LIAO Kai; LIU Shifeng

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Research on Identification Method of Voltage Sag Cause Based on BiLSTM

更新时间：2025-11-18

- Research on Identification Method of Voltage Sag Cause Based on BiLSTM
- Vol. 42, Issue 1, Pages: 32-37+42(2022)
- 作者机构：
  
  1. 西南交通大学
  2. 国网湖南省电力有限公司电力科学研究院
  3. 湖南大道电气设备有限公司
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM714.2
- Published：2022
- 稿件说明：
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SU Tingting, PENG Hexiang, WANG Can, et al. Research on Identification Method of Voltage Sag Cause Based on BiLSTM[J]. 2022, 42(1): 32-37+42.
DOI：

SU Tingting, PENG Hexiang, WANG Can, et al. Research on Identification Method of Voltage Sag Cause Based on BiLSTM[J]. 2022, 42(1): 32-37+42. DOI：

摘要

电压暂降是配电网中常见的电能质量问题之一，准确辨识电压暂降原因对制定有效的电压暂降综合防治方案、实现电网—用户责任划分等具有重要意义。提出一种基于双向长短期记忆神经网络(Bidirectional Long Short Term Memory

BiLSTM)的电压暂降原因辨识方法。首先，提取电压暂降时域特征和S变换能量熵，构建电压暂降原因辨识综合特征指标；其次，建立适用于电压暂降分类的BiLSTM网络，实现电压暂降原因的辨识；最后，设置多分类问题的评估指标，通过仿真对所提辨识方法的有效性进行验证。结果表明，所提方法能辨识5种电压暂降扰动源，且具有较高的准确性。

Abstract

Voltage sag is one of the most common power quality problems in distribution network. Accurately identifying the causes of voltage sag is of great significance to formulate comprehensive prevention and control scheme of voltage sag and division of power grid user responsibility. A method for identifying the cause of voltage sag based on bidirectional long-term and short-term memory（BiLSTM）neural network is proposed. Firstly

the time-domain characteristics of voltage sag and S-transform energy entropy are extracted

and the comprehensive characteristic index of voltage sag cause identification is constructed.Secondly

a BiLSTM network suitable for voltage sag classification is established to identify the causes of voltage sag.Finally

the evaluation index of multi classification problem is set

and the effectiveness of the proposed identification method is verified by simulation. Simulation results show that the proposed method can identify five voltage sag disturbance sources with high accuracy.

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