[1]刘一丹,张 敬,秦晓丹,等.基于改进神经网络PID 控制的动态电压恢复器控制策略研究[J].机械与电子,2026,44(03):119-126.
 LIU Yidan,ZHANG Jing,QIN Xiaodan,et al.Research on Control Strategy of Dynamic Voltage Restorer Based onImproved Neural Network PID Control[J].Machinery & Electronics,2026,44(03):119-126.
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基于改进神经网络PID 控制的动态电压恢复器
控制策略研究
()
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
44
期数:
2026年03期
页码:
119-126
栏目:
电力控制
出版日期:
2026-03-25

文章信息/Info

Title:
Research on Control Strategy of Dynamic Voltage Restorer Based on
Improved Neural Network PID Control
文章编号:
1001-2257(2026)03-0119-08
作者:
刘一丹张 敬秦晓丹王 克钟 义刘 静谭风雷
(国网江苏省电力有限公司超高压分公司,江苏 南京 211102)
Author(s):
LIU YidanZHANG JingQIN XiaodanWANG KeZHONG YiLIU JingTAN Fenglei
(EHV Branch,State Grid Jiangsu Electric Power Co.,Ltd.,Nanjing 211102,China)
关键词:
动态电压恢复器神经网络混合优化算法谐波治理
Keywords:
dynamic voltage restorerneural networkhybrid optimization algorithmharmonic mitigation
分类号:
TM714.2
文献标志码:
A
摘要:
为解决动态电压恢复器模糊控制中谐波难以滤除的问题,提出基于改进神经网络的PID 控制
策略。该控制策略通过模糊神经网络实现PID控制器的参数自适应调节,并结合遗传算法与反向传播算法
实现调节精细化,同时能够有效滤除谐波。在MATLAB/Simulink仿真平台上搭建相关模型进行验证,仿
真结果表明,所提出的控制策略在抑制系统电压跌落的基础上,有效提高了消除网络谐波的能力。
Abstract:
To address the challenge of difficult harmonic filtering in fuzzy control of dynamic voltage
restorers (DVRs),a PID control strategy based on an improved neural network is proposed.This strategy
adaptively adjusts the parameters of PID controller using a fuzzy neural network (FNN).Furthermore,the
adjustment process is refined by integrating genetic and backpropagation algorithms,while effectively suppressing
harmonics.Simulation models were developed on the MATLAB/Simulink platform for validation.
The results demonstrate that the proposed control strategy not only mitigates voltage sags effectively,but
also significantly improves the capability to eliminate grid harmonics.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2025-09-18
基金项目:国网江苏省电力有限公司科技项目(J2024117)
作者简介:刘一丹 (1972-),男,辽宁大连人,硕士,高级工程师,研究方向为同步调相机运行检修技术等。
更新日期/Last Update: 2026-04-29