自动化与仪表2024,Vol.39Issue(12) :65-69.DOI:10.19557/j.cnki.1001-9944.2024.12.014

基于DlgSILENT的分布式光伏短路电流自动化监测系统

Distributed Photovoltaic Short-circuit Current Automatic Monitoring System Based on DIgSILENT

赵晶 庞怡君 管春伟 崔艳昭
自动化与仪表2024,Vol.39Issue(12) :65-69.DOI:10.19557/j.cnki.1001-9944.2024.12.014

基于DlgSILENT的分布式光伏短路电流自动化监测系统

Distributed Photovoltaic Short-circuit Current Automatic Monitoring System Based on DIgSILENT

赵晶 1庞怡君 1管春伟 1崔艳昭1
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作者信息

  • 1. 国网山东省电力公司青岛供电公司,青岛 266002
  • 折叠

摘要

分布式光伏系统短路故障分析过程中,采用简化电路模型法完成短路电流计算,忽略了光伏系统的动态特性和非线性行为,得出的监测结果误差较大.因此,提出基于DIgSILENT的分布式光伏短路电流自动化监测系统.引入完全自适应噪声集合经验模态分解算法,得到干扰抑制后的信号序列.基于鲸鱼优化算法改进神经网络构建短路故障识别模型,得到短路电流自动化监测结果.测试结果表明,该系统输出的短路电流自动化监测结果RM SE值始终小于0.1,满足电流监测精度要求.

Abstract

In the process of analyzing short-circuit faults in distributed photovoltaic systems,the simplified circuit model method is used to calculate the short-circuit current,ignoring the dynamic characteristics and nonlinear behav-ior of the photovoltaic system,resulting in significant errors in the monitoring results.Therefore,a distributed photo-voltaic short-circuit current automatic monitoring system based on DIgSILENT is proposed.Introduce a fully adaptive noise set empirical mode decomposition algorithm to obtain the signal sequence after interference suppression.A neu-ral network improved based on whale optimization algorithm is used to construct a short-circuit fault recognition model.The test results show that the RMSE value of the short-circuit current automatic monitoring output by the sys-tem is always less than 0.1,which meets the accuracy requirements of current monitoring.

关键词

DIgSILENT/分布式光伏/短路电流/改进神经网络/自动化在线监测

Key words

DIgSILENT/distributed photovoltaics/short circuit current/improve neural networks/automation online monitoring

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出版年

2024
自动化与仪表
天津市工业自动化仪表研究所 天津市自动化学会

自动化与仪表

CSTPCD
影响因子:0.548
ISSN:1001-9944
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