[1]殷 伟,付柳笛,周陈斌,等.基于实时分布式计算平台的智能变电站设备在线监测研究[J].机械与电子,2021,(12):48-53.
 YIN Wei,FU Liudi,ZHOU Chenbin,et al.Research on Online Monitoring of Intelligent Substation Equipment Based on a Real-time Distributed Computing Platform[J].Machinery & Electronics,2021,(12):48-53.
点击复制

基于实时分布式计算平台的智能变电站设备在线监测研究()
分享到:

机械与电子[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2021年12期
页码:
48-53
栏目:
自动控制与检测
出版日期:
2021-12-28

文章信息/Info

Title:
Research on Online Monitoring of Intelligent Substation Equipment Based on a Real-time Distributed Computing Platform
文章编号:
1001-2257 ( 2021 ) 12-0048-06
作者:
殷 伟 1 付柳笛 1 周陈斌 1 姜健琳 2 李金梅 2
1. 国网苏州供电公司,江苏 苏州 215000 ; 2. 上海泽鑫电力科技股份有限公司,上海 201206
Author(s):
YIN Wei1 FU Liudi1 ZHOU Chenbin1 JIANG Jianlin2 LI Jinmei2
(1.State Grid Suzhou Power Supply Company , Suzhou 215000 , China ;
2.Shanghai Zexin Electric Power Technology Co. , Ltd. , Shanghai 201206 , China )
关键词:
实时分布式计算智能变电站在线监测
Keywords:
real-time distributed computing intelligent substation online monitoring
分类号:
TM73
文献标志码:
A
摘要:
提出了实时分布式计算平台,利用开源技术将在线监测获得的数据存储到计算平台进行数据处理,从而达到自动故障检测和分析的目的。实时分布式计算平台具有强大的计算能力,能为设备提供更为强大的数据整合和分析水平,有利于变电站设备自动状态监控。改进的监测系统已在智能变电站内 EMI 在线监测设备上得到应用,结果表明,通过对设备运行数据进行分析及计算,提高了变电站在线监测设备的故障诊断和状态监控水平。
Abstract:
A real-time distributed computing platform is proposed , which uses open source technology to store the data obtained from online monitoring in the computing platform for data processing , to achieve the purpose of automatic fault detection and analysis.The real-time distributed computing platform has strong computing power , and can provide more powerful data integration and analysis for the equipment , and it is conducive to the automatic state monitoring of substation equipment.The improved monitoring system has been applied to EMI online monitoring equipment in an intelligent substation.The results show that the fault diagnosis and condition monitoring of substation online monitoring equipment are improved by analyzing and calculating the equipment operation data.

参考文献/References:

[ 1 ] 笃峻,张海宁,柏杨,等 . 智能变电站设备状态监测系统通信关键技术及实现[ J ] . 电力自动化设备,2016 , 36( 4 ): 151-156.

[ 2 ] 王帅,姜敏,李江林,等 . 全维度智能变电站设备状态监测关键技术研究[ J ] . 电测与仪表, 2020 , 57 ( 7 ): 82-86.
[ 3 ] 胡宇卿 . 变电站微机保护及自动化设备的电磁干扰分析[ J ] . 通讯世界, 2017 ( 3 ): 206.
[ 4 ] NESBITT A , STEWART B G , MCMEEKIN S G , et al.A novel approach to high voltage substation surveillance using radio frequency interference measurement[ C ]// 2009 IEEE Lectrical Insulation Conference , 2009 : 159-163.
[ 5 ] IEEE.IEEE Standard for intelligent electronic devices cyber security capabilities : IEEE Std 1686-2013 [ S ] . New york : IEEE , 2014.
[ 6 ] SCHNEIDER B I , MILLER B R , SAUNDERS B V. NIST?s digital library of mathematical functions [ J ] . Physics today , 2018 , 71 ( 2 ):48-53.
[ 7 ] LIU Z , SEO H , GROSCHDL J , et al.Efficient implementation of NIST-compliant elliptic curve cryptography for 8-bit AVR-based sensor nodes [ J ] .IEEE Transactions on information forensics and security ,2016 , 11 ( 7 ): 1385-1397.
[ 8 ] AREVALO F , DIPRASETYA M R , SCHWUNG A.A cloud-based architec-ture for condition monitoring based on machine learning [ C ]// 2018 IEEE 16th International Conference on Industrial Informatics( INDIN ), 2018 : 163-168.
[ 9 ] OLEIWI B K.Scouting and controlling for mobile robot based raspberry Pi 3 [ J ] .Journal of computational and theoretical nanoscience , 2019 , 16 ( 1 ): 79-83.
[ 10 ] ISAH H , ZULKERNINE F.A scalable and robust framework for dataStream ingestion [ C ]// 2018 IEEE International Conference on Big Data ( Big Data ),2018 : 2900-2905.
[ 11 ] 王欣,邱昕,慕福奇,等 . 基于 MCAPI 的嵌入式多核通信机制的研究[ J ] . 微电子学与计算机,2017 , 34( 11 ): 85-88.
[ 12 ] 郭昆,宋杰,王洁萍,等 .NoSQL 数据库间数据交换代价研究[ J ] . 计算机工程与科学, 2016 , 38 ( 1 ): 33-40.
[ 13 ] 曾 强,缪 力,秦 拯 . 面 向 大 数 据 处 理 的 Hadoop 与 MongoDB 整合技 术研 究[ J ] . 计 算机 应 用与 软件,2016 , 33 ( 2 ): 21-24 , 37.
[ 14 ] MITICHE I , MORISON G , NESBITT A , et al. Classification of multiple electromagnetic interference events in high-voltage power plant [ C ]// 2018 53rd International Universities Power Engineering Conference( UPEC ),2018 : 1-4.
[ 15 ] HUANG N E , SHEN Z , LONG S R , et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[ J ] .Proceedings mathematical physical and engineering sciences , 1998 , 454 ( 1971 ): 903-995.
[ 16 ] SLATER J , NESBITT A , MORISON G , et al.Application of empirical mode decomposition in identifying key frequencies for EMI diagnostic measurements [ C ]// 2018 53rd International Universities Power Engineering Conference ( UPEC ), 2018 : 1-5.
[ 17 ] MITICHE I , JENKINS M D , BOREHAM P , et al. Deep residual neural network for EMI event classification using bispectrum representations [ C ]// 2018 26th European Signal Processing Conference ( EUSIPCO ),2018 : 186-190.

备注/Memo

备注/Memo:
收稿日期: 2021-08-10
作者简介:殷 伟 ( 1971- ),男,江苏苏州人,硕士,高级工程师,主要研究方向为电网二次系统及继电保护专业管理。
更新日期/Last Update: 2021-12-28