Research on Intelligent Verification System of High Voltage Electric Energy Metering Device Based on Power Cloud

To address the issues of low efficiency, poor security, insufficient compatibility, and difficulties in traceability associated with high-voltage electric energy metering (HVEEM) device verification methods, this paper proposes a design scheme for a remote verification system (RVS) of such devices b...

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Main Authors: Fangqing Zhang, Jiang Guo, Fang Yuan, Yongjie Shi, Bingyuan Tan, Dongfang Yao
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Electronics
Subjects:
Online Access:https://www.mdpi.com/2079-9292/12/11/2493
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author Fangqing Zhang
Jiang Guo
Fang Yuan
Yongjie Shi
Bingyuan Tan
Dongfang Yao
author_facet Fangqing Zhang
Jiang Guo
Fang Yuan
Yongjie Shi
Bingyuan Tan
Dongfang Yao
author_sort Fangqing Zhang
collection DOAJ
description To address the issues of low efficiency, poor security, insufficient compatibility, and difficulties in traceability associated with high-voltage electric energy metering (HVEEM) device verification methods, this paper proposes a design scheme for a remote verification system (RVS) of such devices based on a power cloud platform (PCP). The system adopts the concept of “high-precision local sampling + remote cloud verification” and develops a local acquisition device with compatibility and high precision to achieve fast acquisition of local electrical parameters. The IEC 61850 communication modeling is utilized to establish unified communication standards between the local device and the PCP. The PCP provides two verification methods: physical error verification based on a multi-channel standard and digital verification based on an improved Backpropagation (BP) neural network simulation model. Leveraging the advantages of power cloud technology, the system enables functions such as electrical energy calculation, remote intelligent error verification, cloud storage, condition monitoring, and early warning. Through testing and application, it has been demonstrated that the system achieves an integration accuracy level better than 0.02. It also exhibits good security, compatibility, and traceability of measurement values while attaining a high level of informatization and intelligence. Particularly, the system shows promising prospects for the remote and efficient verification of large-scale and multi-type high-voltage metering devices.
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spelling doaj.art-3c25501117ee44b5b57bef5c91166c562023-11-18T07:45:40ZengMDPI AGElectronics2079-92922023-06-011211249310.3390/electronics12112493Research on Intelligent Verification System of High Voltage Electric Energy Metering Device Based on Power CloudFangqing Zhang0Jiang Guo1Fang Yuan2Yongjie Shi3Bingyuan Tan4Dongfang Yao5Intelligent Power Equipment Technology Research Center, Wuhan University, Wuhan 430072, ChinaIntelligent Power Equipment Technology Research Center, Wuhan University, Wuhan 430072, ChinaIntelligent Power Equipment Technology Research Center, Wuhan University, Wuhan 430072, ChinaIntelligent Power Equipment Technology Research Center, Wuhan University, Wuhan 430072, ChinaMaintenance & Test Center of EHV Power Transmission Company, China Southern Power Grid, Guangzhou 510700, ChinaMaintenance & Test Center of EHV Power Transmission Company, China Southern Power Grid, Guangzhou 510700, ChinaTo address the issues of low efficiency, poor security, insufficient compatibility, and difficulties in traceability associated with high-voltage electric energy metering (HVEEM) device verification methods, this paper proposes a design scheme for a remote verification system (RVS) of such devices based on a power cloud platform (PCP). The system adopts the concept of “high-precision local sampling + remote cloud verification” and develops a local acquisition device with compatibility and high precision to achieve fast acquisition of local electrical parameters. The IEC 61850 communication modeling is utilized to establish unified communication standards between the local device and the PCP. The PCP provides two verification methods: physical error verification based on a multi-channel standard and digital verification based on an improved Backpropagation (BP) neural network simulation model. Leveraging the advantages of power cloud technology, the system enables functions such as electrical energy calculation, remote intelligent error verification, cloud storage, condition monitoring, and early warning. Through testing and application, it has been demonstrated that the system achieves an integration accuracy level better than 0.02. It also exhibits good security, compatibility, and traceability of measurement values while attaining a high level of informatization and intelligence. Particularly, the system shows promising prospects for the remote and efficient verification of large-scale and multi-type high-voltage metering devices.https://www.mdpi.com/2079-9292/12/11/2493high voltage electric energy meteringintelligent verificationpower cloudneural networkIEC 61850
spellingShingle Fangqing Zhang
Jiang Guo
Fang Yuan
Yongjie Shi
Bingyuan Tan
Dongfang Yao
Research on Intelligent Verification System of High Voltage Electric Energy Metering Device Based on Power Cloud
Electronics
high voltage electric energy metering
intelligent verification
power cloud
neural network
IEC 61850
title Research on Intelligent Verification System of High Voltage Electric Energy Metering Device Based on Power Cloud
title_full Research on Intelligent Verification System of High Voltage Electric Energy Metering Device Based on Power Cloud
title_fullStr Research on Intelligent Verification System of High Voltage Electric Energy Metering Device Based on Power Cloud
title_full_unstemmed Research on Intelligent Verification System of High Voltage Electric Energy Metering Device Based on Power Cloud
title_short Research on Intelligent Verification System of High Voltage Electric Energy Metering Device Based on Power Cloud
title_sort research on intelligent verification system of high voltage electric energy metering device based on power cloud
topic high voltage electric energy metering
intelligent verification
power cloud
neural network
IEC 61850
url https://www.mdpi.com/2079-9292/12/11/2493
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