Low-voltage power grid data abnormity traceability method and system based on association matching analysis
The invention discloses a low-voltage power grid data abnormity traceability method, system, device and medium based on correlation matching analysis, and the method comprises the steps: employing the measurement data of a low-voltage power distribution area terminal, including the power, voltage, c...
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| creator | HAN RONGJIE WANG QIFENG FANG XIANG KIM MIN-HO CHEN YIFANG LIU JIAN WANG YI XING SHUANGSHUANG ZHOU GUOHUA CHEN YIXUAN TU YONGWEI ZHANG JIANSONG LAI HANBIN FAN LIBO JIANG JIAN CHIA BIN HUANG YANG YI SUN ZHIQING NI XIABING FENG XUE XUAN YI CHEN YUANZHONG LI YA LAI YIBO HOU WEIHONG ZHAO JIANPENG ZHANG XUDONG LIU XINGYE XU RONGYONG |
| description | The invention discloses a low-voltage power grid data abnormity traceability method, system, device and medium based on correlation matching analysis, and the method comprises the steps: employing the measurement data of a low-voltage power distribution area terminal, including the power, voltage, current and other information collected by intelligent ammeters of a distribution transformer node and a user node; establishing a topology detection model based on virtual impedance, and deeply analyzing and measuring the electrical distance between the nodes; by introducing a double-implicit-layer recurrent neural network, modeling is carried out on a mapping relation among power flow variables in measurement data of each node, and correlation matching among the nodes is realized; based on correlation matching analysis among the nodes, virtual impedance values among the nodes are calculated, so that whether topology connection among the nodes is abnormal or not can be accurately detected, and users with abnormal t |
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JIANG JIAN ; CHIA BIN HUANG ; YANG YI ; SUN ZHIQING ; NI XIABING ; FENG XUE ; XUAN YI ; CHEN YUANZHONG ; LI YA ; LAI YIBO ; HOU WEIHONG ; ZHAO JIANPENG ; ZHANG XUDONG ; LIU XINGYE ; XU RONGYONG</creator><creatorcontrib>HAN RONGJIE ; WANG QIFENG ; FANG XIANG ; KIM MIN-HO ; CHEN YIFANG ; LIU JIAN ; WANG YI ; XING SHUANGSHUANG ; ZHOU GUOHUA ; CHEN YIXUAN ; TU YONGWEI ; ZHANG JIANSONG ; LAI HANBIN ; FAN LIBO ; JIANG JIAN ; CHIA BIN HUANG ; YANG YI ; SUN ZHIQING ; NI XIABING ; FENG XUE ; XUAN YI ; CHEN YUANZHONG ; LI YA ; LAI YIBO ; HOU WEIHONG ; ZHAO JIANPENG ; ZHANG XUDONG ; LIU XINGYE ; XU RONGYONG</creatorcontrib><description>The invention discloses a low-voltage power grid data abnormity traceability method, system, device and medium based on correlation matching analysis, and the method comprises the steps: employing the measurement data of a low-voltage power distribution area terminal, including the power, voltage, current and other information collected by intelligent ammeters of a distribution transformer node and a user node; establishing a topology detection model based on virtual impedance, and deeply analyzing and measuring the electrical distance between the nodes; by introducing a double-implicit-layer recurrent neural network, modeling is carried out on a mapping relation among power flow variables in measurement data of each node, and correlation matching among the nodes is realized; based on correlation matching analysis among the nodes, virtual impedance values among the nodes are calculated, so that whether topology connection among the nodes is abnormal or not can be accurately detected, and users with abnormal t</description><language>chi ; eng</language><subject>CALCULATING ; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; 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establishing a topology detection model based on virtual impedance, and deeply analyzing and measuring the electrical distance between the nodes; by introducing a double-implicit-layer recurrent neural network, modeling is carried out on a mapping relation among power flow variables in measurement data of each node, and correlation matching among the nodes is realized; based on correlation matching analysis among the nodes, virtual impedance values among the nodes are calculated, so that whether topology connection among the nodes is abnormal or not can be accurately detected, and users with abnormal t</description><subject>CALCULATING</subject><subject>CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>CONVERSION OR DISTRIBUTION OF ELECTRIC POWER</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>ELECTRICITY</subject><subject>GENERATION</subject><subject>PHYSICS</subject><subject>SYSTEMS FOR STORING ELECTRIC ENERGY</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNjTEKwkAQRdNYiHqH8QApkiDWEhQLsbIPk-yYDO7uhJ3BkNsbwQNY_ffgwV9nr5tM-Vu8YU8wykQJ-sQOHBoCtlFSYJvBEnaELfuvBLJBHGB0oLMaBWhRyYFEQFXpGI0XDmjdwLFfQvSzsm6z1RO90u63m2x_OT_qa06jNKTjchHJmvpeFMfyUFZVear-aT4gjUH3</recordid><startdate>20231219</startdate><enddate>20231219</enddate><creator>HAN RONGJIE</creator><creator>WANG QIFENG</creator><creator>FANG XIANG</creator><creator>KIM MIN-HO</creator><creator>CHEN YIFANG</creator><creator>LIU JIAN</creator><creator>WANG YI</creator><creator>XING SHUANGSHUANG</creator><creator>ZHOU GUOHUA</creator><creator>CHEN YIXUAN</creator><creator>TU YONGWEI</creator><creator>ZHANG JIANSONG</creator><creator>LAI HANBIN</creator><creator>FAN LIBO</creator><creator>JIANG JIAN</creator><creator>CHIA BIN HUANG</creator><creator>YANG YI</creator><creator>SUN ZHIQING</creator><creator>NI XIABING</creator><creator>FENG XUE</creator><creator>XUAN YI</creator><creator>CHEN YUANZHONG</creator><creator>LI YA</creator><creator>LAI YIBO</creator><creator>HOU WEIHONG</creator><creator>ZHAO JIANPENG</creator><creator>ZHANG XUDONG</creator><creator>LIU XINGYE</creator><creator>XU RONGYONG</creator><scope>EVB</scope></search><sort><creationdate>20231219</creationdate><title>Low-voltage power grid data abnormity traceability method and system based on association matching analysis</title><author>HAN RONGJIE ; 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establishing a topology detection model based on virtual impedance, and deeply analyzing and measuring the electrical distance between the nodes; by introducing a double-implicit-layer recurrent neural network, modeling is carried out on a mapping relation among power flow variables in measurement data of each node, and correlation matching among the nodes is realized; based on correlation matching analysis among the nodes, virtual impedance values among the nodes are calculated, so that whether topology connection among the nodes is abnormal or not can be accurately detected, and users with abnormal t</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING CONVERSION OR DISTRIBUTION OF ELECTRIC POWER COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRICITY GENERATION PHYSICS SYSTEMS FOR STORING ELECTRIC ENERGY SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Low-voltage power grid data abnormity traceability method and system based on association matching analysis |
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