A. Mazare, L. Ionescu, D. Vişan, N. Belu, I. Lita, T. Eilks, V. Stan, C. Colceriu
{"title":"Intelligent system for determining the consumer profile and generate alarm in case of significant deviations from the profile","authors":"A. Mazare, L. Ionescu, D. Vişan, N. Belu, I. Lita, T. Eilks, V. Stan, C. Colceriu","doi":"10.1109/SIITME.2017.8259926","DOIUrl":null,"url":null,"abstract":"Electricity transmission networks have undergone significant changes over time but especially in the last decade through the emergence of small suppliers of electricity from unconventional sources but also through the emergence of new consumers. In this context, electricity consumption monitoring systems have also evolved from standard meters to smart meters and smart grids. The solution which we propose in this paper brings several improvements to smart metering systems that exist in commercial solutions or in other works papers. Our proposed solution uses a fully autonomous, easy-to-install monitoring system which can be installed at different points in the power transmission network. The acquired data are analyzed by a high-level analysis system based on artificial intelligence (ANN). This allows the automatic identification of a one-day consumer profile. Further, by continuing the monitoring, it is possible to identify deviations from that profile and trigger alarms in this case. The solution can be used to detect potential fraud or unintended loss of energy that may occur because of malfunction of some devices.","PeriodicalId":138347,"journal":{"name":"2017 IEEE 23rd International Symposium for Design and Technology in Electronic Packaging (SIITME)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 23rd International Symposium for Design and Technology in Electronic Packaging (SIITME)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIITME.2017.8259926","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Electricity transmission networks have undergone significant changes over time but especially in the last decade through the emergence of small suppliers of electricity from unconventional sources but also through the emergence of new consumers. In this context, electricity consumption monitoring systems have also evolved from standard meters to smart meters and smart grids. The solution which we propose in this paper brings several improvements to smart metering systems that exist in commercial solutions or in other works papers. Our proposed solution uses a fully autonomous, easy-to-install monitoring system which can be installed at different points in the power transmission network. The acquired data are analyzed by a high-level analysis system based on artificial intelligence (ANN). This allows the automatic identification of a one-day consumer profile. Further, by continuing the monitoring, it is possible to identify deviations from that profile and trigger alarms in this case. The solution can be used to detect potential fraud or unintended loss of energy that may occur because of malfunction of some devices.