Sam Moayedi, Hamed Nabizadeh Rafsanjani, S. Shom, M. Alahmad, C. Ahn
{"title":"用于电源管理应用的实时远程能耗定位","authors":"Sam Moayedi, Hamed Nabizadeh Rafsanjani, S. Shom, M. Alahmad, C. Ahn","doi":"10.1080/17512549.2019.1699858","DOIUrl":null,"url":null,"abstract":"ABSTRACT Electricity generation continue to increase to meet the ever-growing demand of the built environment. Building’s miscellaneous plug loads are targeted for energy savings potentials. However, to achieve these savings, monitoring their energy consumption and providing comprehensive real-time energy usage information to the end-user is paramount. Real-time energy monitoring devices are significant tools for this purpose. However, deploying these devices for each load and for entire building, is cost-prohibitive. An alternative approach is to deploy tools to remotely identify the location of active-loads in real-time. This research proposes the development of the Energy Node Locating Method (ENLM) platform that remotely locates and measures power consuming loads at every electrical node, in the building, in real-time based on Sequence Time Domain Reflectometry (STDR). The proposed ENLM utilizes the measured time-delay between an injected and reflected signal at a branch circuit from any connected load to calculate the length of the physical wire to identify the location of energy usage. This information with real-time power consumption data are correlated with occupant’s entry data to identify where and how much energy is used. Various tests are conducted to validate the proposed platform, and the results confirm the validity of the platform.","PeriodicalId":46184,"journal":{"name":"Advances in Building Energy Research","volume":"15 1","pages":"662 - 682"},"PeriodicalIF":2.1000,"publicationDate":"2019-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17512549.2019.1699858","citationCount":"3","resultStr":"{\"title\":\"Real-time remote energy consumption location for power management application\",\"authors\":\"Sam Moayedi, Hamed Nabizadeh Rafsanjani, S. Shom, M. Alahmad, C. Ahn\",\"doi\":\"10.1080/17512549.2019.1699858\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Electricity generation continue to increase to meet the ever-growing demand of the built environment. Building’s miscellaneous plug loads are targeted for energy savings potentials. However, to achieve these savings, monitoring their energy consumption and providing comprehensive real-time energy usage information to the end-user is paramount. Real-time energy monitoring devices are significant tools for this purpose. However, deploying these devices for each load and for entire building, is cost-prohibitive. An alternative approach is to deploy tools to remotely identify the location of active-loads in real-time. This research proposes the development of the Energy Node Locating Method (ENLM) platform that remotely locates and measures power consuming loads at every electrical node, in the building, in real-time based on Sequence Time Domain Reflectometry (STDR). The proposed ENLM utilizes the measured time-delay between an injected and reflected signal at a branch circuit from any connected load to calculate the length of the physical wire to identify the location of energy usage. This information with real-time power consumption data are correlated with occupant’s entry data to identify where and how much energy is used. Various tests are conducted to validate the proposed platform, and the results confirm the validity of the platform.\",\"PeriodicalId\":46184,\"journal\":{\"name\":\"Advances in Building Energy Research\",\"volume\":\"15 1\",\"pages\":\"662 - 682\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2019-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/17512549.2019.1699858\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Building Energy Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/17512549.2019.1699858\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CONSTRUCTION & BUILDING TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Building Energy Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/17512549.2019.1699858","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
Real-time remote energy consumption location for power management application
ABSTRACT Electricity generation continue to increase to meet the ever-growing demand of the built environment. Building’s miscellaneous plug loads are targeted for energy savings potentials. However, to achieve these savings, monitoring their energy consumption and providing comprehensive real-time energy usage information to the end-user is paramount. Real-time energy monitoring devices are significant tools for this purpose. However, deploying these devices for each load and for entire building, is cost-prohibitive. An alternative approach is to deploy tools to remotely identify the location of active-loads in real-time. This research proposes the development of the Energy Node Locating Method (ENLM) platform that remotely locates and measures power consuming loads at every electrical node, in the building, in real-time based on Sequence Time Domain Reflectometry (STDR). The proposed ENLM utilizes the measured time-delay between an injected and reflected signal at a branch circuit from any connected load to calculate the length of the physical wire to identify the location of energy usage. This information with real-time power consumption data are correlated with occupant’s entry data to identify where and how much energy is used. Various tests are conducted to validate the proposed platform, and the results confirm the validity of the platform.