{"title":"A Commercial Building Plug Load Management System That Uses Internet of Things Technology to Automatically Identify Plugged-In Devices and Their Locations","authors":"Amy LeBar, Kim L. Trenbath, Bennett Doherty, William Livingood","volume":177,"journal":"International Journal of Energy and Environmental Engineering","pagesStart":279,"pagesEnd":288,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10012286","abstract":"
Plug and process loads (PPLs) account for a large portion of U.S. commercial building energy use. There is a huge potential to reduce whole building consumption by targeting PPLs for energy savings measures or implementing some form of plug load management (PLM). Despite this potential, there has yet to be a widely adopted commercial PLM technology. This paper describes the Automatic Type and Location Identification System (ATLIS), a PLM system framework with automatic and dynamic load detection (ADLD). ADLD gives PLM systems the ability to automatically identify devices as they are plugged into the outlets of a building. The ATLIS framework takes advantage of smart, connected devices to identify device locations in a building, meter and control their power, and communicate this information to a central database. ATLIS includes five primary capabilities: location identification, communication, control, energy metering, and data storage. A laboratory proof of concept (PoC) demonstrated all but the energy metering capability, and these capabilities were validated using a series of system tests. The PoC was able to identify when a device was plugged into an outlet and the location of the device in the building. When a device was moved, the PoC\u2019s dashboard and database were automatically updated with the new location. The PoC implemented controls to devices from the system dashboard so that devices maintained correct schedules regardless of where they were plugged in within the building. ATLIS\u2019s primary technology application is improved PLM, but other applications include asset management, energy audits, and interoperability for grid-interactive efficient buildings. An ATLIS-based system could also be used to direct power to critical devices, such as ventilators, during a brownout or blackout. Such a framework is an opportunity to make PLM more widespread and reduce the amount of energy consumed by PPLs in current and future commercial buildings.<\/p>","references":"[1]\tU.S. Energy Information Administration, \u201cAnnual Energy Outlook 2020,\u201d 2020.\r\n[2]\tA. J. Kandt and M. R. Langner, \u201cPlug Load Management System Field Study,\u201d Golden, CO (United States), Feb. 2019, doi: 10.2172\/1495720.\r\n[3]\tM. R. Langner, R. Langner, and T.-K. L. Trenbath, \u201cIntegrating Smart Plug and Process Load Controls into Energy Management Information System Platforms: A Landscaping Study,\u201d Golden, CO (United States), Jun. 2019, doi: 10.2172\/1530714.\r\n[4]\tK. Trenbath, B. Doherty, K. Vrabel, and C. Burke, \u201cEmerging Technologies for Improved Plug Load Management Systems: Learning Behavior Algorithms and Automatic and Dynamic Load Detection,\u201d in ACEEE Summer Study on Energy Efficiency in Buildings, 2020. (Online). 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