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Context-Aware Plug-Load Identification Toward Enhanced Energy Efficiency in the Built Environment

Abstract:

Electrical plug loads and appliances have evolved over time to provide sophisticated functions to occupants in a building, and they account for a big share of building's energy consumption. Despite their evolution, they are still unmanageable in commercial and industrial buildings, unlike lighting or air conditioning that are fixed infrastructures managed by an intelligent software layer, such as a building management system. The qualities of heterogeneity, numerosity, spatial irregularity, and displaceability have impeded efficient management of plug loads, unless they are appropriately identified in real time. Decades of efforts in both intrusive and nonintrusive load monitoring have not yielded any sufficiently reliable universal mechanism to identify plug loads. In this article, a practical method of uniquely identifying plug loads using a novel socket cyber-physical system is proposed. This socket/receptacle can access the metadata and operational data of plug loads in an automated fashion, thus yielding a live digital profile of plug loads connected to sockets. Based on acquired intelligence, a supervisory control system can contextually identify the plug loads to provide several digitalized services. Various benefits and use cases of the proposed smart cyber-physical system are explained, inclusive of improvement in operational energy efficiency of plug loads.