Non-Intrusive Load Monitoring in industrial settings: A systematic review

Giulia Tanoni, Emanuele Principi and Stefano Squartini

Renewable and Sustainable Energy Reviews, 2024, vol. 202, issue C

Abstract: Addressing climate change and promoting sustainable energy practices is a pressing issue in our era and requires a comprehensive transformation of our energy production, transportation, and consumption methods. This is particularly relevant for industries and residential buildings, which together represent 70% of the total electricity demand. The Smart Grid, with its real-time data collection and renewable energy management capabilities, promotes energy awareness and intelligent energy transactions. Recent studies have highlighted the untapped potential for energy reduction in industrial settings. However, the effective deployment of advanced methodologies to enhance energy efficiency in these settings necessitates a detailed understanding of consumption patterns Non-Intrusive Load Monitoring (NILM), a technique that disaggregates consumption at the device level, has been identified as a key strategy in this context. Although NILM has been widely applied in residential settings, the need for its application in industrial settings is increasingly acknowledged, given the complexities associated with installing electrical sensors in such environments. Notably, the last review dedicated to NILM for industrial settings was published in 2015. In light of the growing body of research, this work aims, for the first time, to systematically collect, organize, and analyze the literature published to date. This is crucial for the ongoing research in this field and to highlight open challenges and limitations.

Keywords: Non-Intrusive Load Monitoring; Industrial loads; Energy consumption; Smart grid; Machine learning; Load identification; Load disaggregation (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.rser.2024.114703

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