Electric energy disaggregation via non-intrusive load monitoring: A state-of-the-art systematic review

Abstract

Appliance energy consumption tracking in a building is one of the vital enablers of energy and cost saving. An economical and viable solution would be to estimate individual appliance consumption from a single-point measurement without using dedicated appliance-wise sensors or sub-meters. Such solutions are called non-intrusive load monitoring or energy disaggregation. Though the technology was introduced around three decades ago, the recent deployments of smart meters and machine learning-based algorithms attract the researcher to develop many novel solutions to the technology. To this end, this paper aims to provide a comprehensive, unbiased, and systematic state-of-the-art review of the energy disaggregation technology by evaluating two research questions. These are, first, how did the research community approach to solve the NILM problem and how has the technology evolved, and second, how do various NILM solutions stand compared to others in terms of a few key attributes. Further, some key challenges and future research directions of the technology are highlighted.