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Non-intrusive load monitoring (NILM) is the task of disaggregating the totalpower consumption into its individual sub-components. Over the years, signalprocessing and machine learning algorithms have been combined to achieve this.A lot of publications and extensive research works are performed on energydisaggregation or NILM for the state-of-the-art methods to reach on thedesirable performance. The initial interest of the scientific community toformulate and describe mathematically the NILM problem using machine learningtools has now shifted into a more practical NILM. Nowadays, we are in themature NILM period where there is an attempt for NILM to be applied inreal-life application scenarios. Thus, complexity of the algorithms,transferability, reliability, practicality and in general trustworthiness arethe main issues of interest. This review narrows the gap between the earlyimmature NILM era and the mature one. In particular, the paper provides acomprehensive literature review of the NILM methods for residential appliancesonly. The paper analyzes, summarizes and presents the outcomes of a largenumber of recently published scholarly articles. Also, the paper discusses thehighlights of these methods and introduces the research dilemmas that should betaken into consideration by researchers to apply NILM methods. Finally, we showthe need for transferring the traditional disaggregation models into apractical and trustworthy framework.

Towards trustworthy Energy Disaggregation: A review of challenges, methods and perspectives for Non-Intrusive Load Monitoring