A Survey on Non-Intrusive Load Monitoring Methodies and Techniques for Energy Disaggregation Problem

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dc.contributor.author Faustine, Anthony
dc.contributor.author Mvungi, Nerey Henry
dc.contributor.author Kaijage, Shubi
dc.contributor.author Michael, Kisangiri
dc.date.accessioned 2019-08-22T07:28:24Z
dc.date.available 2019-08-22T07:28:24Z
dc.date.issued 2017-03
dc.identifier.uri http://dspace.nm-aist.ac.tz/handle/123456789/417
dc.description Research Article published by Cornell University en_US
dc.description.abstract The rapid urbanization of developing countries coupled with explosion in construction of high rising buildings and the high power usage in them calls for conservation and e cient energy program. Such a programme require monitoring of end-use appliances energy consumption in real-time. The worldwide recent adoption of smart-meter in smart-grid, has led to the rise of Non-Intrusive Load Monitoring (NILM); which enables estimation of appliance-speci c power consumption from building's aggregate power consumption reading. NILM provides households with cost-e ective real-time monitoring of end-use appliances to help them understand their con- sumption pattern and become part and parcel of energy conservation strategy. This paper presents an up to date overview of NILM system and its associated methods and techniques for energy disaggregation problem. This is followed by the review of the state-of-the art NILM algorithms. Furthermore, we review several perfor- mance metrics used by NILM researcher to evaluate NILM algorithms and discuss existing benchmarking framework for direct comparison of the state of the art NILM algorithms. Finally, the paper discuss potential NILM use-cases, presents an overview of the public available dataset and highlight challenges and future research directions. en_US
dc.language.iso en en_US
dc.publisher Cornell University en_US
dc.subject Research Subject Categories::NATURAL SCIENCES en_US
dc.title A Survey on Non-Intrusive Load Monitoring Methodies and Techniques for Energy Disaggregation Problem en_US
dc.type Article en_US

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