Research Article published by Cornell University
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.