Due to the continuous increase in the global energy demand, it is essential to find solutions
to improve energy efficiency. Non-intrusive load monitoring (NILM) is one of the most …

Short-term building energy consumption prediction is of great significance to the optimal
operation of building energy systems and conservation. Machine-learning models are …

The load disaggregation concept is gaining attention due to the increasing need for
optimized energy utilization and detailed characterization of electricity consumption profiles …

Behind the meter (BTM) distributed energy resources (DERs), such as photovoltaic (PV)
systems, battery energy storage systems (BESSs), and electric vehicle (EV) charging …

The massive deployment of smart meters in most Western countries in recent decades has
allowed the creation and development of a significant variety of applications, mainly related …

With the continuous increase in the proportion of renewable energy, accurate forecasting of
various tasks within integrated energy systems (IES) is becoming increasingly important …

This paper is devoted to the appliance load monitoring based on the harmonic analysis of
the steady-state current. The use of the current harmonic content enables a high accuracy in …

In the recent years, non-intrusive load monitoring (NILM) technique has received much
attention among researchers because of its effective monitoring of events and extraction of …

This paper proposes a new approach for load identification using a combination of fast
Fourier transform (FFT) and dynamic time warping (DTW) techniques. In this approach, first …

Toward the future smart energy consumption, non-intrusive load monitoring is a technology
with great potential by realizing the energy disaggregation in a user-friendly way. However …