The rapid development of technology in the electrical energy sector within the last 20 years
has led to growing electric power needs through the increased number of electrical …

Nonintrusive appliance load monitoring (NIALM) allows disaggregation of total electricity
consumption into particular appliances in domestic or industrial environments. NIALM …

In this paper we evaluate several well-known and widely used machine learning algorithms
for regression in the energy disaggregation task. Specifically, the Non-Intrusive Load …

In this article an energy disaggregation architecture using elastic matching algorithms is
presented. The architecture uses a database of reference energy consumption signatures …

A data-driven methodology to improve the energy disaggregation accuracy during Non-
Intrusive Load Monitoring is proposed. In detail, the method uses a two-stage classification …

Non-Intrusive Load Monitoring aims to extract the energy consumption of individual
electrical appliances through disaggregation of the total power load measured by a single …

Significant progress has been achieved in managing energy consumption in the residential
sector in recent years. However, the industrial sector requires better coverage due to its …

In this paper we evaluate several well-known and widely used machine learning algorithms
for regression in the energy disaggregation task. Specifically, the Non-Intrusive Load …

Non-intrusive load monitoring (NILM) has recently become a promising and trending topic in
energy management. Although several NILM-based solutions were proposed, a commercial …

An extension of the baseline non-intrusive load monitoring approach for energy
disaggregation using temporal contextual information is presented in this paper. In detail …