The market for energy management technology is promising, driven by the increasing demand for energy-efficient solutions and the growing adoption of smart homes and buildings. Key trends and ...

Nonintrusive load monitoring (NILM) is an effective approach for energy management that disaggregates the total power measured at the main power inlet into appliance-level power signals. NILM ...

A comprehensive toolkit for synthesizing photovoltaic (PV) energy injection into public NILM datasets. This project enables researchers to create realistic scenarios of residential solar energy ...

Non-intrusive load monitoring (NILM) is a key way to cost-effectively acquire appliance-level information in advanced metering infrastructure (AMI). Recently, federated learning has enabled NILM to ...

With the increasing demand for the refined management of residential loads, the study of the non-invasive load monitoring (NILM) technologies has attracted much attention in recent years. This paper ...

Machine learning is an Artificial Intelligence (or AI) application, an idea that came into being by giving machines access to data and letting them learn by themselves. AI has been making headlines, ...

Non-Intrusive Load Monitoring (NILM) is a technique for inferring the electrical usage patterns of individual devices within a larger electrical system without the need for direct measurement of each ...

Abstract: The non-intrusive load monitoring (NILM) is the basis and key to the sensing and measurement of the digital grid. However, the NILM algorithms, which rely on the training dataset, suffer ...

This code repository implements four weight pruning algorithms designed to reduce the size of Zhang et al.'s sequence-to-point deep learning model for use in energy disaggreation / non-intrusive load ...

Abstract: Online non-intrusive load monitoring algorithms have captivated academia and industries as parsimonious solutions for household energy efficiency monitoring as well as a safety control, ...

In the traditional non-invasive load monitoring (NILM) algorithms, the identification accuracy is enhanced with the increased network scale while sacrificing the calculation speed, which restricts the ...