[HTML][HTML] Towards trustworthy energy disaggregation: A review of challenges, methods, and perspectives for non-intrusive load monitoring

M Kaselimi, E Protopapadakis, A Voulodimos… - Sensors, 2022 - mdpi.com
Non-intrusive load monitoring (NILM) is the task of disaggregating the total power
consumption into its individual sub-components. Over the years, signal processing and …

Electric energy disaggregation via non-intrusive load monitoring: A state-of-the-art systematic review

S Dash, NC Sahoo - Electric Power Systems Research, 2022 - Elsevier
Appliance energy consumption tracking in a building is one of the vital enablers of energy
and cost saving. An economical and viable solution would be to estimate individual …

An event-driven convolutional neural architecture for non-intrusive load monitoring of residential appliance

D Yang, X Gao, L Kong, Y Pang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Nowadays, the advancement of non-intrusive load monitoring (NILM) is hastened by the
everincreasing requirements for smart power utilization and demand side management …

IoT based approach for load monitoring and activity recognition in smart homes

P Franco, JM Martinez, YC Kim, MA Ahmed - ieee access, 2021 - ieeexplore.ieee.org
Appliance load monitoring in smart homes has been gaining importance due to its
significant advantages in achieving an energy efficient smart grid. The methods to manage …

Real-time non-intrusive load monitoring: A light-weight and scalable approach

CL Athanasiadis, TA Papadopoulos, DI Doukas - Energy and Buildings, 2021 - Elsevier
Non-intrusive load monitoring (NILM) is a topic that lately attracts both the academic and the
industrial interest. NILM is used to reveal useful information regarding the consumption …

A scalable real-time non-intrusive load monitoring system for the estimation of household appliance power consumption

C Athanasiadis, D Doukas, T Papadopoulos… - Energies, 2021 - mdpi.com
Smart-meter technology advancements have resulted in the generation of massive volumes
of information introducing new opportunities for energy services and data-driven business …

A smart home energy management system utilizing neurocomputing-based time-series load modeling and forecasting facilitated by energy decomposition for smart …

YH Lin, HS Tang, TY Shen, CH Hsia - IEEE Access, 2022 - ieeexplore.ieee.org
The key advantage of using power-utility-owned smart meters is the ability to transmit
electrical energy consumption data to power utilities' remote data centers for various …

A low-rank learning-based multi-label security solution for industry 5.0 consumers using machine learning classifiers

A Sharma, S Rani, AK Bashir, M Krichen… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
The need for networking in smart industries known as Industry 5.0 has grown critical, and it
is especially important for the security and privacy of the applications. To counter threats to …

Load modelling and non-intrusive load monitoring to integrate distributed energy resources in low and medium voltage networks

AFM Jaramillo, DM Laverty, DJ Morrow… - Renewable Energy, 2021 - Elsevier
In many countries distributed energy resources (DER)(eg photovoltaics, batteries, wind
turbines, electric vehicles, electric heat pumps, air-conditioning units and smart domestic …

Methods and attributes for customer-centric dynamic electricity tariff design: A review

T Rahman, ML Othman, SBM Noor… - … and Sustainable Energy …, 2024 - Elsevier
Most of the developed and develo** countries around the world are delving into the
implementation of demand response (DR) strategies in demand side management (DSM) to …