Non-intrusive load monitoring: A review

PA Schirmer, I Mporas - IEEE Transactions on Smart Grid, 2022 - ieeexplore.ieee.org
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 …

[HTML][HTML] Aggregated demand-side energy flexibility: A comprehensive review on characterization, forecasting and market prospects

F Plaum, R Ahmadiahangar, A Rosin, J Kilter - Energy Reports, 2022 - Elsevier
Existing grids have been designed with traditional large centralized generation in mind;
however, with the ever-increasing utilization of renewable distributed energy resources, the …

Plug-Mate: An IoT-based occupancy-driven plug load management system in smart buildings

ZD Tekler, R Low, C Yuen, L Blessing - Building and Environment, 2022 - Elsevier
Plug load management systems are touted as promising solutions to reduce the rising
energy consumption of plug loads in commercial buildings through different load monitoring …

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 …

Application of load monitoring in appliances' energy management–A review

I Abubakar, SN Khalid, MW Mustafa, H Shareef… - … and Sustainable Energy …, 2017 - Elsevier
Energy monitoring is one of the important aspects of the energy management, as such there
is a need to monitor the power consumption of a premises before planning some of the …

Smart home energy management system–a review

AQH Badar, A Anvari-Moghaddam - Advances in Building Energy …, 2022 - Taylor & Francis
Smart grid is providing new opportunities and techniques for supplying high energy demand
of the ever growing energy industry. One-third of the total energy demand comes from the …

A survey on machine learning-based performance improvement of wireless networks: PHY, MAC and network layer

M Kulin, T Kazaz, E De Poorter, I Moerman - Electronics, 2021 - mdpi.com
This paper presents a systematic and comprehensive survey that reviews the latest research
efforts focused on machine learning (ML) based performance improvement of wireless …

LSTM and edge computing for big data feature recognition of industrial electrical equipment

CF Lai, WC Chien, LT Yang… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
With the rapid development of Industrial Internet of Things, the category and quantity of
industrial equipment will increase gradually. For centralized monitoring and management of …

[HTML][HTML] Design and implementation of an Internet-of-Things-enabled smart meter and smart plug for home-energy-management system

IB Dhaou - Electronics, 2023 - mdpi.com
The demand response program is an important feature of the smart grid. It attempts to
reduce peak demand, improve the smart grid efficiency, and ensure system reliability …

Sequence to point learning based on bidirectional dilated residual network for non-intrusive load monitoring

Z Jia, L Yang, Z Zhang, H Liu, F Kong - International Journal of Electrical …, 2021 - Elsevier
Abstract Non-Intrusive Load Monitoring (NILM) or Energy Disaggregation, seeks to save
energy by decomposing corresponding appliances power reading from an aggregate power …