Recent trends of smart nonintrusive load monitoring in buildings: A review, open challenges, and future directions

Y Himeur, A Alsalemi, F Bensaali… - … Journal of Intelligent …, 2022 - Wiley Online Library
Smart nonintrusive load monitoring (NILM) represents a cost‐efficient technology for
observing power usage in buildings. It tackles several challenges in transitioning into a more …

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 …

Cyber–physical security of powertrain systems in modern electric vehicles: Vulnerabilities, challenges, and future visions

J Ye, L Guo, B Yang, F Li, L Du… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Power electronics systems have become increasingly vulnerable to cyber-physical threats
due to their growing penetration in the Internet-of-Things (IoT)-enabled applications …

A learnable image-based load signature construction approach in NILM for appliances identification

Y Zhang, H Wu, Q Ma, Q Yang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
One of the tasks of Non-Intrusive Load Monitoring (NILM) is load identification, which aims to
extract and classify altered electrical signals after switching events are detected. In this …

Low-frequency non-intrusive load monitoring of electric vehicles in houses with solar generation: generalisability and transferability

A Vavouris, B Garside, L Stankovic, V Stankovic - Energies, 2022 - mdpi.com
Electrification of transportation is gaining traction as a viable alternative to vehicles that use
fossil-fuelled internal combustion engines, which are responsible for a major part of carbon …

Effective identification of distributed energy resources using smart meter net‐demand data

AF Moreno Jaramillo, J Lopez‐Lorente… - IET Smart …, 2022 - Wiley Online Library
International policies and targets to globally reduce carbon dioxide emissions have
contributed to increasing penetration of distributed energy resources (DER) in low‐voltage …

Distributed energy resources electric profile identification in low voltage networks using supervised machine learning techniques

AFM Jaramillo, J Lopez-Lorente, DM Laverty… - IEEE …, 2023 - ieeexplore.ieee.org
Increasing integration of distributed energy resources (DER) in the electrical network has led
distribution network operators to unprecedented challenges. This issue is compounded by …

Electric vehicle identification in low-sampling non-intrusive load monitoring systems using machine learning

S Khaleghian, T Tran, J Cho, A Harris… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
The prediction is that by 2030, electric vehicles (EVs) will make up 40% of total passenger
car sales in the USA. This surge in EV adoption poses a significant challenge to the electric …

Identifying household EV models via weighted power recurrence graphs

H Wang, J Ma, J Zhu - Electric Power Systems Research, 2023 - Elsevier
Electric vehicles (EVs) are becoming the mainstream transport means in the near future and
will play an important role in smart grids with the benefit of energy storage and power factor …

Non-Intrusive Load Monitoring for Feeder-Level EV Charging Detection: Sliding Window-Based Approaches to Offline and Online Detection

C Martin, F Ke, H Wang - 2023 IEEE 7th Conference on Energy …, 2023 - ieeexplore.ieee.org
Understanding electric vehicle (EV) charging on the distribution network is key to effective
EV charging management and aiding decarbonization across the energy and transport …