[HTML][HTML] Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives

Y Himeur, K Ghanem, A Alsalemi, F Bensaali, A Amira - Applied Energy, 2021 - Elsevier
Enormous amounts of data are being produced everyday by sub-meters and smart sensors
installed in residential buildings. If leveraged properly, that data could assist end-users …

A survey of recent advances in edge-computing-powered artificial intelligence of things

Z Chang, S Liu, X Xiong, Z Cai… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) has created a ubiquitously connected world powered by a
multitude of wired and wireless sensors generating a variety of heterogeneous data over …

Control and optimisation of power grids using smart meter data: A review

Z Chen, AM Amani, X Yu, M Jalili - Sensors, 2023 - mdpi.com
This paper provides a comprehensive review of the applications of smart meters in the
control and optimisation of power grids to support a smooth energy transition towards the …

Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects

T Berghout, M Benbouzid, SM Muyeen - International Journal of Critical …, 2022 - Elsevier
Abstract In modern Smart Grids (SGs) ruled by advanced computing and networking
technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this …

A survey on cybersecurity, data privacy, and policy issues in cyber-physical system deployments in smart cities

H Habibzadeh, BH Nussbaum, F Anjomshoa… - Sustainable Cities and …, 2019 - Elsevier
Abstract Deployments of Cyber Physical Systems (CPSs) in smart cities are poised to
significantly improve healthcare, transportation services, utilities, safety, and environmental …

Cyber threats to smart grids: Review, taxonomy, potential solutions, and future directions

J Ding, A Qammar, Z Zhang, A Karim, H Ning - Energies, 2022 - mdpi.com
Smart Grids (SGs) are governed by advanced computing, control technologies, and
networking infrastructure. However, compromised cybersecurity of the smart grid not only …

Electricity theft detection base on extreme gradient boosting in AMI

Z Yan, H Wen - IEEE Transactions on Instrumentation and …, 2021 - ieeexplore.ieee.org
Metering data from the advanced metering infrastructure can be used to find abnormal
electricity behavior for the detection of electricity theft, which causes huge financial losses to …

Smart grid big data analytics: Survey of technologies, techniques, and applications

D Syed, A Zainab, A Ghrayeb, SS Refaat… - IEEE …, 2020 - ieeexplore.ieee.org
Smart grids have been gradually replacing the traditional power grids since the last decade.
Such transformation is linked to adding a large number of smart meters and other sources of …

FedDetect: A novel privacy-preserving federated learning framework for energy theft detection in smart grid

M Wen, R Xie, K Lu, L Wang… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
In smart grids, a major challenge is how to effectively utilize consumers' energy consumption
data while preserving security and privacy. In this article, we tackle this challenging issue …

Detecting false data attacks using machine learning techniques in smart grid: A survey

L Cui, Y Qu, L Gao, G Xie, S Yu - Journal of Network and Computer …, 2020 - Elsevier
The big data sources in smart grid (SG) enable utilities to monitor, control, and manage the
energy system effectively, which is also promising to advance the efficiency, reliability, and …