[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 …

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 …

Artificial intelligence enabled demand response: Prospects and challenges in smart grid environment

MA Khan, AM Saleh, M Waseem, IA Sajjad - Ieee Access, 2022 - ieeexplore.ieee.org
Demand Response (DR) has gained popularity in recent years as a practical strategy to
increase the sustainability of energy systems while reducing associated costs. Despite this …

A survey on cybersecurity challenges, detection, and mitigation techniques for the smart grid

S Tufail, I Parvez, S Batool, A Sarwat - Energies, 2021 - mdpi.com
The world is transitioning from the conventional grid to the smart grid at a rapid pace.
Innovation always comes with some flaws; such is the case with a smart grid. One of the …

Data privacy preservation and security in smart metering systems

MS Abdalzaher, MM Fouda, MI Ibrahem - Energies, 2022 - mdpi.com
Smart meters (SMs) can play a key role in monitoring vital aspects of different applications
such as smart grids (SG), alternative currents (AC) optimal power flows, adversarial training …

Performance analysis of electricity theft detection for the smart grid: An overview

Z Yan, H Wen - IEEE Transactions on Instrumentation and …, 2021 - ieeexplore.ieee.org
Electricity theft has been a growing concern for the smart grid. It can be defined as follows:
illegal customers use energy from electric utilities without a contract or manipulate their …

[HTML][HTML] Deep learning for intelligent demand response and smart grids: A comprehensive survey

P Boopathy, M Liyanage, N Deepa, M Velavali… - Computer Science …, 2024 - Elsevier
Electricity is one of the mandatory commodities for mankind today. To address challenges
and issues in the transmission of electricity through the traditional grid, the concepts of smart …

Pattern-based and context-aware electricity theft detection in smart grid

RK Ahir, B Chakraborty - Sustainable Energy, Grids and Networks, 2022 - Elsevier
The smart grid offers numerous potential benefits for energy management by two-way
information transmission. However, the incorporation of smart infrastructure such as smart …

A review of non-technical loss attack models and detection methods in the smart grid

MG Chuwa, F Wang - Electric Power Systems Research, 2021 - Elsevier
The advanced metering infrastructure is a key building block for the smart grid, which is
responsible for facilitating communication between the smart meter and the electricity …

Anomaly detection and classification in power system state estimation: Combining model-based and data-driven methods

S Asefi, M Mitrovic, D Ćetenović, V Levi… - … Energy, Grids and …, 2023 - Elsevier
Power system state estimation is being faced with different types of anomalies. These might
include bad data caused by gross measurement errors or communication system failures …