[HTML][HTML] Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives
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 …
installed in residential buildings. If leveraged properly, that data could assist end-users …
Machine learning driven smart electric power systems: Current trends and new perspectives
MS Ibrahim, W Dong, Q Yang - Applied Energy, 2020 - Elsevier
The current power systems are undergoing a rapid transition towards their more active,
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …
FedDetect: A novel privacy-preserving federated learning framework for energy theft detection in smart grid
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 …
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
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 …
energy system effectively, which is also promising to advance the efficiency, reliability, and …
Non-technical losses: A systematic contemporary article review
Non-technical losses refer to all electricity consumption not billed and represent a significant
problem that has consequences to all sectors and a substantial negative impact on some …
problem that has consequences to all sectors and a substantial negative impact on some …
Review of the data-driven methods for electricity fraud detection in smart metering systems
In smart grids, homes are equipped with smart meters (SMs) to monitor electricity
consumption and report fine-grained readings to electric utility companies for billing and …
consumption and report fine-grained readings to electric utility companies for billing and …
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 …
illegal customers use energy from electric utilities without a contract or manipulate their …
Security risk modeling in smart grid critical infrastructures in the era of big data and artificial intelligence
Smart grids (SG) emerged as a response to the need to modernize the electricity grid. The
current security tools are almost perfect when it comes to identifying and preventing known …
current security tools are almost perfect when it comes to identifying and preventing known …
Reliable industry 4.0 based on machine learning and IOT for analyzing, monitoring, and securing smart meters
The modern control infrastructure that manages and monitors the communication between
the smart machines represents the most effective way to increase the efficiency of the …
the smart machines represents the most effective way to increase the efficiency of the …
[HTML][HTML] Deep learning for intelligent demand response and smart grids: A comprehensive survey
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 …
and issues in the transmission of electricity through the traditional grid, the concepts of smart …