[HTML][HTML] Systematic review of energy theft practices and autonomous detection through artificial intelligence methods
E Stracqualursi, A Rosato, G Di Lorenzo… - … and Sustainable Energy …, 2023 - Elsevier
Energy theft poses a significant challenge for all parties involved in energy distribution, and
its detection is crucial for maintaining stable and financially sustainable energy grids. One …
its detection is crucial for maintaining stable and financially sustainable energy grids. One …
Review of application of high frequency smart meter data in energy economics and policy research
The rapid popularization of advanced metering infrastructure (AMI) smart meters produces
customer high-frequency energy consumption data. These data provide diverse options for …
customer high-frequency energy consumption data. These data provide diverse options for …
Advanced Deep Learning Models for 6G: Overview, Opportunities and Challenges
The advent of the sixth generation of mobile communications (6G) ushers in an era of
heightened demand for advanced network intelligence to tackle the challenges of an …
heightened demand for advanced network intelligence to tackle the challenges of an …
[HTML][HTML] Hybrid KNN-SVM machine learning approach for solar power forecasting
Predictions about solar power will have a significant impact on large-scale renewable
energy plants. Photovoltaic (PV) power generation forecasting is particularly sensitive to …
energy plants. Photovoltaic (PV) power generation forecasting is particularly sensitive to …
An overview of reinforcement learning-based approaches for smart home energy management systems with energy storages
The paper's state-of-the-art review focuses on an in-depth evaluation of smart home energy
management systems which employ reinforcement learning-based methods to integrate …
management systems which employ reinforcement learning-based methods to integrate …
Household electricity consumer classification using novel clustering approach, review, and case study
There is an increasing demand for electricity on a global level. Thus, the utility companies
are looking for the effective implementation of demand response management (DRM). For …
are looking for the effective implementation of demand response management (DRM). For …
Quantum Reinforcement Learning for Spatio-Temporal Prioritization in Metaverse
A metaverse is composed of a physical-space and virtual-space, with the aim of having
users in both the virtual reality and the real world experience. Prioritization is essential, but it …
users in both the virtual reality and the real world experience. Prioritization is essential, but it …
[HTML][HTML] CNN-AdaBoost based hybrid model for electricity theft detection in smart grid
As the use of deep learning models is increased in smart grid systems, especially in load
forecasting, supply-demand response, vulnerability detection, and finding abnormal …
forecasting, supply-demand response, vulnerability detection, and finding abnormal …
LITE-FORT: Lightweight three-stage energy theft detection based on time series forecasting of consumption patterns
S Aoufi, A Derhab, M Guerroumi… - Electric Power Systems …, 2023 - Elsevier
Energy theft is one of the serious threats to smart grid. It occurs when meter readings are
illegally manipulated. In this paper, we propose LITE-FORT, an energy theft detector based …
illegally manipulated. In this paper, we propose LITE-FORT, an energy theft detector based …
Privacy-Preserving Federated Learning System (f-PPLS) for military focused area classification
Accurate classification of military-focused areas using machine learning techniques is
crucial for meeting military criteria. However, preserving high data privacy in aerial image …
crucial for meeting military criteria. However, preserving high data privacy in aerial image …