Load forecasting techniques and their applications in smart grids
The growing success of smart grids (SGs) is driving increased interest in load forecasting
(LF) as accurate predictions of energy demand are crucial for ensuring the reliability …
(LF) as accurate predictions of energy demand are crucial for ensuring the reliability …
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 …
Clustering and ensemble based approach for securing electricity theft detectors against evasion attacks
In smart power grids, electricity theft causes huge economic losses to electrical utility
companies. Machine learning (ML), especially deep neural network (DNN) models hold …
companies. Machine learning (ML), especially deep neural network (DNN) models hold …
A survey on key management and authentication approaches in smart metering systems
The implementation of the smart grid (SG) and cyber-physical systems (CPS) greatly
enhances the safety, reliability, and efficiency of energy production and distribution. Smart …
enhances the safety, reliability, and efficiency of energy production and distribution. Smart …
Federated Learning for Smart Grid: A Survey on Applications and Potential Vulnerabilities
The Smart Grid (SG) is a critical energy infrastructure that collects real-time electricity usage
data to forecast future energy demands using information and communication technologies …
data to forecast future energy demands using information and communication technologies …
A novel evasion attack against global electricity theft detectors and a countermeasure
The smart grid advanced metering infrastructure (AMI) is vulnerable to electricity theft cyber-
attacks in which malicious smart meters report low readings to reduce the consumers' bills …
attacks in which malicious smart meters report low readings to reduce the consumers' bills …
Privacy-Preserving Data-Driven Learning Models for Emerging Communication Networks: A Comprehensive Survey
With the proliferation of Beyond 5G (B5G) communication systems and heterogeneous
networks, mobile broadband users are generating massive volumes of data that undergo …
networks, mobile broadband users are generating massive volumes of data that undergo …
Towards Secured Smart Grid 2.0: Exploring Security Threats, Protection Models, and Challenges
Many nations are promoting the green transition in the energy sector to attain neutral carbon
emissions by 2050. SG2 is expected to explore data-driven analytics and enhance …
emissions by 2050. SG2 is expected to explore data-driven analytics and enhance …
Privacy-preserving detection of power theft in smart grid change and transmit (CAT) advanced metering infrastructure
For energy management and billing purposes, advanced metering infrastructure (AMI)
requires periodic transmission of consumer power consumption readings by smart meters to …
requires periodic transmission of consumer power consumption readings by smart meters to …
Electricity theft detection using deep reinforcement learning in smart power grids
In smart power grids, smart meters (SMs) are deployed at the end side of customers to report
fine-grained power consumption readings periodically to the utility for energy management …
fine-grained power consumption readings periodically to the utility for energy management …