[HTML][HTML] Dynamic modeling, stability analysis and control of interconnected microgrids: A review
This paper reviews concepts of interconnected microgrids (IMGs) as well as compare and
classify their modeling, stability analysis, and control methods. To develop benefits of …
classify their modeling, stability analysis, and control methods. To develop benefits of …
Deep learning for cybersecurity in smart grids: Review and perspectives
Protecting cybersecurity is a non‐negotiable task for smart grids (SG) and has garnered
significant attention in recent years. The application of artificial intelligence (AI), particularly …
significant attention in recent years. The application of artificial intelligence (AI), particularly …
Resilient secondary control and stability analysis for DC microgrids under mixed cyber attacks
Distributed control technology has significantly improved the regulation of dc microgrid
systems. However, it also introduces potential cyber-security threats during the …
systems. However, it also introduces potential cyber-security threats during the …
Fusion of microgrid control with model-free reinforcement learning: Review and vision
Challenges and opportunities coexist in microgrids as a result of emerging large-scale
distributed energy resources (DERs) and advanced control techniques. In this paper, a …
distributed energy resources (DERs) and advanced control techniques. In this paper, a …
Reinforcement learning-based intelligent control strategies for optimal power management in advanced power distribution systems: A survey
Intelligent energy management in renewable-based power distribution applications, such as
microgrids, smart grids, smart buildings, and EV systems, is becoming increasingly important …
microgrids, smart grids, smart buildings, and EV systems, is becoming increasingly important …
Experimental validation of a remedial action via Hardware-in-the-Loop System against cyberattacks targeting a lab-scale PV/Wind Microgrid
This paper experimentally validates the effectiveness of a primary/backup framework in
preventing/mitigating the impacts of false data injection (FDI) cyberattacks targeting a lab …
preventing/mitigating the impacts of false data injection (FDI) cyberattacks targeting a lab …
Destabilizing attack and robust defense for inverter-based microgrids by adversarial deep reinforcement learning
The controllers of inverter-based resources (IBRs) can be adjustable by grid operators to
facilitate regulation services. Considering the increasing integration of IBRs at power …
facilitate regulation services. Considering the increasing integration of IBRs at power …
A review of AI-based cyber-attack detection and mitigation in microgrids
In this paper, the application and future vision of Artificial Intelligence (AI)-based techniques
in microgrids are presented from a cyber-security perspective of physical devices and …
in microgrids are presented from a cyber-security perspective of physical devices and …
Reinforcement learning-based method to exploit vulnerabilities of false data injection attack detectors in modular multilevel converters
Implementing control schemes for modular multilevel converters (M2Cs) involves both a
cyber and a physical level, leading to a cyber-physical system (CPS). At the cyber level, a …
cyber and a physical level, leading to a cyber-physical system (CPS). At the cyber level, a …
A comprehensive survey on the security of smart grid: Challenges, mitigations, and future research opportunities
In this study, we conduct a comprehensive review of smart grid security, exploring system
architectures, attack methodologies, defense strategies, and future research opportunities …
architectures, attack methodologies, defense strategies, and future research opportunities …