9 papers
Multimodal Large Language Model Framework for Safe and Interpretable Grid-Integrated EVs
Jean Douglas Carvalho, Hugo Kenji, Ahmad Mohammad Saber +3
The integration of electric vehicles (EVs) into smart grids presents unique opportunities to enhance both transportation systems and energy networks. However, ensuring safe and int…
A Kolmogorov-Arnold Network for Interpretable Cyberattack Detection in AGC Systems
Jehad Jilan, Niranjana Naveen Nambiar, Ahmad Mohammad Saber +3
Automatic Generation Control (AGC) is essential for power grid stability but remains vulnerable to stealthy cyberattacks, such as False Data Injection Attacks (FDIAs), which can di…
Potential of Quantum Computing Applications for Smart Grid Digital Twins and Future Directions
Arianne Ornella Lemo, Ahmad Mohammad Saber, Deepa Kundur +1
The convergence of digital twin technology and quantum computing is opening new horizons for the modeling, control, and optimization of smart grid systems. This paper reviews the c…
Large Language Model-Based Framework for Explainable Cyberattack Detection in Automatic Generation Control Systems
Muhammad Sharshar, Ahmad Mohammad Saber, Davor Svetinovic +3
The increasing digitization of smart grids has improved operational efficiency but also introduced new cybersecurity vulnerabilities, such as False Data Injection Attacks (FDIAs) t…
Optimal Planning for Enhancing the Resilience of Modern Distribution Systems Against Cyberattacks
Armita Khashayardoost, Ahmad Mohammad Saber, Deepa Kundur
The increasing integration of IoT-connected devices in smart grids has introduced new vulnerabilities at the distribution level. Of particular concern is the potential for cyberatt…
Adversarial Attacks on Deep Learning-Based False Data Injection Detection in Differential Relays
Ahmad Mohammad Saber, Aditi Maheshwari, Amr Youssef +1
The application of Deep Learning-based Schemes (DLSs) for detecting False Data Injection Attacks (FDIAs) in smart grids has attracted significant attention. This paper demonstrates…