4 papers
Quantum-Accelerated Deep Reinforcement Learning for Frequency Regulation Enhancement
Amin Masoumi, Mert Korkali
In modern power systems, frequency regulation is a fundamental prerequisite for ensuring system reliability and assessing the robustness of expansion projects. Conventional feedbac…
Quantum-Embedded Dynamic Security Control using Hybrid Deep Reinforcement Learning
Amin Masoumi, Mert Korkali
Dynamic security control (DSC) is considered a pivotal step for the future power grid, which is increasingly penetrated by inverter-based resources. However, the efficiency of such…
Transient-Stability-Aware Frequency Provision in IBR-Rich Grids via Information Gap Decision Theory and Deep Learning
Amin Masoumi, Mert Korkali
This paper introduces a framework to address the critical loss of transient stability caused by reduced inertia in grids with high inverter-based resource (IBR) penetration. The pr…
Deep-Learning-Directed Preventive Dynamic Security Control via Coordinated Demand Response
Amin Masoumi, Mert Korkali
Unlike common faults, three-phase short-circuit faults in power systems pose significant challenges. These faults can lead to out-of-step (OOS) conditions and jeopardize the system…