9 papers
Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features
George Dimas, Amin Masoumi, Mert Korkali
Security-constrained unit commitment (SCUC) couples binary commitment, economic dispatch, reserves, and network security over a multiperiod horizon, making an exact solution comput…
Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features
George Dimas, Amin Masoumi, Mert Korkali
Security-constrained unit commitment (SCUC) couples binary commitment, economic dispatch, reserves, and network security over a multiperiod horizon, which makes an exact solution e…
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…
Quantum-Enhanced Reinforcement Learning for Power Grid Security Assessment
Benjamin M. Peter, Mert Korkali
The increasingly challenging task of maintaining power grid security requires innovative solutions. Novel approaches using reinforcement learning (RL) agents have been proposed to…