2 citations · 2 across the 6 of their papers we have counts for
6 papers
Nested-Loop Trajectory-Informed Variational Quantum Solver for Interior-Point OPF
Farshad Amani, Amin Kargarian
Optimal power flow (OPF) solved by an interior-point method (IPM) requires repeatedly solving Newton linear systems. When variational quantum linear solvers (VQLS) are used, each I…
Event-Driven Deep RL Dispatcher for Post-Storm Distribution System Restoration
Farshad Amani, Faezeh Ardali, Amin Kargarian
Natural hazards such as hurricanes and floods damage power grid equipment, forcing operators to replan restoration repeatedly as new information becomes available. This paper devel…
Learning Optimal Crew Dispatch for Grid Restoration Following an Earthquake
Farshad Amani, Faezeh Ardali, Amin Kargarian
Post-disaster crew dispatch is a critical but computationally intensive task. Traditional mixed-integer linear programming methods often require minutes to several hours to compute…
Learning Interior Point Method Central Path Projection for Optimal Power Flow
Farshad Amani, Amin Kargarian, Ramachandran Vaidyanathan
This paper proposes a learning-based approach to accelerate the interior-point method (IPM) for solving optimal power flow (OPF) problems by learning the structure of the IPM centr…
Quantum Optimization for Optimal Power Flow: CVQLS-Augmented Interior Point Method
Farshad Amani, Amin Kargarian
This paper presents a quantum-enhanced optimization approach for solving optimal power flow (OPF) by integrating the interior point method (IPM) with a coherent variational quantum…
Optimal Power Flow Solutions via Noise-Resilient Quantum-Inspired Interior-Point Methods
Farshad Amani, Amin Kargarian
This paper presents three quantum interior-point methods (QIPMs) tailored to tackle the DC optimal power flow (DCOPF) problem using noisy intermediate-scale quantum devices. The op…