2 citations · 3 across the 7 of their papers we have counts for
9 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…
Explicit Ensemble Learning Surrogate for Joint Chance-Constrained Optimal Power Flow
Amir Bahador Javadi, Amin Kargarian
The increasing penetration of renewable generation introduces uncertainty into power systems, challenging traditional deterministic optimization methods. Chance-constrained optimiz…
Learning Constraint Surrogate Model for Two-stage Stochastic Unit Commitment
Amir Bahador Javadi, Amin Kargarian, Mort Naraghi-Pour
The increasing penetration of renewable energy sources introduces significant uncertainty in power system operations, making traditional deterministic unit commitment approaches co…
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…
A Benchmark Library for Distributed Power System Analysis and Optimization
Milad Hasanzadeh, Amin Kargarian
DPLib is an open-source benchmark library created to support research and development in distributed power system analysis and optimization. Unlike centralized tools such as MATPOW…
Accelerating L-shaped Two-stage Stochastic SCUC with Learning Integrated Benders Decomposition
Fouad Hasan, Amin Kargarian
Benders decomposition is widely used to solve large mixed-integer problems. This paper takes advantage of machine learning and proposes enhanced variants of Benders decomposition f…
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…
Flood-aware Optimal Power Flow for Proactive Day-ahead Transmission Substation Hardening
Mohadese Movahednia, Amin Kargarian
Power system components, particularly electrical substations, may be severely damaged due to flooding, resulting in prolonged power outages and resilience degradation. This problem…