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20222026
most citedOptimal Power Flow Solutions via Noise-Resilient Quantum-Inspired Interior-Point Methods

2 citations · 3 across the 7 of their papers we have counts for

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eess.SY2026

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…

eess.SY2025

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…

eess.SY2025

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…

eess.SY2025

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…

eess.SY2023★ 2 cited

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…