collaborators

5 papers

eess.SY2026

Quantum Hardware-in-the-Loop for Optimal Power Flow in Renewable-Integrated Power Systems

Zeynab Kaseb, Rahul Rane, Aleksandra Lekic +4

Quantum computing has emerged as a promising computational paradigm to address unresolved challenges in the modeling and control of modern power systems. However, most existing stu…

cs.ET2026

A Framework for Solving Continuous Energy and Power System Problems using Adiabatic Quantum Computing

Zeynab Kaseb, Matthias Moller, Peter Palensky +1

The increasing scale and nonlinearity of modern energy and power system problems pose significant challenges to classical numerical solvers. In parallel, advances in quantum and qu…

quant-ph2026

Performance Comparison of Gate-Based and Adiabatic Quantum Computing for AC Power Flow Problem

Zeynab Kaseb, Matthias Moller, Peter Palensky +1

We present the first direct comparison between gate-based quantum computing (GQC) and adiabatic quantum computing (AQC) paradigms for solving the AC power flow (PF) equations. The…

eess.SY2025

Adaptive Informed Deep Neural Networks for Power Flow Analysis

Zeynab Kaseb, Stavros Orfanoudakis, Pedro P. Vergara +1

This study introduces PINN4PF, an end-to-end deep learning architecture for power flow (PF) analysis that effectively captures the nonlinear dynamics of large-scale modern power sy…

eess.SY2025

Data driven approach towards more efficient Newton-Raphson power flow calculation for distribution grids

Shengyuan Yan, Farzad Vazinram, Zeynab Kaseb +8

Power flow (PF) calculations are fundamental to power system analysis to ensure stable and reliable grid operation. The Newton-Raphson (NR) method is commonly used for PF analysis…