activity
20242026
collaborators

9 papers

eess.SY2026

Power Grid Infrastructure for AI Data Centers

Amir Sajadi, Muhy Eddin Za'ter, Maria Vabson +2

This article addresses recent advances in artificial intelligence, which have set off an astounding race among technology frontiers to build large data centers. It provides insight…

eess.SY2026

Empirical Assessment of Time-Series Foundation Models For Power System Forecasting Applications

Muhy Eddin Za'ter, Bri-Mathias Hodge

Accurate forecasting of electric load and renewable generation is essential for reliable and cost effective power system operations. Recent advances in transformer based and founda…

eess.SY2026

A Multi-Stage Warm-Start Deep Learning Framework for Unit Commitment

Muhy Eddin Za'ter, Anna Van Boven, Bri-Mathias Hodge +1

Maintaining instantaneous balance between electricity supply and demand is critical for reliability and grid instability. System operators achieve this through solving the task of…

cs.LG2025

Residual Correction Models for AC Optimal Power Flow Using DC Optimal Power Flow Solutions

Muhy Eddin Za'ter, Bri-Mathias Hodge, Kyri Baker

Solving the nonlinear AC optimal power flow (AC OPF) problem remains a major computational bottleneck for real-time grid operations. In this paper, we propose a residual learning p…

cs.LG2025

Learning a Generalized Model for Substation Level Voltage Estimation in Distribution Networks

Muhy Eddin Za'ter, Bri-Mathias Hodge

Accurate voltage estimation in distribution networks is critical for real-time monitoring and increasing the reliability of the grid. As DER penetration and distribution level volt…

eess.SY2025

Leveraging Multi-Task Learning for Multi-Label Power System Security Assessment

Muhy Eddin Za'ter, Amir Sajad, Bri-Mathias Hodge

This paper introduces a novel approach to the power system security assessment using Multi-Task Learning (MTL), and reformulating the problem as a multi-label classification task.…