121 citations · 211 across the 27 of their papers we have counts for
5 papers · 1 filter
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…
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…
Semi-Supervised Multi-Task Learning Based Framework for Power System Security Assessment
Muhy Eddin Za'ter, Amirhossein Sajadi, Bri-Mathias Hodge
This paper develops a novel machine learning-based framework using Semi-Supervised Multi-Task Learning (SS-MTL) for power system dynamic security assessment that is accurate, relia…
Foundation Models for the Electric Power Grid
Hendrik F. Hamann, Thomas Brunschwiler, Blazhe Gjorgiev +24
Foundation models (FMs) currently dominate news headlines. They employ advanced deep learning architectures to extract structural information autonomously from vast datasets throug…
An Unsupervised Clustering-Based Short-Term Solar Forecasting Methodology Using Multi-Model Machine Learning Blending
Cong Feng, Mingjian Cui, Bri-Mathias Hodge +3
Solar forecasting accuracy is affected by weather conditions, and weather awareness forecasting models are expected to improve the performance. However, it may not be available and…