3 papers
cs.LG2025
gridfm-datakit-v1: A Python Library for Scalable and Realistic Power Flow and Optimal Power Flow Data Generation
Alban Puech, Matteo Mazzonelli, Celia Cintas +11
We introduce gridfm-datakit-v1, a Python library for generating realistic and diverse Power Flow (PF) and Optimal Power Flow (OPF) datasets for training Machine Learning (ML) solve…
cs.LG2024
Accelerating Quasi-Static Time Series Simulations with Foundation Models
Alban Puech, François Mirallès, Jonas Weiss +5
Quasi-static time series (QSTS) simulations have great potential for evaluating the grid's ability to accommodate the large-scale integration of distributed energy resources. Howev…
eess.SY2024
Optimal Power Grid Operations with Foundation Models
Alban Puech, Jonas Weiss, Thomas Brunschwiler +1
The energy transition, crucial for tackling the climate crisis, demands integrating numerous distributed, renewable energy sources into existing grids. Along with climate change an…