collaborators

13 papers

cs.LG2026

GUIDE-VAE: Advancing Data Generation with User Information and Pattern Dictionaries

Kutay Bölat, Simon Tindemans

Generative modelling of multi-user datasets has become prominent in science and engineering. Generating a data point for a given user requires employing user information, and conve…

stat.AP2026

The Living Forecast: Evolving Day-Ahead Predictions into Intraday Reality

Kutay Bölat, Peter Palensky, Simon Tindemans

Accurate intraday forecasts are essential for power system operations, complementing day-ahead forecasts that gradually lose relevance as new information becomes available. This pa…

eess.SY2025

Scalable Iterative Algorithm for Solving Optimal Transmission Switching with De-energization

Benoît Jeanson, Mathieu Tanneau, Simon Tindemans

Transmission System Operators routinely use transmission switching as a tool to manage congestion and ensure system security. Motivated by sub-transmission operations at RTE, this…

math.OC2025

Feedback Enhancement of Time Series Aggregation for Power System Expansion Planning

Ruiqi Zhang, Ensieh Sharifnia, Simon H. Tindemans

As a consequence of the high variability of load demand and renewable generation, long-term and high-resolution inputs are required for power system expansion planning, making the…

eess.SY2025

Extreme value distributions of peak loads for non-residential customer segments

Shaohong Shi, Eric A. Cator, Jacco Heres +1

Electrical grid congestion is a growing challenge in Europe, driving the need for accurate prediction of load, particularly of peak load. Non-time-resolved models of peak load offe…

cs.LG2025

MLMC-based Resource Adequacy Assessment with Active Learning Trained Surrogate Models

Ruiqi Zhang, Simon H. Tindemans

Multilevel Monte Carlo (MLMC) is a flexible and effective variance reduction technique for accelerating reliability assessments of complex power system. Recently, data-driven surro…