45 citations · 67 across the 29 of their papers we have counts for
6 papers · 1 filter
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…
Self-Certifying Primal-Dual Optimization Proxies for Large-Scale Batch Economic Dispatch
Michael Klamkin, Mathieu Tanneau, Pascal Van Hentenryck
Recent research has shown that optimization proxies can be trained to high fidelity, achieving average optimality gaps under 1% for large-scale problems. However, worst-case analys…
Enhanced Renewable Energy Forecasting using Context-Aware Conformal Prediction
Alireza Moradi, Mathieu Tanneau, Reza Zandehshahvar +1
Artificial intelligence (AI) is increasingly used to support renewable energy forecasting and grid operations. As renewable penetration grows, reliable probabilistic forecasting is…
PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flow
Michael Klamkin, Mathieu Tanneau, Pascal Van Hentenryck
Machine Learning (ML) techniques for Optimal Power Flow (OPF) problems have recently garnered significant attention, reflecting a broader trend of leveraging ML to approximate and/…
Enhanced Renewable Energy Forecasting and Operations through Probabilistic Forecast Aggregation
Alireza Moradi, Mathieu Tanneau, Reza Zandehshahvar +1
Accurate and reliable forecasting of renewable energy generation is crucial for the efficient integration of renewable sources into the power grid. In particular, probabilistic for…
Dual Conic Proxy for Semidefinite Relaxation of AC Optimal Power Flow
Guancheng Qiu, Mathieu Tanneau, Pascal Van Hentenryck
The nonlinear, non-convex AC Optimal Power Flow (AC-OPF) problem is fundamental for power systems operations. The intrinsic complexity of AC-OPF has fueled a growing interest in th…