5 papers
Bayesian Inference for Estimating Generation Costs in Electricity Markets
Matthias Pirlet, Adrien Bolland, Alexandre Huynen +3
Estimating generation costs from observed electricity market data is essential for market simulation, strategic bidding, and system planning. To that end, we model the relationship…
Gym-TORAX: Open-source software for integrating reinforcement learning with plasma control simulators in tokamak research
Antoine Mouchamps, Arthur Malherbe, Adrien Bolland +1
This paper presents Gym-TORAX, a Python package enabling the implementation of Reinforcement Learning (RL) environments for simulating plasma dynamics and control in tokamaks. User…
Cost Estimation in Unit Commitment Problems Using Simulation-Based Inference
Matthias Pirlet, Adrien Bolland, Gilles Louppe +1
The Unit Commitment (UC) problem is a key optimization task in power systems to forecast the generation schedules of power units over a finite time period by minimizing costs while…
Optimal Control of Renewable Energy Communities subject to Network Peak Fees with Model Predictive Control and Reinforcement Learning Algorithms
Samy Aittahar, Adrien Bolland, Guillaume Derval +1
We propose in this paper an optimal control framework for renewable energy communities (RECs) equipped with controllable assets. Such RECs allow its members to exchange production…
Behind the Myth of Exploration in Policy Gradients
Adrien Bolland, Gaspard Lambrechts, Damien Ernst
In order to compute near-optimal policies with policy-gradient algorithms, it is common in practice to include intrinsic exploration terms in the learning objective. Although the e…