Learning to Bid in FCR Markets: data and algorithms
Published: 30 April 2026| Version 1 | DOI: 10.17632/htprbf47dg.1
Contributors:
Marius Potfer, Cheng Wan, Pierre GruetDescription
Companion code to the research paper, for reproducibility purposes.
Files
Steps to reproduce
The full steps to reproduce are available in the file README.md. Here are the main steps : Ensure the required python packages are installed (listed in the file requirements.txt). Then running the python files run_simulation.py, run_simulation_full_info.py and main generates a few runs of the algorithms, one might specify as an argument the number of steps and the number of repetitions of the learning simulation to run (for monte carlo purposes). The graphs can then be produced in Numerics.ipynb and Make_Graphs_fcr.ipynb.
Institutions
- ENSAE ParisÎle-de-France, Palaiseau
Categories
Online Auction, Electricity Market