Posts by Collection

Electricity price forecasting on the day-ahead market using machine learning

Published in Applied Energy, 2022

A benchmark of the state-of-the-art Machine Learning techniques on Electricity Price Forecasting for various european datasets, with application of Explainability tools (shap values).

Recommended citation: Léonard Tschora, Erwan Pierre, Marc Plantevit, Céline Robardet, Electricity price forecasting on the day-ahead market using machine learning, Applied Energy, Volume 313, 2022, 118752, ISSN 0306-2619
Download Paper

Forecasting electricity prices: An optimize then predict-based approach

Published in International Symposium on Intelligent Data Analysis, 2023

Paper presented at the Intelligent Data Analysis 2023 conference, where it was awarded the frontier prize for best paper.

Recommended citation: Leonard Tschora, Erwan Pierre, Marc Plantevit, Céline Robardet, (2023). Forecasting Electricity Prices: An Optimize Then Predict-Based Approach. In: Crémilleux, B., Hess, S., Nijssen, S. (eds) Advances in Intelligent Data Analysis XXI. IDA 2023. Lecture Notes in Computer Science, vol 13876. Springer, Cham. https://doi.org/10.1007/978-3-031-30047-9_35 (2010).
Download Paper

Electricity Price Forecasting based on Order Books: a differentiable optimization approach

Published in DSAA 2023, 2023

This work was presented during the 10th IEEE International Conference on Data Science and Advanced Analytics Conference.

Recommended citation: Leonard Tschora, Tias Guns, Erwan Pierre, Marc Plantevit and Céline. Robardet, Electricity Price Forecasting based on Order Books: a differentiable optimization approach, 2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA), Thessaloniki, Greece, 2023, pp. 1-10, doi: 10.1109/DSAA60987.2023.10302542.
Download Paper | Download Slides

Portfolio item number 1

Short description of portfolio item number 1

Portfolio item number 2

Short description of portfolio item number 2