Ghent University Academic Bibliography

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Risk-sensitive reinforcement learning-based strategies for dutch implicit balancing

Seyedsoroush Karimi Madahi (UGent) , Fabio Pavirani (UGent) , Bert Claessens (UGent) and Chris Develder (UGent)

(2025) 2025 21ST INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM. In International Conference on the European Energy Market p.1-6
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- Conference Paper
- P1
- open access
System-aware reinforcement learning for optimized implicit imbalance participation in Belgium

Fabio Pavirani (UGent) , Seyedsoroush Karimi Madahi (UGent) , Bert Claessens (UGent) and Chris Develder (UGent)

(2025) 2025 21ST INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM. In International Conference on the European Energy Market
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- Journal Article
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Predicting and publishing accurate imbalance prices using Monte Carlo Tree Search

Fabio Pavirani (UGent) , Jonas Van Gompel, Seyedsoroush Karimi Madahi (UGent) , Bert Claessens (UGent) and Chris Develder (UGent)

(2025) APPLIED ENERGY. 392.
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Frequency containment reserve and imbalance participation : a battery-integrated reinforcement learning strategy

Fabio Pavirani (UGent) , Seyedsoroush Karimi Madahi (UGent) , Bert Claessens (UGent) and Chris Develder (UGent)

(2024) PROCEEDINGS OF THE 15TH ACM INTERNATIONAL CONFERENCE ON FUTURE AND SUSTAINABLE ENERGY SYSTEMS, E-ENERGY 2024. p.482-483
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Demand response for residential building heating : effective Monte Carlo Tree Search control based on physics-informed neural networks

Fabio Pavirani (UGent) , Gargya Gokhale (UGent) , Bert Claessens (UGent) and Chris Develder (UGent)

(2024) ENERGY AND BUILDINGS. 311.

Academic Bibliography

Risk-sensitive reinforcement learning-based strategies for dutch implicit balancing

System-aware reinforcement learning for optimized implicit imbalance participation in Belgium

Predicting and publishing accurate imbalance prices using Monte Carlo Tree Search

Frequency containment reserve and imbalance participation : a battery-integrated reinforcement learning strategy

Demand response for residential building heating : effective Monte Carlo Tree Search control based on physics-informed neural networks

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