Glenn Ceusters

Pleinlaan 2
1050 Brussels
Belgium
Pleinlaan 2
1050 Brussel
Belgium

Research activity per year

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Dive into the research topics where Glenn Ceusters is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

1 Similar Profiles

1 Finished

VLAOO13: Baekeland mandate: Safe reinforcement learning for optimal control in multi-energy systems
Messagie, M., Nowe, A. & Ceusters, G.
1/01/20 → 31/12/24
Project: Applied

118 Citations
5 h-index
6 Article
2 Conference paper
2 Preprint

Real-world validation of safe reinforcement learning, model predictive control and decision tree-based home energy management systems
Ruddick, J., Ceusters, G., Van Kriekinge, G., Genov, E., De Cauwer, C., Coosemans, T. & Messagie, M., Dec 2024, In: Energy and AI. 18, 19 p., 100448.
Research output: Contribution to journal › Article › peer-review

Open Access

2 Citations (Scopus)
An adaptive safety layer with hard constraints for safe reinforcement learning in multi-energy management systems
Ceusters, G., Putratama, M. A., Franke, R., Nowé, A. & Messagie, M., Dec 2023, In: Sustainable Energy, Grids and Networks. 36, 2023, 14 p., 101202.
Research output: Contribution to journal › Article › peer-review

Open Access
File
5 Citations (Scopus)

17 Downloads (Pure)
Data-driven non-parametric chance-constrained model predictive control for microgrids energy management using small data batches
Babić, L., Lauricella, M., Ceusters, G. & Biskoping, M., 17 Aug 2023, In: Frontiers in Control Engineering. 4, 2023, 14 p., 1237759.
Research output: Contribution to journal › Article › peer-review

Open Access
File
75 Downloads (Pure)
Safe reinforcement learning for multi-energy management systems with known constraint functions
Ceusters, G., Camargo, L. R., Franke, R., Nowé, A. & Messagie, M., Apr 2023, In: Energy and AI. 12, 17 p., 100227.
Research output: Contribution to journal › Article › peer-review

Open Access
File
11 Citations (Scopus)

82 Downloads (Pure)
Safe reinforcement learning for multi-energy management systems with known constraint functions.
Ceusters, G., Camargo, L. R., Franke, R., Nowé, A. & Messagie, M., 8 Jul 2022, ArXiv.
Research output: Working paper › Preprint

Open Access

Code for "Real-world validation of safe reinforcement learning, model predictive control and decision tree-based home energy management systems" paper
Ruddick, J. J. (Creator), Ceusters, G. (Creator), Genov, E. (Creator) & Van Kriekinge, G. (Creator), GitHub, 5 Aug 2024
https://github.com/EVERGi/real_validation_saferl_treec_paper/
Dataset

Glenn Ceusters

Fingerprint

Collaborations and top research areas from the last five years

Dive into details

VLAOO13: Baekeland mandate: Safe reinforcement learning for optimal control in multi-energy systems

Real-world validation of safe reinforcement learning, model predictive control and decision tree-based home energy management systems

An adaptive safety layer with hard constraints for safe reinforcement learning in multi-energy management systems

Data-driven non-parametric chance-constrained model predictive control for microgrids energy management using small data batches

Safe reinforcement learning for multi-energy management systems with known constraint functions

Safe reinforcement learning for multi-energy management systems with known constraint functions.

Code for "Real-world validation of safe reinforcement learning, model predictive control and decision tree-based home energy management systems" paper

Glenn Ceusters

Fingerprint

Collaborations and top research areas from the last five years

Projects

VLAOO13: Baekeland mandate: Safe reinforcement learning for optimal control in multi-energy systems

Research output

Real-world validation of safe reinforcement learning, model predictive control and decision tree-based home energy management systems

An adaptive safety layer with hard constraints for safe reinforcement learning in multi-energy management systems

Data-driven non-parametric chance-constrained model predictive control for microgrids energy management using small data batches

Safe reinforcement learning for multi-energy management systems with known constraint functions

Safe reinforcement learning for multi-energy management systems with known constraint functions.

Datasets

Code for "Real-world validation of safe reinforcement learning, model predictive control and decision tree-based home energy management systems" paper