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Journal articles
A reinforcement learning framework for optimal operation and maintenance of power grids
R. Rocchetta 1
Author
L. Bellani 2
Author
M. Compare 3
Author
Enrico Zio 4
Author IdHAL : enrico-zio
E. Patelli 5
Author
1
UNIBO - Alma Mater Studiorum Università di Bologna [Bologna] (Via Zamboni, 33 - 40126 Bologna - Italy)
2
Aramis s.l.r. (Italy)
3
DENG - Dipartimento di Energia [Milano] (Via Lambruschini 4, 20156 Milano - Italy)
- POLIMI - Politecnico di Milano [Milan] (Piazza Leonardo da Vinci, 32 20133 Milano - Italy)
4
CRC - Centre de recherche sur les Risques et les Crises (Rue Claude Daunesse CS 10207 06904 Sophia-Antipolis Cedex - France)
- MINES ParisTech - École nationale supérieure des mines de Paris (60, boulevard Saint-Michel 75006 Paris - France)
- PSL - Université Paris sciences et lettres (60 rue Mazarine 75006 Paris - France)
5
Institute for risk and Uncertainty (United Kingdom)
- University of Liverpool (Liverpool L69 3BX, United Kingdom - United Kingdom)
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Journal articles
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https://hal-mines-paristech.archives-ouvertes.fr/hal-02275029
Contributor : Magalie Prudon <>
Submitted on : Friday, August 30, 2019 - 2:47:40 PM
Last modification on : Friday, October 30, 2020 - 12:04:04 PM
Contributor : Magalie Prudon <>
Submitted on : Friday, August 30, 2019 - 2:47:40 PM
Last modification on : Friday, October 30, 2020 - 12:04:04 PM
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Identifiers
- HAL Id : hal-02275029, version 1
- DOI : 10.1016/j.apenergy.2019.03.027
Collections
ENSMP | CRC-PARISTECH | CRC-THESE | ENSMP_CRC | PARISTECH | INSTITUT-TELECOM | PSL
Citation
R. Rocchetta, L. Bellani, M. Compare, Enrico Zio, E. Patelli. A reinforcement learning framework for optimal operation and maintenance of power grids. Applied Energy, Elsevier, 2019, 241, pp.291-301. ⟨10.1016/j.apenergy.2019.03.027⟩. ⟨hal-02275029⟩
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