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Article

27 Citations

6,116 Views

31 Pages

Deep Learning Optimal Control for a Complex Hybrid Energy Storage System

Gabriel Zsembinszki,
Cèsar Fernández,
David Vérez and
Luisa F. Cabeza

Buildings2021, 11(5), 194;https://doi.org/10.3390/buildings11050194

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3 May 2021

Deep Reinforcement Learning (DRL) proved to be successful for solving complex control problems and has become a hot topic in the field of energy systems control, but for the particular case of thermal energy storage (TES) systems, only a few studies...

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Proceeding Paper

2,299 Views

5 Pages

Sun and Thermal Energy: Europe’s Precious Energy Sources for Efficient Industries and Buildings

Serena Scotton,
Régis Decorme,
Marco Calderoni,
Sergio Valentino Costa,
Alessandra Cuneo,
Andrea Frazzica,
Stefano Barberis,
Federica Fuligni,
Francesco Martinelli and
Fabio Magrassi

Proceedings2019, 20(1), 3;https://doi.org/10.3390/proceedings2019020003

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19 July 2019

In this workshop, we discussed the progress of five Horizon 2020 projects—HYCOOL, SHIP2FAIR, THERMOSS, SUNHORIZON and HYBUILD—all implementing solar thermal and renewable technologies for buildings and for the industrial sector. The discussion offer...

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Article

4 Citations

2,780 Views

18 Pages

Experimental Assessment of the Influence of the Design on the Performance of Novel Evaporators with Latent Energy Storage Ability

Boniface Dominick Mselle,
Gabriel Zsembinszki,
David Veréz,
Emiliano Borri,
Andreas Strehlow,
Birgo Nitsch and
Luisa F. Cabeza

Appl. Sci.2022, 12(4), 1813;https://doi.org/10.3390/app12041813

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10 February 2022

This study was carried out within the HYBUILD project, as part of the task aimed at developing novel evaporators for compact and direct integration of phase-change materials (PCM) into air-conditioning systems for efficient utilization of solar energ...

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