Zobrazeno 1 - 10
of 108
pro vyhledávání: '"Carrillo, Rafael E."'
Autor:
Scharnhorst, Paul, Schubnel, Baptiste, Carrillo, Rafael E., Alet, Pierre-Jean, Jones, Colin N.
Publikováno v:
Sustainable Energy, Grids and Networks Volume 39 Sustainable Energy, Grids and Networks, Volume 39, September 2024, 101512
Residential and commercial buildings, equipped with systems such as heat pumps (HPs), hot water tanks, or stationary energy storage, have a large potential to offer their consumption flexibility as grid services. In this work, we leverage this flexib
Externí odkaz:
http://arxiv.org/abs/2311.05402
Autor:
Scharnhorst, Paul, Schubnel, Baptiste, Carrillo, Rafael E., Alet, Pierre-Jean, Jones, Colin N.
Buildings are a promising source of flexibility for the application of demand response. In this work, we introduce a novel battery model formulation to capture the state evolution of a single building. Being fully data-driven, the battery model ident
Externí odkaz:
http://arxiv.org/abs/2210.03604
Publikováno v:
IEEE Transactions on Industry Applications, Vol. 58, No. 2, pp 1429-1439, March-April 2022
The correct assessment of battery states is essential to maximize battery pack performances while ensuring reliable and safe operation. This work introduces EIS2MOD, a novel modelling framework for Li-ion cells based on Distribution of Relaxation Tim
Externí odkaz:
http://arxiv.org/abs/2203.08515
Autor:
Scharnhorst, Paul, Schubnel, Baptiste, Carrillo, Rafael E., Alet, Pierre-Jean, Jones, Colin N.
Publikováno v:
In Sustainable Energy, Grids and Networks September 2024 39
Autor:
Stauffer, Yves, Saba, Fabio, Carrillo, Rafael E., Boegli, Max, Malengo, Andrea, Hutter, Andreas
A new method for accurate indirect heat accounting in apartment buildings has been recently developed by the Centre Suisse d'Electronique et de Microtechnique (CSEM). It is based on a data driven approach aimed to the smart networking of any type of
Externí odkaz:
http://arxiv.org/abs/2111.02459
Accurate forecasting of solar power generation with fine temporal and spatial resolution is vital for the operation of the power grid. However, state-of-the-art approaches that combine machine learning with numerical weather predictions (NWP) have co
Externí odkaz:
http://arxiv.org/abs/2107.13875
Autor:
Schubnel, Baptiste, Carrillo, Rafael E., Taddeo, Paolo, Casals, Lluc Canals, Salom, Jaume, Stauffer, Yves, Alet, Pierre-Jean
Publikováno v:
Journal of Building Performance Simulation (2020), 13:6, 707-719
Power consumption in buildings show non-linear behaviors that linear models cannot capture whereas recurrent neural networks (RNNs) can. This ability makes RNNs attractive alternatives for the model-predictive control (MPC) of buildings. However RNN
Externí odkaz:
http://arxiv.org/abs/2010.12257
We present a three-step method to perform system identification and optimal control of non-linear systems. Our approach is mainly data driven and does not require active excitation of the system to perform system identification. In particular, it is
Externí odkaz:
http://arxiv.org/abs/2003.08099
Autor:
Simeunović, Jelena, Schubnel, Baptiste, Alet, Pierre-Jean, Carrillo, Rafael E., Frossard, Pascal
Publikováno v:
In Applied Energy 1 December 2022 327
Autor:
Pratley, Luke, McEwen, Jason D., d'Avezac, Mayeul, Carrillo, Rafael E., Onose, Alexandru, Wiaux, Yves
Next-generation radio interferometers, such as the Square Kilometre Array (SKA), will revolutionise our understanding of the universe through their unprecedented sensitivity and resolution. However, standard methods in radio interferometry produce re
Externí odkaz:
http://arxiv.org/abs/1702.06800