Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Baptiste Schubnel"'
Publikováno v:
Nuclear Physics B, Vol 912, Iss C, Pp 463-484 (2016)
This is a survey of a novel approach, called “ETH approach”, to the quantum theory of events happening in isolated physical systems and to the effective time evolution of states of systems featuring events. In particular, we attempt to present a
Externí odkaz:
https://doaj.org/article/55af492707994d139a747594926b01c9
Autor:
Paul Scharnhorst, Baptiste Schubnel, Carlos Fernández Bandera, Jaume Salom, Paolo Taddeo, Max Boegli, Tomasz Gorecki, Yves Stauffer, Antonis Peppas, Chrysa Politi
Publikováno v:
Applied Sciences, Vol 11, Iss 8, p 3518 (2021)
We introduce the Python-based open-source library Energym, a building model library to test and benchmark building controllers. The incorporated building models are presented with a brief explanation of their function, location and technical equipmen
Externí odkaz:
https://doaj.org/article/de59a13a317d409c8efd89184ab8dc89
Autor:
Rafael E. Carrillo, Martin Leblanc, Baptiste Schubnel, Renaud Langou, Cyril Topfel, Pierre-Jean Alet
Publikováno v:
Energies, Vol 13, Iss 21, p 5763 (2020)
Operating power systems with large amounts of renewables requires predicting future photovoltaic (PV) production with fine temporal and spatial resolution. State-of-the-art techniques combine numerical weather predictions with statistical post-proces
Externí odkaz:
https://doaj.org/article/1cfeaa05accf44219f828d016c7aa889
Autor:
Paolo Taddeo, Alba Colet, Rafael E. Carrillo, Lluc Casals Canals, Baptiste Schubnel, Yves Stauffer, Ivan Bellanco, Cristina Corchero Garcia, Jaume Salom
Publikováno v:
Energies, Vol 13, Iss 5, p 1188 (2020)
The electricity sector foresees a significant change in the way energy is generated and distributed in the coming years. With the increasing penetration of renewable energy sources, smart algorithms can determine the difference about how and when ene
Externí odkaz:
https://doaj.org/article/303c580be029401bb7834ae964ec2a2d
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 32:4096-4110
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
Publikováno v:
2022 IEEE Power & Energy Society General Meeting (PESGM).
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
Publikováno v:
Applied Energy. 327:120127
Accurate forecasting of photovoltaic (PV) and wind production is crucial for the integration of more renewable energy sources into the power grid. To address the limited resolution and costs of methods based on numerical weather predictions (NWP), we
Publikováno v:
Annales Henri Poincaré. 20:299-335
The quantum theory of indirect measurements in physical systems is studied. The example of an indirect measurement of an observable represented by a self-adjoint operator $${\mathcal {N}}$$ with finite spectrum is analyzed in detail. The Hamiltonian
Autor:
Antonis Peppas, Max Boegli, Paul Scharnhorst, Carlos Fernández Bandera, Chrysa Politi, Baptiste Schubnel, Tomasz T. Gorecki, Paolo Taddeo, Jaume Salom, Yves Stauffer
Publikováno v:
Applied Sciences, Vol 11, Iss 3518, p 3518 (2021)
Applied Sciences
Volume 11
Issue 8
Applied Sciences
Volume 11
Issue 8
We introduce the Python-based open-source library Energym, a building model library to test and benchmark building controllers. The incorporated building models are presented with a brief explanation of their function, location and technical equipmen
Autor:
Martin Leblanc, Renaud Langou, Pierre-Jean Alet, Cyril Topfel, Rafael E. Carrillo, Baptiste Schubnel
Publikováno v:
Energies, Vol 13, Iss 5763, p 5763 (2020)
Energies; Volume 13; Issue 21; Pages: 5763
Energies; Volume 13; Issue 21; Pages: 5763
Operating power systems with large amounts of renewables requires predicting future photovoltaic (PV) production with fine temporal and spatial resolution. State-of-the-art techniques combine numerical weather predictions with statistical post-proces