Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Pierre-Julien Trombe"'
Publikováno v:
Energies, Vol 5, Iss 3, Pp 621-657 (2012)
Accurate wind power forecasts highly contribute to the integration of wind power into power systems. The focus of the present study is on large-scale offshore wind farms and the complexity of generating accurate probabilistic forecasts of wind power
Externí odkaz:
https://doaj.org/article/2bed9684e3384f7d98993c5871606228
Autor:
Remco Verzijlbergh, Pierre Pinson, Jakob W. Messner, Harmen J. J. Jonker, Pim van Dorp, Ciaran Gilbert, Pierre-Julien Trombe
Accurate short-term power forecasts are crucial for the reliable and efficient integration of wind energy in power systems and electricity markets. Typically, forecasts for hours to days ahead are based on the output of numerical weather prediction m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::519498862a454058e74d893600b818f7
https://strathprints.strath.ac.uk/70770/1/Gilbert_etal_Wind_Energy_2020_Statistical_post_processing_of_turbulence_resolving_weather_forecasts_for_offshore_wind.pdf
https://strathprints.strath.ac.uk/70770/1/Gilbert_etal_Wind_Energy_2020_Statistical_post_processing_of_turbulence_resolving_weather_forecasts_for_offshore_wind.pdf
Autor:
Juan M. Morales, Henrik Madsen, Emil B. Iversen, Jan Kloppenborg Møller, Pierre-Julien Trombe
Publikováno v:
Wind Energy. 20:33-44
Short-term (hours to days) probabilistic forecasts of wind power generation provide useful information about the associated uncertainty of these forecasts. Standard probabilistic forecasts are usually issued on a per-horizon-basis, meaning that they
Intrahourly fluctuations in wind power generation cause various technical and economic challenges for wind farm integration. With increasing levels of wind energy uptake, managing these fluctuations is likely to require further attention. Intrahourly
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f44f5606f91462a622146b94baedc3a
https://doi.org/10.1016/b978-0-08-100504-0.00008-1
https://doi.org/10.1016/b978-0-08-100504-0.00008-1
Autor:
Stefano Alessandrini, Christophe Baehr, Ricardo Bessa, Philippe Blanc, Audun Botterud, Edgardo D. Castronuovo, Carlos F.M. Coimbra, Alain Dabas, Romain Dupin, Gregor Giebel, Robin Girard, Paula Gómez, Sven-Erik Gryning, Sue Ellen Haupt, Rich H. Inman, Pedro A. Jiménez, George Kariniotakis, Andreas Kazantzidis, Branko Kosović, Kevin Laquaine, Jared A. Lee, Pierre Massip, Manuel Matos, Nicoló Mazzi, Andrea Michiorri, Torben Mikkelsen, Ewan O'Connor, Laura Frías Paredes, Hugo T.C. Pedro, Pierre Pinson, Lourdes Ramirez-Santigosa, Gordon Reikard, Jan Remund, Lucie Rottner, Javier Sanz Rodrigo, Mikael Sjöholm, Simone Sperati, Nicole Stoffels, Irene Suomi, Pierre-Julien Trombe, Panagiotis Tzoumanikas, Loïc Vallance, Nikola Vasiljević, Claire L. Vincent, Lueder von Bremen, Stefan Wilbert, Zhi Zhou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::38ad8068f6d6059cfc31ccf302fc48be
https://doi.org/10.1016/b978-0-08-100504-0.01002-7
https://doi.org/10.1016/b978-0-08-100504-0.01002-7
Probabilistic Forecasts of Wind Power Generation Accounting for Geographically Dispersed Information
Publikováno v:
Tastu, J, Pinson, P, Trombe, P-J & Madsen, H 2014, ' Probabilistic forecasts of wind power generation accounting for geographically dispersed information ', IEEE Transactions on Smart Grid, vol. 5, no. 1, pp. 480-489 . https://doi.org/10.1109/TSG.2013.2277585
Forecasts of wind power generation in their probabilistic form are a necessary input to decision-making problems for reliable and economic power systems operations in a smart grid context. Thanks to the wealth of spatially distributed data, also of h
Autor:
Pierre Pinson, Andrea N. Hahmann, B. Jensen, Niels Einar Jensen, Nicolaos Antonio Cutululis, Caroline Draxl, Lisbeth Pedersen, Thomas Bøvith, Gregor Giebel, Henrik Madsen, Claire Louise Vincent, Anders Sommer, Nina F. Le, Pierre-Julien Trombe
Publikováno v:
Wind Energy. 17:1767-1787
Offshore wind fluctuations are such that dedicated prediction and control systems are needed for optimizing the management of wind farms in real-time. In this paper, we present a pioneer experiment – Radar@Sea – in which weather radars are used f
Publikováno v:
Proceedings of the ISES Solar World Congress 2015.
Publikováno v:
Solar Energy
Solar Energy, Elsevier, 2016, 133, pp.55-72. ⟨10.1016/j.solener.2016.03.064⟩
David, M, Ramahatana, F, Trombe, P-J & Lauret, P 2016, ' Probabilistic forecasting of the solar irradiance with recursive ARMA and GARCH models ', Solar Energy, vol. 133, no. August, pp. 55-72 . https://doi.org/10.1016/j.solener.2016.03.064
Solar Energy, Elsevier, 2016, 133, pp.55-72. ⟨10.1016/j.solener.2016.03.064⟩
David, M, Ramahatana, F, Trombe, P-J & Lauret, P 2016, ' Probabilistic forecasting of the solar irradiance with recursive ARMA and GARCH models ', Solar Energy, vol. 133, no. August, pp. 55-72 . https://doi.org/10.1016/j.solener.2016.03.064
International audience; Forecasting of the solar irradiance is a key feature in order to increase the penetration rate of solar energy into the energy grids. Indeed, the anticipation of the fluctuations of the solar renewables allows a better managem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c33c7a85acb2809aa9a7b4fea0f2cff
https://hal.archives-ouvertes.fr/hal-01310208/document
https://hal.archives-ouvertes.fr/hal-01310208/document
Publikováno v:
Trombe, P-J, Pinson, P & Madsen, H 2012, ' A General Probabilistic Forecasting Framework for Offshore Wind Power Fluctuations ', Energies, vol. 5, no. 3, pp. 621-657 . https://doi.org/10.3390/en5030621
Energies, Vol 5, Iss 3, Pp 621-657 (2012)
Energies
Energies; Volume 5; Issue 3; Pages: 621-657
Energies, Vol 5, Iss 3, Pp 621-657 (2012)
Energies
Energies; Volume 5; Issue 3; Pages: 621-657
Accurate wind power forecasts highly contribute to the integration of wind power into power systems. The focus of the present study is on large-scale offshore wind farms and the complexity of generating accurate probabilistic forecasts of wind power