Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Bedassa R. Cheneka"'
Associating Synoptic-Scale Weather Patterns with Aggregated Offshore Wind Power Production and Ramps
Publikováno v:
Energies, Vol 14, Iss 13, p 3903 (2021)
Large-scale weather patterns and their variability can influence both the amount of wind power production and its temporal variation, i.e., wind power ramps. In this study, we use a self-organizing map to cluster hourly sea level pressure into a disc
Externí odkaz:
https://doaj.org/article/e0428b9b185f48b0839226ebc6cb8640
Publikováno v:
Advances in Meteorology, Vol 2016 (2016)
Downscaling of seasonal hindcasts over East Africa with the regional climate model (RCM) COSMO-CLM (CCLM), forced by the global climate model (GCM) and MPI-ESM, is evaluated. The simulations are done for five months (May to September) for a ten-year
Externí odkaz:
https://doaj.org/article/7d44f89d1b9b433fad76a1285db9b1b3
Associating Synoptic-Scale Weather Patterns with Aggregated Offshore Wind Power Production and Ramps
Publikováno v:
Energies, 14(13)
Energies; Volume 14; Issue 13; Pages: 3903
Energies, Vol 14, Iss 3903, p 3903 (2021)
Energies; Volume 14; Issue 13; Pages: 3903
Energies, Vol 14, Iss 3903, p 3903 (2021)
Large-scale weather patterns and their variability can influence both the amount of wind power production and its temporal variation, i.e., wind power ramps. In this study, we use a self-organizing map to cluster hourly sea level pressure into a disc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d15b65fd0d5a3f838d817ada8d142cbc
https://doi.org/10.3390/en14133903
https://doi.org/10.3390/en14133903
Publikováno v:
Journal of Physics: Conference Series, 1618(6)
Large-scale weather systems have the potential to modulate offshore wind energy production. The Northern European sea areas have recently seen a rapid increase in wind power capacity and thus there is a need to understand how different weather system
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2319f749a27572b1a2f1aa765ca024b2
http://resolver.tudelft.nl/uuid:9c8a2249-367c-4503-b8b2-079d9b9840c6
http://resolver.tudelft.nl/uuid:9c8a2249-367c-4503-b8b2-079d9b9840c6
Publikováno v:
Wind Energy Science, Vol 5, Pp 1731-1741 (2020)
Wind Energy Science, 5(4)
Wind Energy Science, 5(4)
Knowledge about the expected duration and intensity of wind power ramps is important when planning the integration of wind power production into an electricity network. The detection and classification of wind power ramps is not straightforward due t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb6e14be6ca6b0359d7f622bd1effc4c
https://www.wind-energ-sci-discuss.net/wes-2020-64/
https://www.wind-energ-sci-discuss.net/wes-2020-64/
Publikováno v:
2020 17th International Conference on the European Energy Market, EEM 2020
A series of probabilistic models were bench-marked during the European Energy Markets forecasting Competition 2020 to assess their relative accuracy in predicting aggregated Swedish wind power generation using as input historic weather forecasts from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c953a65d5f72d2d6282bb99473bf100
https://doi.org/10.1109/eem49802.2020.9221929
https://doi.org/10.1109/eem49802.2020.9221929
Publikováno v:
2020 17th International Conference on the European Energy Market, EEM 2020
A hybrid neural network model, comprising of a convolutional neural network and a multilayer perceptron network, has been developed for day-ahead forecasting of regional scale wind power production. This model requires operational weather forecasts a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c7ef49be3eed1b8d312bc4bb7eccbaeb
http://resolver.tudelft.nl/uuid:f43af433-b989-4f69-8ece-e122b0a7238c
http://resolver.tudelft.nl/uuid:f43af433-b989-4f69-8ece-e122b0a7238c
Publikováno v:
Advances in Meteorology, Vol 2016 (2016)
Downscaling of seasonal hindcasts over East Africa with the regional climate model (RCM) COSMO-CLM (CCLM), forced by the global climate model (GCM) and MPI-ESM, is evaluated. The simulations are done for five months (May to September) for a ten-year
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17e55ccbb0d95dd4112d64aa8a41c78f
https://doaj.org/article/7d44f89d1b9b433fad76a1285db9b1b3
https://doaj.org/article/7d44f89d1b9b433fad76a1285db9b1b3