Zobrazeno 1 - 10
of 65
pro vyhledávání: '"Hans Bergström"'
Autor:
Anna Rutgersson, Heidi Pettersson, Erik Nilsson, Hans Bergström, Marcus B. Wallin, E. Douglas Nilsson, Erik Sahlée, Lichuan Wu, E. Monica Mårtensson
Publikováno v:
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 72, Iss 1, Pp 1-23 (2020)
In situ measurements representing the marine atmosphere and air–sea interaction are taken at ships, buoys, stationary moorings and land-based towers, where each observation platform has structural restrictions. Air–sea fluxes are often small, and
Externí odkaz:
https://doaj.org/article/681a1b54e0a74849993b28622e4a96dc
Publikováno v:
Energies, Vol 14, Iss 1, p 158 (2020)
A probabilistic machine learning method is applied to icing related production loss forecasts for wind energy in cold climates. The employed method, called quantile regression forests, is based on the random forest regression algorithm. Based on the
Externí odkaz:
https://doaj.org/article/92f6835e68944379a2b822a3cdcbc993
Publikováno v:
Advances in Meteorology, Vol 2017 (2017)
Streaky structures of narrow (8-9 km) high wind belts have been observed from SAR images above the Baltic Sea during stably stratified conditions with offshore winds from the southern parts of Sweden. Case studies using the WRF model and in situ airc
Externí odkaz:
https://doaj.org/article/521784db1bb54352a336fe64b98b67ee
Publikováno v:
Atmosphere, Vol 10, Iss 4, p 194 (2019)
A conically scanning, continuous-wave LIDAR is placed on an island in the central Baltic Sea with large open-water fetch, providing wind and turbulence profiles up to 300 m height. LIDAR and Weather Research and Forecasting (WRF) profiles from one ye
Externí odkaz:
https://doaj.org/article/657bc8da531a4381b9dfcc774538477c
Publikováno v:
Wind Energy. 22:764-779
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d106e7b7478db3047d7060e2748a7d6
https://doi.org/10.1002/we.2320
https://doi.org/10.1002/we.2320
Publikováno v:
Energies; Volume 14; Issue 1; Pages: 158
Energies, Vol 14, Iss 158, p 158 (2021)
Energies, Vol 14, Iss 158, p 158 (2021)
A probabilistic machine learning method is applied to icing related production loss forecasts for wind energy in cold climates. The employed method, called quantile regression forests, is based on the random forest regression algorithm. Based on the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d092672824f223f1ecf7f7dbe204ae6c
Publikováno v:
Atmosphere
Volume 10
Issue 4
Atmosphere, Vol 10, Iss 4, p 194 (2019)
Volume 10
Issue 4
Atmosphere, Vol 10, Iss 4, p 194 (2019)
A conically scanning, continuous-wave LIDAR is placed on an island in the central Baltic Sea with large open-water fetch, providing wind and turbulence profiles up to 300 m height. LIDAR and Weather Research and Forecasting (WRF) profiles from one ye
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e36fd165715599b210b12166352daa5d
Publikováno v:
Renewable Energy. 96:784-791
A previously developed model based on MERRA reanalysis data underestimates the high-frequency variability and step changes of hourly, aggregated wind power generation. The goal of this work is to restore these fluctuations. Since the volatility of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::283f781caa803213537d77f4d351cd95
https://doi.org/10.1016/j.renene.2016.05.008
https://doi.org/10.1016/j.renene.2016.05.008
Autor:
E. Monica Mårtensson, Erik Nilsson, E. Douglas Nilsson, Heidi Pettersson, Marcus B. Wallin, Erik Sahlée, Anna Rutgersson, Hans Bergström, Lichuan Wu
Publikováno v:
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 72, Iss 1, Pp 1-23 (2020)
In situ measurements representing the marine atmosphere and air–sea interaction are taken at ships, buoys, stationary moorings and land-based towers, where each observation platform has structural restrictions. Air–sea fluxes are often small, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc3c1aa707c10730b558b6eb56c85814
https://doi.org/10.1080/16000870.2019.1697601
https://doi.org/10.1080/16000870.2019.1697601
Publikováno v:
Wind Energy Science, Vol 3, Pp 667-680 (2018)
The problem of icing on wind turbines in cold climates is addressed using probabilistic forecasting to improve next- day forecasts of icing and related production losses. A case study of probabilistic forecasts was generated for a two- week period. U
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5484e2c4e2a06085a4279d09ac6adf57
http://urn.kb.se/resolve?urn=urn:nbn:se:smhi:diva-4995
http://urn.kb.se/resolve?urn=urn:nbn:se:smhi:diva-4995
