Using Satellite SAR to Characterize the Wind Flow around Offshore Wind Farms

Charlotte Bay Hasager, Pauline Vincent, Jake Badger, Merete Badger, Alessandro Di Bella, Alfredo Peña, Romain Husson and Patrick J. H. Volker
Additional contact information
Charlotte Bay Hasager: Technical University of Denmark, Wind Energy Department, Frederiksborgvej 399, Roskilde 4000, Denmark
Pauline Vincent: Collecte Localisation Satellites, Avenue La Pérouse, Bâtiment le Ponant, Plouzané 29280, France
Jake Badger: Technical University of Denmark, Wind Energy Department, Frederiksborgvej 399, Roskilde 4000, Denmark
Merete Badger: Technical University of Denmark, Wind Energy Department, Frederiksborgvej 399, Roskilde 4000, Denmark
Alessandro Di Bella: Technical University of Denmark, Wind Energy Department, Frederiksborgvej 399, Roskilde 4000, Denmark
Alfredo Peña: Technical University of Denmark, Wind Energy Department, Frederiksborgvej 399, Roskilde 4000, Denmark
Romain Husson: Collecte Localisation Satellites, Avenue La Pérouse, Bâtiment le Ponant, Plouzané 29280, France
Patrick J. H. Volker: Technical University of Denmark, Wind Energy Department, Frederiksborgvej 399, Roskilde 4000, Denmark

Energies, 2015, vol. 8, issue 6, 1-27

Abstract: Offshore wind farm cluster effects between neighboring wind farms increase rapidly with the large-scale deployment of offshore wind turbines. The wind farm wakes observed from Synthetic Aperture Radar (SAR) are sometimes visible and atmospheric and wake models are here shown to convincingly reproduce the observed very long wind farm wakes. The present study mainly focuses on wind farm wake climatology based on Envisat ASAR. The available SAR data archive covering the large offshore wind farms at Horns Rev has been used for geo-located wind farm wake studies. However, the results are difficult to interpret due to mainly three issues: the limited number of samples per wind directional sector, the coastal wind speed gradient, and oceanic bathymetry effects in the SAR retrievals. A new methodology is developed and presented. This method overcomes effectively the first issue and in most cases, but not always, the second. In the new method all wind field maps are rotated such that the wind is always coming from the same relative direction. By applying the new method to the SAR wind maps, mesoscale and microscale model wake aggregated wind-fields results are compared. The SAR-based findings strongly support the model results at Horns Rev 1.

Keywords: wind farm wake; offshore; satellite; SAR; remote sensing (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2015
References: View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
https://www.mdpi.com/1996-1073/8/6/5413/pdf (application/pdf)
https://www.mdpi.com/1996-1073/8/6/5413/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:8:y:2015:i:6:p:5413-5439:d:50765

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().