Author(s):
Fernandes, Miguel 
; Costa, P. ; Estanqueiro, Ana
Date: 2011
Persistent ID: http://hdl.handle.net/10400.9/1500
Origin: Repositório do LNEG
Subject(s): Wind resource; Offshore; Wind parks
Document details
Improving offshore wind resource assessments using a data assimilation technique
Description
Wind research and industry partners in collaboration with the EU have created the FP7 NORSEWInD project with the main objective of delivering to the North, Baltic and Irish Sea areas high quality wind atlases for offshore wind resource assessment. The state-of-the-art atmospheric mesoscale model WRF is used to map the wind resource at 90m a.g.l. for the North Sea area. A model domain with a spatial resolution of 20x20 km is used to simulate a winter and a summer month (November 2008 and July 2009). It is coupled with a Newtonian relaxation assimilation technique to ingest surface wind data provided from QuikSCAT (QS) satellite and sea surface temperature (SST) data from GHRSST Level 4 analysis. Wind results from the model are validated against observational data from the anemometric mast FINO1 and the spatial improvement of the average wind field at 90 m a.g.l is calculated. Improvements of more than 5% were obtained from using data assimilation on the overall domain. Each source has shown a distinct impact on the analyzed periods. The QS assimilation had higher impact during the summer period whereas SST assimilation was significant during the winter period. At FINO 1 location, improvements on the vertical wind profile were obtained from the SST assimilation. The MAE and RMSE statistical parameters were slightly improved.
Wind research and industry partners in collaboration with the EU have created the FP7 NORSEWInD project with the main objective of delivering to the North, Baltic and Irish Sea areas high quality wind atlases for offshore wind resource assessment. The state-of-the-art atmospheric mesoscale model WRF is used to map the wind resource at 90m a.g.l. for the North Sea area. A model domain with a spatial resolution of 20x20 km is used to simulate a winter and a summer month (November 2008 and July 2009). It is coupled with a Newtonian relaxation assimilation technique to ingest surface wind data provided from QuikSCAT (QS) satellite and sea surface temperature (SST) data from GHRSST Level 4 analysis. Wind results from the model are validated against observational data from the anemometric mast FINO1 and the spatial improvement of the average wind field at 90 m a.g.l is calculated. Improvements of more than 5% were obtained from using data assimilation on the overall domain. Each source has shown a distinct impact on the analyzed periods. The QS assimilation had higher impact during the summer period whereas SST assimilation was significant during the winter period. At FINO 1 location, improvements on the vertical wind profile were obtained from the SST assimilation. The MAE and RMSE statistical parameters were slightly improved.
Document Type
Conference Object
Language English
Language English
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