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Background Methodology Results Or…. Why ?.... How ?.... What ?....

A new wind resource map for the North Sea Combining the strengths of Earth Observation data, Mesoscale Modelling and Mast Measurements European Offshore Wind, 14 September 2009, Stockholm Joe Phillips < joe.phillips@garradhassan.com >. Contents. Background Methodology Results Or….

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Background Methodology Results Or…. Why ?.... How ?.... What ?....

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  1. A new wind resource map for the North SeaCombining the strengths of Earth Observation data, Mesoscale Modelling and Mast MeasurementsEuropean Offshore Wind, 14 September 2009, StockholmJoe Phillips < joe.phillips@garradhassan.com >

  2. Contents • Background • Methodology • Results Or…. Why ?.... How ?.... What ?....

  3. Background Wind Resource is critical ► High enough energy production ► High enough certainty Onshore measurements ► Relatively inexpensive ► Standard industry practice Offshore measurements ► Relatively expensive ► Varied industry approach At an early stage, wind mapping can add value to aid site selection and feasibility

  4. Background For early stage projects several data sources may be considered ► Published Studies ◪ e.g. European Wind Atlas, UK RE Atlas, GH-GL 1995 EU Study etc ► ReAnalysis Data ► Coastal meteorological stations ► Offshore meteorological stations ► Earth Observation data ► Mesoscale Modelling ► Offshore met masts Each data source has strengths and weaknesses ► So, why not combine them to ….. ◪ Accentuate strengths ◪ Mitigate weaknesses

  5. Use as ‘calibration point’ to inject absolute accuracy Use to characterise broad synoptic spatial trends IMAGE: ESA Use to establish wind variation close to the coast Method - rationale Source StrengthsWeaknesses Offshore Met Mast  Best absolute accuracyOnly for single point  Long-term representation Earth Observation  Wide spatial coverageLow absolute accuracy Unusable in coastal areas Limited temporal coverage Mesoscale Modelling  Localised coastal variationModerate absolute accuracy

  6. Synoptic Grid (Calibration) Final Grid (Quadrant Blending) Method - overview CORMA – Composite Offshore Resource Mapping Analysis Mast Analysis (GH Standard Practise) EO Analysis (Matrix Averaging) Meso Model (MC2 – coastal grids) Recently utilised for the EC FP7 Project – WindSpeed (www.windspeed.eu)

  7. Mast 6.5 6.3 5.9 6.7 6.6 6.3 EO Synoptic Grid Final Grid 7.1 7.0 7.0 Meso Model EO Analysis Matrix Averaging

  8. Mast 9.2 9.9 9.7 8.9 9.0 9.1 EO Synoptic Grid Final Grid - 9.4 9.5 Meso Model EO Analysis Matrix Averaging

  9. Mast EO Synoptic Grid Final Grid Meso Model EO Analysis Matrix Averaging

  10. Mast EO Synoptic Grid Final Grid Meso Model MEAN 1.01 1.00 1.01 0.99 0.98 1.02 0.99 1.01 1.00 1.01 1.00 1.01 0.99 0.98 1.02 0.99 1.01 1.00 EO Analysis Matrix Averaging Long-term normalised wind map

  11. Mast EO Synoptic Grid Final Grid Meso Model Mast Analysis Standard GH procedures ► Campaign traceability checks ► Raw data screening ► Mast effect corrections ► Long-term adjustment ► Wind shear analysis Resulting in….. ► Long-term mean wind ► Long-term wind rose ► At hub height level Calibrate EO Grid to Long-term mean wind speed

  12. Mast absAC3= absAC4((1/dx2)/DN) + absAD3((1/dy2)/DN) + ED4((1/(dx2+dy2))/DN) dx Where, DN = (1/dx2)+(1/dy2)+(1/(dx2+dy2)) A dy B EO Synoptic Grid Final Grid C Meso speed-up applied along row D E EO F Meso speed-up applied outwards (Inverse Distance Weighted Average) G absAF11=absAF10(AF11/AF10) H absAF10=EF9(AF10/AF9) I Meso Model J K L 1 2 3 4 5 6 7 8 9 10 11 12 Meso Model MC2 Model ► NWP model, run as series of climate simulations ► Aim is to capture local coastal variation Quadrant Blending

  13. Results – 1. EO Matrix Averaging Notes on Stage 1 ► ERS 1 & 2 Missions ► Matrix Averaging ► Normalised synoptic variation ► Coarse resolution (~25km)

  14. Results – 2. Calibration to Mast Notes on Stage 2 ► FINO-1 as reference node ► Shear analysis to 80m ► LT mean wind speed = 9.8m/s ► Uniform calib. of EO grid

  15. Results – 3. Meso Quadrant Blending Notes on Stage 3 ► Meso quadrant blending ► Final resolution = 5km ► Some noise (just like life !) ► Primarily measurement-based

  16. Validation Notes on Validation ► 5 published estimates ► Bias = 0.04 m/s ► Mean abs. error = 0.23 m/s ► RMS error = 0.62 m/s

  17. Conclusions CORMA method introduced ► Composite Offshore Resource Mapping Analysis ► Combining strengths of three data sources ► Measurement-driven technique (with support from modelling) Applications ► Wind mapping for new markets ► Site finding and feasibility (+/- 0.5 m/s) North Sea wind map ► North Sea used as example region ► GH will provide pictured final wind map free of charge ► Including GIS data ► Visit us at stand B0828 ! ► NORSEWInD Project to spearhead further development in this field. (www.norsewind.eu)

  18. Acknowledgements Many thanks to data providers… ► KNMI ► ESA ► NordzeeWind (NZW-MEP) ► BSH ► DONG ► Norwegian Meteorological Institute And to contributing authors… ► Nick Baldock ► Jerome Jacquemin ► Sam Crawley ► Dan Bacon

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