WFES 2014 EUDP Global Wind Atlas: New, Unique, and Dedicated dataset for the Global Atlas Presented by Jake Badger EUDP is a Danish fund for development and demonstration projects from the Danish Energy Agency
Context The global wind atlas objectives are to: provide wind resource data accounting for high resolution effects use microscale modelling to capture small scale wind speed variability (crucial for better estimates of aggregated wind resource) Suitable for aggregation and upscaling analysis and energy integration analysis for energy planners and policy makers WARNING: Not suitable for developers and site resource assessment IPCC SRREN report: range tech. pot. 19 125 PWh / year (onshore and near shore) 2
Importance of resolution and microscale modelling Wind resource (power density) calculated at different resolutions 50 km 10 km 5 km 50 km 324 W/m 2 328 W/m 2 378 W/m 2 398 W/m 2 2.5 km 0.1 km 323 W/m 2 505 W/m 2 410 W/m 2 641 W/m 2 mean power density of total area mean power density for windiest 50% of area 3
Importance of resolution Mean wind power density for windiest half of area 4
Importance of resolution Note: Even for Danish landscape effect can give 25 % boast in wind resource at the windiest 5 percentile. Mean wind power density for 10% of area 5
Input: newly available global dataset Reanalysis: atmospheric data Product Model system Horizontal resolution Period covered Temporal resolution ERA Interim reanalysis T255, 60 vertical levels, 4DVar ~0.7 0.7 1989-present 3- and 6- hourly NASA GAO/MERRA GEOS5 data assimilation system (Incremental Analysis Updates), 72 levels 0.5 0.67 1979-present 3-hourly NCAR CFDDA MM5 (regional model)+ FDDA ~40 km 1985-2005 hourly CFSR NCEP GFS (global forecast system) ~38 km 1979-2009 (& updating) hourly Topography: surface description Elevation Shuttle Radar Topography Mission (SRTM), version 2.1, released 2009 ASTER Global Digital Elevation Model (ASTER GDEM), version 1, released 2009 Land cover ESA GlobCover, version 2.1, released 2008, resolution 90 m resolution 30 m resolution 300 m 6
Reanalysis data from NCEP DOE II 1980-2009 mean wind at 10 m direct from dataset Wind speed shows variation in part due to changing surface roughness length. Tendency for lower winds over land, higher winds over sea. Sub-grid scale variation of orography and roughness will lead to marked variation in wind 7
Reanalysis data from NCEP DOE II 1980-2009 generalized mean wind speed at 10 m and z 0 = 10 cm Wind speed shows less variation, roughness length is now 10 cm everywhere Less contrast between land and sea Generalized wind climate is the link to downscaling models described sectorwise, for different heights and different roughness lengths (WAsP libfile) 8
The GWA jobs MGRS grid zones form basis of the job structure MRGS grid zones are divided into 4 pieces (total 4903) 2439 jobs required
Example jobs
Example jobs
EUDP Global Wind Atlas Output Heights: 50, 100, 200 m Weibull A and k for 12 direction sectors Aggregated products based on calculations at 250 m grid spacing Verification against mesoscale existing national wind atlases Verification against SAR offshore resource estimation 12
Application of high resolution resource data Wind Atlas for South Africa (WASA) experience in planning Credit: Cornelius van der Westhuizen, CSIR, South Africa See also: www.windaba.co.za/wp-content/uploads/2013/10/cornelius-van-der- Westhuizen-Methodolody-and-initial-results-of-the-DEA-wind-SEA.pdf 13
Application of high resolution resource data DTU PhD working on advanced GIS applications of Global Wind Atlas Conversion of high resolution wind climate data to technical potential incorporating optimization. EU JRC project developing technical potential data for TIMES-EU, derived from Global Wind Atlas Conversion and aggregation to formats for integrated assessment modelling (IAM). 14
Summary To discover the true global wind resource and make it available for all provide wind resource data accounting for high resolution effects use a unified methodology using newer higher reanalysis datasets verification and publication of the methodology are important be applied for aggregation and upscaling analysis and energy integration analysis for energy planners and policy makers Look out for 2 nd end-user workshop late 2014. 15
Thank you for listening jaba@dtu.dk Acknowledgement This work is undertaken in collaboration with the Danish Energy Agency and funded by grant EUDP 11-II, Globalt Vind Atlas, 64011-0347 16
Project overview 17
Calculation of local wind climates at microscale Job Management Console Job Creation Results Exporter WAsP Worker