EUDP Global Wind Atlas: New, Unique, and Dedicated dataset for the Global Atlas

DTU Wind Energy, Technical University of Denmark Presented by Jake Badger EUDP is a Danish fund for development and demonstration projects from the Danish Energy Agency

WFES 2014

DTU Wind Energy, Technical University of Denmark

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

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IPCC SRREN report: range tech. pot. 19 – 125 PWh / year (onshore and near shore)

Context

DTU Wind Energy, Technical University of Denmark

Importance of resolution and microscale modelling

Wind resource (power density) calculated at different resolutions

10 km 5 km

2.5 km 0.1 km

50 km

50 km

324 W/m2

378 W/m2

328 W/m2

398 W/m2

323 W/m2

410 W/m2

505 W/m2

641 W/m2

mean power density of total area mean power density for windiest 50% of area 3

DTU Wind Energy, Technical University of Denmark

Importance of resolution

Mean wind power density for windiest half of area

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DTU Wind Energy, Technical University of Denmark

Importance of resolution

Mean wind power density for 10% of area

Note: Even for Danish landscape effect can give 25 % boast in wind resource at the windiest 5 percentile.

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DTU Wind Energy, Technical University of Denmark

Input: newly available global dataset Reanalysis: atmospheric data

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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 resolution 90 m ASTER Global Digital Elevation Model (ASTER GDEM), version 1, released 2009 resolution 30 m Land cover ESA GlobCover, version 2.1, released 2008, resolution 300 m

DTU Wind Energy, Technical University of Denmark

Reanalysis data from NCEP DOE II 1980-2009 mean wind at 10 m direct from dataset

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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

DTU Wind Energy, Technical University of Denmark

Reanalysis data from NCEP DOE II 1980-2009 generalized mean wind speed at 10 m and z0 = 10 cm

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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)

DTU Wind Energy, Technical University of Denmark

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

DTU Wind Energy, Technical University of Denmark

Example jobs

DTU Wind Energy, Technical University of Denmark

Example jobs

DTU Wind Energy, Technical University of Denmark

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

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DTU Wind Energy, Technical University of Denmark

Application of high resolution resource data

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Credit: Cornelius van der Westhuizen, CSIR, South AfricaSee also: www.windaba.co.za/wp-content/uploads/2013/10/Cornelius-van-der-Westhuizen-Methodolody-and-initial-results-of-the-DEA-wind-SEA.pdf

Wind Atlas for South Africa (WASA) experience in planning

DTU Wind Energy, Technical University of Denmark

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).

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DTU Wind Energy, Technical University of Denmark

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 2nd end-user workshop late 2014.

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DTU Wind Energy, Technical University of Denmark

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

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DTU Wind Energy, Technical University of Denmark

Project overview

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DTU Wind Energy, Technical University of Denmark

Job Creation Job Management Console

WAsP Worker Results Exporter

Calculation of local wind climates at microscale