dtu wind energy · 2017-05-09 · dtu wind energy, technical university of denmark 03 november 2016...
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![Page 1: DTU Wind Energy · 2017-05-09 · DTU Wind Energy, Technical University of Denmark 03 November 2016 Experiences • Data easily accessible and free • Few copyright considerations](https://reader033.vdocuments.us/reader033/viewer/2022042414/5f2dfe64e13ad83c40388d9d/html5/thumbnails/1.jpg)
Experiences, best practice, pitfalls and challengesDTU Wind Energy
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03 November 2016DTU Wind Energy, Technical University of Denmark
WASA fundamentals and guiding principles
• Public domain [and free]–67 966 data downloads and 4 800 other downloads
• Traceable and transparent [methodology]
• Industry-standard [tools and procedures]
• Uncertainties assessed [to the extent possible]
• Platform for future development [research based]
Results of the Wind Atlas for South Africa (WASA)
WASA Project Team, 8 April 2014, Cape Town
This is exactly what is needed for educational purposes!
Experiences and best practice2
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03 November 2016DTU Wind Energy, Technical University of Denmark
WASA data in education WASA data and materials used for:
• Course exercises
• Course project work
• Master thesis work
• Special course reports
• Teaching materials
• Lectures and talks
• Fundamental for grid planning
• Validation of models– boundary-layer theory– microscale models– mesoscale models– Global Wind Atlas– and many more
Experiences and best practice3
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03 November 2016DTU Wind Energy, Technical University of Denmark
Experiences• Data easily accessible and free
• Few copyright considerations
• WASA data are ‘real data’
• Easy to mimic real-life projects
• State-of-the-art data quality
• WASA project well documented
• Tools and software available
• WASA part of wider tradition
• SA climatology challenging
⇒WASA data are excellent for teaching and project work
Experiences and best practice4
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03 November 2016DTU Wind Energy, Technical University of Denmark
Best practiceEngineering best practice
• IEC standards
• Measnet guidelines
• WAsP best practices
• WRF best practices
• WASA R&D etc.
Educational best practice
• Well-described methodology
• Lots of material available
• Continuing education too
Experiences and best practice5
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03 November 2016DTU Wind Energy, Technical University of Denmark
Pitfalls and challenges• Mean statistics and pdf’s
– Wind power is distributions– Meteorology / climatology– Prognostic / diagnostic
• Reality and model world– Measurements and modelling– Model operational envelopes– Model resolution
• Engineering best practice– Sensitivity analyses– Uncertainty assessment– Reporting practices
• Implementation for teaching– Few challenges
Experiences and best practice6
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03 November 2016DTU Wind Energy, Technical University of Denmark
Final remarks about uncertainty• Knowledge of the surface data is very important
Experiences and best practice7