PhD Summer School: Remote Sensing for Wind Energy

11 – 15 June 2018
Venue: DTU Wind Energy, Risø Campus, Roskilde

This 4.5-day summer school will focus on advances in remote sensing techniques useful in wind energy. The themes to be covered are development, instrument configuration, signal processing, data analysis and applications of various remote sensing instruments including LIDAR and SAR both ground- and satellite-based instruments. Applied use includes wind resource mapping, wind profiling, power curve, wind loads, turbulence, and wind turbine control. Theoretical aspects of scattering and atmospheric boundary-layer characteristics relevant in remote sensing for wind energy will also be covered. Practical experiments will demonstrate remote sensing methodologies, and advantages and limitations will be discussed.


• Charlotte Bay Hasager, (chair)
• Alfredo Pena,
• Ebba Dellwik,
• Jakob Mann,
• Merete Badger,
• Michael Courtney,
• Mikael Sjöholm,
• Nikola Vasiljevic,
• Rozenn Wagner,
• Torben Krogh Mikkelsen,

Secretary: Camilla Brix Olsen 

We plan hands-on exercises. Please bring your laptop.

Credits for the course are 2.5 ECTS. 

This includes 34 hours of preparation time studying the Compendium of the PhD Summer School: Remote Sensing for Wind Energy available at

Cost for participants:
250 euros per PhD students 
2000 euros per non-PhD students

Deadline for registration:  15 May 2018

Register for the course  (link)

The registration fee covers participation in the summer school, course material and listing of recommended reading, lunches and coffee breaks from Monday to Friday. 

Registration DOES NOT include the hotel booking.

For further details e-mail Charlotte Hasager at

Learning objectives:

A student who has met the objectives of the course will be able to: 

  • To identify remote sensing instruments for wind energy regarding data types

  • To compare various remote sensing data from different sensors

  • To use flow correction for lidars above hills

  • To develop a typical measurement plan using remote sensing devices for wind data

  • To evaluate data from remote sensing instrument using signal processing methods

  • To calculate the flow adjustment for wind lidars above hills

  • To explain remote sensing techniques for observing turbulence

  • To identify faulty data from remote sensing instruments



Charlotte Bay Hasager
Senior Scientist
DTU Wind Energy
+45 46 77 50 14