Course Overview

Unlock the power of scientific programming to advance wind resource assessment. This course equips participants with practical skills in Python and its scientific ecosystem—including NumPy, pandas, xarray, and geopandas—as well as QGIS for geospatial data handling. You’ll learn to perform robust numerical wind resource assessments using specialised tools like Windkit and PyWAsP, gaining hands-on experience in processing, analysing, and visualising wind data.

Main Goal

To be Updated.

Skills To Be Gained

After this course, you can

1. Develop and apply scientific programming techniques tailored to wind resource assessment.
2. Use Python and QGIS to process and interpret reanalysis, terrain, and wind measurement datasets.
3. Perform advanced numerical analyses with Windkit and PyWAsP to evaluate wind resources and support wind energy project development.
4. Build a comprehensive understanding of the methodologies, data sources, and best practices fundamental to modern wind resource assessment.
5. Ideal for programmers and engineers eager to bridge the gap between software development and renewable energy analytics, this course provides the tools and knowledge needed to contribute effectively to wind energy projects.

Practical Notes

This course will be stackable with other LLL courses that will be developed by DTU Wind, to form certain specialisations or micro-degrees.