Overordnede kursusmål
Writing code to solve complex problems is an essential skill for
researchers and engineers in wind energy. This course helps
students to develop this skill in the wind energy context through:
mastering Python basics; learning core principles and best
practices for programming; practicing usage of fundamental software
development tools and techniques such as version control and
architecture design; leveraging scientific computation tools
commonly used in the wind energy field, like numpy, matplotlib and
scipy; developing, evaluating and communicating Python
scripts/libraries for wind energy applications through hands-on
coding projects, peer code reviews and code presentations.
Læringsmål
En studerende, der fuldt ud har opfyldt kursets mål, vil kunne:
- Explain core concepts of computational thinking and scientific
programming with examples from wind energy
- Write Python functions and scripts for basic wind energy
applications
- Utilize Python packages common to wind energy applications,
such as numpy, matplotlib, scipy, etc.
- Manipulate data stored in the most common wind energy formats,
demonstrating skills such as loading from/saving to file,
performing computations, and visualizing results
- Do version control on documents/projects for wind energy
applications with a typical Git workflow (change, add and
commit)
- Write and debug code using VS Code and related extensions
- Communicate code orally and also in writing, via diagrams,
comments, commit messages, and documentation
- Critically analyze code for good coding practices such as
modularity, maintainability, adherence to stylistic conventions,
etc.
Kursusindhold
The course consists of 13 modules covering the following
content/topics in the wind energy application context:
- Foundational Programming Tools, such as Git for version control
and VS Code.
- Python basics for wind energy applications, covering topics such
as basic data structure, control flow, functions and modules.
- Scientific programming essentials for wind energy with numpy,
matplotlib and scipy, such as manipulating, visualizing data from
wind energy, and solving scientific computing problems relevant for
wind energy.
- Computational thinking and good programming practices for wind
energy, such as class and object-oriented programming, software
architecture design, code quality and testing.
The students will practice what they learned in a final hands-on
programming project for selected wind energy applications, among
topics like wind resource assessment, wind turbine modeling and
wind power forecasting.
Sidst opdateret
02. maj, 2025