Table of contents

The course is connected to the following study programs

  • Offshore Wind Energy

Teaching language

English

Recommended previous knowledge

Previous working experience in offshore industries and energy sector.

Learning outcomes

After the successful completion of the course, the students should:

  • be able to import and display data from SCADA systems.
  • be able to pre-process large datasets containing different types of variables.
  • be able to analyse the performance data from the turbines in the offshore wind farm and use it for the efficient management of offshore wind projects.
  • be able to perform basic data mining for wind energy analytics.

Contents

Introduction to Python programming - Importing relevant SCADA data - Pre-processing data (inspect, clean, working with timestamps, imputation techniques) - Plot relevant data and display basic statistics - Data mining (outlier detection and basic association rules)

Teaching and learning methods

Online lectures and exercises (Python programming). Estimated workload for the average student is approximately 70 hours.

Examinations

Assessment of the group project assignment leading to Pass/Fail. These assignments can be undertaken in groups with a maximum of 4 members. The group as a whole is graded. Further information on the assessment criterion will be given in Canvas at the beginning of the semester.

Student evaluation

A digital evaluation will be organized in accordance with the quality system for education, chapter 4.1.

Offered as a free-standing course

Yes, if there are places available.

Admission Requirement if given as a free-standing course

Admission requirements for the course are the same as for the Study programme on Offshore Wind
Last updated from FS (Felles studentsystem) Oct. 15, 2026 10:07:56 AM