Course Overview
This course equips wind engineers with practical, data-supported methodologies and tools to estimate the remaining useful life (RUL) of existing assets. By combining numerical models with historical operational data, this data-driven procedure creates an estimation of the actual consumed fatigue lifetime of an asset and supports informed lifecycle decisions. To enable participants to gain hands-on experience, the coursework leverages outputs from DTU Wind software tools, where open-access tools are provided to the participants, and results from proprietary tools (or data-driven surrogate model versions of them) are also provided.
Main Goal
To be Updated.
Teaching & Assessment
The course follows a project-based learning format, where participants work with a real load model or dataset from an existing wind turbine, a relevant SCADA dataset, and regulatory information for a specific location.
The program begins with lectures and tool demonstrations – including an introduction to the problem – followed by guided project work. In the final stage, participants present their results and justify their chosen methodologies. Both synchronous and asynchronous teaching methods are used.
Skills To Be Gained
After this course, you can:
- + Apply uncertainty quantification and propagation techniques using surrogate models.
- + Process and analyse SCADA data for wind turbine operations.
- + Use methodologies to recover fatigue load history from historical data, employing digital twins and virtual sensing techniques.
- + Identify relevant end-of-life decisions for wind assets and assess their feasibility based on economic and regulatory criteria.
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. For instance, we offer a series of courses that can be combined to form the specialisation "Data-Driven Decision Making for Wind Farm Operations." This specialisation includes four courses, with "Model-Based Estimation of Remaining Useful Life" serving as the entry point.
Meet Your Instructors
Senior Scientist
Researcher
Researcher
Researcher
Admissions
Requirements
- + Solid understanding of the wind energy sector and wind turbine design or engineering processes, typically gained through a master's degree in wind energy or equivalent industry experience.
- + Familiarity with Python programming.
How to Apply
Complete the Online Application Form
Submit Required Documents
Academic Transcripts
Statement of Purpose
CV / Resume
2 Letters of Recommendation:
- Application Review & Interview (if applicable)
- Offer Letter & Enrollment
Application Deadline: July 31, 2025
Fees & Funding
Tuition Fees
EU Students: €9,500/year
Non-EU Students: €16,500/year
Scholarships Available
- + Green Future Scholarship – Merit-based financial aid for top applicants.
- + Women in Renewable Energy – Supports female students in STEM fields.
- + Industry-Sponsored Fellowships – Partnership grants from energy companies.
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