PhD Position in Experimental Validation of Wind Farm Flow Control

This PhD position at Delft University of Technology focuses on advancing wind farm efficiency by experimentally validating novel flow control strategies. The project combines physics-based wind farm models with wind tunnel and field data to enhance predictive accuracy and assess the effectiveness of wake-mixing techniques like the Helix approach. The successful candidate will work at the intersection of wind energy aerodynamics, control systems, and data-driven modeling, with a strong emphasis on integrating physical insights with empirical data. Teaching activities (up to 20%) will complement the research, offering valuable mentorship experience. The position is ideal for engineers and scientists passionate about renewable energy and interdisciplinary research.

• Develop and apply data-fusion methods to combine physics-based wind farm models with experimental data (wind tunnel and field measurements).
• Improve and calibrate wind farm models using extensive experimental datasets from the HKN project.
• Quantify uncertainties in wind farm models and experimentally assess the performance of advanced wake-mixing strategies like Helix.
• Conduct research at the intersection of wind farm aerodynamics, advanced control, system identification, and data-driven modeling.
• Collaborate with peers, students, and stakeholders to advance the understanding and application of wind farm control strategies.
• Participate in teaching activities (up to 20% of workload), including supervising lab sessions, assisting in courses, and mentoring undergraduate students.
• Present research findings at conferences and publish results in peer-reviewed journals.