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Postdoc Health-Aware Control for Offshore Wind Turbines and Wind Farms

This Post-doctoral research position will be part of the R&D project AIMWind – Analytics for asset Integrity Management of Wind Farms (WFs). AIMWIND is a …

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Mekelweg, Delft, Zuid-Holland
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
38 - 38 uur


This Post-doctoral research position will be part of the R&D project AIMWind – Analytics for asset Integrity Management of Wind Farms (WFs). AIMWIND is a collaboration between TU Delft in The Netherlands, and the University of Agder and NORCE in Norway. Large, offshore wind farms are gaining prominence due to the increasing interest and dependence on renewable energy. The harsh operating conditions of offshore Wind Turbines (WTs) favour the occurrence of faults to key electric and mechanical components such as pitch actuator, gearbox and converter, as well as fatigue and failures in structural components including blades and tower. As these phenomena may lead to costly failures of WTs, there is a need for control systems algorithms that can consider the current health status of the WT and keep structural loads and stress or wear on components below an acceptable level. In this way, a WT residual useful life can be optimized, thus leading to lower operating costs and lower cost of energy.

The PostDoc position will be offered at the Delft University of Technology (TUD), at the Delft Center for Systems and Control, which is part of the Maritime, Mechanical and Materials Engineering Faculty. The position is initially for one year but can be extended to a total of three years upon a successful evaluation.

The position will focus on developing and combining both so-called fault-tolerant control laws, as well as structural load-limiting ones for individual WTs. At WF level, the information on each WT health status would allow to develop novel power dispatch algorithms. Such algorithms would allow to maximize the WF power production while preventing to over-stress damaged WTs, thus increasing their Residual Useful Life (RUL) with respect to a non-health-aware control strategy. While the proposed WT and WF control strategy would be developed using reduced-order mathematical models, it will later be tested and validated in medium or high-fidelity simulators, such as FAST Farm or SOWFA. Due to the intrinsic uncertainty introduced by the use of reduced order models, and the stochastic nature of the operating conditions faced by WTs, the work will also focus on quantifying and propagating the effects of such uncertainties over medium to long time horizons.

In particular, the following main tasks will be part of the intended work program:

  1. Develop a fault-tolerant control law that takes into account the presence of faults into electric and mechanical components of a WT.
  2. Develop a load-limiting control law, that takes into consideration current structural health of a WT and predicted operating and environmental conditions.
  3. Develop a WF-level power dispatch control law that can optimize overall power produced while allowing individual WT to maximize their RUL.

Study the effect of stochastic uncertainties on the developed algorithms, by employing suitable uncertainty-propagation techniques, and make them robust in a stochastic sense.

The department Delft Center for Systems and Control (DCSC) of the faculty Mechanical, Maritime and Materials Engineering, coordinates the education and research activities in systems and control at Delft University of Technology. The Centers' research mission is to conduct fundamental research in systems dynamics and control, involving dynamic modelling, advanced control theory, optimisation and signal analysis. The research is motivated by advanced technology development in physical imaging systems, renewable energy, robotics and transportation systems.


Applicants should have the following qualifications:

  • Ph.D. degree (or close to completion) in Systems and Control, Applied Mathematics, Mechanical Engineering, Electrical Engineering or a related field.
  • Strong mathematical skills, deep understanding of control systems theory, proficiency in numerical methods and interest to work at the intersection of System Theory and Renewable Energies.
  • Good programming skills (e.g., in Matlab).
  • Excellent English language and communication skills (Dutch not required).
  • Expertise in wind turbines modelling and control and in stochastic methods such as Polynomial Chaos Expansion or Gaussian Process Regression is highly appreciated.

The candidate will be working closely with other PhD and post-doctoral fellows under the project AIMWind.


TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (salary indication: €3491-€4402 per month).

Additional information

For information about this vacancy, you can contact Riccardo Ferrari, Assistant professor, email: r.ferrari@tudelft.nl, tel: +31 (0)15 2783519.

For information about the selection procedure, please contact Irina Bruckner, HR advisor, email: application-3me@tudelft.nl.