PhD Position on lifetime aware operations and wind farm control

Candidates have a master degree in one of the following or related fields : fluid mechanics, aerospace engineering, mathematical engineering, mechanical engineering, or computational physics. They should have a good background or interest in wind energy, fluid mechanics, optimization, simulation, and programming (Fortran, C / C++, Python, …). Proficiency in English is a requirement. The position adheres to the European policy of balanced ethnicity, age and gender. Persons of all origins and gender are encouraged to apply.BACKGROUND

Europe aims at massive investments in wind energy, with over 300 GW offshore developments by 2050. Much of these installations will be in the North-Sea basin, where the combination of excellent wind conditions and an abundance of sand banks provides favorable conditions for bottom fixed wind farms. At this scale of development, wind farms start to mutually interact through farm wakes that can extend for 50km and more. In fact, recent climate simulations have found significant uncertainty on North-Sea wind conditions induced by unknown offshore development scenarios, much larger than, e.g., the uncertainty introduced by climate change. At a time when the business model of wind energy is becoming subsidy free, this leads to large uncertainties in planning and development, but also significant trends in both energy yields, and market prices over the life time of a wind farm are expected as a result of climate change and increased penetration of renewable energy in the overall energy system. Consequently wind-farm control and operations should adapt to these trends over the wind-farms life time, leading to a robust optimal control problem (over the wind farms life time) in which operations and wind-farms control need to be jointly addressed.

PHD PROJECT DESCRIPTIONThe research aims at the development of a robust optimal control methodology that couples existing turbine and farm wake models and turbine component lifetime models, and takes into account expected trends in climate change and energy prices over the wind-farm’s life time. To this end, existing wind-farm engineering models such as WAYVE (https : / / gitlab.kuleuven.be / TFSO-software / wayve) from the group of J. Meyers are combined with climate change scenarios and market scenario’s developed by other groups in the consortium. The research involves extensive Python code and optimization algorithm development, as well as supercomputing. This PhD position is supervised by Prof. Johan Meyers and hosted in the Turbulent Flow Simulation and Optimization (TFSO) research group at the department of Mechanical Engineering. The research is part of the project “Addressing Impacts of Changing Climates and Energy Markets on Offshore Wind Farms (ACCEMO)” led by Prof. Nicole van Lipzig (KU Leuven), Prof. Erik Delarue (KU Leuven), Prof. Jan Helsen (VUB), and Prof. Johan Meyers (KU Leuven). The research is also integrated into the broader wind-farm control research of the TFSO group at KU Leuven. Currently, various other projects on wind farm planning and control are ongoing, allowing for vivid interactions with many researchers in the same team at one of the leading research institutes on wind farms worldwide.Immediate start is possible. The PhD position lasts for the duration of four years, and is carried out at the University of Leuven. The candidate also takes up a limited amount (approx. 10% of the time) of teaching activities. The remuneration is generous and is in line with the standard KU Leuven rates. It consists of a net monthly salary of about 2400 Euro (in case of dependent children or spouse, the amount can be somewhat higher); social security is also included. Following Belgian law, the salary is automatically adjusted for inflation based on the smoothed health index.