Wind farm wake flow recovery with the use of kites

Wind farm wake flow recovery with the use of kites

Kokkedee, Jop (TU Delft Electrical Engineering, Mathematics and Computer Science)

Bierbooms, W.A.A.M. (mentor)
Allaerts, D.J.N. (mentor)
Schmehl, R. (graduation committee)
van Zuijlen, A.H. (graduation committee)

Delft University of Technology

Electrical Engineering | Sustainable Energy Technology

2022-06-28

With an ever increasing demand for sustainable energy, limitations of current sustainable technologies are studied widely. In wind farms, the so-called wake effect provides the biggest limitation on wind farm total power output. Using wind from the unaffected boundary layer to re-energize the wind flow in the wake provides a method of limiting this wake effect. In this study, kites are introduced to steer the wind flow of the unaffected boundary layer into the wake through a downwash velocity. RANS (Reynolds-averaged Navier-Stokes) simulations are performed in Computational Fluid Dynamics (CFD) software OpenFOAM of the atmospheric boundary layer (1), a small four-turbine wind farm (2) and a wind farm with static kites between the turbines (3). The turbines are modelled through the actuator disc approach, and kites are introduced through the more complex actuator line method. Results of the athmospheric boundary layer (ABL) and wind farm simulations correspond well with literature. Through extensive kite parameter studies, an optimal layout of kites in the wind farm is presented yielding a wind farm efficiency increase of 2.3 %, which increases over 5% for even larger kites. Kite size and the kite’s downstream location show to impact the re-energising levels of the wake flow the most. The kites generate a downwash wake instead of a single downwash velocity, a finding that should further be studied in future research.

Wind Energy
Kites
Energy Efficiency
Wake Aerodynamics
Atmoshperic Boundary Layer
WInd Farm
Actuator Disk Method
Actuator Line Method
OpenFOAM
CFD

http://resolver.tudelft.nl/uuid:79bb9fd7-6646-4e85-b562-c93a38189b98

Student theses

master thesis

© 2022 Jop Kokkedee