Modelling wind farm induction using high/low fidelity tools

Today’s wind energy prediction procedures ignore the flow deceleration, also known as blockage, caused by the wind farm on the
approaching wind, resulting in a power overprediction bias that pervades the entire farm. Numerical large eddy simulations (LES)
of wind farms immersed in atmospheric boundary layers (ABL) will be used to study the phenomenon and derive a fastengineering
blockage model, capable of estimating blockage effects as a function of wind farm properties, ABL thermal stability
and complex terrain morphology. Such model will be coupled with a reduced order turbine wake model to predict the entire wind
farm flow. Besides, accurately capturing gravity waves using LES is not straightforward, as gravity waves physics involves spatial
scales much greater than the size of the wind farm or of the turbulence scales. Consequently, the project also aims at defining
standards and producing benchmarks for such computationally intense simulations.

Faculty Supervisor:

Joshua Brinkerhoff

Student:

Partner:

Delft University of Technology

Discipline:

Engineering

Sector:

Education

University:

The University of British Columbia - Okanagan

Program: