Reduced-Order Models of Wind Farm Blockage and Far-Field Wake Recovery

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Wind energy is Canada's fastest-growing form of renewable energy, with annual investment in Canada exceeding one billion dollars in 2019. Still, achieving national renewable energy targets will require Canada's wind capacity to be significantly increased in the coming decades. New projects require accurate prediction of the energy production potential of a planned wind farm. Such predictions are made using wind farm design tools such as OpenWind®, an industry-leading software developed by UL LLC for layout planning and resource estimation of proposed wind energy sites. To yield accurate predictions, wind farm design software require well-validated but simultaneously low-cost models that capture the aeolian and aerodynamic processes within the wind farm. While such models have been used for hundreds of wind projects, recent studies have shown that the recovery of the low-energy wake downwind and the blockage effect upwind of the wind farm are poorly predicted. Far-field recovery of the wake behind a wind farm is very important for assessing the impact of neighboring wind farms on the overall generation potential. Blockage effects, where the oncoming wind slows down in response to the presence of the wind farm, were historically assumed to be negligible. Recent studies, however, have shown that ignoring blockage yields over-prediction of the wind farm's generation potential. In collaboration with UL, a large series of high-fidelity computational fluid dynamic simulations will be conducted of virtual wind farms, from which improved reduced-order models for wind farm blockage and far-field wake recovery will be developed and validated against field measurements of real wind farms. The project promises to increase the accuracy of power forecasting for new wind projects and promote investment in Canada's wind-rich coastal and northern regions, accelerating Canada's transition to clean energy sources.