Abstract
Abstract. This paper details the background to the WakeBlaster model: a purpose-built, parabolic three-dimensional RANS solver, developed by ProPlanEn. WakeBlaster is a field model, rather than a single turbine model; it therefore eliminates the need for an empirical wake superposition model. It belongs to a class of very fast (a few core seconds, per flow case) mid-fidelity models, which are designed for industrial application in wind farm design, operation, and control. The domain is a three-dimensional structured grid, a node spacing of a tenth of a rotor diameter, by default. WakeBlaster uses eddy viscosity turbulence closure, which is parameterized by the local shear, time-lagged turbulence development, and stability corrections for ambient shear and turbulence decay. The model prescribes a profile at the end of the near wake, and the spatial variation of ambient flow, by using output from an external flow model.
Highlights
In wind farms, wind turbines located downstream of other turbines will experience wake losses
Using single turbine wake models means that the wake from each turbine is propagated independently, wake expansion is not impacted by neighbouring wakes, and multiple wake deficits are superimposed using an empirical wake superposition model
Single wake models are based on an approach suggested 40 years ago, by Lissaman (1979) and Lissaman et al (1982), who transferred the work of Abramovich (1963) on free jets to wind turbine wakes
Summary
Wind turbines located downstream of other turbines will experience wake losses. Given the importance of wake losses, it may appear contradictory that many in the industry still use analytical single turbine wake models. Single wake models are based on an approach suggested 40 years ago, by Lissaman (1979) and Lissaman et al (1982), who transferred the work of Abramovich (1963) on free jets to wind turbine wakes. The increased computational power and scalability available today allows higher-fidelity wake models to be used in the iterative process of wind farm design. These models widen the operational envelope, include more physics, and reduce model uncertainties in non-standard situations.
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