Quantum mechanics

Horizontal axis

Engineering

Wind tunnel

Aerospace engineering

Marine engineering

Skew

Vertical axis

Telecommunications

Wind speed

Physics

Wake

Environmental science

Turbine

Wind power

Structural engineering

Engineering drawing

Meteorology

Asymmetry

Electrical engineering

Applied Energy

Predicting the spatial evolution of horizontal-axis turbine wakes is a key factor to enhance the performance of wind and hydrokinetic power plants. The yaw angle misalignment is not only important to account for the uncertainty of the wind direction, but also a control strategy to improve the energy production averaged over the turbine array. In this paper, a new wake model, based on the skew-normal distribution and conservation of mass and momentum, is proposed to predict the turbine wake velocity distribution for given yaw angles. The new model is experimentally validated through wake measurements of yawed miniature wind and hydrokinetic turbines, in wind tunnel and open channel flows, respectively. Predictive capabilities extend from the spatial distribution of the maximum velocity deficit at hub height, to the spanwise asymmetry of the velocity distribution about the wake center.

Wake model for horizontal-axis wind and hydrokinetic turbines in yawed conditions