[Paper Review] Influence of atmospheric conditions on the power production of utility-scale wind turbines in yaw misalignment

Michael F. Howland, Carlos Moral González+6 more|arXiv (Cornell University)|Jul 31, 2020

Wind Energy Research and Development4 citations

TL;DR

This study develops a physics-based model for predicting power production of utility-scale wind turbines in yaw misalignment, accounting for atmospheric wind shear, veer, and turbine control systems. It shows that power scales approximately as cos²(γ) rather than cos³(γ), with significant asymmetry due to wind speed and direction gradients across the rotor, invalidating standard symmetric models used in wake steering optimization.

ABSTRACT

The intentional yaw misalignment of leading, upwind turbines in a wind farm, termed wake steering, has demonstrated potential as a collective control approach for wind farm power maximization. The optimal control strategy, and resulting effect of wake steering on wind farm power production, are in part dictated by the power degradation of the upwind yaw misaligned wind turbines. In the atmospheric boundary layer, the wind speed and direction may vary significantly over the wind turbine rotor area, depending on atmospheric conditions and stability, resulting in freestream turbine power production which is asymmetric as a function of the direction of yaw misalignment and which varies during the diurnal cycle. In this study, we propose a model for the power production of a wind turbine in yaw misalignment based on aerodynamic blade elements which incorporates the effects of wind speed and direction changes over the turbine rotor area in yaw misalignment. A field experiment is performed using multiple utility-scale wind turbines to characterize the power production of yawed freestream operating turbines depending on the wind conditions, and the model is validated using the experimental data. The resulting power production of a yaw misaligned variable speed wind turbine depends on a nonlinear interaction between the yaw misalignment, the atmospheric conditions, and the wind turbine control system.

Motivation & Objective

• To address the inaccuracy of symmetric power models (e.g., P ∝ cos³(γ)) in predicting power loss during yaw misalignment.
• To quantify how atmospheric wind shear and veer affect the asymmetric power response of yawed wind turbines.
• To develop a predictive model that incorporates turbine control systems (generator torque) and spatial wind profiles.
• To validate the model using field data from utility-scale turbines in India under real atmospheric conditions.
• To enable more accurate wake steering control by replacing generic power loss assumptions with site-specific, asymmetric power predictions.

Proposed method

• Develops a blade element momentum (BEM)-based model that computes aerodynamic forces across the rotor disk under yaw misalignment.
• Incorporates measured wind speed and direction profiles across the rotor height using MET mast and LiDAR data.
• Models the generator torque control system to compute angular velocity Ω(γ), which is not proportional to cos(γ) as assumed in prior models.
• Uses the computed Ω(γ) and local wind conditions to calculate power output P(γ) as a function of yaw angle.
• Validates the model against field measurements from multiple utility-scale turbines in a real wind farm in northwest India.
• Compares model predictions to the standard cos³(γ) model and evaluates asymmetry in power response for positive vs. negative yaw angles.

Experimental results

Research questions

• RQ1 How does atmospheric wind shear and veer affect the power production of a yaw misaligned wind turbine?
• RQ2 Why does the standard cos³(γ) model fail to predict actual power loss in yawed turbines?
• RQ3 How does the generator torque control system influence angular velocity and power output under yaw misalignment?
• RQ4 To what extent is the power response of a yawed turbine asymmetric with respect to the direction of yaw misalignment?
• RQ5 Can a physics-based model incorporating wind profiles and control systems improve power prediction accuracy for wake steering applications?

Key findings

• The power of a yaw misaligned wind turbine scales approximately as cos²(γ), not cos³(γ), due to the failure of the angular velocity to follow cos(γ) under generator torque control.
• The power response is asymmetric: power loss differs for positive and negative yaw angles due to wind speed and direction gradients across the rotor.
• Field data from a utility-scale wind farm in India confirmed that the standard cos³(γ) model underestimates power loss and fails to capture asymmetry.
• The model's prediction of P(γ) ≈ P(0)·cos²(γ) with site-specific deviations accurately matches experimental data, validating the approach.
• The asymmetry arises from the combination of wind shear, veer, blade rotation direction, and turbine control system dynamics.
• Future wake steering strategies must use site-specific, asymmetric power models rather than symmetric cos³(γ) approximations to avoid suboptimal control.