Abstract
Abstract. Wind turbines are designed to align themselves with the incoming wind direction. However, turbines often experience unintentional yaw misalignment, which can significantly reduce the power production. The unintentional yaw misalignment increases for turbines operating in the wake of upstream turbines. Here, the combined effects of wakes and yaw misalignment are investigated, with a focus on the resulting reduction in power production. A model is developed, which considers the trajectory of each turbine blade element as it passes through the wake inflow in order to determine a power–yaw loss exponent. The simple model is verified using the HAWC2 aeroelastic code, where wake flow fields have been generated using both medium- and high-fidelity computational fluid dynamics simulations. It is demonstrated that the spatial variation in the incoming wind field, due to the presence of wakes, plays a significant role in the power loss due to yaw misalignment. Results show that disregarding these effects on the power–yaw loss exponent can yield a 3.5 % overestimation in the power production of a turbine misaligned by 30∘. The presented analysis and model is relevant to low-fidelity wind farm optimization tools, which aim to capture the combined effects of wakes and yaw misalignment as well as the uncertainty on power output.
Highlights
As the global wind energy sector continues to grow, there is a strong demand for a decreased levelized cost of energy
This paper focuses on the estimation of power loss of a wind turbine when yawed in wake and aims to extend the work of Urbán et al (2019), who used the dynamic wake meandering (DWM) model in conjunction with the aeroelastic tool, HAWC2, to study the effects of axisymmetric wake profiles on a misaligned wind turbine
The same effect can be observed to a lesser extent for the DWM simulation results on the left of Fig. 5
Summary
As the global wind energy sector continues to grow, there is a strong demand for a decreased levelized cost of energy. With this demand comes an increasing need for accurate and efficient computational tools, which are able to improve the design of wind farms and optimize annual energy production. In the early phases of wind farm design, optimization tools provide estimates of energy production and the costs during construction, installation, and operation. McKay et al (2013) have shown yaw misalignment of up to 35◦ for turbines operating in the wakes of aligned upstream turbines based on field measurements for a 6-month period. The probability of a turbine affected by wakes to be yaw misaligned ±25◦ was more than 25 %
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
