Transient response of the flexible blade of horizontal-axis wind turbines in wind gusts and rapid yaw changes

Ebrahimi, Abbas; Sekandari, Mahmood

doi:10.1016/j.energy.2017.12.115

Cited by 46 publications

(15 citation statements)

References 31 publications

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“…He attributed the lag to the time it takes to accelerate the flow after a decrease in axial induction. Ebrahimi & Sekandari (2018) observed a similar delay in thrust change after a step change in wind speed. A linear regression fit is applied to the relationship between and from the experiment, revealing a shallower slope than that of the simulation data (figure 4 d ).…”

Section: Resultsmentioning

confidence: 74%

“…This study also showed a qualitative picture of the wake response to a 30 step change in yaw angle using the vortex wake model, demonstrating that it took approximately 9 rotor revolutions for the wake to fully stabilize. Ebrahimi & Sekandari (2018) simulated the effect of step changes in both wind speed and yaw angle on power production and blade loading, finding the time scale for stabilization to be 4–5 s. Finally, Andersen & Sørensen (2018) used large eddy simulations (LES) to investigate the power output response to changes in wind speed and direction. They found a lag between peaks in thrust force and peaks in power that they attributed to generator inertia and the time scale of the controller.…”

Section: Introductionmentioning

confidence: 99%

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Mechanisms of dynamic near-wake modulation of a utility-scale wind turbine

2021

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The current study uses large eddy simulations to investigate the transient response of a utility-scale wind turbine wake to dynamic changes in atmospheric and operational conditions, as observed in previous field-scale measurements. Most wind turbine wake investigations assume quasi-steady conditions, but real wind turbines operate in a highly stochastic atmosphere, and their operation (e.g. blade pitch, yaw angle) changes constantly in response. Furthermore, dynamic control strategies have been recently proposed to optimize wind farm power generation and longevity. Therefore, improved understanding of dynamic wake behaviours is essential. First, changes in blade pitch are investigated and the wake expansion response is found to display hysteresis as a result of flow inertia. The time scales of the wake response to different pitch rates are quantified. Next, changes in wind direction with different time scales are explored. Under short time scales, the wake deflection is in the opposite direction of that observed under quasi-steady conditions. Finally, yaw changes are implemented at different rates, and the maximum inverse wake deflection and time scale are quantified, showing a clear dependence on yaw rate. To gain further physical understanding of the mechanism behind the inverse wake deflection, the streamwise vorticity in different parts of the wake is quantified. The results of this study provide guidance for the design of advanced wake flow control algorithms. The lag in wake response observed for both blade pitch and yaw changes shows that proposed dynamic control strategies must implement turbine operational changes with a time scale of the order of the rotor time scale or slower.

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Section: Resultsmentioning

confidence: 74%

Section: Introductionmentioning

confidence: 99%

Mechanisms of dynamic near-wake modulation of a utility-scale wind turbine

2021

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“…All the aforementioned works on HAWTs neglect the ABL and analyze a wind gust bigger than the analyzed turbine by means of simplified models. The investigated gust impacts on the whole rotor can be counteracted by the turbine control systems [33]. No work about the aeroelastic response of the blades of a large HAWT immersed in the ABL and locally impacted by a wind gust (i.e., soliciting only one blade) was found in the current literature.…”

Section: Introductionmentioning

confidence: 99%

Fluid–Structure Interaction Simulations of a Wind Gust Impacting on the Blades of a Large Horizontal Axis Wind Turbine

et al. 2020

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The effect of a wind gust impacting on the blades of a large horizontal-axis wind turbine is analyzed by means of high-fidelity fluid–structure interaction (FSI) simulations. The employed FSI model consisted of a computational fluid dynamics (CFD) model reproducing the velocity stratification of the atmospheric boundary layer (ABL) and a computational structural mechanics (CSM) model loyally reproducing the composite materials of each blade. Two different gust shapes were simulated, and for each of them, two different amplitudes were analyzed. The gusts were chosen to impact the blade when it pointed upwards and was attacked by the highest wind velocity due to the presence of the ABL. The loads and the performance of the impacted blade were studied in detail, analyzing the effect of the different gust shapes and intensities. Also, the deflections of the blade were evaluated and followed during the blade’s rotation. The flow patterns over the blade were monitored in order to assess the occurrence and impact of flow separation over the monitored quantities.

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“…7 More recently, the computational fluid dynamics (CFD) tool, which solves the Reynolds-averaged Navier–Stokes (RANS) or unsteady RANS (URANS) equations associated with various turbulence models, begins to play an important role in evaluating gust effects on wind turbines. 1,8–10 However, this practice requires a very fine dynamic moving mesh to adapt to the interaction between the structural deformation of the body and the aerodynamic force subjected, which requires high computational cost, making it almost unrealistic for the industrial community. To overcome this challenge, a number of prescribed velocity methods have been developed over the past years, such as the field velocity method (FVM) and resolved gust approach (RGA).…”

Section: Introductionmentioning

confidence: 99%

A methodological exploration for efficient prediction of airfoil response to gusts in wind engineering

Wang

2019

Proceedings of the Institution of Mechanical Engineers, Part A:

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This paper presents several approaches for efficient estimation of airfoil response to gust via computational fluid dynamics and reduced-order modeling. A computational fluid dynamics code enabling simulation of aerodynamics under an arbitrary-shaped discrete gust is adopted. Convolution models using baseline sharp-edge gust response either obtained by the closed-form Küssner functions or computational fluid dynamics methods are established. A parametric approximation function model for gust response is identified via the least square optimization of the computational fluid dynamics-obtained sharp-edge responses. Finally, an example taking advantage of the aerodynamic response by the above methods to simulate the aeroelastics of an airfoil performing a plunging-twisting coupled motion under various gusts is presented. The present practice indicates that the reduced-order modelings are not only more efficient compared to direct computational fluid dynamics simulations, but also have a satisfactory accuracy in gust response predictions.

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Transient response of the flexible blade of horizontal-axis wind turbines in wind gusts and rapid yaw changes

Cited by 46 publications

References 31 publications

Mechanisms of dynamic near-wake modulation of a utility-scale wind turbine

Mechanisms of dynamic near-wake modulation of a utility-scale wind turbine

Fluid–Structure Interaction Simulations of a Wind Gust Impacting on the Blades of a Large Horizontal Axis Wind Turbine

A methodological exploration for efficient prediction of airfoil response to gusts in wind engineering

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