A study of the wake effects on the wind characteristics and fatigue loads for the turbines in a wind farm

Kim, Soohyun; Shin, Hyung-Ki; Joo, Young-Chul; Kim, Keon-Hoon

doi:10.1016/j.renene.2014.08.054

Cited by 75 publications

(36 citation statements)

References 14 publications

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“…This task has been recently attracting much interest in the scientific community dealing with wind energy: the expected lifetime of a component is gradually becoming a parameter depending on the history of the operation of a wind turbine, rather than an estimate provided at the design phase. This connects the present work to an important future development: the analysis and modeling of fatigue loads [41,42]. In the perspective that in the future, it could be possible to formulate and connect careful modelings of the rotor, drive-train and wind field for wake and non-waked operation, in order to build a theoretical framework from wind to gear and from gear to wind, it is certainly valuable to start from the experimental evidence, as has been done in this work.…”

Section: Discussionsupporting

confidence: 55%

Wind Turbine Loads Induced by Terrain and Wakes: An Experimental Study through Vibration Analysis and Computational Fluid Dynamics

et al. 2017

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Abstract:A wind turbine is a very well-known archetype of energy conversion system working at non-stationary regimes. Despite this, a deep mechanical comprehension of wind turbines operating in complicated conditions is still challenging, especially as regards the analysis of experimental data. In particular, wind turbines in complex terrain represent a very valuable testing ground because of the possible combination of wake effects among nearby turbines and flow accelerations caused by the terrain morphology. For these reasons, in this work, a cluster of four full-scale wind turbines from a very complex site is studied. The object of investigation is vibrations, at the level of the structure (tower) and drive-train. Data collected by the on-board condition monitoring system are analyzed and interpreted in light of the knowledge of wind conditions and operating parameters collected by the Supervisory Control And Data Acquisition (SCADA). A free flow Computational Fluid Dynamics (CFD) simulation is also performed, and it allows one to better interpret the vibration analysis. The main outcome is the interpretation of how wakes and flow turbulences appear in the vibration signals, both at the structural level and at the drive-train level. Therefore, this wind to gear approach builds a connection between flow phenomena and mechanical phenomena in the form of vibrations, representing a precious tool for assessing loads in different working conditions.

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Section: Discussionsupporting

confidence: 55%

Wind Turbine Loads Induced by Terrain and Wakes: An Experimental Study through Vibration Analysis and Computational Fluid Dynamics

et al. 2017

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“…Besides significant power losses, rotors exposed to upstream turbines' wakes experience higher unsteady loading (Kim et al, 2015). The reduced power and increased rotor loads are dependent on the downstream turbine's lateral and streamwise location in the wake, the upstream turbine's control settings and the characteristics of the incoming wind.…”

Section: Introductionmentioning

confidence: 99%

Wind tunnel study on power output and yaw moments for two yaw-controlled model wind turbines

2018

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Abstract. In this experimental wind tunnel study the effects of intentional yaw misalignment on the power production and loads of a downstream turbine are investigated for full and partial wake overlap. Power, thrust force and yaw moment are measured on both the upstream and downstream turbine. The influence of inflow turbulence level and streamwise turbine separation distance are analyzed for full wake overlap. For partial wake overlap the concept of downstream turbine yawing for yaw moment mitigation is examined for different lateral offset positions.Results indicate that upstream turbine yaw misalignment is able to increase the combined power production of the two turbines for both partial and full wake overlap. For aligned turbine setups the combined power is increased between 3.5 % and 11 % depending on the inflow turbulence level and turbine separation distance. The increase in combined power is at the expense of increased yaw moments on both the upstream and downstream turbine. For partial wake overlap, yaw moments on the downstream turbine can be mitigated through upstream turbine yawing. Simultaneously, the combined power output of the turbine array is increased. A final test case demonstrates benefits for power and loads through downstream turbine yawing in partial wake overlap. Yaw moments can be decreased and the power increased by intentionally yawing the downstream turbine in the opposite direction.

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“…Before closing, we observe that collective interactions between turbines in a wind plant also change the local flow field in the plant's vicinity [30,31], in turn compromising plant efficiency [32,33]. Decomposing plant-induced variability from natural environmental factors is often complicated [30,34].…”

Section: Discussionmentioning

confidence: 95%

Variability of the Wind Turbine Power Curve

Bandi

Apt

2016

Applied Sciences

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Wind turbine power curves are calibrated by turbine manufacturers under requirements stipulated by the International Electrotechnical Commission to provide a functional mapping between the mean wind speed v and the mean turbine power output P. Wind plant operators employ these power curves to estimate or forecast wind power generation under given wind conditions. However, it is general knowledge that wide variability exists in these mean calibration values. We first analyse how the standard deviation in wind speed σ v affects the mean P and the standard deviation σ P of wind power. We find that the magnitude of wind power fluctuations scales as the square of the mean wind speed. Using data from three planetary locations, we find that the wind speed standard deviation σ v systematically varies with mean wind speed v, and in some instances, follows a scaling of the form σ v = C × v α ; C being a constant and α a fractional power. We show that, when applicable, this scaling form provides a minimal parameter description of the power curve in terms of v alone. Wind data from different locations establishes that (in instances when this scaling exists) the exponent α varies with location, owing to the influence of local environmental conditions on wind speed variability. Since manufacturer-calibrated power curves cannot account for variability influenced by local conditions, this variability translates to forecast uncertainty in power generation. We close with a proposal for operators to perform post-installation recalibration of their turbine power curves to account for the influence of local environmental factors on wind speed variability in order to reduce the uncertainty of wind power forecasts. Understanding the relationship between wind's speed and its variability is likely to lead to lower costs for the integration of wind power into the electric grid.

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A study of the wake effects on the wind characteristics and fatigue loads for the turbines in a wind farm

Cited by 75 publications

References 14 publications

Wind Turbine Loads Induced by Terrain and Wakes: An Experimental Study through Vibration Analysis and Computational Fluid Dynamics

Wind Turbine Loads Induced by Terrain and Wakes: An Experimental Study through Vibration Analysis and Computational Fluid Dynamics

Wind tunnel study on power output and yaw moments for two yaw-controlled model wind turbines

Variability of the Wind Turbine Power Curve

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