the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Periods of constant wind speed: How long do they last in the turbulent atmospheric boundary layer?
Abstract. A non-investigated feature of the atmospheric turbulent wind, named periods of constant wind speed, is introduced and investigated. We hypothesize that such periods of constant wind speed are related to characteristic wind field structures (e.g., ramps or jets), which when interacting with a wind turbine may induce particular dynamical responses. Therefore, this study focuses on the characterization of the constant wind speed periods in terms of their lengths, probability of occurrence, and extreme events. Atmospheric offshore wind data are analyzed. Our findings reveal that the statistics of long constant wind speed periods are an intrinsic feature of the atmospheric boundary layer and show the challenging power law behaviour of extreme events, which depends on the local conditions and the precise definition of wind speed thresholds. A comparison to wind time series generated with standard synthetic wind models and to time series from ideal stationary turbulence suggests that these structures are not characteristics of small-scale turbulence but seem to be consequences of larger-scale structures of the atmospheric boundary layer, and thus are a typical multi-scale effect. Given the conclusive results, we show that the Continuous Time Random Walk model, as a non-standard wind model, can be adapted to generate the statistics of those periods of constant wind speed measured from the atmospheric turbulent wind.
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CC1: 'Comment on wes-2024-32', Subharthi Chowdhuri, 23 May 2024
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Dear Authors,
Nice work! The authors may like to see the following papers, where a similar analysis has been proposed.
1. https://pubs.aip.org/aip/pof/article/32/7/076601/1065485
2. https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.9.014601
Thanks for your kind attention.
Disclaimer: this community comment is written by an individual and does not necessarily reflect the opinion of their employer.Citation: https://doi.org/10.5194/wes-2024-32-CC1 -
RC1: 'Comment on wes-2024-32', Anonymous Referee #1, 18 Jun 2024
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General comments
The paper is strong in the technical aspects with well selected analyses to possibly support the hypothesis that the distribution of the CWS event durations can be described with an exponent.
While it is an interesting topic to address, and important to highlight that the standard turbulence model is inadequate, the paper lacks proper motivation. More information would be needed to determine how these events may increase the WT loads. Are they coherent, i.e. do they occur throughout the heights enveloping the rotor area? Which design case of the IEC WT design standard do they fit into, or is a new design case needed (Introduction, L31)? How can the knowledge of these events help the WT and wind plant controller? Can an event be predicted from past few seconds of data?
A major shortcoming is that the period of the observation used for the analysis is too short. Much more data must be analyzed for a meaningful publication. One could for example object against using the statement "conclusive", not once but twice: in the Abstract, and in the section 4.2, page 11. When the period of data collection is extended, the data could then also be separated by wind direction, surface heat flux, and possibly expose additional properties.
The curvature of the spectrum (figures 5, 6, 7) indicates imperfect power law. There is curvature present even at the long durations, which does not help the results being conclusive. One would need to propose a theory at least trying to explain the power-law with physical characteristics of the boundary layer (stability, surface roughness, ...) and then blame the disagreement on incomplete data or another possible cause.
Specific comments
Abstract
L3: please elaborate on "particular dynanmic responses"
L6: what is meant by "the challenging power law behaviour" and why is this introduced with a reference to extreme events? Extreme events are not mentioned anywhere in the paper, other than extremely long CWS duration. Speaking of extreme events ... please verify if they perhaps follow any of the typical extreme event distributionsSection 2.1
L109: It is hard to imagine how would a WT know that a CWS event is imminent and switch into the appropriate control mode in practice.Section 3.4
L158: Good that the effect of the threshold amplitude is analyzed. Would it not be appropriate to add the resulting alpha exponent as another row in Table 3 and so enable easy comparison of different alphas?Citation: https://doi.org/10.5194/wes-2024-32-RC1
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