• Wind and Structures
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• v.38 no.4
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• pp.277-293
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• 2024

The recorded thunderstorm winds at a point contain tri-directional components. The probabilistic characteristics of such recorded winds in terms of instantaneous mean wind speed and direction, and the probability distribution and the time-frequency dependent crossed and non-crossed power spectral density functions for the high-frequency fluctuating wind components are unclear. In the present study, we analyze the recorded tri-directional thunderstorm wind components by separating the recorded winds in terms of low-frequency time-varying mean wind speed and high-frequency fluctuating wind components in the alongwind direction and two orthogonal crosswind directions. We determine the time-varying mean wind speed and direction defined by azimuth and elevation angles, and analyze the spectra of high-frequency wind components in three orthogonal directions using continuous wavelet transforms. Additionally, we evaluate the coherence between each pair of fluctuating winds. Based on the analysis results, we develop empirical spectral models and lagged coherence models for the tri-directional fluctuating wind components, and we indicate that the fluctuating wind components can be treated as Gaussian. We show how they can be used to generate time histories of the tri-directional thunderstorm winds.

• Wind and Structures
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• v.31 no.5
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• pp.419-430
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• 2020

Weibull distribution is a conspicuous distribution known for its accuracy and its usage for wind energy analysis. The two and three parameter Weibull distributions are adopted in this study to fit wind speed data. The daily mean wind speed data of Ennore, Tamil Nadu, India has been used to validate the procedure. The parameters are estimated using maximum likelihood method, least square method and moment method. Four statistical tests namely Root mean square error, R2 test, Kolmogorov-Smirnov test and Anderson-Darling test are employed to inspect the fitness of Weibull probability density functions. The value of shape factor, scale factor, wind speed and wind power are determined at a height of 100m using extrapolation of numerical equations. Also, the value of capacity factor is calculated mathematically. This study provides a way to evaluate feasible locations for wind energy assessment, which can be used at any windy site throughout the world.

• Atmosphere
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• v.20 no.2
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• pp.195-210
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• 2010

This study uses mesoscale model WRF to investigate characteristics of wind fields in South Korea, a region with a complex terrain. Hourly wind fields were simulated for one year representing mean characteristics of an 11-year period from year 1998 to year 2008. The simulations were performed on a nested grid from 27 km down to 1 km horizontal resolution. Seasonal variation of wind speed indicates that wind is strongest during the spring and winter seasons. Spatial distribution of mean wind speed shows wind energy potential at its peak in mountainous region of Gangwon-do, the east coast, and Jeju Island. Wind speed peaks at night in mountainous and eastern coastal regions, and in the afternoon inland and in the southwestern coastal region. The simulated wind map was verified with four upper-air sounding observations. Wind speed was shown to have a more pronounced overestimation tendency relative to observation in the winter rather than summer. The results of this wind mapping study help identify locations with the highest wind energy potential in South Korea.

• Wind and Structures
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• v.35 no.6
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• pp.385-394
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• 2022

The energy demand of the world is increasing rapidly, mainly using fossil energy, which causes environmental damage. The wind is free and clean energy to solve the environmental problems. Thailand is one of the developing nations, and the majority of its energy is obtained from petroleum, natural gas and coal. The objective of this study is to test the characteristics of wind energy at Khon Kaen in Thailand. The wind measurement tools, the 3-cup anemometers to measure wind speed, and wind vanes to measure wind direction, were mounted on a wind tower mast to record wind data at the heights of 60, 90 and 120 meters above ground level (AGL) for 5 years between January 2012 and December 2016. The results show that the annual mean wind speeds were 3.79, 4.32 and 4.66 m/s, respectively. The highest mean wind speeds occurred in June, August and December, in order, and the lowest occurred in September. The majority of prevailing wind directions were from the North-East and South-West directions. The average annual wind shear coefficient was 0.297. Furthermore, five wind turbines with rated power from 0.85 to 4.5 MW were selected to estimate the wind energy output and it was found that the maximum AEP and CF were achieved from the low cut-in speed and high hub-height wind turbines. This important information will help to develop wind energy applications, such as the plan to produce electricity and the calculation of the wind load that affects tall and large structures.

• Wind and Structures
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• v.23 no.3
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• pp.191-209
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• 2016

Wind tunnel tests of a 1/2200-scale mountainous terrain model have been carried out to investigate local wind characteristics at a bridge location in southeast Tibet, China. Flows at five key locations on the bridge at deck level were measured for 26 directions. It was observed that wind characteristics (including mean wind velocity and overall turbulence intensity) vary significantly depending on the approaching wind direction and measurement position. The wind inclination angle measured in the study fluctuated between $-18^{\circ}$ and $+16^{\circ}$ and the ratio of mean wind velocity to reference wind velocity was small when the wind inclination angles were large, especially for positive wind inclination angles. The design standard wind speed and the minimum critical wind speed for flutter rely on the wind inclination angle and should be determined from the results of such tests. The variation of wind speed with wind inclination angles should be of the asymmetry step type. The turbulence characteristics of the wind were found to be similar to real atmospheric flows.

• Journal of Wind Energy
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• v.3 no.2
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• pp.34-41
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• 2012

The paper is focusing on investigating the control characteristics of the baseline controller of 5 MW wind turbine provided by NREL(National Renewable Energy Laboratory). The baseline controller consist of two control logics, a maximum power tracking control below the rated wind speed and a constant power control above the rated wind speed. In the low wind speed, the mean generator power for changing the turbulent intensity and the optimal constant is studied through numerical simulations using FAST program. On the other hand, the constant power control logic and the constant control logic are compared in the high wind speed. It is confirmed that optimal constant is closely related to the turbulent intensity in low wind speed region and the constant torque control has better performance than the constant power control with respect to mechanical load in high wind speed region.

• Journal of the Korean Solar Energy Society
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• v.32 no.2
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• pp.95-104
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• 2012

This study purposed to predict wind energy for small size wind power generators at 50m above the ground in each area using mean wind speed data for 10 minutes collected from 2001 to 2011 by meteorological data in large cities having over 60% of 15 story (50m) or higher apartments including Seoul, Daejeon, Gwangju and Daegu representing the inland region, and Busan, Incheon and Ulsan representing the coastal region. In the results of analysis, we confirmed close agree ment between observatory weather data and probability density distribution obtained using Weibull's parameters, and this suggests that Weibull's parameter is applicable to the estimation of wind energy. Hourly output energy using the mean wind speed for 10 minutes and output energy obtained from Weibull's parameter showed an error less than 5%, and thus it was found that wind energy can be evaluated using Weibull's modulus.

• Wind and Structures
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• v.30 no.1
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• pp.85-97
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• 2020

The accurate estimation of the buffeting response of a bridge pylon is related to the quality of the bridge construction. To evaluate the influence of wind field characteristics on the buffeting response of a pylon in a trumpet-shaped mountain pass, this paper deduced a multimodal coupled buffeting frequency domain calculation method for a variable-section bridge tower under the twisted wind profile condition based on quasi-steady theory. Through the long-term measurement of the wind field of the trumpet-shaped mountain pass, the wind characteristics were studied systematically. The effects of the wind characteristics, wind yaw angles, mean wind speeds, and wind profiles on the buffeting response were discussed. The results show that the mean wind characteristics are affected by the terrain and that the wind profile is severely twisted. The optimal fit distribution of the monthly and annual maximum wind speeds is the log-logistic distribution, and the generalized extreme value I distribution may underestimate the return wind speed. The design wind characteristics will overestimate the buffeting response of the pylon. The buffeting response of the pylon is obviously affected by the wind yaw angle and mean wind speed. To accurately estimate the buffeting response of the pylon in an actual construction, it is necessary to consider the twisted effect of the wind profile.

• Wind and Structures
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• v.33 no.6
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• pp.423-435
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• 2021

Although existing algorithms can predict wind speed using historical observation data, for engineering feasibility, most use moment methods and probability density functions to estimate fitted parameters. However, extreme wind speed prediction accuracy for long-term return periods is not always dependent on how the optimized frequency distribution curves are obtained; long-term return periods emphasize general distribution effects rather than marginal distributions, which are closely related to potential extreme values. Moreover, there are different wind speed parent sample types; how to theoretically select the proper extreme value distribution is uncertain. The influence of different sampling time intervals has not been evaluated in the fitting process. To overcome these shortcomings, updated steps are introduced, involving parameter sensitivity analysis for different sampling time intervals. The extreme value prediction accuracy of unknown parent samples is also discussed. Probability analysis of mean wind is combined with estimation of the probability plot correlation coefficient and the maximum likelihood method; an iterative estimation algorithm is proposed. With the updated steps and comparison using a Monte Carlo simulation, a fitting policy suitable for different parent distributions is proposed; its feasibility is demonstrated in extreme wind speed evaluations at Longhua and Chuansha meteorological stations in Shanghai, China.

• Wind and Structures
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• v.8 no.6
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• pp.389-406
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• 2005

The results of reference wind speed calculation in Croatia as a base for the revision of the Croatian standards for wind loads upon structures are presented. Wind speed averaged over 10 minutes, at 10 m height, in a flat, open terrain, with a 50-year mean return period is given for 27 meteorological stations in Croatia. It is shown that the greatest part of Croatia is covered with expected reference wind speeds up to 25 m/s. Exceptions are stations with specific anemometer location open to the bura wind which is accelerated due to the channelling effects of local orography and the nearby mountain passes where the expected reference wind speed ranges between 38 m/s and 55 m/s. The methodology for unifying all available information from wind measurements regardless of the averaging period is discussed by analysing wind speed variability at the meteorological station in Hvar.