• 국제초고층학회논문집
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• 제8권4호
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• pp.313-324
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• 2019

This paper presents the analysis of wind speeds data measured on top of three neighboring high-rise buildings close to a beach in Xiamen city, China, during Typhoon "Usagi" 2013. Wind tunnel simulation was carried out to validate the field measurement results. Turbulence intensity, turbulence integral scale, power spectrum and cross correlation of recorded wind speed were studied in details. The low frequency trend component of the typhoon speed was also discussed. The field measurement results show turbulence intensity has strong dependence to the wind speed, upwind terrain and even the relative location to the Typhoon center. The low frequency fluctuation could severely affect the characteristics of wind. Cross correlation of the measured wind speeds on different buildings also showed some dependence on the upwind terrain roughness. After typhoon made landfall, the spatial correlation of wind speeds became weak with the coherence attenuating quickly in frequency domain.

• Wind and Structures
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• 제32권2호
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• pp.161-167
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• 2021

In this study, the artificial neural network (ANN) method was used for estimating the monthly mean wind speed of Sivas, in the central part of Turkey. Eighteen years of wind speed data obtained from nine measurement stations during the period of 2000-2017 at 10 m height was used for ANN analysis. It was found that mean absolute percentage error (MAPE) ranged from 3.928 to 6.662, mean bias error (MBE) ranged from -0.089 to -0.003, while root mean square error (RMSE) ranged from 0.050 to 0.157 and R2 ranged from 0.86 to 0.966. ANN models provide a good approximation of the wind speed for all measurement stations, however, a tendency to underestimate is also obvious.

• 한국환경과학회지
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• 제9권6호
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• pp.475-482
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• 2000

The purpose of this study is to find out the temporal and spatial characteristics of the diurnal wind variation between coastal and inland areas using the hourly wind data of 58 AWS-stations in the South Korea which are collected during the 10 years from 1980. Diurnal variation is investigated by using the Fast Fourier Transform(FFT), and the wind direction in investigated by comparing C(sub)r with C(sub)v represented the constancy of wind. For the scalar wind speed, the maximum wind speed occurs in the daytime 14h to 16h. The maximum diurnal amplitude at coastal areas occurs from 12h to 16h, and is about 2 hours faster than that at inland areas. Vector mean wind speed is strong at coastal areas and Chupungnyong, Kumi, Taegu of inland areas. The diurnal variation ellipses make a right angle with coastline show that the land and sea breezes are prevailing. The constancy of wind is strong at all observations in January. In the relationship between $C_r and C_v, C_v is higher than C_r$.

• 환경영향평가
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• 제16권6호
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• pp.503-510
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• 2007

Since 1990s many skyscrapers have been built in Seoul. However, gusty winds occur among tall buildings by descending turbulences due to the upper air blocking. This study aims to investigate the wind characteristics of skyscraper prevailing wind direction. In order to evaluate the building wind in this area, The wind speed and the wind direction were measured using propeller type RM-Young wind monitor in this study. The maximum wind speed was recorded by 15.1 m/sec and the main wind direction is WNW and NW. The ultimate purpose of this study is to figure out the phenomena of building wind impact and also to provide essential basic data for establishing proper guidelines in building wind impact assessment for skyscrapers in Korea.

• Wind and Structures
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• 제15권1호
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• pp.1-15
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• 2012

High-resolution wind data were acquired from a 100-m high offshore tower during the passage of Typhoon Hagupit in September, 2008. The meteorological tower was equipped with an ultrasonic anemometer and a number of cup anemometers at heights between 10 and 100 m. Wind characteristics of the strong typhoon, such as mean wind speed and wind direction, turbulence intensity, turbulence integral length scale, gust factor and power spectra of wind velocity, vertical profiles of mean wind speed were investigated in detail based on the wind data recorded during the strong typhoon. The measured results revealed that the wind characteristics in different stages during the typhoon varied remarkably. Through comparison with non-typhoon wind measurements, the phenomena of enhanced levels of turbulence intensity, gust factors, turbulence integral length scale and spectral magnitudes in typhoon boundary layer were observed. The monitored data and analysis results are expected to be useful for the wind-resistant design of offshore structures and buildings on seashores in typhoon-prone regions.

• 대한토목학회논문집
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• 제30권6B호
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• pp.617-625
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• 2010

풍속의 세제곱에 비례하는 풍력발전기의 전기발전량을 효과적으로 증대시키기 위해서는, 풍속이 강한 부지 선정이 중요하다. 일반적으로 내륙지역보다 풍속이 강한 연안지역에 풍력발전기를 설치하는 것이 바람직하다. 또, 해상풍력개발은 풍력발전기의 중요한 단점 중 하나인 소음 문제를 해결할 수 있는 방법으로 기대된다. 풍력개발 사업을 실행하는 과정에서, 어떤 지역의 풍력발전 가능성을 미리 파악하는 것은 풍력발전의 최적지를 선정하는데 있어서 중요한 요소들 중 하나이다. 본 연구는 기상청이 10년간 관측한 제주도 14개 지역의 풍향 및 풍속데이터를 가지고 제주 연안지역의 풍력발전 가능성에 대해 검토하였다. 풍력발전기의 설치높이를 80 m로 가정하고 풍속데이터를 보정하였으며, 이 값을 가지고 풍력에너지 밀도와 연간 풍력에너지량을 산출하였다. 그리고 모든 관측지점의 연간 전기발전량과 에너지취득률은 3,000 KW 풍력발전기에 관한 정보를 이용하여 산출되었다.

• 한국환경과학회지
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• 제14권11호
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• pp.1015-1026
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• 2005

The southeastern coastal area of the Korean peninsula has a complex terrain including an irregular coastline and moderately high mountains. This implies that mesoscale circulations such as mountain-valley breeze and land-sea breeze can play an important role in wind field and ocean forcing. In this study, to improve the accuracy of complex coastal rind field(surface wind and sea surface wind), we carried out the sensitivity experiments based on PBL schemes in PSU/NCAR Mesoscale Model (MM5), which is being used in the operational system at Korea Meteorological Administration. Four widely used PBL parameterization schemes in sensitivity experiments were chosen: Medium-Range Forecast (MRF), High-resolution Blackadar, Eta, and Gayno-Seaman scheme. Thereafter, case(2004. 8. 26 - 8. 27) of weak-gradient flows was simulated, and the time series and the vertical profiles of the simulated wind speed and wind direction were compared with those of hourly surface observations (AWS, BUOY) and QuikSCAT data. In the simulated results, the strength of rind speed of all schemes was overestimated in complex coastal regions, while that of about four different schemes was underestimated in islands and over the sea. Sea surface wind using the Eta scheme showed the highest wind speed over the sea and its distribution was similar to the observational data. Horizontal distribution of the simulated wind direction was very similar to that of real observational data in case of all schemes. Simulated and observed vertical distribution of wind field was also similar under boundary layer(about 1 km), however the simulated wind speed was underestimated in upper layer.

• Asian Journal of Atmospheric Environment
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• 제9권4호
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• pp.288-297
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• 2015

In this study, wind conditions and its energy potential have been assessed by conducting a Weibull analysis of the wind speed data (over the period of 2002-2011) measured from a port city (Mongla) and an isolated island (Sandwip) in Bangladesh. The monthly mean wind speed at Mongla ranged from 1.60 m/s (December) to 2.47 m/s (April). The monthly values of Weibull shape parameter (k) were from 1.27 to 2.53. In addition, the values of the scale parameter (c) and the monthly wind power density ranged from 1.76 to 2.79 m/s and 3.95 to $17.45W/m^2$, respectively. The seasonal mean wind speed data varied from 1.72 (fall) to 2.29 m/s (spring) with the wind power density from 5.33 (fall) to $14.26W/m^2$ (spring). In the case of Sandwip, the results were comparable to those of Mongla, but moderate reductions in all the comparable variables were observed. The wind data results of these two areas have been compared with those of eight other locations in the world with respect to wind power generation scale. According to this comparison, the wind power generation scale for Mongla and Sandwip was adequate for stand-alone small/micro-scale applications such as local household consumption, solar-wind hybrid irrigation pumps, and battery charging.

• Wind and Structures
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• 제28권6호
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• pp.381-388
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• 2019

This paper described the application of Geospatial Analysis in determining mean wind speed, $V_h$ for wind load calculation imposed to electrical transmission tower structural design. The basic wind speed data on available station obtained from Malaysian Meteorology Department is adjusted by considering terrain and ground roughness factor. The correlation between basic wind speed, terrain factor and ground roughness stated in EN-50341-1 is used to obtain the $V_h$ for overhead transmission line elements 50 m above ground. Terrain factor, $k_r$ and ground roughness, $z_0$ in this study are presented by land use types of study area. Wind load is then calculated by using equation stated in design code EN-50341-1 by using the adjusted mean wind speed. Scatter plots of $V_h$ for different $k_r$and $z_0$ are presented in this paper to see the effect of these parameters to the value of $V_h$. Geospatial analysis is used to represent the model of $V_h$. This model can be used to determine possible area that will subject to wind load which severe to the stability of transmission tower and transmission line.

• 신재생에너지
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• 제16권1호
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• pp.15-24
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• 2020

For mechanical load testing of wind turbines, capture matrix is constructed for various range of wind speeds according to the international standard IEC 61400-13. The conventional method wastes considerable amount of data by its invalid data policy -segment data into 10 minutes then remove invalid ones. Previously, we have suggested an alternative way to save the total amount of data to build a capture matrix, but the efficient selection of data has been still under question. The paper introduces optimization algorithms to construct capture matrix with less data. Heuristic algorithm (simple stacking and lowest frequency first), population method (particle swarm optimization) and Q-Learning accompanied with epsilon-greedy exploration are compared. All algorithms show better performance than the conventional way, where the distribution of enhancement was quite diverse. Among the algorithms, the best performance was achieved by heuristic method (lowest frequency first), and similarly by particle swarm optimization: Approximately 28% of data reduction in average and more than 40% in maximum. On the other hand, unexpectedly, the worst performance was achieved by Q-Learning, which was a promising candidate at the beginning. This study is helpful for not only wind turbine evaluation particularly the viewpoint of cost, but also understanding nature of wind speed data.