최근 기상자료에 의한 지표면조도구분별 돌풍률 평가

김병조,하영철 한국풍공학회 2015 한국풍공학회지 Vol.19 No.2

Design wind speeds for estimating wind loading of structures were based on the 10 minute mean wind speed or the gust wind speed having 3 second averaging time. The 10 minute mean wind speed might be applied to estimate wind load of buildings and the 3 second gust wind speed might be applied to high frequency structures such as claddings. The gust wind speed is affected by the conditions of surroundings, so it convenient to estimate gust wind speed by the product of gust factor and 10 minute mean wind speed. This study estimates gust factor suitable for the surface roughness categories, which is reflecting a severe change of surface roughness by rapid urbanization process and recent abnormal weather by global warming. Wind speed values are established from data of 10-minute mean and 3 second gust wind speed collected at 68 meteorological offices recent past 40 years from 1973 to 2012 and surface roughness categories are used previous study result. For estimating gust factor, it is assumed that the range of maximum monthly value of mean wind speed has limited from 16m/s to 18m/s and gust factors have constant value, if wind speeds are below 16m/s or over 36m/s. By the results of study, it is known that gust factors of surface roughness category C are similar to those of B and gust factors of surface roughness category D are different from other categories. Therefore, empirical formula of gust factor on surface roughness category B and C was suggested on the same type and on surface roughness category D was suggested on different type. 구조물의 풍하중을 산정할 때의 설계풍속은 10분 평균풍속 또는 가스트풍속(3초평균풍속)을 적용한다. 건축물의 경우 10분 평균풍속 사용하고 있으나, 외장재 등과 같이 고진동수를 가지는 구조물의 경우에는 가스트풍속을 사용한다. 가스트풍속은 기상대 주변의 영향을 크게 받기 때문에, 일반적으로 10분 평균풍속에 돌풍율을 곱하여 산정하는 것이 편리하다. 본 연구는 최근 우리나라의 기상변화와 경제 발전에 따른 기상대 주변의 지표면상태의 변화를 반영하여 지표면조도에 알맞은 돌풍률을 평가한 것이다. 해석자료는 최근 40년간(1973년~2012년)의 전국 68개 기상관측소의 기상자료와 선행연구에서 제시한 지표면조도구분을 활용하였다. 돌풍률을 추정할 때 평균풍속의 월최대값 범위는 16m/s~36m/s로 하였고, 16m/s 이하와 36m/s 이상에서는 돌풍률을 일정하게 하였다. 연구결과 지표면조도구분 B지역과 C지역의 돌풍률은 거의 유사하게 나타났고, 지표면조도구분 D지역은 다른 지역의 돌풍률과 차이를 보였다. 따라서 지표면조도구분 B, C지역의 돌풍률은 통합하여 평가하였고, 지표면조도구분 D지역만 따로 분류하여 돌풍률을 평가하여 제시하였다.

건축물의 주골조 설계용 풍향계수의 추정

권성난,신동현,최심국,하영철 한국풍공학회 2019 한국풍공학회지 Vol.23 No.1

The types of wind in Korea shall be divided into Typhoon, Frontal system storm and Monsoon. Korean peninsula has geographical characteristics both having many mountains and surrounding three sides by sea. Because of these, the wind speed presents different values to wind direction in each region. For the wind-force resisting design of buildings, wind speed for the 100 year's return period defined in KBC (Korean Building Code) 2016 shall be used at all directions. KBC2016 does not take into account the wind directional effect. Therefore, wind loads evaluated by KBC2016 may be somewhat conservative. In this paper, the 10-minute mean wind speed date at 16 wind direction in 10 regional weather stations were collected, and the wind speeds for 100 year's return period at 16 wind directions were evaluated. To homogenize the collected wind data, the effective height has been considered for each wind direction, and both the gust factor method and the visual measurement method were used to judge the surface roughness category. Gumbel's distribution was has been selected to estimate the wind speed for 100 year's return period at 16 wind directions. Empirical exceed probability was used Hazen method. Compatibility both Gumbel's distribution and Hazen plot was judged by conformity assesment function. Based on these, wind directional coefficients at each region were evaluated. By comparing the wind directional coefficient each regions, the characteristics of the wind speed both each region and each wind direction were discussed. 우리나라의 바람은 계절풍, 태풍, 저기압 전선풍으로 나눌 수 있다. 또한 우리나라는 산지가 많고 삼 면이 바다로 둘러싸인 지리적인 특성도 갖고 있다. 이로 인해 각 지역의 풍향마다 풍속이 균일하게 불어오지 않는다. 내풍설계 시 사용하는 풍속은 건축구조기준에 규정된 100년 재현기대풍속을 전풍향에 대해 동일하게 사용한다. 이 값은 풍향을 고려하지 않기 때문에 다소 보수적인 설계가 될수 있다. 이 연구에서는 10개 지역을 대상으로 16풍향에 대한 분풍속을 수집하여 풍향별 100년 재현기대풍속을 산출하였다. 기상청에서 수집한 자료를 균질하게 하기 위해 풍향별로 유효높이를 고려하였고, 지표면조도구분을 하는 방법으로 가스트계수방법과 목측방법을 사용하였다. 풍향별 100년 재현기대풍속을 산정하기 위한 확률분포는 Gumbel분포를 사용하였고, 경험적 초과확률로는 Hazen방법을 이용하였으며, Gumbel분포와 Hazen방법의 적합성은 적합성평가함수에 의해 판단하였다. 이것을 토대로 각 지역의 풍향계수를 산출하였고, 풍향계수의 비교를 통해 지역별, 풍향별 풍속의 특성을 파악하였다.

Geospatial analysis of wind velocity to determine wind loading on transmission tower

Nur H. Hamzah,Fathoni Usman 한국풍공학회 2019 Wind and Structures, An International Journal (WAS Vol.28 No.6

This paper described the application of Geospatial Analysis in determining mean wind speed, 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 for overhead transmission line elements 50 m above ground. Terrain factor, and ground roughness, 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 for different and are presented in this paper to see the effect of these parameters to the value of . Geospatial analysis is used to represent the model of . 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.

우리 나라의 바람 일변동 특성

송봉근,김영섭,이동인,한영호 한국환경과학회 2000 한국환경과학회지 Vol.9 No.6

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 to 1989. Diurnal variation is investigated by using the Fast Fourier Transform(FFT), and the wind direction is investigated by comparing C_r with C_v represented the constancy of wind. For the scalar wind speed, the maximum wind speed occurs in the daytime from 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.

Computational Methods of Average Wind Speed and Direction

Lee, Chee-Cheong,Park, Soo-Hong The Korea Institute of Information and Commucation 2010 Journal of information and communication convergen Vol.8 No.1

Wind speed and wind direction are usually taken using two parameters: wind speed and wind direction. This paper studies the average wind speed and direction calculation methods. The paper first introduces to basic wind's knowledge, and then presents several methods in calculating average wind speed and direction. Lastly some graphs are plotted base on these computational methods and the implementation of these methods in an actual buoy system.

Power Curve of a Wind Generator Suitable for a Low Wind Speed Site to Achieve a High Capacity Factor

Yoon, Gihwan,Lee, Hyewon,Lee, Sang Ho,Hur, Don,Cheol, Yong The Korean Institute of Electrical Engineers 2014 Journal of Electrical Engineering & Technology Vol.9 No.3

It is well known that energy generated by a wind generator (WG) depends on the wind resources at the installation site. In other words, a WG installed in a high wind speed area can produce more energy than that in a low wind speed area. However, a WG installed at a low wind site can produce a similar amount of energy to that produced by a WG installed at a high wind site if the WG is designed with a rated wind speed corresponding to the mean wind speed of the site. In this paper, we investigated the power curve of a WG suitable for Korea's southwestern coast with a low mean wind speed to achieve a high capacity factor (CF). We collected the power curves of the 11 WGs of the 6 WG manufacturers. The probability density function of the wind speed on Korea's southwestern coast was modeled using the Weibull distribution. The annual energy production by the WG was calculated and then the CFs of all of the WGs were estimated and compared. The results indicated that the WG installed on the Korea's southwestern coast could obtain a CF higher than 40 % if it was designed with the lower rated speed corresponding to the mean wind speed at the installation site.

Power Curve of a Wind Generator Suitable for a Low Wind Speed Site to Achieve a High Capacity Factor

Gihwan Yoon,Hyewon Lee,Sang Ho Lee,Don Hur,Yong Cheol Kang 대한전기학회 2014 Journal of Electrical Engineering & Technology Vol.9 No.3

It is well known that energy generated by a wind generator (WG) depends on the wind resources at the installation site. In other words, a WG installed in a high wind speed area can produce more energy than that in a low wind speed area. However, a WG installed at a low wind site can produce a similar amount of energy to that produced by a WG installed at a high wind site if the WG is designed with a rated wind speed corresponding to the mean wind speed of the site. In this paper, we investigated the power curve of a WG suitable for Korea’s southwestern coast with a low mean wind speed to achieve a high capacity factor (CF). We collected the power curves of the 11 WGs of the 6 WG manufacturers. The probability density function of the wind speed on Korea’s southwestern coast was modeled using the Weibull distribution. The annual energy production by the WG was calculated and then the CFs of all of the WGs were estimated and compared. The results indicated that the WG installed on the Korea’s southwestern coast could obtain a CF higher than 40 % if it was designed with the lower rated speed corresponding to the mean wind speed at the installation site.

On Extraction of Time-varying Mean Wind Speed from Wind Record Based on Stationarity Index

Jun Chen,Min Wu 한국기상학회 2012 Asia-Pacific Journal of Atmospheric Sciences Vol.48 No.3

We have proposed in a previous study a non-stationary wind model to represent the typhoon record as a summation of a time-varying mean wind speed (TVM) and a stationary turbulence. This note further suggests a quantitative scheme, rather than the previous qualitative method, to find the best TVM for any given wind record. Trial TVMs are first extracted from the wind record by a data-processing technique named empirical mode decomposition. For each TVM, its corresponding turbulent component is computed by removing the TVM from the original wind record, and the degree of stationarity of the turbulence component is checked. The best TVM is taken as the one that leads to the maximum degree of stationarity. The degree of stationarity of turbulence is quantified by two indicators: β the ratio of horizontal wind variability and wind speed; and γ the ratio of friction velocity at different Reynolds averaging periods. The applicability of the suggested scheme is validated with 550 typhoon and 3300 monsoon records of 10 minute duration and at different measurement heights. Threshold values for the two stationary indicators β and γ are determined using field measurements and their sensitivities to the Reynolds averaging periods are discussed. Observations in this study demonstrate that the suggested scheme is proper for finding the TVM of a wind record. For a stationarity quantification of 10 minute duration record, the γindicator with 30 second Reynolds averaging period is recommended. We have proposed in a previous study a non-stationary wind model to represent the typhoon record as a summation of a time-varying mean wind speed (TVM) and a stationary turbulence. This note further suggests a quantitative scheme, rather than the previous qualitative method, to find the best TVM for any given wind record. Trial TVMs are first extracted from the wind record by a data-processing technique named empirical mode decomposition. For each TVM, its corresponding turbulent component is computed by removing the TVM from the original wind record, and the degree of stationarity of the turbulence component is checked. The best TVM is taken as the one that leads to the maximum degree of stationarity. The degree of stationarity of turbulence is quantified by two indicators: β the ratio of horizontal wind variability and wind speed; and γ the ratio of friction velocity at different Reynolds averaging periods. The applicability of the suggested scheme is validated with 550 typhoon and 3300 monsoon records of 10 minute duration and at different measurement heights. Threshold values for the two stationary indicators β and γ are determined using field measurements and their sensitivities to the Reynolds averaging periods are discussed. Observations in this study demonstrate that the suggested scheme is proper for finding the TVM of a wind record. For a stationarity quantification of 10 minute duration record, the γindicator with 30 second Reynolds averaging period is recommended.

A Prediction Method for Short-Term Wind Power Generation using Feature Vector Extraction of Wind Direction and Wind Speed in Jeju Island

손남례 한국차세대컴퓨팅학회 2017 한국차세대컴퓨팅학회 논문지 Vol.13 No.6

In this paper, we propose a wind power forecasting method that takes into consideration wind characteristics to improve the accuracy of wind power prediction. The proposed method involves extracting wind characteristics and predicting power generation. Correlation analysis of power generation amount, wind direction, and wind speed is performed for extracting wind characteristics. Based on the correlation between the wind direction and the wind speed, the feature vector is extracted by clustering using the K-means method. In the prediction part, machine learning is performed using the SVR (support vector regression) that generalizes the SVM (support vector machine) so that an arbitrary real value can be predicted. To verify the accuracy and feasibility of the proposed method, we used the data collected from three different locations of the Jeju Island wind farm. Experimental results show that the error of the proposed method is better than that of existing wind power generation methods.

한국에서 풍속 변화에 관한 연구 : 1월과 8월을 대상으로

이승호 대한지리학회 2012 대한지리학회지 Vol.47 No.3

이 연구에서는 겨울과 여름철의 풍속변화를 파악하기 위하여 남한 13개 지점의 1961년부터 2010년까지 1월과 8월의 평균풍속과 최대풍속, 강풍일수, 폭풍일수를 분석하였다. 평균풍속과 최대풍속은 1월과 8월에 해안에 위치한 부산, 제주, 울산, 포항에서 비교적 큰 폭으로 감속하였다. 강풍일수와 폭풍일수도 해안에 위치한 지점에서 감소한 경향이다. 1월 풍속이 크게 감소한 지점에서 풍속과 평균기온 사이에 비교적 높은 음의 상관관계가 있는 반면, 8월에는 두 변수 간의 상관관계가 낮다. 또한 강풍일(평균풍속 5m/sec. 이상일)과 폭풍일(일 최대풍속 13.gm/sec. 이상일)의 빈도가 비교적 높은 지점에서는 1월평균기온과 1월의 강풍일 및 폭풍일수 사이에 비교적 높은 음의 상관관계가 있다. 이는 1월의 바람 특성이 기온상승에 따라 바뀔 수 있다는 것을 시사한다. This study aimed to investigate the change of wind speed during winter and summer seasons for 50 years(1961-201O). It were analyzed the mean wind speed, maximum wind speed, windy days and storm days on January and August of 13 weather stations in South Korea. The mean wind speed was decreased in the coastal region(Busan, Jeju, Ulsan, Pohang) in winter and summer seasons. Also it was similar to windy day. The relationship between wind speed and mean temperature has negative correlation in winter season. The relationship is low in summer season. The number of windy day and storm day has negative relation with monthly mean temperature.