• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.8
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• pp.905-911
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• 2012

To establish a floating offshore wind turbine simulation model, a tension leg platform is added to an onshore wind turbine. The wind load is calculated by using meteorological administration data and a power law that defines the wind velocity according to the height from the sea surface. The wind load is applied to the blade and wind tower at a regular distance. The relative Morison equation is employed to generate the wave load. The rated rotor speed (18 rpm) is applied to the hub as a motion. The dynamic behavior of a 2-MW floating offshore wind turbine subjected to the wave excitation and wind load is analyzed. The flexible effects of the wind tower and the blade are analyzed. The flexible model of the wind tower and blade is established to examine the natural frequency of the TLP-type offshore wind turbine. To study the effect of the flexible tower and blade on the floating offshore wind turbine, we modeled the flexible tower model and flexible tower-blade model and compared it with a rigid model.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.103-103
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• 2019

본 연구에서는 Terra MODIS 위성영상과 Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) 모형을 이용하여 2012년부터 2017년까지 한반도 전국의 증발산량을 산정하고 플럭스 타워 실측 증발산량과 비교하였다. METRIC은 전 세계에 널리 적용된 바 있는 에너지 수지 기반의 Surface Energy Balance Algorithm for Land (SEBAL) 모형의 개념과 기술을 기반으로 현열(Sensible Heat Flux) 추정 모듈을 개선한 모형이다. 본 연구에서 METRIC 모형은 기존 C#으로 개발되어 있던 SEBAL 코드에서 현열 추정 모듈을 수정하였고 연산 속도 개선을 위해 Python으로 재작성하였다. METRIC 모형의 위성 자료로 Terra MODIS 위성의 MOD13A2(16day, 1km) NDVI, MOD11A1(Daily, 1km) Land Surface Temperature (LST) 및 MCD43A3(Daily, 500m) Albedo를 구축하였으며 500m 공간해상도의 Albedo는 1000m 해상도로 resample하여 활용하였다. 기상자료는 기상청 기상관측소의 풍속, 풍속측정높이, 습도, 10분 간격 이슬점 온도, 일사량 자료를 위성 자료와 같은 공간해상도로 내삽(Interpolation)하여 구축하였다. 모형결과 검증을 위해 국내 플럭스 타워 (설마천, 청미천, 덕유산) 증발산량 관측 자료와의 결정계수(Coefficient of determination, $R^2$), RMSE(Root mean square error) relative RMSE (RMSE%), Nash-Sutcliffe efficiency (NSE) 및 IOA(Index of Agreement)를 산정하고, 기존 SEBAL 모형 결과와의 비교를 통해 본 모형의 개선점을 보이고자 한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.10-14
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• 2016

육상의 증발산량(evapotranspiration, ET)은 대기 중 수증기의 상변화를 통해 대기와 지표 사이의 물과 에너지 순환에 영향을 미치며, 강수량, 유출량과 함께 수자원에 영향을 미치는 주요 인자이다. 강수량과 유출량은 직접 관측이 가능한 반면, 증발산량은 숨어있는 잠열로서 관측하기 어렵다. 플럭스 타워나 라이지메타(Lysimeter) 등을 이용하여 증발산량을 직접 관측하고 있으나 이들 지상관측은 일부 지점(point)에서 제한적으로 이루어지고 있으며, 관측 지점의 수를 확대하게되면 관측 기기의 유지 보수 등의 많은 시간과 비용이 든다는 한계가 있다. 이러한 지상관측의 한계를 극복하고 넓은 영역의 증발산량 변화를 관측하기 위해 위성을 이용한 증발산량을 추정하는 연구가 활발히 진행되고 있다. 기상청 국가기상위성센터(National Meteorological Satellite Center, NMSC)에서는 우리나라 최초의 정지 기상 위성인 천리안 위성(Communication, Ocean and Meteorological Satellite, COMS) 자료를 지표 에너지 수지식(Surface Energy Budget Equation)에 적용하여 동아시아 지역의 지면과 식생 특성을 반영한 '일(daily) 증발산량 산출 알고리즘'을 개발하였다. 현열을 계산하기 위해 다양한 입력 변수가 사용되어지고 계산 과정이 복잡하기 때문에, 본 연구에서는 '반 경험적인 계수인 B 계수 모델'을 사용하여 현열 산출 기법을 단순화하였다. 본 알고리즘을 이용하여 2011년 4월부터 현재까지 동아시아(위도 $20{\sim}50^{\circ}N$, 경도 $100{\sim}145^{\circ}E$)의 해상도 1km의 일 증발산량을 산출하였고, 위성 증발산량의 검증을 위해 지면 특성이 다른 청미천(농경지), 설마천(혼효림) 지역의 플럭스 타워 증발산량 자료(유량조사사업단 제공)와 비교 분석하였다. 2011년 4월부터 2014년 12월까지 청미천 지역에서의 플럭스 타워 관측과 비교한 결과, 총 665개 자료에 대하여 RMSE는 2.82 mm/day, Bias는 2.56 mm/day의 결과를 보였다. 동일한 기간에 대하여 설마천 지역에서의 플럭스 타워 관측과 비교한 결과, 총 582개 자료에 대하여 RMSE는 1.92 mm/day, Bias는 1.45 mm/day의 결과를 보였다. 기상청 국가기상위성센터의 위성증발산량이 봄과 가을철에 다소 높게 산출되는 경향이 있었으나, 증발산량의 변화경향은 유사하게 나타났다. 이러한 결과를 바탕으로 동아시아 지역 위성 증발산량 변화를 감시하고 있으며 향후, 수문 및 기후 분야에서 가뭄 모니터링 등의 연구에도 활용할 수 있을 것이다.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.27 no.5
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• pp.358-363
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• 2015

As a preparation process for successful establishment of demonstration offshore wind farm, analyses have been made for working time at the construction site where working time is defined as the time available for marine operation to take place under given weather conditions. Data used are hourly wave and wind data from met mast, HeMOSU-1, and 3 hour numerical model data from Korea Meteorological Administration (KMA). Seasonal results show the minimum working time during winter and moderate during autumn and spring. The most working time was seen during summer on average. Monthly analyses show the most working time in May, June, and August which was higher than the working time in July and September. Working time reaches at steady state and no significant change was seen above wave height of 1.5 m and wind speed of 8 m/s.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.5
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• pp.326-332
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• 2012

In this paper, error analyses on the calculation of offshore wind speed have been conducted using HeMOSU-1 data to develop offshore wind energy in Yeonggwang sea of Korea and onshore observed wind data in Buan, Gochang and Yeonggwang for 2011. Offshore wind speed data at 98.69 m height above M.S.L is estimated using relational expression induced by linear regression analysis between onshore and offshore wind data. In addition, estimated offshore wind speed data is set at 87.65 m above M.S.L using power law wind profile model with power law exponent(0.115) and its results are compared with the observed data. As a result, the spatial adjustment error are 1.6~2.2 m/s and the altitude adjustment error is approximately 0.1 m/s. This study shows that the altitude adjustment error is about 5% of the spatial adjustment error. Thus, long term observed data are needed when offshore wind speed was estimated by onshore wind speed data. because the conversion of onshore wind data lead to large error.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.55.2-55.2
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• 2011

The final site of offshore wind power plant should be decided by comprehensive examination of various conditions such as wind resource, sea depth, geology, grid connection, social circumstance and environmental issue. Wind condition is typically regarded as the most important factor because wind energy increases in proportion to wind velocity and it directly relates to the amount of power output, efficiency of power plant and profitability. Advanced countries in the offshore wind power sector such as Denmark, UK and Germany, they are analyzing wind resource accurately by installing the meteorological mast in the ocean in order to get the optimal type of wind turbine and maximum generation efficiency. Also, it is made much of designing offshore power plant on the basis of actual measurement by met-mast and those wind farms have a chance to get the loan with reduced interest rate in project financing. In Korea, the HEMOSU-1 is installed in the ocean around Wido island to analyze wind resource of test bed of 100MW offshore wind power on october last year. This paper deals with the design and construction procedure of the first met-mast in Korea and also shows the site characteristics of test bed. Therefore, this paper will give useful information to local governments and private business sector who are trying to construct offshore wind farm and it can also be a good reference for the following projects of meteorological mast in near future.

• Journal of the Korean Solar Energy Society
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• v.34 no.2
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• pp.60-65
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• 2014

A meteorological(met) tower is the first structure installed during the planning stages of offshore wind farm. The purpose of this paper is to design the met tower with tripod bucket type support structure and to install the sensors. The support structure consist of a central steel shaft connected to three cylindrical steel suction buckets which is more cheaper than monopile or jacket type. And the remote wind condition sensors and marine monitoring equipment, including adcp, pressure type tide gauge, wave height sensors, and scour sensors, remote power supply are installed. The manufactured met tower constructed on sea area which is in front of Gasa island. All of functions of met tower showed normal operation conditions and the wind data got by remote data collection system successfully.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.266-274
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• 2022

In this study, a smoothing method was applied to improve the accuracy of peak wave period estimation using the water surface elevation observed from the Oceanographic and Meteorological Observation Tower located on the west coast of the Korean Peninsula. Validation of the application of the smoothing method was per- formed using variance of the surface elevation and total amount wave energy, and then the effect on the application of smoothing was analyzed. As a result of the analysis, the correlation coefficient between variance of the surface elevation and total amount wave energy was 0.9994, confirming that there was no problem in applying the method. Thereafter, as a result of reviewing the effect of smoothing, it was found to be reduced by about 4 times compared to the confidence interval of the existing estimated spectrum, confirming that the accuracy of the estimated peak wave period was improved. It was found that there was a statistically significant difference in proba- bility density between 4 and 6 seconds due to the smoothing application. In addition, for optimal smoothing, the appropriate number of smoothings according to the significant wave height range was calculated using a statistical technique, and the number of smoothings was found to increase due to the unstable spectral shape as the significant wave height decreased.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.251-267
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• 2021

Remotely sensed vegetation indices (VIs) are empirically related with gross primary productivity (GPP) in various spatio-temporal scales. The uncertainties in GPP-VI relationship increase with temporal resolution. Uncertainty also exists in the eddy covariance (EC)-based estimation of GPP, arising from the partitioning of the measured net ecosystem CO2 exchange (NEE) into GPP and ecosystem respiration (RE). For two forests and two agricultural sites, we correlated the EC-derived GPP in various time scales with three different near-surface remotely sensed VIs: (1) normalized difference vegetation index (NDVI), (2) enhanced vegetation index (EVI), and (3) near infrared reflectance from vegetation (NIRv) along with NIRvP (i.e., NIRv multiplied by photosynthetically active radiation, PAR). Among the compared VIs, NIRvP showed highest correlation with half-hourly and monthly GPP at all sites. The NIRvP was used to test the reliability of GPP derived by two different NEE partitioning methods: (1) original KoFlux methods (GPP_Ori) and (2) machine-learning based method (GPP_ANN). GPP_ANN showed higher correlation with NIRvP at half-hourly time scale, but there was no difference at daily time scale. The NIRvP-GPP correlation was lower under clear sky conditions due to co-limitation of GPP by other environmental conditions such as air temperature, vapor pressure deficit and soil moisture. However, under cloudy conditions when photosynthesis is mainly limited by radiation, the use of NIRvP was more promising to test the credibility of NEE partitioning methods. Despite the necessity of further analyses, the results suggest that NIRvP can be used as the proxy of GPP at high temporal-scale. However, for the VIs-based GPP estimation with high temporal resolution to be meaningful, complex systems-based analysis methods (related to systems thinking and self-organization that goes beyond the empirical VIs-GPP relationship) should be developed.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.6
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• pp.146-154
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• 2023

In this study, the peak wave period T_p and mean wave period T₀₂ and T_{m-1, 0}, which are major parameters for classifying ocean characteristics, were calculated using water surface elevation data observed from the second west coast oceanographic and meteorological observation tower. In addition, the ratio of abnormal data, correlation analysis, and optimal probability density function were estimated. In the case of T_p among the calculated representative periods, the proportion of abnormal data was 5.73% and 0.67% at each point, and T₀₂ was 4.35% and 0.01%. T_{m-1, 0} was found to be 2.82% and 0.03%. Meanwhile, as a result of analyzing the relationship between T₀₂ and T_p, the relationship was calculated to be 0.53 and 0.63 for each point. The relationship between T_{m-1, 0} and T_p was 1.15 and 1.32, respectively, and T₀₂, T_{m-1, 0} was 1.18 and 1.22. As a result of estimating the optimal probability density function of the calculated representative period, T_p followed the 'Log-normal' and 'Normal' distributions at each point, and T₀₂ was 'Gamma', 'Normal' distribution and T_{m-1, 0} showed that 'Log-normal' and 'Normal' distribution were dominant, respectively. It is decided that these results can be used as basic data for wave analysis conducted on the west coast.