• Journal of the Korean Solar Energy Society
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• v.32 no.3
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• pp.146-152
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• 2012

To install a wind power generator, the survey on the wind environment resources must be conducted in advance. The survey on the wind environment resources is to collect and analyze data regarding the wind speed and direction on a data logger. The data logger consists of a sensor, signal processing circuit and storage device. According to the analysis of the stored data, the amount of power generation by the types of generators can be predicted and the most optimal generator including safety grade can be selected, and in case of installing a generator in the future, it can be utilized as basic data regarding supporting base and foundation construction method of survey points. Data logger was developed for a small wind power generator that is suitable for the international standard(IEC 61400) by using DSP-F28335 micro controller in this paper. It was developed to measure the wind speed of 1 [m/s]~17 [m/s], the wind direction of 0 [$^{\circ}$]~359 [$^{\circ}$], and temperature of -30 [$^{\circ}C$]~50 [$^{\circ}C$], and the comparative experiment with other companies' data loggers was conducted, and an error was measured to be less than ${\pm}0.1$ [m/s] for wind speed and less than +1 [$^{\circ}$] for wind direction.

• Journal of Ocean Engineering and Technology
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• v.35 no.6
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• pp.414-425
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• 2021

Overcrowding of high-rise buildings in urban zones change the airflow pattern in the surrounding areas. This causes building wind, which adversely affects the wind environment. Building wind can generate more serious social damage under extreme weather conditions such as typhoons. In this study, to analyze the wind speed and wind speed ratio quantitatively, we installed five anemometers in Haeundae, where high-rise buildings are dense, and conducted on-site monitoring in the event of typhoon OMAIS to determine the characteristics of wind over skyscraper towers surround the other buildings. At point M-2, where the strongest wind speed was measured, the maximum average wind speed in 1 min was observed to be 28.99 m/s, which was 1.7 times stronger than that at the ocean observatory, of 17.0 m/s, at the same time. Furthermore, when the wind speed at the ocean observatory was 8.2 m/s, a strong wind speed of 24 m/s was blowing at point M-2, and the wind speed ratio compared to that at the ocean observatory was 2.92. It is judged that winds 2-3 times stronger than those at the surrounding areas can be induced under certain conditions due to the building wind effect. To verify the degree of wind speed, we introduced the Beaufort wind scale. The Beaufort numbers of wind speed data for the ocean observatory were mostly distributed from 2 to 6, and the maximum value was 8; however, for the observation point, values from 9 to 11 were observed. Through this study, it was possible to determine the characteristics of the wind environment in the area around high-rise buildings due to the building wind effect.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3A
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• pp.209-216
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• 2009

The structural stability as well as economical efficiency of the wind sensitive structures are strongly dependant on accurate evaluation of the design wind speed. Present study demonstrates a useful wind data obtained at the wind monitoring tower in the Kwangyang Suspension Bridge site. Moreover the Measure-Correlate-Predict (MCP) method has been applied to estimate the long-term wind data at the bridge site based on the wind data at the local weather station. The measured data indicate that the turbulent intensities and roughness exponents are strongly affected by the wind direction and surrounding topography. The new design wind speed based on MCP method is 20m/s lower than that at the original estimation, and the resulting design wind load is only 36% of the old prediction. The field measurement of wind data is recommended to ensure the economical and secure design of the wind sensitive structures because the measured wind data reveal much different from the estimated one due to local topography.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.107-112
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• 2015

This paper introduces an evolutionary nonlinear regression based compensation technique for the short-range prediction of wind speed using AWS(Automatic Weather Station) data. Development of an efficient MOS(Model Output Statistics) is necessary to correct systematic errors of the model, but a linear regression based MOS is hard to manage an irregular nature of weather prediction. In order to solve the problem, a nonlinear and symbolic regression method using GP(Genetic Programming) is suggested for a development of MOS wind forecast guidance. Also FCM(Fuzzy C-Means) clustering is adopted to mitigate bias of wind speed data. The purpose of this study is to evaluate the accuracy of the estimation by a GP based nonlinear MOS for 3 days prediction of wind speed in South Korean regions. This method is then compared to the UM model and has shown superior results. Data for 2007-2009, 2011 is used for training, and 2012 is used for testing.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.68-68
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• 2017

Measurements of solar wind speed near the Sun (< 0.1 AU) are important for understanding acceleration mechanism of solar wind as well as space weather predictions, but hard to directly measure them. For the first time, we provide 2D solar wind speed maps in the LASCO field of view using three consecutive days data. By applying the Fourier convolution and inverse Fourier transform, we decompose the 3D intensity data (r, PA, t) into the 4D one (r, PA, t, v). Then, we take the weighted mean along speed to determine the solar wind speeds that gives V(r, PA, t) in every 30 min. The estimated radial speeds are consistent with those given by an artificial flow and plasma blobs. We find that the estimated speeds are moderately correlated with those from slow CMEs and those from IPS observations. A comparison of yearly solar wind speed maps in 2000 and 2009 shows that they have very remarkable differences: azimuthally uniform distribution in 2000 and bi-modal distribution (high speed near the poles and low speed near the equator) in 2009.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1338-1341
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• 2002

The Weibull probability density function and the Rayleigh function are compared by analyzing the relations of the capacity factors which are compared the actual wind speed frequency curve with which are modelled using the probability density functions with different mean wind speeds. For this analysis, the wind speed means of arithmetic, root mean square, cubic mean cuberoot, and standard deviations are computed from the measured wind speed data of a specific site and the coefficients of probability density functions are calculated. The capacity factors for Vestas 850[kW] wind turbine are calculated and analyzed. The results shows that the wind speed frequency curve by Rayleigh function is more close to the actual curve than by Weibull function. The more the wind speed frequency curve is close to the actual one, the more the capacity factors become large values.

• Journal of Power Electronics
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• v.8 no.4
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• pp.345-353
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• 2008

In this paper, a novel loss minimization of an induction generator in wind energy generation systems is presented. The proposed algorithm is based on the flux level reduction, for which the generator d-axis current reference is estimated using support vector regression (SVR). Wind speed is employed as an input of the SVR and the samples of the generator d-axis current reference are used as output to train the SVR algorithm off-line. Data samples for wind speed and d-axis current are collected for the training process, which plots a relation of input and output. The predicted off-line function and the instantaneous wind speed are then used to determine the d-axis current reference. It is shown that the effect of loss minimization is more significant at low wind speed and the loss reduction is about to 40% at 4[m/s] wind speed. The validity of the proposed scheme has been verified by experimental results.

• Korean Journal of Applied Biomechanics
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• v.31 no.3
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• pp.162-167
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• 2021

Objective: This study aimed to identify the different wind speed categories and competitive level among windsurfers through GPS variables to provide the useful information on the development of training programs for enhancing windsurfers' performance. Method: Data from 69 female athletes who participated in 27 races during the 2018-2019 windsurfing season were used for the analysis. Average board speed, total race time, total distance, upwind race time, downwind race time, beam reach race time were collected through GPS. Unconfirmed data were excluded along with penalty point data. The wind conditions were classified as light, light to medium, medium, medium to heavy, and heavy wind, the competitive levels were classified as level 1, level 2, and level 3. Results: As for the average board speed, the level 1 or level 2 group showed higher board speed than the level 3 group in all wind conditions except for the light wind. The total race time and upwind race time showed less time in level 1 or level 2 group than level 3 group in all wind conditions. The total distance, downwind race time and beam reach race time showed less distance and time in level1 group than level 3 group under sufficient wind conditions. Conclusion: Our results show that the aerobic capacity to sustain pumping during upwind course in wind conditions below 15 kts effects performance. In wind conditions of 15 kts or more, indicated that the board control for the fast board speed and small distance required during up, down, beam reach courses had an effect on competition performance. This information can be provided to windsurfers and coaching as basic data for training programs to improve performance.

• Proceedings of the KSRS Conference
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• v.1
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• pp.146-149
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• 2006

Marine surface winds observed by two microwave sensors, SeaWinds and Advanced Microwave Scanning Radiometer (AMSR), on the Advanced Earth Observing Satellite-II (ADEOS-II) are evaluated by comparison with off-shore moored buoy observations. The wind speed and direction observed by SeaWinds are in good agreement with buoy data with root-mean-squared (rms) differences of approximately 1 m $s^{-1}$ and $20^{\circ}$, respectively. No systematic biases depending on wind speed or cross-track wind vector cell location are discernible. The effects of oceanographic and atmospheric environments on the scatterometry are negligible. The wind speed observed by AMSR also exhibited reasonable agreement with the buoy data in general with rms difference of 1.2 m $s^{-1}$. Systematic bias which was observed in earlier versions of the AMSR winds has been removed by algorithm refinements. Intercomparison of wind speeds globally observed by SeaWinds and AMSR on the same orbits also shows good agreements. Global wind speed histograms of the SeaWinds data and European Centre for Medium-range Weather Forecasts (ECMWF) analyses agree precisely with each other, while that of the AMSR wind shows slight deviation from them.

• Journal of the Korean Solar Energy Society
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• v.31 no.3
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• pp.1-7
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• 2011

In the performance test for wind turbines of medium and large, The reference met-mast should be installed for measurement reference wind speed as IEC 61400-12-1 standards and design of booms for mounted an anemometer must be considered exactly. Boom-mounted cup anemometer are influenced by flow distortion of the mast and the boom. Therefore design of booms must be important so that flow distortion due to booms should be kept below 0.5%. But, in some cases at size of met-mast structure, the distance of boom from mast is longer then measurement of wind speed is impossible because of oscillation of boom-mounted anemometer. In this paper, We measured a wind speed at several point from mast and boom and we analyzed the error of wind speed at each point of measurement. Also, we will suggest a correction method using the data curve fitting about errors of wind speed between each point of mounted anemometer.