• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• Journal of Environmental Science International
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• v.17 no.2
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• pp.195-201
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• 2008

Damage from typhoon disaster can be mitigated by grasping and dealing with the damage promptly for the regions in typhoon track. What is this work, a technique to analyzed dangerousness of typhoon should be presupposed. This study estimated 10 m level wind speed using 700 hPa wind by typhoon, referring to GPS dropwindsonde study of Franklin(2003). For 700 hPa wind, 30 km resolution data of Regional Data Assimilation Prediction System(RDAPS) were used. For roughness length in estimating wind of 10 m level, landuse data of USGS are employed. For 10 m level wind speed of Typhoon Rusa in 2002, we sampled AWS site of $7.4{\sim}30km$ distant from typhoon center and compare them with observational data. The results show that the 10 m level wind speed is the estimation of maximum wind speed which can appear in surface by typhoon and it cannot be compared with general hourly observational data. Wind load on domestic buildings relies on probability distributions of extreme wind speed. Hence, calculated 10 m level wind speed is useful for estimating the damage structure from typhoon.

• Journal of the Korean Solar Energy Society
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• v.28 no.6
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• pp.24-32
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• 2008

This paper discussed the Feasibility study of wind power generation considering the topographical characteristics of Korea. In order to estimate the exact generation of wind power plants, we analyzed and compared wind resources in mountain areas and plain areas by introducing not only wind speed, the most important variable, but also wind distribution and wind standard deviation that can reflect the influence of landform sufficiently. According to the results of this study, generation was almost the same at wind power plants installed in southwestern coastal areas where wind speed was low as at those installed in mountain areas in Gangwondo where wind speed was high. This demonstrates that the shape parameter of wind distribution is low due to the characteristics of mountain areas, and the standard deviation of wind speed is large due to the effect of mountain winds, therefore, actual generation compared to southwestern coastal areas is almost similar in mountain areas even though wind speed is high.

• Journal of Ecology and Environment
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• v.37 no.2
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• pp.91-97
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• 2014

Little is known about how the increased porosity of a deciduous windbreak, which results from loss of leaves, influences wind speed reduction. We hypothesized that, with loss of foliage, the wind speed reduction effectiveness of a deciduous windbreak decreases on near leeward side but not on further leeward side and that wind speed recovers faster in the full foliage season than in other seasons. During summer, autumn, and winter (full, medium, and non-foliage season, respectively), we observed wind speed and direction around a deciduous windbreak in a traditional Korean village on windward and near and further leeward sides (at -8H, 2H, and 6H; H = 20 m, a windbreak height). We used a linear mixed effects model to determine that the relative wind speed reduction at 2H significantly decreased from 83% to 48% ($F_{2,111.97}=73.6$, P < 0.0001) with the loss of foliage. However, the relative wind speed reduction at 6H significantly increased from 26% to 43% ($F_{2,98.54}=18.5$, P < 0.0001). Consequently, wind speed recovery rate between 2H and 6H in summer was two times higher than in autumn and ten times higher than in winter ($F_{2,102.93}=223.1$, P < 0.0001). These results indicate that deciduous windbreaks with full foliage seem to induce large turbulence and increase wind speed recovery rate on leeward side. Our study suggests that further research is needed to find the optimal foliage density of a deciduous windbreak for maximizing windbreak effectiveness regardless of seasonal foliage changes.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.36-36
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• 2000

The paper presents a speed control algorithm for a full pitch-controlled wind turbine system. Torque of a blade generated by wind energy is non-linear function of a wind speed, angular velocity, and pitch angle of the blade. The design of a cor_troller, in general, is performed by linearizing the torque in the vicinity of a operating point assuming the angular velocity of the blade is constant. For speed control, however, the angular velocity is no longer a constant, so that linearization of the torque in terms of a wind speed and pitch angle is impossible. In this study, a reference pitch model is derived in terms of a wind speed, angular velocity, and pitch angle, which makes it possible to design a controller without linearizing the non-linear torque model of the blade. The validity of the algorithm is demonstrated with the results produced through sets of experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.2
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• pp.109-116
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• 2001

The paper presents a speed control algorithm for a full pitch-controlled wind turbine system. Torque of a blade generated by wind energy is a nonlinear function of wind speed, angular velocity, and pitch angle of the blade. The design of the controller, in general, is performed by linearizing the torque in the vicinity of the operating point assuming the angular velocity of the blade is constant. For speed control, however the angular velocity is on longer a constant, so that linearization of the torque in terms of wind speed and pitch angle is impossible. In this study, a reference pitch model is derived in terms of a wind speed, angular velocity, and pitch angle, which makes it possible to design a controller without linearizing the nonlinear torque model of the blade. This paper also suggests a method of designing a hydraulic control system for changing the pitch angle of the blade.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.19-27
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• 2015

Technologies of wind power generation for development of alternative energy technology have been accumulated over the past 20 years. Wind power generation is environmentally friendly and economical because it uses the wind blowing in nature as energy resource. In order to operate wind power generation efficiently, it is necessary to accurately predict wind speed changing every moment in nature. It is important not only averagely how well to predict wind speed but also to minimize the largest absolute error between real value and prediction value of wind speed. In terms of generation operating plan, minimizing the largest absolute error plays an important role for building flexible generation operating plan because the difference between predicting power and real power causes economic loss. In this paper, we propose a method of wind speed prediction using numeric prediction algorithm-based wind speed forecast model made to analyze the wind speed forecast given by the Meteorological Administration and pattern value for considering seasonal property of wind speed as well as changing trend of past wind speed. The wind speed forecast given by the Meteorological Administration is the forecast in respect to comparatively wide area including wind generation farm. But it contributes considerably to make accuracy of wind speed prediction high. Also, the experimental results demonstrate that as the rate of wind is analyzed in more detail, the greater accuracy will be obtained.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.1812-1821
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• 2014

Wind has been a rapidly growing renewable power source for the last twenty years. Since wind behavior is chaotic in nature, its forecasting is not easy. At the same time, developing an accurate forecasting method is essential when wind farms are integrated into the power grid. In fact, wind speed forecasting tools can solve issues related to grid stability and reserve allocation. In this paper 30 hours ahead wind speed profile forecast is proposed using Adaptive Wavelet Neural Network (AWNN). The implemented AWNN uses a Mexican hat mother Wavelet, and Morlet Mother Wavelet for seven, eight and nine levels decompositions. For wind speed forecasting, the time series data on wind speed has been gathered from the National Renewable Energy Laboratory (NREL) website. In this work, hourly averaged 10-min wind speed data sets for the year 2004 in the Midwest ISO region (site number 7263) is taken for analysis. Data sets are normalized in the range of [-1, 1] to improve the training performance of forecasting models. Total 8760 samples were taken for this forecasting analysis. After the forecasting phase, statistical parameters are calculated to evaluate system accuracy, comparing different configurations.

• Wind and Structures
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• v.23 no.6
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• pp.577-594
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• 2016

In this paper a practical modelling methodology is presented for a series of aero- servo- elastic- coupled numerical analyses of small wind turbine operation, with particular emphasis on variable speed generator modelling in various wind speed conditions. The following characteristics are determined using the available computer tools: the tip speed ratio as a function of the generator constant (under the assumption of constant wind speed), the turbine coefficient of power as a function of the tip speed ratio (the torque curve is modified accordingly and generator speed and power curves are plotted), turbine power curves and coefficient of power curve as functions of the incoming wind speed. The last stage is to determine forces and torques acting on rotor blades and turbine tower for specific incoming wind speeds in order to examine the impact of the stall phenomena on these values (beyond the rated power of the turbine). It is shown that the obtained results demonstrate a valuable guideline for small wind turbines design process.

• 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.