• Smart Structures and Systems
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• v.21 no.5
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.

• Ocean and Polar Research
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• v.43 no.1
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• pp.1-14
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• 2021

In this study, extreme wind speeds in the Western North Pacific (WNP) were estimated using reanalysis wind fields synthesized with an empirical typhoon vortex model. Reanalysis wind data used is the Fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5) data, which was deemed to be the most suitable for extreme value analysis in this study. The empirical typhoon vortex model used has the advantage of being able to realistically reproduce the asymmetric winds of a typhoon by using the gale/storm-forced wind radii information in the 4 quadrants of a typhoon. Using a total of 39 years of the synthesized reanalysis wind fields in the WNP, extreme value analysis is applied to the General Pareto Distribution (GPD) model based on the Peak-Over-Threshold (POT) method, which can be used effectively in case of insufficient data. The results showed that the extreme analysis using the synthesized wind data significantly improved the tendency to underestimate the extreme wind speeds compared to using only reanalysis wind data. Considering the difficulty of obtaining long-term observational wind data at sea, the result of the synthesized wind field and extreme value analysis developed in this study can be used as basic data for the design of offshore structures.

• Wind and Structures
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• v.20 no.3
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• pp.389-404
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• 2015

In this study, residential building damage states observed from a post-tornado damage survey in Joplin after a 2011 EF 5 tornado were used to reconstruct the near-surface wind field. It was based on well-studied relationships between Degrees of Damage (DOD) of building and wind speeds in the Enhanced Fujita (EF) scale. A total of 4,166 one- or two-family residences (FR12) located in the study area were selected and their DODs were recorded. Then, the wind speeds were estimated with the EF scale. The peak wind speed profile estimated from damage of buildings was used to fit a translating analytical vortex model. Agreement between simulated peak wind speeds and observed damages confirms the feasibility of using post-tornado damage surveys for reconstructing the near-surface wind field. In addition to peak wind speeds, the model can create the time history of wind speed and direction at any given point, offering opportunity to better understand tornado parameters and wind field structures. Future work could extend the method to tornadoes of different characteristics and therefore improve model's generalizability.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1157-1167
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• 2010

This paper details a method for establishing a wind energy map having($1Km{\times}1Km$) resolution. The map is essential for measurement and efficiency-testing of wind energy resources and wind site analysis. To this end, a statistical wind field model is estimated that covers 345,682 regions obtained by $1Km{\times}1Km$ lattices made over South Korea. The paper derives various characteristics of a regional wind energy resource under the statistical wind field model and estimates them to construct the wind energy map. Kolmogorov-Smirnov test, based on TMY(typical meteorological year) wind data of 76 weather station areas, shows that a Log-normal model is adequate for the statistical wind field model. The model is estimated by using the wind speed data of 345,682 regions provided by the National Institute of Meteorological Research(NIMR). Various wind energy statistics are studied under the Log-normal wind field model. As an application, the wind energy density(W$/m^2$) map of South Korea is constructed with a resolution of $1Km{\times}1Km$ and its utility for the wind site analysis is discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.918-922
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• 2016

As the number of wind farms operating has increased, the interest of the central unit commitment and dispatch for wind power has increased as well. Wind power forecast is necessary for effective power system management and operation with high wind power penetrations. This paper presents the centralized wind power forecasting method, which is a forecast to combine all wind farms in the area into one, using time series models. Also, this paper proposes a prediction model modified with wind forecast error compensation. To demonstrate the improvement of wind power forecasting accuracy, the proposed method is compared with persistence model and new reference model which are commonly used as reference in wind power forecasting using Jeju Island data. The results of case studies are presented to show the effectiveness of the proposed wind power forecasting method.

• New & Renewable Energy
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• v.4 no.2
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• pp.87-93
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• 2008

Wind tunnel test for the 12% scaled model of NREL Phase VI wind turbine was conducted in KARI low speed wind tunnel for $2006{\sim}2007$. The 1st and 2nd test was designed to find out the wind tunnel test method for the blade manufacturing accuracy and surface treatment method by using the composite and aluminum blades. And the 3rd test was designed to study the scale effect. The chord extension method which was used for Bo-105 40% scaled model was adapted for scale effect correction. Test results shows that the chord extension method works well for the torque slope but the maximum torque for scaled model is about 8% below than the real scale model. New correction method to correct this offset was proposed.

• Wind and Structures
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• v.6 no.1
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• pp.41-52
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• 2003

Rain-wind induced vibrations of cables are a challenging problem in the design of cable-stayed bridges. The precise excitation mechanism of the complex interaction between structure, wind and rain is still unknown. A theoretical model that is able to accurately simulate the observed phenomena is not available. This paper presents a mathematical model describing rain-wind induced vibrations as movement-induced vibrations using the quasi-steady strip theory. Both, the vibrations of the cable and the movement of the water rivulet on the cable surface can be described by the model including all geometrical and physical nonlinearities. The analysis using the stability and bifurcation theory shows that the model is capable of simulating the basic phenomena of the vibrations, such as dependence of wind velocity and cable damping. The results agree well with field data and wind tunnel tests. An extensive experimental study is currently performed to calibrate the parameters of the model.

• Wind and Structures
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• v.18 no.5
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• pp.549-566
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• 2014

In spite of progress in the numerical simulation of typhoon wind field in atmospheric boundary layer (ABL), using typhoon wind field model in conjunction with Monte Carlo simulation method can only accurately evaluate typhoon wind field over a general terrain. This method is not enough for a reliable evaluation of typhoon wind field over the actual complex terrain with surface roughness and topography variations. To predict typhoon wind field over the actual complex terrain in ABL, a hybrid numerical simulation method combined typhoon simulation used the typhoon wind field model proposed by Meng et al. (1995) and CFD simulation in which the Reynolds averaged Navier-Stokes (RANS) equations and k-${\varepsilon}$ turbulence model are used. Typhoon wind filed during typhoon Dujuan and Imbudo are simulated using the hybrid numerical simulation method, and compared with the results predicted by the typhoon wind field model and the wind field measurement data collected by Fugro Geotechnical Services (FGS) in Hong Kong at the bridge site from the field monitoring system of wind turbulence parameters (FMS-WTP) to validate the feasibility and accuracy of the hybrid numerical simulation method. The comparison demonstrates that the hybrid numerical simulation method gives more accurate prediction to typhoon wind speed and direction, because the effect of topography is taken into account in the hybrid numerical simulation method.

• Journal of Industrial Technology
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• v.35
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• pp.95-102
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• 2015

Two extreme wind speed prediction models, the EWM(Extreme wind speed model) in IEC61400-1 and the Gumbel method were compared in this study. The two models were used to predict extreme wind speeds of six different sites in Korea and the results were compared with long term wind data. The NCAR reanalysis data were used for inputs to two models. Various periods of input wind data were tried from 1 year to 50 years and the results were compared with the 50 year maximum wind speed of NCAR wind data. It was found that the EWM model underpredicted the extreme wind speed more than 5 % for two sites. Predictions from Gumbel method overpredicted the extreme wind speed or underpredicted it less than 5 % for all cases when the period of the input data is longer than 10 years. The period of the input wind data less than 3 years resulted in large prediction errors for Gumbel method. Predictions from the EWM model were not, however, much affected by the period of the input wind data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2183-2189
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• 2011

Since main portion of the required electric power in Jeju Island is provided from the mainland through two HVDC lines, Jeju HVDC has a most significant impact on Jeju power system. Average wind speed of Jeju Island is the highest among several candidates in South Korea. So, Jeju Island has been a suitable site for the construction of wind farms where several wind farms are now operating and several others to be sited. Since the large-scale wind generation could have adverse impacts on the stable operation of Jeju power system, wind power is also important for the stability of Jeju power system. Therefore, accurate modeling of Jeju HVDC and wind farms is required for stability analysis of Jeju power system. In this paper, PSS/E-based dynamic modeling of Jeju HVDC and DFIG wind farms is proposed. Model-writing technique of PSS/E is used to develop USRAUX model and USRMDL model for controlling the frequency of HVDC and imposing an operation limit of wind power, respectively. Dynamic characteristics of Jeju HVDC and DFIG wind farms are analyzed through the dynamic simulations. The simulation results show the effectiveness of the developed models for Jeju power system.