• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.231-232
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• 2023

With taller buildings and larger typhoons, the impact of building winds is growing. During the 11th Typhoon Hinnamno in 2022, the building wind in Busan L City exceeded 60m/s, reaching the highest speed ever. Although many studies have been conducted on reducing the wind load of buildings, which is one of the problem factors caused by strong wind speed, there is a lack of research on wind speed reducing sculptures that can directly control strong wind speed. In this paper, several types of wind speed reduction sculptures were proposed to solve these problems, and the wind speed reduction capability of the proposed sculptures was analyzed through computational fluid dynamics (CFD). These results can contribute to suggesting effective design methods for improving the urban environment and reducing pedestrian stress.

• Wind and Structures
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• v.8 no.6
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• pp.389-406
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• 2005

The results of reference wind speed calculation in Croatia as a base for the revision of the Croatian standards for wind loads upon structures are presented. Wind speed averaged over 10 minutes, at 10 m height, in a flat, open terrain, with a 50-year mean return period is given for 27 meteorological stations in Croatia. It is shown that the greatest part of Croatia is covered with expected reference wind speeds up to 25 m/s. Exceptions are stations with specific anemometer location open to the bura wind which is accelerated due to the channelling effects of local orography and the nearby mountain passes where the expected reference wind speed ranges between 38 m/s and 55 m/s. The methodology for unifying all available information from wind measurements regardless of the averaging period is discussed by analysing wind speed variability at the meteorological station in Hvar.

• New & Renewable Energy
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• v.7 no.1
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• pp.15-21
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• 2011

In recent years, many countries have been endeavoring to exploit the offshore wind energy in terms of overcoming the limitations of on-land wind energy. Considering that mountains cover 70 percent of the Korean Peninsula and arable plains for wind energy are negligibly small, Korean government aggressively drives the offshore wind development of the Korean Peninsula. As part of preliminary investigation of offshore wind resources, KEPCO-RI (Korea Electric Power Corporation-Research Institute) has been analyzing marine buoy datasets measured at 5 positions over the period of 12 years, including estimation of extreme wind speed. It can be observed that variation of yearly wind speed, monthly wind speed as well as frequency distribution of wind direction. Wind classes of buoy sites are estimated by extrapolated average wind speed using log law. In addition, wind turbine class based on IEC code is assessed for evaluation of suitable wind turbine.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.92-99
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• 2016

A wind turbine is controlled for the purpose of obtaining the maximum power below its rated wind speed. Among the methods of obtaining the maximum power, TSR (Tip Speed Ratio) optimal control and P&O (Perturbation and Observation) control are widely used. The P&O control algorithm using the turbine power and rotational speed is simple, but its slow response is a weak point. Whereas TSR control's response is fast, it requires the precise wind speed. A method of measuring or estimating the wind speed is used to obtain a precise value. However, estimation methods are mostly used, because it is difficult to avoid the blade interference when measuring the wind speed near the blades. Neural networks and various numerical methods have been applied for estimating the wind speed, because it involves an inverse problem. However, estimating the wind speed is still a difficult problem, even with these methods. In this paper, a new method is introduced to estimate the wind speed in the wind-power graph by using the turbine power and rotational speed. Matlab/Simulink is used to confirm that the proposed method can estimate the wind speed properly to obtain the maximum power.

• Atmosphere
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• v.26 no.3
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• pp.461-471
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• 2016

A quality check algorithm for the Weather Information Service Engine pulsed Doppler wind lidar is developed from a view point of spatial and temporal consistencies of observed wind speed. Threshold values for quality check are determined by statistical analysis on the standard deviation of 3-component of wind speed obtained by a wind lidar, and the vertical gradient of horizontal wind speed obtained by a radiosonde system. The algorithm includes carrier-to-noise ratio (CNR) check, data availability check, and vertical gradient of horizontal wind speed check. That is, data sets whose CNR is less than -29 dB, data availability is less than 90%, or vertical gradient of horizontal wind speed is less than $-0.028s^{-1}$ or larger than $0.032s^{-1}$ are classified as 'doubtful', and flagged. The developed quality check algorithm is applied to data obtained at Bucheon station for the period from 1 to 30 September 2015. It is found that the number of 'doubtful' data shows maxima around 2000 m high, but the ratio of 'doubtful' to height-total data increases with increasing height due to atmospheric boundary height, cloud, or rainfall, etc. It is also found that the quality check by data availability is more effective than those by carrier to noise ratio or vertical gradient of horizontal wind speed to remove an erroneous noise data.

• New & Renewable Energy
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• v.17 no.4
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• pp.1-8
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• 2021

To determine the wind turbine class in the offshore of the Korean Peninsula, the reference wind speed for a 50-y return period at the hub height of a wind turbine was estimated using the reanalysis data sets. The most recent reanalysis data, ERA5, showed the highest correlation coefficient (R) of 0.82 with the wind speed measured by the Southwest offshore meteorological tower. However, most of the reanaysis data sets except CFSR underestimated the annual maximum wind speed. The gust factor of converting the 1 h-average into the 10 min-average wind speed was 1.03, which is the same as the WMO reference, using several meteorological towers and lidar measurements. Because the period, frequency, and path of typhoons invading the Korean Peninsula has been changing owing to the climate effect, significant differences occurred in the estimation of the extreme wind speed. Depending on the past data period and length, the extreme wind speed differed by more than 30% and the extreme wind speed decreased as the data period became longer. Finally, a reference wind speed map around the Korean Peninsula was drawn using the data of the last 10 years at the general hub-height of 100 m above the sea level.

• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.288-293
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• 2008

A predictive model of wind speed in the wind farm has very important meanings. This paper presents an estimation model of wind speed based on time series analysis using the observed wind data at Hangyeong Wind Farm in Jeju island, and verification of the predictive model. In case of Hangyeong Wind Farm and Haengwon Wind Farm, The ARIMA(Autoregressive Integrated Moving Average) predictive model was appropriate, and the wind speed estimation model was developed by means of parametric estimation using Maximum likelihood Estimation.

• Journal of Wind Energy
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• v.9 no.4
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• pp.40-46
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• 2018

In this study, a three-dimensional Navier-Stokes simulation around Wido Island was performed to analyze the wake effect behind an island. A 10 m/s wind speed and pressure boundary conditions were assigned for the inflow and outflow boundary conditions, respectively. Wido Island was modeled using GIS data. A prevailing wind from the north-northwest direction was determined based on QuikSCAT satellite data. A computational domain of $40km{\times}20km{\times}5km$ covering Wido Island was applied for numerical analysis. Sixty points were specified to extract the wind speed data. A wind speed profile inside the atmospheric boundary layer was compared with a wind profile using a simple power law. It turns out that the wake effect decreases the mean wind speed by 5% more or less, which corresponds to a 14% decrease in wind energy. Thus, the installation of a meteorological mast or development of a wind farm behind Wido Island is not highly recommended.

• 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.