• 한국태양에너지학회 논문집
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• 제32권1호
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• pp.1-7
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• 2012

Predictions of wind speed for six different near-shore sites were made using the NCAR (National Center for Atmospheric Research) wind data. The distances between the NCAR sites and prediction sites were varied between 40km and 150km. A well-known wind energy prediction program, WindPRO, was used. The prediction results were compared with the measured data from the AWS(Automated Weather Stations). Although the NCAR wind data were located far away from the AWS sites, the prediction errors were within 9% for all the cases. In terms of sector-wise wind energy distributions, the predictions were fairly close to the measurements, and the error in predicting main wind direction was less than $30^{\circ}$. This proves that the NCAR wind data are very useful in roughly estimating wind energy in offshore or near-shore sites where offshore wind farm might be constructed in Korea.

• Wind and Structures
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• 제26권6호
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• pp.383-395
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• 2018

An accurate determination of wind speed distribution is the basis for an evaluation of the wind energy potential required to design a wind turbine, so it is important to estimate unknown parameters of wind speed distribution. In this paper, Gumbel distribution is used in modelling wind speed data, and alternative robust estimation methods to estimate its parameters are considered. The methodologies used to obtain the estimators of the parameters are least absolute deviation, weighted least absolute deviation, median/MAD and least median of squares. The performances of the estimators are compared with traditional estimation methods (i.e., maximum likelihood and least squares) according to bias, mean square deviation and total mean square deviation criteria using a Monte-Carlo simulation study for the data with and without outliers. The simulation results show that least median of squares and median/MAD estimators are more efficient than others for data with outliers in many cases. However, median/MAD estimator is not consistent for location parameter of Gumbel distribution in all cases. In real data application, it is firstly demonstrated that Gumbel distribution fits the daily mean wind speed data well and is also better one to model the data than Weibull distribution with respect to the root mean square error and coefficient of determination criteria. Next, the wind data modified by outliers is analysed to show the performance of the proposed estimators by using numerical and graphical methods.

• 한국대기환경학회지
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• 제23권5호
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• pp.585-595
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• 2007

Representative impacts and effectiveness of surface meteorological observation data assimilation were examined in order to use wind resources estimation around southern coastal area of the Korean Peninsula. The data used in study are observational wind and temperature data at 5 and 41 sites of Regional Meteorological Offices and Automatical Weather Systems, respectively. Observation wind speed data tends to show small effective radius with limited area. Especially assimilation impacts of data observed at peninsula type sites like Yeosu play only around the inside of the peninsula. This limited effective radius for wind speed is caused by the strong correlation between topography and wind speed. And the efficient radius for surface air temperature is larger than that of wind. Data assimilation for observational air temperature is useful to increase the accuracy of wind energy estimation. However assimilation of wind data requires special care in its application due to high sensitivity of topographical complexity.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2010년도 춘계학술대회 초록집
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• pp.184.1-184.1
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• 2010

In order to research the way to evaluate wind resource without actual Met Mast data, this paper has been carried out on the southeastern region of Jeju island, Korea. Although wind turbine has been an economical alternative energy resource, misjudging the prediction of lifetime or payback period occurs because of the inaccurate assessment of wind resource and the location of wind turbine. Using WindPRO(Ver. 2.7), a software for wind farm design developed by EMD from Denmark, wind resources for the southeastern region of Jeju island was analyzed, and the performance of WindPRO prediction was evaluated in detail. Met Mast data in Su-san 5.5Km far from Samdal wind farm, AWS in Sung-san 4.5km far from Samdal wind farm, and Korea Wind Map data had been collected for this work.

• 산업기술연구
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• 제29권B호
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• pp.181-186
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• 2009

The wind data measured from automated weather stations (AWS) at complex terrains in Korea was used to predict the wind velocity at nearby sites that are several kilometers away. The ten-minute averaged wind data was measured at a height of 10 meters. A commercial CFD code, WindSIM, based on the weighted averaged Navier-Stokes equation was employed. The results were compared with the data measured using meteorological masts (MM) at a height of 40 meters. The predictions using the AWS data and WindSIM showed good agreements with the measured data.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2008년도 추계학술대회 논문집
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• pp.262-267
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• 2008

The long-term wind data are reconstructed from the short-term meteorological data to design the 4 MW offshore wind park which will be constructed at Woljeong-ri, Jeju island, Korea. Using two MCP (Measure-Correlate-Predict) models, the relative deviation of wind speed and direction from two neighboring reference weather stations can be regressed at each azimuth sector. The validation of the present method is checked about linear and matrix MCP models for the sets of measured data, and the characteristic wind turbulence is estimated from the ninety-percent percentile of standard deviation in the probability distribution. Using the Gumbel's model, the extreme wind speed of fifty-year return period is predicted by the reconstructed long-term data. The predicted results of this analysis concerning turbulence intensity and extreme wind speed are used for the calculation of fatigue life and extreme load in the design procedure of wind turbine structures at offshore wind farms.

• 한국안전학회지
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• 제27권5호
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• pp.158-163
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• 2012

This study is concerned with the estimation of wind speeds for return period in cellularized district of Busan by the recent meteorological data. Recently standard of the wind load in Busan area is determined by using meteorological wind speed data which is observed on Automated Synoptic Observing System(ASOS) only. Applying the existing basic wind speed that is 40m/s to the construction design of Busan area is inefficient. Because the wind speeds of Busan area show different amounts depend on the location of cellularized district. This research analyze the observed data of wind speeds of cellularized district in Busan based on Automate Weather System(AWA). In addition that we compute regional wind speeds for return period by using Gumbel distribution and study and compare with the existing basic wind speeds after evaluating appropriateness by Hazen's plot method.

• Nuclear Engineering and Technology
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• 제55권10호
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• pp.3599-3616
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• 2023

After a nuclear power plant (NPP) accident, it would be helpful to predict the movement of the radioactive plume emitted from the NPP as accurately as possible to protect the nearby population. Radioactive plumes are mainly affected by wind direction and speed. Since it is difficult to identify the wind direction and speed immediately after the accident, a good understanding of the historical wind data could save many lives and ensure smoother evacuation procedures. In this study, wind data for the past 10 years are analyzed for the five NPPs in the Republic of Korea (ROK). The analyzed data include wind direction and wind speed from 2012 to 2021. In particular, the characteristics of the wind field blowing from the NPPs to the nearest densely populated regions are examined. Finally, suggestions to improve evacuation plans are made.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2009년도 춘계학술발표대회 논문집
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• pp.277-280
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• 2009

Wind monitoring system is an absolutely-required system for assessing a performance and fatigue load of the wind energy generator in an on-shore wind energy experimental research complex. It was implemented for the purpose of monitoring the wind information measured from a meteorological tower at the monitoring house and of utilizing the measured data for the performance assessment, by using the LabVIEW program. Then, by adding the performance assessment-related data acquired from the wind energy generator during the performance assessment and the data recorder for synchronizing the data of meteorological tower, the system was implemented. Because it transmitted the data by converting the output 'RS-232' of data logger which measures the wind condition into CAN protocol, the data error rate was minimized, This paper is intended to explain the developed wind data monitoring system.

• Wind and Structures
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• 제4권2호
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• pp.131-146
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• 2001

A full-scale synchronized data acquisition system was set up on the roof of the experimental building at the Texas Tech University Wind Engineering Research Field Laboratory to simultaneously collect approaching wind data, conical vortex images, and roof corner suction pressure data. One-second conditional sampling technique has been applied in the data analysis, which makes it possible to separately evaluate the influencing effects of the horizontal wind angle of attack, ${\theta}$, and the vertical wind angle of attack, ${\varphi}$. Results show a clear cause-and-effect relationship between the incident wind, conical vortices, and the induced roof-corner high-suction pressures. The horizontal wind angle of attack, ${\theta}$, is shown to be the most significant factor in influencing the overall vortex structure and the suction pressures beneath. It is further revealed that the vertical wind angle of attack, ${\varphi}$, plays a critical role in generating the instantaneous peak suction pressures near the roof corner.