• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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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.

• Wind and Structures
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• v.34 no.6
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• pp.469-482
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• 2022

The generalized extreme value distribution (GEVD) is frequently used to fit the block maximum of environmental parameters such as the annual maximum wind speed. There are several methods for estimating the parameters of the GEV distribution, including the least-squares method (LSM). However, the application of the LSM with the expected order statistics has not been reported. This study fills this gap by proposing a fitting method based on the expected order statistics. The study also proposes a plotting position to approximate the expected order statistics; the proposed plotting position depends on the distribution shape parameter. The use of this approximation for distribution fitting is carried out. Simulation analysis results indicate that the developed fitting procedure based on the expected order statistics or its approximation for GEVD is effective for estimating the distribution parameters and quantiles. The values of the probability plotting correlation coefficient that may be used to test the distributional hypothesis are calculated and presented. The developed fitting method is applied to extreme thunderstorm and non-thunderstorm winds for several major cities in Canada. Also, the implication of using the GEVD and Gumbel distribution to model the extreme wind speed on the structural reliability is presented and elaborated.

• Wind and Structures
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• v.19 no.5
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• pp.467-480
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• 2014

The estimation of wind speed values used in codes and standards is an integral part of the wind load evaluation process. In a number of codes and standards, wind speeds outside of tropical cyclone prone regions are estimated using a single probability distribution developed from observed wind speed data, with no distinction made between the types of causal wind hazard (e.g., thunderstorm). Non-tropical cyclone wind hazards (i.e., thunderstorm, non-thunderstorm) have been shown to possess different probability distributions and estimation of non-tropical cyclone wind speeds based on a single probability distribution has been shown to underestimate wind speeds. Current treatment of non-tropical cyclone wind hazards in worldwide codes and standards is touched upon in this work. Meteorological data is available at a considerable number of United States (U.S.) stations that have information on wind speed as well as the type of causal wind hazard. In this paper, probability distributions are fit to distinct storm types (i.e., thunderstorm and non-thunderstorm) and the results of these distributions are compared to fitting a single probability distribution to all data regardless of storm type (i.e., co-mingled). Distributions fitted to data separated by storm type and co-mingled data will also be compared to a derived (i.e., "mixed") probability distribution considering multiple storm types independently. This paper will analyze two extreme value distributions (e.g., Gumbel, generalized Pareto). It is shown that mixed probability distribution, on average, is a more conservative measure for extreme wind speed estimation. Using a mixed distribution is especially conservative in situations where a given wind speed value for either storm type has a similar probability of occurrence, and/or when a less frequent storm type produces the highest overall wind speeds. U.S. areas prone to multiple non-tropical cyclone wind hazards are identified.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.1
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• pp.16-24
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• 2014

Long-term measured wind data are absolutely necessary to estimate extreme offshore wind speed. However, it is almost impossible to collect offshore wind measured data. Therefore, typhoon simulation is widely used to analyze offshore wind conditions. In this paper, 74 typhoons which affected the western sea of Korea during 1978-2012(35 years) were simulated using Holland(1980) model. The results showed that 49.02 m/s maximum wind speed affected by BOLAVEN(1215) at 100 m heights of HeMOSU-1 (Herald of Meteorological and Oceanographic Special Unit - 1) was the biggest wind speed for 35 years. Meanwhile, estimated wind speeds were compared with observed data for MUIFA, BOLAVEN, SANBA at HeMOSU-1. And to estimate extreme wind speed having return periods, extreme analysis was conducted by assuming 35 annual maximum wind speed at four site(HeMOSU-1, Gunsan, Mokpo and Jeju) in western sea of the Korean Peninsular to be Gumbel distribution. As a results, extreme wind speed having 50-year return period was 50 m/s, that of 100-year was 54.92 m/s at 100 m heights, respectively. The maximum wind speed by BOLAVEN could be considered as a extreme winds having 50-year return period.

• 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.

• Structural Engineering and Mechanics
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• v.6 no.5
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• pp.555-569
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• 1998

The reliability of antenna tower designed for a n-year design wind speed is determined by considering the variability of the strength of the component members and of the mean wind speed. For obtaining the n-year design wind speed, maximum annual wind speed is assumed to follow Gumbel Type-1 distribution. Following this distribution of the wind speed, the mean and standard deviation of stresses in each component member are worked out. The variability of the strength of members is defined by means of the nominal strength and a coefficient of variation. The probability of failure of the critical members of tower is determined by the first order second moment method (FOSM) of reliability analysis. Using the above method, the reliability against allowable stress failure of the critical members as well as the system reliabilities for a 75 m tall antenna tower, designed for n-year design wind speed, are presented.

• Wind and Structures
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• v.18 no.6
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• pp.633-650
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• 2014

The uncertainty of extreme wind speeds is one key contributor to the uncertainty of wind loads and their effects on structures. The probability distribution of annual extreme wind speeds may be characterized using a classical Gumbel Type distribution. The expression that establishes the relationship between the extreme wind speeds at different recurrence periods and the corresponding coefficients of variation is formulated, and its efficacy is validated. The coefficients of variation are calibrated to be about 0.125 and 0.184 according to defined Chinese and US design specifications, respectively. Based on the wind data of 54 cities in China, 49 meteorological stations in the US, 3 stations in Singapore, the coefficients span intervals of (0.1, 0.35), (0.08, 0.20) and (0.06, 0.14), respectively. For hurricanes in the US, the coefficients range approximately from 0.3 to 0.4. This convenient technique is recommended as one alternative tool for coefficient of variation analyses in the future revisions of related codes. The sensitivities of coefficients of variation for 49 meteorological stations in the US are quantified and demonstrated. Some contradictions and incompatibilities can be clearly detected and illustrated by comparing the coefficients of variation obtained with different combinations of recurrence period wind data.

• Nuclear Engineering and Technology
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• v.47 no.1
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• pp.59-65
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• 2015

Background: After the Fukushima accident, the importance of hazard analysis for extreme external events was raised. Methods: To analyze typhoon-induced hazards, which are one of the significant disasters of East Asian countries, a statistical analysis using the extreme value theory, which is a method for estimating the annual exceedance frequency of a rare event, was conducted for an estimation of the occurrence intervals or hazard levels. For the four meteorological variables, maximum wind speed, instantaneous wind speed, hourly precipitation, and daily precipitation, the parameters of the predictive extreme value theory models were estimated. Results: The 100-year return levels for each variable were predicted using the developed models and compared with previously reported values. It was also found that there exist significant long-term climate changes of wind speed and precipitation. Conclusion: A fragility analysis should be conducted to ensure the safety levels of a nuclear power plant for high levels of wind speed and precipitation, which exceed the results of a previous analysis.

• 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.

• 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.