• Journal of the Korean Solar Energy Society
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• 제36권4호
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• pp.11-20
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• 2016

For accurate wind resource assessment and wind turbine performance test, it is essential to secure wind data covering a rotor plane of wind turbine including a hub height. In general, we can depict wind speed profile by extrapolating or interpolating the wind speed data measured from a meteorological tower where multiple anemometers are mounted at different heights using a power-law of wind speed profile. The most important parameter of a power-law equation is a vertical wind profile exponent which represents local characteristics of terrain and land cover. In this study, we calculated diurnal vertical wind profile exponents of 8 locations in Jeju Island who possesses excellent wind resource according to the GUM (Guide to the Expression of Uncertainty in Measurement) to evaluate its uncertainty. Expanded uncertainty is calculated by combined standard uncertainty, which is the result of composing type A standard uncertainty with type B standard uncertainty. Although pooled standard deviation should be considered to derive type A uncertainty, we used the standard deviation of vertical wind profile exponent of each day avoiding the difficult of uncertainty evaluation of diurnal wind profile variation. It is anticipated that the evaluated uncertainties of diurnal vertical wind profile exponents at 8 locations in Jeju Island are to be registered as a national standard reference data and widely used in the relevant areas.

• Journal of the Korean Solar Energy Society
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• 제30권6호
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• pp.10-15
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• 2010

The installed capacity of wind turbines in KOREA are growing and enlarging by the central government's support program. Thus, the importance of power performance verification and its uncertainty analysis are recognizing rapidly. This paper described the power testing results of a 3MW wind turbine and analysed an uncertainty level of measurements. The measured power curves are very closely coincide with the calculated one and the annual power production under the given Rayleigh wind speed distribution are estimated with the 3.6~12.7% of uncertainty but, in the dominant wind speed region as 7~8m/s, the uncertainty are stably decreased to 6.3~5.3%.

• Journal of the Korean Solar Energy Society
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• 제26권4호
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• pp.63-71
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• 2006

The installed capacity of wind turbines in KOREA are growing and enlarging by the central government's support program. Thus, the importance of power performance verification and its uncertainty analysis are recognizing rapidly. This paper described the Power testing results of a 1.5MW wind turbine and analysed an uncertainty level of measurements. The measured power curves are very closely coincide with the calculated one and the annual power production under the given Rayleigh wind speed distribution are estimated with the $4.7{\sim}22.0%$ of uncertainty but, in the dominant wind speed region as $7{\sim}8m/s$, the uncertainty are stably decreased to $7{\sim}8%$.

• Journal of the Korean Solar Energy Society
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• 제30권4호
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• pp.79-85
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• 2010

The uncertainty in WindCube LIDAR measurements, which are specific to wind profiling at less than 200m above ground levelin wind resource assessments, was analyzed focusing on the error caused by its volume sampling principle. A two-month SODAR measurement campaign conducted in an urban environment was adopted as the reference wind profile assuming that various atmospheric boundary layer shapes had been captured. The measurement error of LIDAR at a height z was defined as the difference in the wind speeds between the SODAR reference data, which was assumed to be a virtually true value, and the numerically averaged wind speed for a sampling volume height interval of $z{\pm}12.5m$. The pattern of uncertainty in the measurement was found to have a maximum in the lower part of the atmospheric boundary layer and decreased with increasing height. It was also found that the relative standard deviations of the wind speed error ratios were 6.98, 2.70 and 1.12% at the heights of 50, 100 and 150m above ground level, respectively.

• Journal of the Korean Solar Energy Society
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• 제31권4호
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• pp.19-26
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• 2011

We are carried out power performance testing for 3MW wind turbine system at Je-ju wind turbine testing Site and analyzed measured data which was stored through monitoring system. In this paper, we described the power performance testing results and analyzed an uncertainty of measured data sets. The power curve with measured power data is closely coincide with designed power curve except for the low wind speed sections(4m/s~7m/s) and the annual energy production which is given Ray leigh distribution was included with 1.5~5.9% of uncertainty in the wind speed region as 4~11m/s. Although the deviation of curve between measured power and designed power is high, the difference of annual energy production is low in the low wind speed region.

• KEPCO Journal on Electric Power and Energy
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• 제6권4호
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• pp.433-438
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• 2020

Accurate forecasting of wind power is important for grid operation. Wind power has intermittent and nonlinear characteristics, which increases the uncertainty in wind power generation. In order to accurately predict wind power generation with high uncertainty, it is necessary to analyze the factors affecting wind power generation. In this paper, 6 factors out of 11 are selected for more accurate wind power generation forecast. These are wind speed, sine value of wind direction, cosine value of wind direction, local pressure, ground temperature, and history data of wind power generated.

• Journal of the Korean Solar Energy Society
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• 제31권3호
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• pp.89-94
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• 2011

In this study, we measured the wind data as new and renewable energy resources and carried out the evaluation of uncertainty about these data with the authentic standards. These data collected at the 20 locations in korea. We carried out the processing and evaluation about these data with standards as ISO, GUM, and IEC. Whereby these data become standards data and the credibility are gained. These data include some information as direction, humidity, pressure, temperature, and energy density. The annual average of wind speed(in Hamo) was measured as 9.5m/s, then the uncertainty was evaluated as ${\pm}0.88m/s$. We judge the credibility of data by expression of reliability quantitatively. In additional, the standards data is able to approach anywhere and it will be used to support of related research and industry.

• Smart Structures and Systems
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• 제21권5호
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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.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2010년 춘계학술대회논문집
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• pp.28-31
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• 2010

In order to clarify the characteristics of power performance and uncertainty of a wind turbine, an investigation was performed in Hangyeong wind farm, Jeju island, Korea. Data were collected for 12 months from Feb. 2, 2008 to Jan. 1, 2009. This study was conducted on the base of the International standard, and observed the methods of mesurement and evaluation form IEC 61400-12. As a result, power performance curve was calculated by measured data and compared with the sixth unit of VESTAS V90-3.0MW in Hangyeong wind farms. In consequence of this paper, uncertainty was estimated from 7% to 14% on the range of the average wind speed from 4m/s to 11m/s.

• Proceedings of the KIEE Conference
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.270-271
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• 2011

Due to integration of wind power, its unpredictable uncertainty can be a very lethal factor in generation dispatch problem. To handle such uncertainty of wind power output, a profit maximization problem is formulated and random wind speed is modeled by Weibull distribution in this paper. A case study is calculated through profit maximization approach with random wind speed. The effect of case study results is evaluated on how the uncertain wind power integration into the power system affects on the generation dispatch.