• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1225-1235
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• 2011

This paper suggests a method for tuning a numerically simulated wind speed data, provided by NIMR(National Institute of Meteorological Research) and generated from a numerical meteorological model to improve a wind resource map with a $1Km{\times}1Km$ resolution. To this end, "tuning factor method" is developed that consists of two procedures. First, estimate monthly wind fields based on a suitably designed statistical wind field model that covers 345,682 regions obtained by $1Km{\times}1Km$ lattice sites in South Korea. The second procedure computes the tuning factor and then tunes the generated wind speeds of each month as well as each lattice site. The second procedure is based on the wind fields estimated by the first procedure. The performance of the suggested tuning method is demonstrated by using two wind data(both TMY and numerically simulated wind speed data) of 75 weather station areas.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.19-27
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• 2012

Wind is an important variable for various scientific communities such as meteorology, climatology, and renewable energy. In this study, numerical simulations using WRF mesoscale model were performed to produce temporal and spatial wind information over the Republic of Korea during 2006. Although the spatial features and monthly variations of the near-surface wind speed were well simulated in the model, the simulated results overestimated the observed values as a whole. To correct these simulated wind speeds, a regression-based statistical algorithm with different constants and coefficients by land cover type was developed using the satellite-derived LST and NDWI. The corrected wind speeds for the algorithm validation showed strong correlation and close agreement with the observed values for each land cover type, with nearly zero mean bias and less than 0.4 m/s RMSE. Therefore, the proposed algorithm using remotely sensed surface observations may be useful for correcting simulated near-surface wind speeds and producing more accurate wind information over the Republic of Korea.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1349-1350
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• 2015

풍속은 다른 기상요소들보다 순간 변동이 심하고 국지성이 강하여 수치 예보 모델만으로 예측의 정확성을 높이기가 어렵다. 기상청의 단기 풍속 예보는 전 지구적 통합 예보모델인 UM(Unified Model)의 예측값에 MOS(Model Output Statictics)를 통한 보정을 수행하며, 보정식의 생성에 다중선형회귀분석 방법을 사용한다. 본 연구자는 유전프로그래밍(Genetic Programming)을 이용한 비선형 회귀분석 기반의 보정식 생성을 통하여 이를 개선한 바 있는데, 본 연구에서는 보다 향상된 성능을 얻기 위하여 GP 기법 측면에서 Automatically Defined Functions과 다군집(Multiple Populations) 수행을 통해 성능을 높이고자 한다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.9
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• pp.929-936
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• 2015

Nacelle anemometers are mounted on wind-turbine nacelles behind blade roots to measure the free-stream wind speed projected onto the wind turbine for control purposes. However, nacelle anemometers measure the transformed wind speed that is due to the wake effect caused by the blades' rotation and the nacelle geometry, etc. In this paper, we derive the Nacelle Transfer Function (NTF) to calibrate the nacelle wind speed to the free-stream wind speed, as required to carry out the performance test of wind turbines according to the IEC 61400-12-2 Wind-Turbine Standard. For the reference free-stream wind data, we use the Light Detection And Ranging (LiDAR) measurement at the Shinan wind power plant located on the Bigeumdo Island shoreline. To improve the simple linear regression NTF, we derive the multiple nonlinear regression NTF. The standard error of the wind speed was found to have decreased by a factor of 9.4, whereas the mean of the power-output residual distribution decreased by 6.5 when the 2-parameter NTF was used instead of the 1-parameter NTF.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.5
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• pp.326-332
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• 2012

In this paper, error analyses on the calculation of offshore wind speed have been conducted using HeMOSU-1 data to develop offshore wind energy in Yeonggwang sea of Korea and onshore observed wind data in Buan, Gochang and Yeonggwang for 2011. Offshore wind speed data at 98.69 m height above M.S.L is estimated using relational expression induced by linear regression analysis between onshore and offshore wind data. In addition, estimated offshore wind speed data is set at 87.65 m above M.S.L using power law wind profile model with power law exponent(0.115) and its results are compared with the observed data. As a result, the spatial adjustment error are 1.6~2.2 m/s and the altitude adjustment error is approximately 0.1 m/s. This study shows that the altitude adjustment error is about 5% of the spatial adjustment error. Thus, long term observed data are needed when offshore wind speed was estimated by onshore wind speed data. because the conversion of onshore wind data lead to large error.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.17-20
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• 2005

This paper presents an overview analysis on the observed wind shear at Pohang Steel Works, focusing on diurnal patterns and the frequency of high nighttime shear at the site in case of land breeze. In addition, this paper discusses the importance of accurate shear estimates for reliable evaluation of wind energy density. In order for a long-term correlation of the site, three Measure-Correlate-Predict methods were tested with Pohang wind data and it was shown that the linear MCP gives poor estimation due to the geographic characteristics of complex terrain where the severe transformation of wind direction was accompanied.

• New & Renewable Energy
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• v.1 no.2 s.2
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• pp.26-33
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• 2005

This paper presents and overview analysis on the observed wind shear at Pohang Steel Works. focusing on diurnal patterns and the frequency of high nighttime shear at the site in case of land breeze. In addition, this paper discusses the importance of accurate shear estimation for reliable evaluation of wind energy density. In order for long-term correlation of the site, three Measure-Correlate-Predict methods were tested with Pohang wind data and it was shown that the linear MCP gives poor estimation due to the topological characteristics of complex terrain where the severe transformation of wind direction was accompanied.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.63-77
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• 2022

Our aim was to reduce estimation errors of a wind velocity model used as an early warning system for weather risk management in the agricultural sector. The Rural Development Administration (RDA) agricultural weather observation network's wind velocity data and its corresponding estimated data from January to December 2020 were used to calculate linear regression equations (Y = aX + b). In each linear regression, the wind estimation error at 87 points and eight time slots per day (00:00, 03:00, 06:00, 09.00, 12.00, 15.00, 18.00, and 21:00) is the dependent variable (Y), while the estimated wind velocity is the independent variable (X). When the correlation coefficient exceeded 0.5, the regression equation was used as the wind velocity correction equation. In contrast, when the correlation coefficient was less than 0.5, the mean error (ME) at the corresponding points and time slots was substituted as the correction value instead of the regression equation. To enable the use of wind velocity model at a national scale, a distribution map with a grid resolution of 250 m was created. This objective was achieved b y performing a spatial interpolation with an inverse distance weighted (IDW) technique using the regression coefficients (a and b), the correlation coefficient (R), and the ME values for the 87 points and eight time slots. Interpolated grid values for 13 weather observation points in rural areas were then extracted. The wind velocity estimation errors for 13 points from January to December 2019 were corrected and compared with the system's values. After correction, the mean ME of the wind velocities reduced from 0.68 m/s to 0.45 m/s, while the mean RMSE reduced from 1.30 m/s to 1.05 m/s. In conclusion, the system's wind velocities were overestimated across all time slots; however, after the correction model was applied, the overestimation reduced in all time slots, except for 15:00. The ME and RMSE improved b y 33% and 19.2%, respectively. In our system, the warning for wind damage risk to crops is driven by the daily maximum wind speed derived from the daily mean wind speed obtained eight times per day. This approach is expected to reduce false alarms within the context of strong wind risk, by reducing the overestimation of wind velocities.

• Journal of the Korean earth science society
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• v.39 no.2
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• pp.139-153
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• 2018

The sea surface wind field has long been obtained from satellite scatterometers or passive microwave radiometers. However, the importance of satellite altimeter-derived wind speed has seldom been addressed because of the outstanding capability of the scatterometers. Satellite altimeter requires the accurate wind speed data, measured simultaneously with sea surface height observations, to enhance the accuracy of sea surface height through the correction of sea state bias. This study validates the wind speeds from the satellite altimeters (GFO, Jason-1, Envisat, Jason-2, Cryosat-2, SARAL) and analyzes characteristics of errors. In total, 1504 matchup points were produced using the wind speed data of Ieodo Ocean Research Station (IORS) and of Korea Meteorological Administration (KMA) buoys at Marado and Oeyeondo stations for 10 years from December 2007 to May 2016. The altimeter wind speed showed a root mean square error (RMSE) of about $1.59m\;s^{-1}$ and a negative bias of $-0.35m\;s^{-1}$ with respect to the in-situ wind speed. Altimeter wind speeds showed characteristic biases that they were higher (lower) than in-situ wind speeds at low (high) wind speed ranges. Some tendency was found that the difference between the maximum and minimum value gradually increased with distance from the buoy stations. For the improvement of the accuracy of altimeter wind speed, an equation for correction was derived based on the characteristics of errors. In addition, the significance of altimeter wind speed on the estimation of sea surface height was addressed by presenting the effect of the corrected wind speeds on the sea state bias values of Jason-1.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.472-473
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• 2008

최근 전력 공급의 안정성을 위해 송전선로에 각종 센서를 볼형태(볼센서)로 장착하여 철탑 및 송전선의 위험 상태를 실시간으로 모니터링해야 하는 필요성이 증대되고 있는데, 본 연구에서는 볼센서의 장착 특성으로 인해 구 표면에 3차원 풍향풍속센서 1개로 3차원 풍향풍 속이 측정 불가능한 문제점을 해결하고자, 2개의 2차원 풍향풍속센서의 측정 데이터를 이용하여 3차원 풍향풍속을 산출하는 방안에 대해 기술하였다. 구 표면을 따르는 풍속 및 풍압 유동해석 결과를 바탕으로, 먼저 구 표면을 따르는 2개의 풍향벡터를 통해 실제 풍향을 산출하고, 실제 풍향에 상대적인 센서 위치에 따른 해석결과에 기준해 보정처리를 함으로써 실제 풍속을 산출하는 방안에 대한 연구를 수행하였다.