• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.278-281
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• 2008

In these days the installation of wind turbines or wind parks includes a high financial risk. So for the planning and the constructing of wind farms, long-term data of wind speed and wind direction is required. However, in most cases only few data are available at the designated places. Traditional Measure-Correlate-Predict (MCP) can extend this data by using data of nearby meteorological stations. But also Neural Networks can create such long-term predictions. The key issue of this paper is to demonstrate the possibility and the quality of predictions using Neural Networks. Thereto this paper compares the results of different MCP Models and Neural Networks for creating long-term data with various indexes.

• Atmosphere
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• v.24 no.3
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• pp.419-432
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• 2014

An assessment of typhoon intensity predictability of numerical models was conducted to develop the typhoon intensity forecast guidance comparing with the RSMC-Tokyo best track data. Root mean square error, box plot analysis and time series of wind speed comparison were performed to evaluate the each model error level. One of noticeable fact is that all models have a trend of error increase as typhoon becomes stronger and the Global Forecast System showed the best performance among the models. In the detailed analysis in two typhoon cases [Danas (1324) and Haiyan (1330)], GFS showed good performance in maximum wind speed and intensity trend in the best track, however it could not simulate well the rapid intensity increasing period. On the other hand, ECMWF and Hurricane-WRF overestimated the typhoon intensity but simulated track trend well.

• Journal of the Korean earth science society
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• v.34 no.7
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• pp.633-644
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• 2013

This study evaluates wind farm efficiency at Haengwon in Jeju Island. The actual energy production at Haengwon wind farm is compared with the estimated energy production based on Korean wind map which is developed at the National Institute of Meteorological Research/KMA. The validation of wind map at Gujwa located near the Haengwon wind farm shows that the wind speed is overestimated. The diurnal variation of wind speed shows a maximum value in the afternoon due to the effect of sea-land breeze. The ratio of the actual energy production at Haengwon wind farm and the estimated energy production based on the Korean wind map is 24.8%, while the distribution of energy frequency is similar each other. The difference of energy production is caused by mechanical error of the turbine and the overestimation of the simulated wind map. This study will contribute to the repowering of turbines for improving the efficiency of wind farm in the future.

• Atmosphere
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• v.17 no.4
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• pp.327-337
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• 2007

In this study, we examined the new ensemble training approach to reduce the systematic error and improve prediction skill of wind by using the Short-range Ensemble prediction system (SENSE), which is the mesoscale multi-model ensemble prediction system. The SENSE has 16 ensemble members based on the MM5, WRF ARW, and WRF NMM. We evaluated the skill of surface wind prediction compared with AWS (Automatic Weather Station) observation during the summer season (June - August, 2006). At first stage, the correction of initial state for each member was performed with respect to the observed values, and the corrected members get the training stage to find out an adaptive weight function, which is formulated by Root Mean Square Vector Error (RMSVE). It was found that the optimal training period was 1-day through the experiments of sensitivity to the training interval. We obtained the weighted ensemble average which reveals smaller errors of the spatial and temporal pattern of wind speed than those of the simple ensemble average.

• 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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.6
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• pp.612-618
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• 2008

Microphone array beamforming method has been recognized as an important aeroacoustic research field and become a standard technique in localizing sound sources. This method also used in flight acoustic measurement, and especially, it is very useful when measure sounds inside the wind tunnel. In measuring sound which is inside the wind tunnel by traditional beamforming method, there are some errors caused by airstream. The speed and the propagation path of the sound changes as it travel through the airstream. This makes the error which the position of sound is changed a little bit to the down stream direction. In this paper, validation test has made about the correction equation for this wind effects of previous researches. And beamforming including shear layer correction was performed about a sound source in the anechoic open-jet wind tunnel.

• 한국신재생에너지학회:학술대회논문집
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• 2006.06a
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• pp.323-324
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• 2006

In the present paper a forecasting system of wind power generation for Walryong Site, Jejudo is presented, which has been developed and evaluated as a first step toward establishing Korea Forecasting Model of Wind Power Generation. The forecasting model, KIER forecaster is constructed based on statistical models and is trained with wind speed data observed at Gosan Weather Station nearby Walryong Si to. Due to short period of measurements at Walryong Site for training statistical model, Gosan wind data were substituted and transplanted to Walryong Site by using Measure-Correlate-Predict technique. Three-hour advanced forecast ins shows good agreement with the measurement at Walryong site with the correlation factor 0.88 and MAE(mean absolute error) 15% under.

• Journal of the Korean Solar Energy Society
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• v.37 no.2
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• pp.1-11
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• 2017

The investigation on reliability of ERA-Interim reanalysis wind data was conducted using wind data from the five met masts measured at inland and coastal areas, Jeju island. Shinchang, Handong, Udo, Susan and Cheongsoo sites were chosen for the met mast location. ERA-Interim reanalysis data at onshore and offshore twenty points over Jeju Island were analyzed for creating Wind Statistics using WindPRO software. Reliability of ERA-Interim reanalysis wind data was assessed by comparing the statistics from the met mast wind data with those predicted at the interest point using the Wind Statistics. The relative errors were calculated for annual average wind speed and annual energy production. In addition, the trend of the error was analyzed with distance from met mast. As a result, ERA-Interim reanalysis wind data was more suitable for offshore wind resource assessment than onshore.

• Journal of the Korean Solar Energy Society
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• v.33 no.1
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• pp.1-6
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• 2013

It is difficult to avoid measurement errors caused by the shading effect of the meteorological tower, which is used for wind resource assessment according to the IEC Standard. This paper presents a validation of the computational flow analysis results by comparing the results with the wind tunnel experiment conducted for Reynolds numbers in the $10^4$ to $10^5$ range, for the preparation of a database for use in an automatic method of correcting met-tower shading errors. A three-dimensional simulation employing the MP (Modified Production) $k-{\varepsilon}$ turbulence model predicted a wind speed deficit in the wake region according to minimum wind speed ratio, within an MAE (Mean Absolute Error) of 2.4%.

• Journal of the Korean Solar Energy Society
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• v.29 no.2
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• pp.22-30
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• 2009

In order to clarify predictive accuracy for the wind resource predicted by running WindPRO(Ver. 2.5) which is software for wind farm design developed by EMD from Denmark, an investigation was carried out at the northeast region of Jeju island. The Hangwon, Susan and Hoichun sites of Jeju island were selected for this study. The measurement period of wind at the sites was for one year. As a result, when the sites had different energy roses, though the two Wind Statistics made by STATGEN module were used for the prediction, it was difficult to exactly predict the energy rose at a given site. On the other hand, when the two Wind Statistics were used to predict the average wind speed, the wind power density and the annual energy production, the relative error was under ${\pm}20%$ which improved more than that when using only one Wind Statistics.