• Journal of the Korean Solar Energy Society
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• v.27 no.1
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• pp.1-9
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• 2007

This paper reveals both the operational situation and the cause of the error occurred in wind turbine generator system of Hangwon wind farm in Jeju island. The four wind turbines were selected for this work, and the monitored period was for six months. Wind resource in the wind farm was analyzed, and the estimated energy production was compared with the actual energy production. As a result, with a decrease of system error, the estimated energy production was in good agreement with the actual energy production. The errors occurring in components such as gearbox and hydraulic motor affected the Availability of the wind turbine. Also, poor external conditions such as a strong wind, lightning and gust caused a standstill of wind turbines.

• Transactions of the Korean hydrogen and new energy society
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• v.24 no.6
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• pp.558-565
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• 2013

This paper presents how to determine AEP(Annual Energy Production) by a small wind turbine in DuckjeokDo island. Evaluation of AEP is introduced to make a self-contained island including renewable energy sources of wind, solar, and tidal energy. To determine the AEP in DuckjeokDo island, a local wind data is analyzed using the annual wind data from Korea Institute of Energy Research firstly. After the wind data is separated in 12-direction, a mean wind speed at each direction is determined. And then, a small wind turbine power curve is selected by introducing the capacity of a small wind turbine and the energy production of the wind turbine according to each wind direction. Finally, total annual wind energy production for each small wind turbine can be evaluated using the local wind density and local energy production considering a mechanical energy loss. Throughout the analytic study, it is found that the AEP of DuckjeokDo island is about 2.02MWh/y and 3.47MWh/y per a 1kW small wind turbine installed at the altitude of 10 m and 21m, respectively.

• Journal of the Korean Solar Energy Society
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• v.33 no.6
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• pp.32-38
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• 2013

In an efforts to encourage renewable energy deployment, the government has initiated so called 1 million green homes program but the accumulated installation capacity of small wind turbine has been about 70kW. It can be explained in several ways such that current subsidy program does not meet public expectations, economic feasibility of wind energy is in doubt or acoustic emission is significant etc. The author investigated annual energy production of Skystream 3.7 wind turbine using measured power curve and wind resource data. The measured power curve of the small wind turbine was obtained through power performance tests at Wol-Ryoung test site. AEP(Annual Energy Production) and CF(Capacity Factor) were evaluated at selected locations with the measured power curve.

• Plant Journal
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• v.12 no.3
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• pp.32-38
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• 2016

In this study, the effect of wake on the energy production of a downstream wind turbine was analyzed on the base of operation practices of wind farm in the coastal complex terrain which has 2 row array of wind turbines. And changes in the variation of wind speed and turbulence intensity was analyzed. In case wind turbines are spaced 4-rotor diameter-apart in the prevailing wind direction, reduction in energy production was confirmed due to the decrease of wind speed and the increase of turbulence intensity by wake. Especially a radical change of wind direction caused wind turbine a sudden stop and energy production significantly reduced. It is considered improvement of yaw brake can prevent the sudden stop and increase energy production.

• Journal of the Korean Solar Energy Society
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• v.24 no.3
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• pp.1-7
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• 2004

Using WAsP, which is PC-program for the vertical and horizontal extrapolation of wind data, annual energy production as well as wind energy density has been predicted for Haengwon wind farm in Jeju island. The predicted results were compared with real data derived from wind turbines in Haengwon wind farm. As the results, in order to produce more electric power, new wind turbines should be located along coastal line, which has comparatively high wind energy density. Also, the roughness length should be inputted to the Map Editor program for better agreement with real annual energy production.

• 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.

• Journal of the Korean Solar Energy Society
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• v.36 no.2
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• pp.9-17
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• 2016

In order to examine how accurately the wind farm design software, WindPRO and Meteodyn WT, predict annual energy production (AEP), an investigation was carried out for Seongsan wind farm of Jeju Island. The one-year wind data was measured from wind sensors on met masts of Susan and Sumang which are 2.3 km, and 18 km away from Seongsan wind farm, respectively. MERRA (Modern-Era Retrospective Analysis for Research and Applications) reanalysis data was also analyzed for the same period of time. The real AEP data came from SCADA system of Seongsan wind farm, which was compare with AEP data predicted by WindPRO and Meteodyn WT. As a result, AEP predicted by Meteodyn WT was lower than that by WindPRO. The analysis of using wind data from met masts led to the conclusion that AEP prediction by CFD software, Meteodyn WT, is not always more accurate than that by linear program software, WindPRO. However, when MERRA reanalysis data was used, Meteodyn WT predicted AEP more accurately than WindPRO.

• Journal of the Korean Solar Energy Society
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• v.32 no.3
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• pp.33-41
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• 2012

As the wind farms in large scale demand enormous amount of construction cost, minimizing the economic burden is essential and also it is very important to measure the wind resources and forecast annual energy production correctly to judge the economic feasibility of the proposed site by way of installing a Met mast at or nearby the site. Wind resources were measured by installing a 80[m] high Met mast at WangdeungYeo Island to conduct the research incorporated in this paper and offshore wind farm was designed using WindPRO. Wind farm of 100[MW] was designed making use of 3 and 4.5[MW] wind generator at the place selected to compare their annual energy production and capacity factor applying the loss factor of 10[%] and 20[%] respectively to each farm. As a result, 336,599[MWh] was generated by applying 3[MW] wind generator while 358,565 [MWh] was produced by 4.5[MW] wind generator. Difference in the energy production by 3[MW] generator was 33,660 [MWh] according to the loss factor with the difference in its capacity factor by 3.8[%]. On the other hand, 23 units of 4.5 [MW] wind generators showed the difference of annual energy production by 35,857 [MWh] with 4.0[%] capacity factor difference.

• Journal of Wind Energy
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• v.9 no.4
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• pp.32-39
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• 2018

In this study, the annual power production of a wind farm according to obstacles and wind data was predicted for the Garyeok-do wind farm in the Saemangeum area. The Saemangeum Garyeok-do wind farm was built in December 2014 by the Korea Rural Community Corporation. Currently, two 1.5 MW wind turbines manufactured by Hyundai Heavy Industries are installed and operated. Automatic weather station data from 2015 to 2017 was used as wind data to predict the annual power production of the wind farm for three consecutive years. For prediction, a commercial computational fluid dynamics tool known to be suitable for wind energy prediction in complex terrain was used. Predictions were made for three cases with or without considering obstacles and wind direction errors. The study found that by considering both obstacles and wind direction errors, prediction errors could be substantially reduced. The prediction errors were within 2.5 % or less for all three years.

• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.300-305
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• 2008

Using WindPRO that was software for windfarm design developed by EMD from Denmark, wind resources for the western Jeju island were analyzed, and the performance of WindPRO prediction was evaluated in detail. The Hansu site and the Yongdang site that were located in coastal region were selected, and wind data for one year at the two sites were analyzed using WindPRO. As a result, the relative error of the Prediction for annual energy Production and capacity factor was about ${\pm}20%$. For evaluating wind energy more accurately, it is necessary to obtain lots of wind data and real electric power production data from real windfarm.