• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.768-769
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• 2007

국내의 풍력자원과 계통자원을 함께 고려해 강원도 풍력발전단지의 최적입지 타당성을 검증. 국내의 풍황 자료를 조사하고 우수한 지역 5곳을 선정한 후, WASP 프로그램을 이용해 최대 에너지 생산 가능한 지역에 풍력발전기의 배치를 결정하였다.

• 풍력에너지저널
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• 제9권4호
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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.

• 풍력에너지저널
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• 제14권4호
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• pp.57-67
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• 2023

This study aimed to investigate differences in turbulence intensity and turbine loads among onshore wind farms located in various types of terrain. To achieve this, simulations were conducted for two onshore wind farms with identical wind turbines and capacity but situated on complex and flat terrains. The simulations used meteorological data gathered over a 10-year period from automatic weather stations nearest to the wind farms. WindSim and WindPRO software tools were employed for wind field and load analysis, respectively. The simulation results revealed that wind farm A, situated on complex terrain, exhibited significantly higher effective turbulence intensity than wind farm B on flat terrain, as expected. Consequently, the load indices of several wind turbines exceeded 100 % in wind farm A, indicating that the turbines could not reach their design lifespan. From the simulation study, aimed at reducing both the effective turbulence intensity and turbine loads, it became evident that while increasing turbine spacing could decrease effective turbulence intensity to some extent, it couldn't completely resolve the issue due to the inherently high ambient turbulence intensity on complex terrain. The problem with wind turbine loads could only be completely resolved by using wind turbines with a turbine class of A+, corresponding to a reference turbulence intensity of 0.18.

• 한국지리정보학회지
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• 제17권4호
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• pp.86-100
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• 2014

본 연구의 목적은 산지 내 풍력발전단지 입지 적합성 분석을 통해 입지선정 가이드라인과 산지 훼손 최소화를 위한 제도적 개선방안을 도출하는 것이다. 먼저 풍력발전단지 입지 적합성 분석을 위해 국내외 사례 및 현장조사, 연구문헌 고찰을 통해 산지 내 풍력발전단지 입지선정을 위한 요인을 도출하고, 요인별 세부항목 및 가중치를 결정하여 이를 바탕으로 각 항목별 세부평가기준을 수립함으로써 입지 적합성 모델을 개발하였다. 강원도를 사례지역으로 선정하여 풍력자원 밀도 데이터, 법적 산지보전지역, 입지 기준 요인 항목별 자료를 토대로 공간 DB를 구축하여 산지 내 풍력발전 입지가능지역을 도출하였다. 일정 개수 이상의 풍력발전기가 입지할 수 있는 풍력발전단지 잠재 입지가능면적의 추정을 위해서 본 연구에서는 근린분석방법인 Block Statistics와 Focal Statistics 방법을 이용하였다. 그 결과 Block Statistics 방법에 의한 풍력발전기 잠재적 입지가능 면적은 1,261ha이며, Focal Statistics 방법에 의한 풍력발전기 잠재적 입지가능 면적은 1,411ha으로 나타났다. 본 연구의 결과를 바탕으로 대규모 절성토에 의한 산림재해 발생 우려 및 산지경관 훼손을 방지하기 위한 저감대책이 마련되어야 할 것이다.

• 산업기술연구
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• 제31권A호
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• pp.119-122
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• 2011

AWS (Automated Weather Station) wind data was used to predict the annual energy production of Gangwon wind farm having a total capacity of 98 MW in Korea. Two common wind energy prediction programs, WAsP and WindSim were used. Predictions were made for three consecutive years of 2007, 2008 and 2009 and the results were compared with the actual annual energy prediction presented in the CDM (Clean Development Mechanism) monitoring report of the wind farm. The results from both prediction programs were close to the actual energy productions and the errors were within 10%.

• 한국태양에너지학회 논문집
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• 제34권2호
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• pp.82-90
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• 2014

The MERRA reanalysis data provided online by NASA was applied to predict the annual energy productions of two largest wind farms in Korea. The two wind farms, Gangwon wind farm and Yeongyang wind farm, are located on complex terrain. For the prediction, a commercial CFD program, WindSim, was used. The annual energy productions of the two wind farms were obtained for three separate years of MERRA data from June 2007 to May 2012, and the results were compared with the measured values listed in the CDM reports of the two wind farms. As the result, the prediction errors of six comparisons were within 9 percent when the availabilities of the wind farms were assumed to be 100 percent. Although further investigations are necessary, the MERRA reanalysis data seem useful tentatively to predict adjacent wind resources when measurement data are not available.

• 한국태양에너지학회 논문집
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• 제31권2호
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• pp.72-81
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• 2011

The wind data obtained from an AWS(Automated Weather Station) was used to predict the AEP(annual energy production) of Gangwon wind farm having a total capacity of 98 MWin Korea. A wind energy prediction program based on the Reynolds averaged Navier-Stokes equation was used. Predictions were made for three consecutive years starting from 2007 and the results were compared with the actual AEPs presented in the CDM (Clean Development Mechanism) monitoring report of the wind farm. The results from the prediction program were close to the actual AEPs and the errors were within 7.8%.

• 한국태양에너지학회 논문집
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• 제35권2호
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• pp.1-10
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• 2015

Promising onshore wind farm sites in Gangwon province of Korea were investigated in this study. Gangwon province was divided into twenty five simulation regions and a commercial program based on Reynolds averaged Navier-Stokes equation was used to find out wind resource maps of the regions. The national wind atlas with a period 2007-2009 developed by Korea institute of energy research was used as climatologies. The wind resource maps were combined to construct a wind resource map of Gangwon province with a horizontal spatial resolution of 100m. In addition to the wind resource, national environmental zoning map, distance from substation, residence and automobile road, Beakdudaegan mountain range, terrain slope, airport and military reservation district were considered to find out promising wind farm sites. A commercial wind farm design program was used to find out developable wind farm capacities in promising wind farm site with and without excluding environmental protection regions. The total wind farm capacities with and without excluding the protection regions were estimated to be 46MW and 598MW, respectively, when a 2MW commercial wind turbine was employed.