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다중 배제분석을 이용한 강원도 내 풍력발전단지 유망후보지 선정
박웅식(Park Ung-Sik),유능수(Yoo Neung-Soo),김진한(Kim, Jin-Han),김관수(Kim Kwan-Soo),민덕호(Min Deok-Ho),이상우(Lee Sang-Woo),백인수(Paek In-Su),김현구(Kim Hyun-Goo) 한국태양에너지학회 2015 한국태양에너지학회 논문집 Vol.35 No.2
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.
MERRA 재해석 자료를 이용한 복잡지형 내 풍력발전단지 연간에너지발전량 예측
김진한(Kim Jin-Han),권일한(Kwon Il-Han),박웅식(Park Ung-Sik),유능수(Yoo Neungsoo),백인수(Paek Ins) 한국태양에너지학회 2014 한국태양에너지학회 논문집 Vol.34 No.2
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.