• Title/Summary/Keyword: 연간에너지발전량

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Prediction of Annual Energy Production of Gangwon Wind Farm using AWS Wind Data (AWS 풍황데이터를 이용한 강원풍력발전단지 연간에너지발전량 예측)

  • Woo, Jae-kyoon;Kim, Hyeon-Gi;Kim, Byeong-Min;Paek, In-Su;Yoo, Neung-Soo
    • Journal of the Korean Solar Energy Society
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    • v.31 no.2
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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%.

Prediction of Annual Energy Production of Wind Farms in Complex Terrain using MERRA Reanalysis Data (MERRA 재해석 자료를 이용한 복잡지형 내 풍력발전단지 연간에너지발전량 예측)

  • Kim, Jin-Han;Kwon, Il-Han;Park, Ung-Sik;Yoo, Neungsoo;Paek, Insu
    • Journal of the Korean Solar Energy Society
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    • v.34 no.2
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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.

AEP Prediction of Gangwon Wind Farm using AWS Wind Data (AWS 풍황데이터를 이용한 강원풍력발전단지 발전량 예측)

  • Woo, Jae-Kyoon;Kim, Hyeon-Ki;Kim, Byeong-Min;Yoo, Neung-Soo
    • Journal of Industrial Technology
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    • v.31 no.A
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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%.

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