Journal of the Korean Solar Energy Society (한국태양에너지학회 논문집)

The Korean Solar Energy Society (한국태양에너지학회)
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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 (Dept. of Mechanical and Mechatronics Engineering, Graduate School, Kangwon National University) ;
  • Kim, Hyeon-Gi (Dept. of Mechanical and Mechatronics Engineering, Graduate School, Kangwon National University) ;
  • Kim, Byeong-Min (Dept. of Mechanical and Mechatronics Engineering, Graduate School, Kangwon National University) ;
  • Paek, In-Su (Dept. of Mechanical and Mechatronics Engineering, Kangwon National University) ;
  • Yoo, Neung-Soo (Dept. of Mechanical and Mechatronics Engineering, Kangwon National University)
  • 우재균 (강원대학교 대학원 기계메카트로닉스공학과) ;
  • 김현기 (강원대학교 대학원 기계메카트로닉스공학과) ;
  • 김병민 (강원대학교 대학원 기계메카트로닉스공학과) ;
  • 백인수 (강원대학교 기계메카트로닉스공학과) ;
  • 유능수 (강원대학교 기계메카트로닉스공학과)
  • Received : 2011.02.07
  • Accepted : 2011.04.04
  • Published : 2011.04.30
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Abstract

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%.

Keywords

References

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