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http://dx.doi.org/10.7836/kses.2011.31.2.072

Prediction of Annual Energy Production of Gangwon Wind Farm using AWS Wind Data  

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)
Publication Information
Journal of the Korean Solar Energy Society / v.31, no.2, 2011 , pp. 72-81 More about this Journal
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
Wind Power; Automatic Weather Station; Annual Energy Production; Complex Terrain; Energy Prediction;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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