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http://dx.doi.org/10.7836/kses.2012.32.6.001

AEP Prediction of a Wind Farm in Complex Terrain - WindPRO Vs. WindSim  

Woo, Jae-Kyoon (Dept. of Mechanical and Mechatronics Engineering, Kangwon National University, Graduate School)
Kim, Hyeon-Gi (Dept. of Mechanical and Mechatronics Engineering, Kangwon National University, Graduate School)
Kim, Byeong-Min (Dept. of Mechanical and Mechatronics Engineering, Kangwon National University, Graduate School)
Gwon, Il-Han (Dept. of Mechanical and Mechatronics Engineering, Kangwon National University, Graduate School)
Baek, 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.32, no.6, 2012 , pp. 1-10 More about this Journal
Abstract
The annual energy production of Gangwon wind farm was predicted for three consecutive years of 2007, 2008 and 2009 using commercial programs, WindPRO and WindSim which are known to be used the most for wind resource prediction in the world. The predictions from the linear code, WindPRO, were compared with both the actual energy prediction presented in the CDM (Clean Development Mechanism) monitoring report of the wind farm and also the predictions from the CFD code, WindSim. The results from WindPRO were close to the actual energy productions and the errors were within 11.8% unlike the expectation. The reason for the low prediction errors was found to be due to the fact that although the wind farm is located in highly complex terrain, the terrain steepness was smaller than a critical angle($21.8^{\circ}$) in front of the wind farm in the main wind direction. Therefore no flow separation was found to occur within the wind farm. The flow separation of the main wind was found to occur mostly behind the wind farm.
Keywords
Wind Power; Automatic Weather Station; AEP(Annual Energy Production); Complex terrain;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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