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Accuracy Assessment of Annual Energy Production Estimated for Seongsan Wind Farm
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 Title & Authors
Accuracy Assessment of Annual Energy Production Estimated for Seongsan Wind Farm
Ju, Beom-Cheol; Shin, Dong-Heon; Ko, Kyung-Nam;
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 Abstract
In order to examine how accurately the wind farm design software, WindPRO and Meteodyn WT, predict annual energy production (AEP), an investigation was carried out for Seongsan wind farm of Jeju Island. The one-year wind data was measured from wind sensors on met masts of Susan and Sumang which are 2.3 km, and 18 km away from Seongsan wind farm, respectively. MERRA (Modern-Era Retrospective Analysis for Research and Applications) reanalysis data was also analyzed for the same period of time. The real AEP data came from SCADA system of Seongsan wind farm, which was compare with AEP data predicted by WindPRO and Meteodyn WT. As a result, AEP predicted by Meteodyn WT was lower than that by WindPRO. The analysis of using wind data from met masts led to the conclusion that AEP prediction by CFD software, Meteodyn WT, is not always more accurate than that by linear program software, WindPRO. However, when MERRA reanalysis data was used, Meteodyn WT predicted AEP more accurately than WindPRO.
 Keywords
Wind Energy;Wind Data;MERRA(Modern-Era Retrospective Analysis for Research and Applications);Annual Energy Production;Computational Fluid Dynamics;
 Language
Korean
 Cited by
 References
1.
Navigant Consulting Inc, Executive summary: World Wind Energy Market Update p.3, 2015

2.
Korea Wind Energy Industry Association, www.kweia.or.kr

3.
Jeong, M. S., Moon, C. J., Kwak, S. H., Choi, M. S., Chang, Y. H., The Energy Production of Offshore Wind Farm Using WindPRO, Journal of power electronics, pp. 267-268, 2010

4.
Jeong, Y. M., Kim, J. K., Kim, Y. D., A study on 750kW Wind farm at Taean Costal National Park using WindPRO, Korean Society for New and Renewable Energy, pp. 181-181, 2010

5.
Kim, H. G., Variation of AEP to wind direction variability, Journal of the Korean Solar Energy Society, pp. 1-8, 2011

6.
CARLOS DIAZ-ASENSIO MANCEBO, Comparison Study For Wind Resource Assesment In Complex Domain Using METEODYN And WINDSIM, Master of science thesis, 2014

7.
CARLOS DIAZ-ASENSIO MANCEBO, BAhri Uzunoglu, A Comparison Study For Two Commercial Wind Resource Analysis CFD Software For An EMBANKMENT, EWEC 2014, 2014

8.
Rienecke, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J., et al., MERRA: NASA's Modern-Era Retrospective Analysis for Research and Applications. J. Climate, Vol. 24, pp. 3624-3648, 2012

9.
Kim, J. H., Kwon, I. H., Park. U. S., Yoo, N. S., and Paek, I. S., Prediction of annual energy production of wind farms in complex terrain using MERRA reanalysis data, Journal of the Korean Solar Energy Society, Vol. 34, No. 2, pp. 82-90, 2014

10.
Song, Y., Kim, H. G., Byen, J. H., Park, I. S., Yoo, N. S., A Feasibility Study on Annual Energy Production of the Offshore Wind Farm using MERRA Reanalysis Data, Journal of the Korean Solar Energy Society, Vol. 35, No. 2, pp. 33-41, 2015 crossref(new window)

11.
Gao. Y., Kim, B. S., Lee, J. H., P, I. S., Yoo, N. S., Prediction of Energy Production of China Donghai Bridge Wind Farm Using MERRA Reanalysis Data, Journal of the Korean Solar Energy Society, Vol. 35, No. 3, pp. 1-8, 2015

12.
Kubik, M.L., Brayshaw D.J., Coker P.J., Barlow J., Exploring the role of reanalysis data in simulating regional wind generation variability over Northern Ireland, Renewable Energy, Vol. 57, pp. 558-561, 2013 crossref(new window)

13.
Olauson, J., Bergkvist, M., Modelling the Swedish wind power production using MERRA reanalysis data. Renewable Energy, Vol. 76, pp. 717-725, 2015 crossref(new window)

14.
Jain, Pramod, Wind Energy Engineering, Mc Graw Hil, 2011

15.
WAsP, http://www.wasp.dk/

16.
energetica INTERNATIONAL, Superior performance and business case certainty combining efficiently predictive and reactive service, $N^{\circ}123$ JULYAUGUST, pp. 54-55, 2012,

17.
National Aeronautics and Space Administration Goddard Space Flight Center, http://gmao.gsfc.nasa.gov/research/merra

18.
WindPRO, http://www.emd.dk/windpro/

19.
MeteodynWT, http://meteodyn.com/

20.
Kim, H. G., Kang, Y. H., Yun, C. Y., Jang, M. S., Long-Term Wind Resource Assessment of Shinan-gun Bigeum-do Using The Wind Farm SCADA Data and Reanalysis Data, The Wind Engineering Institute of Korea, Vol. 17, No. 4, pp. 127-132, 2013