Browse > Article
http://dx.doi.org/10.3795/KSME-B.2015.39.9.735

Verification of the Validity of WRF Model for Wind Resource Assessment in Wind Farm Pre-feasibility Studies  

Her, Sooyoung (Multidisciplinary Graduate School Program for Wind Energy, Jeju Nat'l Univ.)
Kim, Bum Suk (Faculty of Wind Energy Engineering Graduate School, Jeju Nat'l Univ.)
Huh, Jong Chul (Dept. of Mechanical Engineering, Jeju Nat'l Univ.)
Publication Information
Transactions of the Korean Society of Mechanical Engineers B / v.39, no.9, 2015 , pp. 735-742 More about this Journal
Abstract
In this paper, we compare and verify the prediction accuracy and feasibility for wind resources on a wind farm using the Weather Research and Forecasting (WRF) model, which is a numerical weather-prediction model. This model is not only able to simulate local weather phenomena, but also does not require automatic weather station (AWS), satellite, or meteorological mast data. To verify the feasibility of WRF to predict the wind resources required from a wind farm pre-feasibility study, we compare and verify measured wind data and the results predicted by WAsP. To do this, we use the Pyeongdae and Udo sites, which are located on the northeastern part of Jeju island. Together with the measured data, we use the results of annual and monthly mean wind speed, the Weibull distribution, the annual energy production (AEP), and a wind rose. The WRF results are shown to have a higher accuracy than the WAsP results. We therefore confirmed that WRF wind resources can be used in wind farm pre-feasibility studies.
Keywords
Weather Research and Forecasting model; Wind Resource; Wind Atlas Analysis and Application Program(WAsP); Meteorological Prediction Data; Wind Farm Pre-feasibuility Study; Weibull Distribution;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 Hwang, Y. S., Lee, W. S., Paek, I. S. and Yoo, N. S., 2009, "Effectiveness of Wind Data from Automated Weather Stations for Wind Resources Prediction," J. of Industrial Technology, No.29 B, pp. 181-186.
2 Oh, H. S., Ko, K. N. and Huh, J. Ch., 2009, "Evaluation of Performance on WindPRO Prediction in the northeast Region of Jeju Island," J. of the Korean Solar Energy Society, Vol. 28, No.2, pp. 22-30.
3 Kyong, N. H., Yoon, J. E., Jang, M. S. and Jang, D. S., 2003, "An Assessment of Offshore Wind Energy Resources Around Korean Peninsula," J. of the Korean Solar Energy Society, Vol. 23, No. 2, pp. 35-41.
4 Kim, B. M., Woo, J. K., Kim, H. G., Paek, I. S. and Yoo. N. S., 2012, "Validation Study of the NCAR Reanalysis Data for a Offshore Wind Energy Prediction," J. of the Korean Solar Energy Society, Vol. 32, No. 1, pp. 1-7.   DOI
5 EMD International Corp., 2010, "WindPRO 2.7 User Guide 3rd edition".
6 Riso National Laboratory, 2007, "WAsP 9 Help Facility, Modeling with WAsP".
7 Moon, S. J., Ko, J. W. and Lee, B. G., 2013, "Power Law Exponent in Coastal Area of Northeastern Jeju Island for the Investigation of Wind Resource," J. of the Korean Society for Geospatial Information System, Vol.21, No.4, pp. 65-71.   DOI
8 Mesoscale & Microscale Meteorology Division, 2012, "WRF-ARW V3 User's Guide," National Center for Atmospheric Research.
9 Munoz-Esparza, D., 2012, "Forecasting the Diabatic Offshore Wind Profile at FINO1 with the WRF Mesoscale Model," DEWI magazin, No. 40, pp. 73-79.
10 Lundquist, J. K., Mirocha, J. D. and Kosovic, B., 2009, "Nesting Large-eddy Simulations Within Mesoscale Simulations in WRF for Wind Energy Applications," WRF User's Workshop 2009.
11 Ecobrain, 2012, "Development of Renewable Energy Prediction system in Smart-grid Test Bed".
12 Chang, T. P., 2011, "Performance Comparison of Six Numerical Methods in Estimating Weibull Parameters for Wind Energy Application," Applied Energy, Vol. 88, pp. 272-282.   DOI   ScienceOn
13 Riso National Laboratory, 1989, "European Wind Atlas".