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2018 Vol.38, Issue 5 Preview Page

October 2018. pp. 11-25
Abstract


References
1 

Ko, K. N., Kim, K. B., and Huh J. C., Characteristics of Wind Energy for Long-term Period (10 years) at Seoguang Site on Jeju Island, Journal of the Korean Solar Energy Society, Vol. 28, No. 3, pp. 45-52, 2008.

2 

Song, H. S., and Kwon, S. D., Assessing Goodness-of-Fit of Weibull Distributions for Wind Resource Prediction, Spring Conference of the Korean Solar Energy Society, pp. 63-65, 2014.

3 

Mathew, S., Wind Energy: Fundamentals, Resource Analysis and Economics, Springer, pp. 68-78, 2006.

10.1007/3-540-30906-3
4 

Seguro, J. V., and Lambert, T. W., Modern estimation of the parameters of the Weibull wind speed distribution for wind energy analysis, Journal of Wind Engineering and Industrial Aerodynamics, Vol. 85, No. 1, pp. 75-84, 2000.

10.1016/S0167-6105(99)00122-1
5 

Chang, T. P., Performance Comparison of Six Numerical Methods in Estimating Weibull Parameters for Wind Energy Application, Applied Energy, Vol. 88, No. 1, pp. 272-282, 2011.

10.1016/j.apenergy.2010.06.018
6 

Yahaya, A.S., Chong, S.Y., Ramli, N.A., and Ahmad, F., Determination of the Best Probability Plotting Position for Predicting Parameters of the Weibull Distribution, International Journal of Applied Science and Technology, Vol. 2, No. 3, pp. 106-111, 2012.

7 

Huh, M., Lee, S., Cha, G., Park, J., and Yoo J., R&statistic Computation, Parkyeongsa, pp. 149-154, 2011.

8 

Kang, D., Ko, K., and Huh, J., Comparative Study of Different Methods for Estimating Weibull Parameters: A Case Study on Jeju Island, South Korea, Energies, Vol. 11, No. 2, 2018.

10.3390/en11020356
9 

Costa Rocha, P. A., de Sousa, R. C., de Andrade, C. F., and da Silva, M. E. V., Comparison of Seven Numerical Methods for Determining Weibull Parameters for Wind Energy Generation in the Northeast Region of Brazil, Applied Energy, Vol. 89, No. 1, pp. 395-400, 2012.

10.1016/j.apenergy.2011.08.003
10 

Ross, R., Graphical Methods for Plotting and Evaluating Weibull Distributed Data, Proceedings of the IEEE International Conference on Properties and Applications of Dielectric Materials, Vol. 1, pp. 250-253, 1994.

10.1109/ICPADM.1994.413986
11 

Deaves, D. M. and Lines, I. G., On the Fitting of Low Mean Windspeed Data to the Weibull Distribution, Journal of Wind Engineering and Industrial Aerodynamics, Vol. 66, No. 3, pp. 169-178, 1997.

10.1016/S0167-6105(97)00013-5
12 

Lun, I. Y. F. and Lam, J. C., A Study of Weibull Parameters Using Long-term Wind Observations, Renewable Energy, Vol. 20, No. 2, pp. 145-153, 2000.

10.1016/S0960-1481(99)00103-2
13 

Yahaya, A. S., Nor, N. M., Jali, N. R. M., Ramli, N. A., Ahmad, F., and Ul-Saufie, A. Z., Determination of the Probability Plotting Position for Type I Extreme Value Distribution, Journal of Applied Sciences, Vol. 12, No. 14, pp. 1501-1506, 2012.

10.3923/jas.2012.1501.1506
14 

Makkonen, L., Plotting Positions in Extreme Value Analysis, Journal of Applied Meteorology and Climatology, Vol. 45, No. 2, pp. 334-340, 2006.

10.1175/JAM2349.1
15 

Kang, D. B. and Ko, K. N., A Comparative Study on the Probability Plotting Positions to Estimate Weibull Parameters, Spring Conference of the Korean Solar Energy Society, pp. 102, 2018.

Information
  • Publisher :Korean Solar Energy Society
  • Publisher(Ko) :한국태양에너지학회
  • Journal Title :Journal of the Korean Solar Energy Society
  • Journal Title(Ko) :한국태양에너지학회지
  • Volume : 38
  • No :5
  • Pages :11-25
  • Received Date :2018. 05. 30
  • Accepted Date : 2018. 10. 30