Document Type : Research Article


1 Division of Industrial Convergence Systems Engineering, Dong-Eui University, Busan, Republic of Korea.

2 Department of e-Business, Busan University of Foreign Studies, Busan, Republic of Korea.

3 Department of Systems Management and Engineering, Pukyong National University, Busan, Republic of Korea.



The power generation sector accounts for a significant portion of GHG emissions, and many countries strive for the large-scale adoption of renewable generation. Although the intermittent nature of renewables brings about complications in energy system planning, the share of renewable generations is increasing to the greatest extent. The wind generation has drawn increasing attention to expanding the use of renewable energy to reduce carbon emissions from the power generation sector, and the estimation of capacity factor is crucial in energy system modeling. This study develops a mathematical model for estimating the capacity factor of a wind farm with the consideration of outage probability of individual turbines. In addition, the power curves and wind speed distribution of the wind farm need to be estimated, which is demonstrated with a wind farm in Korea. It is asserted that the proposed method may render the wind farm capacity factor effectively. Thus, the results from this study can be useful for energy system modeling involving wind generations.


Main Subjects

  1. Dhople, S.V. and Domínguez-García, A.D., "A Framework to Determine the Probability Density Function for the Output Power of Wind Farms", Proceedings of 2012 IEEE North American Power Symposium, (2012), 1-6. (
  2. Larsen, T.C. and Rez P., "Estimates of the Capacity Factor of Wind Farms in the United States", Journal of Sustainable Energy Engineering, Vol. 5, (2017), 194-206. (
  3. Sulaeman, S., Benidris, M., Mitra, J., and Singh, C., "A Wind Farm Reliability Model Considering Both Wind Variability and Turbine Forced Outages", IEEE Transactions on Sustainable Energy, Vol. 8, (2017), 629-637. (
  4. Ayoub, M.F.M., Reliability Assessment of Wind Turbines, Design Optimization of Wind Energy Conversion Systems with Applications, IntechOpen, London, United Kingdom, (2020), 183-194. (https:/ 10.5772/intechopen.89747).
  5. Billinton, R., Wee, C.L., and Hamoud, G., "Digital Computer Algorithms for the Calculation of Generating Capacity Reliability Indices", IEEE Transactions on Power Apparatus and Systems, PAS-101(1), (1982), 203-211. (
  6. Pérez, J.M.P., Márquez, F.P.G., Tobias, A., and Papaelias, M., "Wind Turbine Reliability Analysis", Renewable and Sustainable Energy Reviews, Vol. 23, (2013), 463-472. ( 03.018).
  7. Pfaffel, S., Faulstich, S., and Rohrig, K., "Performance and Reliability of Wind Turbines: A Review", Energies, Vol. 10, (2017), 1904. (https://doi. org.10.3390/en10111904)
  8. Billinton, R. and Allan, R.N., Reliability Evaluation of Power Systems (2nd Ed.), Springer, New York, United States of America, (1996). (
  9. Paik, C., Chung, Y., and Kim, Y.J., "ELCC-Based Capacity Credit Estimation Accounting for Uncertainties in Capacity Factors and Its Application to Solar Power in Korea", Renewable Energy, Vol. 164, (2021), 833-841. (
  10. Söder, L, Tómasson, E., Estanqueiro, A., Flynn, D., Hodge, B.-M., Kiviluoma, J., Korpås, M., Neau, E., Couto, A., Pudjianto, D., Strbac, G., Burke, D., Gómez, T., Das, K., Cutululis, N.A., Hertem, D.V., Höschle, H., Matevosyan, J., von Roon, S., Carlini, E.M., Caprabianca, M., and de Vries, L., "Review of Wind Generation within Adequacy Calculations and Capacity Markets for Different Power Systems", Renewable and Sustainable Energy Reviews, Vol. 119, (2020), 109540. (https://doi. org/10.1016/j.rser.2019.109540).
  11. Ditkovich, Y. and Kuperman, A., "Comparison of Three Methods for Wind Turbines Capacity Factor Estimation", The Scientific World Journal, (2014), 805238. (
  12. Cooperman, A. and Martinez, M., "Load Monitoring for Active Control of Wind Turbines", Renewable and Sustainable Energy Reviews, Vol. 41, (2015), 189-201. (
  13. Sohoni, V., Gupta, S.C., and Nema, R.K., "A Critical Review on Wind Turbine Power Curve Modelling Techniques and Their Applications in Wind Based Energy Systems", Journal of Energy, (2016), 8519785. (
  14. Kim, K.H., Ju, Y.C., and Kim, D.H., "Power Performance Testing and Uncertainty Analysis for a 1.5MW Wind Turbine", Journal of Korean Solar Energy Society, Vol. 26, (2006), 63-71. (https://www.ksesjournal.
  15. Kim, K.H. and Hyun, S.G., "Power Performance Testing and Uncertainty Analysis for a 3.0MW Wind Turbine", Journal of Korean Solar Energy Society, Vol. 30, (2010), 10-15. ( pdf/byqn/kses-2010-030-06-0.pdf).
  16. Bokde, N.D., Feijoo, A.E., and Villanueva, D., "Wind Turbine Power Curves Based on the Weibull Cumulative Distribution Function", Applied Sciences, Vol. 8, (2018), 1-18. (
  17. Ihaddadene, R., Ihaddadene, N., and Mostefaoui, M., "Estimation of Monthly Wind Speed Distribution Basing on Hybrid Weibull Distribution", World Journal of Engineering, Vol. 13, (2016), 509-515. (
  18. Lee, J.C.Y., Fields, M.J., and Lundquist, J.K., "Assessing Variability of Wind Speed: Comparison and Validation of 27 Methodologies", Wind Energy Science, Vol. 3, (2018), 845-868. (
  19. Mohammadi, K., Alavi, O., Mostafaeipour, A., Goudarze, N., and Jalilvand, M., "Assessing Different Parameters Estimation Methods, of Weibull Distribution to Compute Wind Power Density", Energy Conversion and Management, Vol. 108, (2016), 322-335. (https://doi. org/10.1016/j.enconman.2015.11.015).
  20. Stephens, M.A., "EDF Statistics for Goodness of Fit and Some Comparisons", Journal of the American Statistical Association, Vol. 69, (1974), 730-737. (