IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v7y2014i4p2676-2700d35419.html
   My bibliography  Save this article

An Approach to Determine the Weibull Parameters for Wind Energy Analysis: The Case of Galicia (Spain)

Author

Listed:
  • Camilo Carrillo

    (Department of Electrical Engineering, University of Vigo, EEI, Campus Univ. s/n, Vigo 36310, Spain)

  • José Cidrás

    (Department of Electrical Engineering, University of Vigo, EEI, Campus Univ. s/n, Vigo 36310, Spain)

  • Eloy Díaz-Dorado

    (Department of Electrical Engineering, University of Vigo, EEI, Campus Univ. s/n, Vigo 36310, Spain)

  • Andrés Felipe Obando-Montaño

    (Department of Electrical Engineering, University of Vigo, EEI, Campus Univ. s/n, Vigo 36310, Spain)

Abstract

The Weibull probability density function (PDF) has mostly been used to fit wind speed distributions for wind energy applications. The goodness of fit of the results depends on the estimation method that was used and the wind type of the analyzed area. In this paper, a study on a particular area (Galicia) was performed to test the performance of several fitting methods. The goodness of fit was evaluated by well-known indicators that use the wind speed or the available wind power density. However, energy production must be a critical parameter in wind energy applications. Hence, a fitting method that accounts for the power density distribution is proposed. To highlight the usefulness of this method, indicators that use energy production values are also presented.

Suggested Citation

  • Camilo Carrillo & José Cidrás & Eloy Díaz-Dorado & Andrés Felipe Obando-Montaño, 2014. "An Approach to Determine the Weibull Parameters for Wind Energy Analysis: The Case of Galicia (Spain)," Energies, MDPI, vol. 7(4), pages 1-25, April.
  • Handle: RePEc:gam:jeners:v:7:y:2014:i:4:p:2676-2700:d:35419
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/7/4/2676/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/7/4/2676/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mathew, Sathyajith & Pandey, K.P. & Kumar.V, Anil, 2002. "Analysis of wind regimes for energy estimation," Renewable Energy, Elsevier, vol. 25(3), pages 381-399.
    2. Jamil, M. & Parsa, S. & Majidi, M., 1995. "Wind power statistics and an evaluation of wind energy density," Renewable Energy, Elsevier, vol. 6(5), pages 623-628.
    3. Hu, Ssu-yuan & Cheng, Jung-ho, 2007. "Performance evaluation of pairing between sites and wind turbines," Renewable Energy, Elsevier, vol. 32(11), pages 1934-1947.
    4. Celik, A.N., 2003. "Assessing the suitability of wind speed probabilty distribution functions based on wind power density," Renewable Energy, Elsevier, vol. 28(10), pages 1563-1574.
    5. Chang, Tian Pau, 2011. "Performance comparison of six numerical methods in estimating Weibull parameters for wind energy application," Applied Energy, Elsevier, vol. 88(1), pages 272-282, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Carta, J.A. & Ramírez, P. & Velázquez, S., 2009. "A review of wind speed probability distributions used in wind energy analysis: Case studies in the Canary Islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 933-955, June.
    2. Shu, Z.R. & Li, Q.S. & Chan, P.W., 2015. "Investigation of offshore wind energy potential in Hong Kong based on Weibull distribution function," Applied Energy, Elsevier, vol. 156(C), pages 362-373.
    3. Liu, Feng-Jiao & Chen, Pai-Hsun & Kuo, Shyi-Shiun & Su, De-Chuan & Chang, Tian-Pau & Yu, Yu-Hua & Lin, Tsung-Chi, 2011. "Wind characterization analysis incorporating genetic algorithm: A case study in Taiwan Strait," Energy, Elsevier, vol. 36(5), pages 2611-2619.
    4. He, Junyi & Chan, P.W. & Li, Qiusheng & Lee, C.W., 2020. "Spatiotemporal analysis of offshore wind field characteristics and energy potential in Hong Kong," Energy, Elsevier, vol. 201(C).
    5. Calif, Rudy & Emilion, Richard & Soubdhan, Ted, 2011. "Classification of wind speed distributions using a mixture of Dirichlet distributions," Renewable Energy, Elsevier, vol. 36(11), pages 3091-3097.
    6. Lidong Zhang & Qikai Li & Yuanjun Guo & Zhile Yang & Lei Zhang, 2018. "An Investigation of Wind Direction and Speed in a Featured Wind Farm Using Joint Probability Distribution Methods," Sustainability, MDPI, vol. 10(12), pages 1-15, November.
    7. El Alimi, Souheil & Maatallah, Taher & Dahmouni, Anouar Wajdi & Ben Nasrallah, Sassi, 2012. "Modeling and investigation of the wind resource in the gulf of Tunis, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5466-5478.
    8. Celik, Ali N. & Kolhe, Mohan, 2013. "Generalized feed-forward based method for wind energy prediction," Applied Energy, Elsevier, vol. 101(C), pages 582-588.
    9. Abul Kalam Azad & Mohammad Golam Rasul & Talal Yusaf, 2014. "Statistical Diagnosis of the Best Weibull Methods for Wind Power Assessment for Agricultural Applications," Energies, MDPI, vol. 7(5), pages 1-30, May.
    10. Belabes, B. & Youcefi, A. & Guerri, O. & Djamai, M. & Kaabeche, A., 2015. "Evaluation of wind energy potential and estimation of cost using wind energy turbines for electricity generation in north of Algeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1245-1255.
    11. Khahro, Shahnawaz Farhan & Tabbassum, Kavita & Mahmood Soomro, Amir & Liao, Xiaozhong & Alvi, Muhammad Bux & Dong, Lei & Manzoor, M. Farhan, 2014. "Techno-economical evaluation of wind energy potential and analysis of power generation from wind at Gharo, Sindh Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 460-474.
    12. Li, Yi & Wu, Xiao-Peng & Li, Qiu-Sheng & Tee, Kong Fah, 2018. "Assessment of onshore wind energy potential under different geographical climate conditions in China," Energy, Elsevier, vol. 152(C), pages 498-511.
    13. Chang, Tian Pau, 2011. "Estimation of wind energy potential using different probability density functions," Applied Energy, Elsevier, vol. 88(5), pages 1848-1856, May.
    14. Chang, Tsang-Jung & Wu, Yu-Ting & Hsu, Hua-Yi & Chu, Chia-Ren & Liao, Chun-Min, 2003. "Assessment of wind characteristics and wind turbine characteristics in Taiwan," Renewable Energy, Elsevier, vol. 28(6), pages 851-871.
    15. Qing, Xiangyun, 2018. "Statistical analysis of wind energy characteristics in Santiago island, Cape Verde," Renewable Energy, Elsevier, vol. 115(C), pages 448-461.
    16. Shoaib, Muhammad & Siddiqui, Imran & Amir, Yousaf Muhammad & Rehman, Saif Ur, 2017. "Evaluation of wind power potential in Baburband (Pakistan) using Weibull distribution function," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1343-1351.
    17. Ahmed, Ahmed Shata, 2011. "Investigation of wind characteristics and wind energy potential at Ras Ghareb, Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2750-2755, August.
    18. Shin, Ju-Young & Ouarda, Taha B.M.J. & Lee, Taesam, 2016. "Heterogeneous mixture distributions for modeling wind speed, application to the UAE," Renewable Energy, Elsevier, vol. 91(C), pages 40-52.
    19. Chang, Tian-Pau & Liu, Feng-Jiao & Ko, Hong-Hsi & Cheng, Shih-Ping & Sun, Li-Chung & Kuo, Shye-Chorng, 2014. "Comparative analysis on power curve models of wind turbine generator in estimating capacity factor," Energy, Elsevier, vol. 73(C), pages 88-95.
    20. Kwami Senam A. Sedzro & Adekunlé Akim Salami & Pierre Akuété Agbessi & Mawugno Koffi Kodjo, 2022. "Comparative Study of Wind Energy Potential Estimation Methods for Wind Sites in Togo and Benin (West Sub-Saharan Africa)," Energies, MDPI, vol. 15(22), pages 1-28, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:7:y:2014:i:4:p:2676-2700:d:35419. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.