IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v32y2007i11p1934-1947.html
   My bibliography  Save this article

Performance evaluation of pairing between sites and wind turbines

Author

Listed:
  • Hu, Ssu-yuan
  • Cheng, Jung-ho

Abstract

This paper presents a simple method for determination of pairing between sites and wind generators. It requires six parameters to describe the matching between turbine models and site characteristics, and the energy output performance can thus be easily estimated and used as the index of pairing effectiveness. To describe a Weibull model of wind speed distribution, the shape parameter and the scale parameter are necessarily required. Besides, four other parameters are chosen to specify the characteristics of the power curve of a wind generator: the cut-in speed, the rated speed, the cut-off speed and the nominal power. By combining these six parameters, the average power output of some particular wind turbine at a specific site can be practically and quickly approximated as a reference for turbine siting consideration. An example is also shown to demonstrate the utilization of the proposed method to choose between a group of wind sites and a list of commercial wind turbines.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:renene:v:32:y:2007:i:11:p:1934-1947
    DOI: 10.1016/j.renene.2006.07.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148106002199
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2006.07.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pallabazzer, Rodolfo & Sebbit, Adam M., 1998. "The wind resources in Uganda," Renewable Energy, Elsevier, vol. 13(1), pages 41-49.
    2. Pallabazzer, Rodolfo, 2004. "Previsional estimation of the energy output of windgenerators," Renewable Energy, Elsevier, vol. 29(3), pages 413-420.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Saheb Koussa, D. & Koussa, M. & Hadji, S., 2016. "Assessment of various WTG (wind turbine generators) production in different Algerian's climatic zones," Energy, Elsevier, vol. 96(C), pages 449-460.
    2. Masseran, Nurulkamal, 2015. "Evaluating wind power density models and their statistical properties," Energy, Elsevier, vol. 84(C), pages 533-541.
    3. Song, Dongran & Yang, Yinggang & Zheng, Songyue & Tang, Weiyi & Yang, Jian & Su, Mei & Yang, Xuebing & Joo, Young Hoon, 2019. "Capacity factor estimation of variable-speed wind turbines considering the coupled influence of the QN-curve and the air density," Energy, Elsevier, vol. 183(C), pages 1049-1060.
    4. 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.
    5. 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.
    6. Herbert, G.M. Joselin & Iniyan, S. & Goic, Ranko, 2010. "Performance, reliability and failure analysis of wind farm in a developing Country," Renewable Energy, Elsevier, vol. 35(12), pages 2739-2751.
    7. Dixon, Christopher & Reynolds, Steve & Rodley, David, 2016. "Micro/small wind turbine power control for electrolysis applications," Renewable Energy, Elsevier, vol. 87(P1), pages 182-192.
    8. Francisco Bilendo & Angela Meyer & Hamed Badihi & Ningyun Lu & Philippe Cambron & Bin Jiang, 2022. "Applications and Modeling Techniques of Wind Turbine Power Curve for Wind Farms—A Review," Energies, MDPI, vol. 16(1), pages 1-38, December.
    9. 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.
    10. de Medeiros, Armando Lúcio Ramos & Araújo, Alex Maurício & de Oliveira Filho, Oyama Douglas Queiroz & Rohatgi, Janardan & dos Santos, Maurílio José, 2015. "Analysis of design parameters of large-sized wind turbines by non-dimensional model," Energy, Elsevier, vol. 93(P1), pages 1146-1154.
    11. 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.
    12. Nansheng Pang & Mengfan Nan & Qichen Meng & Siyang Zhao, 2021. "Selection of Wind Turbine Based on Fuzzy Analytic Network Process: A Case Study in China," Sustainability, MDPI, vol. 13(4), pages 1-17, February.
    13. Carrillo, C. & Obando Montaño, A.F. & Cidrás, J. & Díaz-Dorado, E., 2013. "Review of power curve modelling for wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 572-581.

    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. Blonbou, Ruddy, 2011. "Very short-term wind power forecasting with neural networks and adaptive Bayesian learning," Renewable Energy, Elsevier, vol. 36(3), pages 1118-1124.
    3. Jean Souza dos Reis & Nícolas de Assis Bose & Ana Cleide Bezerra Amorim & Vanessa de Almeida Dantas & Luciano Andre Cruz Bezerra & Leonardo de Lima Oliveira & Samira de Azevedo Emiliavaca & Maria de F, 2023. "Wind and Solar Energy Generation Potential Features in the Extreme Northern Amazon Using Reanalysis Data," Energies, MDPI, vol. 16(22), pages 1-27, November.
    4. Mohammed, Y.S. & Mustafa, M.W. & Bashir, N., 2014. "Hybrid renewable energy systems for off-grid electric power: Review of substantial issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 527-539.
    5. Olaofe, Z.O., 2018. "Review of energy systems deployment and development of offshore wind energy resource map at the coastal regions of Africa," Energy, Elsevier, vol. 161(C), pages 1096-1114.
    6. 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.
    7. Mazzeo, Domenico & Oliveti, Giuseppe & Labonia, Ester, 2018. "Estimation of wind speed probability density function using a mixture of two truncated normal distributions," Renewable Energy, Elsevier, vol. 115(C), pages 1260-1280.
    8. Amelio, M & Bova, S, 2000. "Exploitation of moderate wind resources by autonomous wind electric pumping systems," Renewable Energy, Elsevier, vol. 21(2), pages 255-269.
    9. Chang, Tsang-Jung & Tu, Yi-Long, 2007. "Evaluation of monthly capacity factor of WECS using chronological and probabilistic wind speed data: A case study of Taiwan," Renewable Energy, Elsevier, vol. 32(12), pages 1999-2010.
    10. Carolin Mabel, M. & Fernandez, E., 2008. "Analysis of wind power generation and prediction using ANN: A case study," Renewable Energy, Elsevier, vol. 33(5), pages 986-992.
    11. Jafarian, M. & Ranjbar, A.M., 2010. "Fuzzy modeling techniques and artificial neural networks to estimate annual energy output of a wind turbine," Renewable Energy, Elsevier, vol. 35(9), pages 2008-2014.
    12. Villanueva, D. & Feijóo, A., 2010. "Wind power distributions: A review of their applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1490-1495, June.
    13. Masseran, Nurulkamal, 2015. "Evaluating wind power density models and their statistical properties," Energy, Elsevier, vol. 84(C), pages 533-541.

    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:eee:renene:v:32:y:2007:i:11:p:1934-1947. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.