IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v14y2010i5p1490-1495.html
   My bibliography  Save this article

Wind power distributions: A review of their applications

Author

Listed:
  • Villanueva, D.
  • Feijóo, A.

Abstract

This paper presents the features of wind power distributions that have been analytically obtained from wind distribution functions. Simple equations establishing a relationship between mean power density and wind speed have been obtained for a given location and wind turbine (WT). Four different concepts relating wind power distribution functions are shown: the power transported by the wind; the theoretical maximum convertible power from it according to the Betz' law; the maximum convertible power from the wind considering more realistic limits that will be explained; finally an even more approximate limit to the maximum power obtained from a wind turbine, considering its parameters. Similarly, four different equations are obtained establishing relationships between the mean power density and the mean wind speed. These equations are very simple and very useful when discarding locations for wind turbine installation.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:rensus:v:14:y:2010:i:5:p:1490-1495
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364-0321(10)00013-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Mihelić-Bogdanić, Alka & Budin, Rajka, 1992. "Specific wind energy as a function of mean speed," Renewable Energy, Elsevier, vol. 2(6), pages 573-576.
    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. Tabar, Vahid Sohrabi & Abbasi, Vahid, 2019. "Energy management in microgrid with considering high penetration of renewable resources and surplus power generation problem," Energy, Elsevier, vol. 189(C).
    2. Bortolini, Marco & Gamberi, Mauro & Graziani, Alessandro & Manzini, Riccardo & Pilati, Francesco, 2014. "Performance and viability analysis of small wind turbines in the European Union," Renewable Energy, Elsevier, vol. 62(C), pages 629-639.
    3. Golpîra, Hêriş & Khan, Syed Abdul Rehman, 2019. "A multi-objective risk-based robust optimization approach to energy management in smart residential buildings under combined demand and supply uncertainty," Energy, Elsevier, vol. 170(C), pages 1113-1129.
    4. Atlason, Reynir & Unnthorsson, Runar, 2014. "Ideal EROI (energy return on investment) deepens the understanding of energy systems," Energy, Elsevier, vol. 67(C), pages 241-245.
    5. Lena Kitzing & Christoph Weber, "undated". "Support mechanisms for renewables: How risk exposure influences investment incentives," EWL Working Papers 1403, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Aug 2014.
    6. Tabar, Vahid Sohrabi & Ghassemzadeh, Saeid & Tohidi, Sajjad, 2019. "Energy management in hybrid microgrid with considering multiple power market and real time demand response," Energy, Elsevier, vol. 174(C), pages 10-23.
    7. Siddiqui, M. Salman & Durrani, Naveed & Akhtar, Imran, 2015. "Quantification of the effects of geometric approximations on the performance of a vertical axis wind turbine," Renewable Energy, Elsevier, vol. 74(C), pages 661-670.
    8. Madariaga, A. & de Alegría, I. Martínez & Martín, J.L. & Eguía, P. & Ceballos, S., 2012. "Current facts about offshore wind farms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3105-3116.
    9. Loukatou, Angeliki & Howell, Sydney & Johnson, Paul & Duck, Peter, 2018. "Stochastic wind speed modelling for estimation of expected wind power output," Applied Energy, Elsevier, vol. 228(C), pages 1328-1340.
    10. Fred Espen Benth & Luca Di Persio & Silvia Lavagnini, 2018. "Stochastic Modeling of Wind Derivatives in Energy Markets," Risks, MDPI, vol. 6(2), pages 1-21, May.
    11. Malik, Abdul Q., 2021. "Renewables for Fiji – Path for green power generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    12. Ahmed, Adil & Khalid, Muhammad, 2019. "A review on the selected applications of forecasting models in renewable power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 9-21.
    13. Son, Yeong Geon & Oh, Byeong Chan & Acquah, Moses Amoasi & Kim, Sung Yul, 2023. "Optimal facility combination set of integrated energy system based on consensus point between independent system operator and independent power producer," Energy, Elsevier, vol. 266(C).
    14. Shirazi, Elham & Jadid, Shahram, 2017. "Cost reduction and peak shaving through domestic load shifting and DERs," Energy, Elsevier, vol. 124(C), pages 146-159.
    15. Feijóo, Andrés & Villanueva, Daniel & Pazos, José Luis & Sobolewski, Robert, 2011. "Simulation of correlated wind speeds: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2826-2832, August.
    16. Masseran, Nurulkamal, 2015. "Evaluating wind power density models and their statistical properties," Energy, Elsevier, vol. 84(C), pages 533-541.
    17. Silvente, Javier & Papageorgiou, Lazaros G., 2017. "An MILP formulation for the optimal management of microgrids with task interruptions," Applied Energy, Elsevier, vol. 206(C), pages 1131-1146.
    18. Yuji Yamada & Takuji Matsumoto, 2023. "Construction of Mixed Derivatives Strategy for Wind Power Producers," Energies, MDPI, vol. 16(9), pages 1-26, April.
    19. Kitzing, Lena, 2014. "Risk implications of renewable support instruments: Comparative analysis of feed-in tariffs and premiums using a mean–variance approach," Energy, Elsevier, vol. 64(C), pages 495-505.
    20. Wang, Peng & Li, Yanting & Zhang, Guangyao, 2023. "Probabilistic power curve estimation based on meteorological factors and density LSTM," Energy, Elsevier, vol. 269(C).
    21. Tabar, Vahid Sohrabi & Jirdehi, Mehdi Ahmadi & Hemmati, Reza, 2017. "Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option," Energy, Elsevier, vol. 118(C), pages 827-839.
    22. Malik, A.Q., 2011. "Assessment of the potential of renewables for Brunei Darussalam," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 427-437, January.

    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. 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.
    3. Ahmed, Ahmed Shata, 2012. "Potential wind power generation in South Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1528-1536.
    4. 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.
    5. Jean Souza dos Reis & Nícolas de Assis Bose & Ana Cleide Bezerra Amorim & Vanessa Dantas Almeida & Luciano Andre Cruz Bezerra & Leonardo de Lima Oliveira & Samira de Azevedo Emiliavaca & Maria de Fáti, 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.
    6. 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.
    7. Ahmed Shata, A.S. & Hanitsch, R., 2006. "The potential of electricity generation on the east coast of Red Sea in Egypt," Renewable Energy, Elsevier, vol. 31(10), pages 1597-1615.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Ahmed, Ahmed Shata, 2010. "Wind energy as a potential generation source at Ras Benas, Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(8), pages 2167-2173, October.
    13. 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.
    14. 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:rensus:v:14:y:2010:i:5:p:1490-1495. 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.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    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.