IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v14y2010i9p3185-3191.html
   My bibliography  Save this article

Wind speed analysis in the province of Alicante, Spain. Potential for small-scale wind turbines

Author

Listed:
  • Cabello, M.
  • Orza, J.A.G.

Abstract

The statistical characteristics of the wind speed in the province of Alicante, southeastern Spain, have been analyzed using 9-year wind data recorded at 2Â m above the ground by 17 weather stations belonging to the Valencian Institute for Agriculture Research (IVIA). The overall mean wind speed in the area is 1.7Â m/s with the windy regions located at the northwest side in the highlands. A clear seasonal and daily pattern is shown with maximum in spring-summer during the central hours of the day, influenced by the sea breeze; and minimum in autumn-winter at night. The wind frequency distributions show two and three modes. The sum-lognormal model is found to be a good fit with very high correlation in all the sites. The extrapolation to 10Â m with the power law and the wind shear exponent [alpha], shows a large underestimation in the northern coastal sites and a good agreement in the innermost locations, when compared to measurements done at 10Â m in a number of stations.

Suggested Citation

  • Cabello, M. & Orza, J.A.G., 2010. "Wind speed analysis in the province of Alicante, Spain. Potential for small-scale wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 3185-3191, December.
    • Handle: RePEc:eee:rensus:v:14:y:2010:i:9:p:3185-3191
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364-0321(10)00182-6
    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. Feretić, Danilo & Tomšić, Željko & Čavlina, Nikola, 1999. "Feasibility analysis of wind-energy utilization in Croatia," Energy, Elsevier, vol. 24(3), pages 239-246.
    2. Farrugia, R.N., 2003. "The wind shear exponent in a Mediterranean island climate," Renewable Energy, Elsevier, vol. 28(4), pages 647-653.
    3. Migoya, Emilio & Crespo, Antonio & Jiménez, Ángel & García, Javier & Manuel, Fernando, 2007. "Wind energy resource assessment in Madrid region," Renewable Energy, Elsevier, vol. 32(9), pages 1467-1483.
    4. Carta, J.A. & Ramírez, P., 2007. "Analysis of two-component mixture Weibull statistics for estimation of wind speed distributions," Renewable Energy, Elsevier, vol. 32(3), pages 518-531.
    5. Jaramillo, O.A. & Borja, M.A., 2004. "Wind speed analysis in La Ventosa, Mexico: a bimodal probability distribution case," Renewable Energy, Elsevier, vol. 29(10), pages 1613-1630.
    6. Aksoy, Hafzullah & Fuat Toprak, Z & Aytek, Ali & Erdem Ünal, N, 2004. "Stochastic generation of hourly mean wind speed data," Renewable Energy, Elsevier, vol. 29(14), pages 2111-2131.
    7. Bivona, S. & Burlon, R. & Leone, C., 2003. "Hourly wind speed analysis in Sicily," Renewable Energy, Elsevier, vol. 28(9), pages 1371-1385.
    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. Sergei Kolesnik & Yossi Rabinovitz & Michael Byalsky & Asher Yahalom & Alon Kuperman, 2023. "Assessment of Wind Speed Statistics in Samaria Region and Potential Energy Production," Energies, MDPI, vol. 16(9), pages 1-35, May.
    2. Irshad, Ahmad Shah & Samadi, Wais Khan & Fazli, Agha Mohammad & Noori, Abdul Ghani & Amin, Ahmad Shah & Zakir, Mohammad Naseer & Bakhtyal, Irfan Ahmad & Karimi, Bashir Ahmad & Ludin, Gul Ahmad & Senjy, 2023. "Resilience and reliable integration of PV-wind and hydropower based 100% hybrid renewable energy system without any energy storage system for inaccessible area electrification," Energy, Elsevier, vol. 282(C).
    3. Wang, Jianzhou & Qin, Shanshan & Jin, Shiqiang & Wu, Jie, 2015. "Estimation methods review and analysis of offshore extreme wind speeds and wind energy resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 26-42.
    4. Oner, Yasemin & Ozcira, Selin & Bekiroglu, Nur & Senol, Ibrahim, 2013. "A comparative analysis of wind power density prediction methods for Çanakkale, Intepe region, Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 491-502.
    5. Santos, J.A. & Rochinha, C. & Liberato, M.L.R. & Reyers, M. & Pinto, J.G., 2015. "Projected changes in wind energy potentials over Iberia," Renewable Energy, Elsevier, vol. 75(C), pages 68-80.
    6. Florin Onea & Andrés Ruiz & Eugen Rusu, 2020. "An Evaluation of the Wind Energy Resources along the Spanish Continental Nearshore," Energies, MDPI, vol. 13(15), pages 1-23, August.
    7. Schallenberg-Rodriguez, Julieta, 2013. "A methodological review to estimate techno-economical wind energy production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 272-287.
    8. Ramenah, H. & Tanougast, C., 2016. "Reliably model of microwind power energy output under real conditions in France suburban area," Renewable Energy, Elsevier, vol. 91(C), pages 1-10.
    9. Sunderland, Keith M. & Narayana, Mahinsasa & Putrus, Ghanim & Conlon, Michael F. & McDonald, Steve, 2016. "The cost of energy associated with micro wind generation: International case studies of rural and urban installations," Energy, Elsevier, vol. 109(C), pages 818-829.
    10. Tiang, Tow Leong & Ishak, Dahaman, 2012. "Technical review of wind energy potential as small-scale power generation sources in Penang Island Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3034-3042.
    11. Früh, Wolf-Gerrit, 2013. "Long-term wind resource and uncertainty estimation using wind records from Scotland as example," Renewable Energy, Elsevier, vol. 50(C), pages 1014-1026.

    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. Früh, Wolf-Gerrit, 2013. "Long-term wind resource and uncertainty estimation using wind records from Scotland as example," Renewable Energy, Elsevier, vol. 50(C), pages 1014-1026.
    3. Jung, Christopher & Schindler, Dirk, 2019. "Wind speed distribution selection – A review of recent development and progress," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    4. Muhammad Fitra Zambak & Catra Indra Cahyadi & Jufri Helmi & Tengku Machdhalie Sofie & Suwarno Suwarno, 2023. "Evaluation and Analysis of Wind Speed with the Weibull and Rayleigh Distribution Models for Energy Potential Using Three Models," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 427-432, March.
    5. Liu, Feng Jiao & Chang, Tian Pau, 2011. "Validity analysis of maximum entropy distribution based on different moment constraints for wind energy assessment," Energy, Elsevier, vol. 36(3), pages 1820-1826.
    6. Arslan, Talha & Bulut, Y. Murat & Altın Yavuz, Arzu, 2014. "Comparative study of numerical methods for determining Weibull parameters for wind energy potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 820-825.
    7. Emilio Gómez-Lázaro & María C. Bueso & Mathieu Kessler & Sergio Martín-Martínez & Jie Zhang & Bri-Mathias Hodge & Angel Molina-García, 2016. "Probability Density Function Characterization for Aggregated Large-Scale Wind Power Based on Weibull Mixtures," Energies, MDPI, vol. 9(2), pages 1-15, February.
    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. Jin, Jingliang & Zhou, Dequn & Zhou, Peng & Miao, Zhuang, 2014. "Environmental/economic power dispatch with wind power," Renewable Energy, Elsevier, vol. 71(C), pages 234-242.
    10. Lepore, Antonio & Palumbo, Biagio & Pievatolo, Antonio, 2020. "A Bayesian approach for site-specific wind rose prediction," Renewable Energy, Elsevier, vol. 150(C), pages 691-702.
    11. Chang, Tian Pau, 2011. "Estimation of wind energy potential using different probability density functions," Applied Energy, Elsevier, vol. 88(5), pages 1848-1856, May.
    12. Goh, H.H. & Lee, S.W. & Chua, Q.S. & Goh, K.C. & Teo, K.T.K., 2016. "Wind energy assessment considering wind speed correlation in Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1389-1400.
    13. Qing, Xiangyun, 2018. "Statistical analysis of wind energy characteristics in Santiago island, Cape Verde," Renewable Energy, Elsevier, vol. 115(C), pages 448-461.
    14. Sergei Kolesnik & Yossi Rabinovitz & Michael Byalsky & Asher Yahalom & Alon Kuperman, 2023. "Assessment of Wind Speed Statistics in Samaria Region and Potential Energy Production," Energies, MDPI, vol. 16(9), pages 1-35, May.
    15. Simon Watson, 2014. "Quantifying the variability of wind energy," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 3(4), pages 330-342, July.
    16. Akdag, S.A. & Bagiorgas, H.S. & Mihalakakou, G., 2010. "Use of two-component Weibull mixtures in the analysis of wind speed in the Eastern Mediterranean," Applied Energy, Elsevier, vol. 87(8), pages 2566-2573, August.
    17. 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.
    18. Muhammet Burak Kılıç & Yusuf Şahin & Melih Burak Koca, 2021. "Genetic algorithm approach with an adaptive search space based on EM algorithm in two-component mixture Weibull parameter estimation," Computational Statistics, Springer, vol. 36(2), pages 1219-1242, June.
    19. Houssem R. E. H. Bouchekara & Yusuf A. Sha’aban & Mohammad S. Shahriar & Saad M. Abdullah & Makbul A. Ramli, 2023. "Sizing of Hybrid PV/Battery/Wind/Diesel Microgrid System Using an Improved Decomposition Multi-Objective Evolutionary Algorithm Considering Uncertainties and Battery Degradation," Sustainability, MDPI, vol. 15(14), pages 1-38, July.
    20. Hu, Qinghua & Wang, Yun & Xie, Zongxia & Zhu, Pengfei & Yu, Daren, 2016. "On estimating uncertainty of wind energy with mixture of distributions," Energy, Elsevier, vol. 112(C), pages 935-962.

    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:9:p:3185-3191. 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.