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Analytical methods for wind persistence: Their application in assessing the best site for a wind farm in the State of Veracruz, Mexico

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  • Cancino-Solórzano, Yoreley
  • Gutiérrez-Trashorras, Antonio J.
  • Xiberta-Bernat, Jorge

Abstract

The properties of wind persistence are an essential parameter in carrying out a complete analysis of possible sites for a wind farm. This parameter can be defined as a measure of the mean duration of wind speed within a given interval of values for a concrete site. In this study the persistence properties are evaluated from the methods based on the autocorrelation function, conditional probability and the curves of speed duration, used satisfactorily by other authors. The statistical analysis of the series of useful persistence is also carried out to validate the results obtained. These methods have been applied to hourly data of wind speed corresponding to five Weather Stations (WS) in the State of Veracruz, Mexico in the period 1995–2006. The results obtained indicate that the coastal areas have the best properties of wind speed persistence and are, therefore, the most indicated for the generation of electricity from this renewable energy source.

Suggested Citation

  • Cancino-Solórzano, Yoreley & Gutiérrez-Trashorras, Antonio J. & Xiberta-Bernat, Jorge, 2010. "Analytical methods for wind persistence: Their application in assessing the best site for a wind farm in the State of Veracruz, Mexico," Renewable Energy, Elsevier, vol. 35(12), pages 2844-2852.
    • Handle: RePEc:eee:renene:v:35:y:2010:i:12:p:2844-2852
    DOI: 10.1016/j.renene.2010.05.008
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    Cited by:

    1. Osvaldo Rodriguez-Hernandez & Manuel Martinez & Carlos Lopez-Villalobos & Hector Garcia & Rafael Campos-Amezcua, 2019. "Techno-Economic Feasibility Study of Small Wind Turbines in the Valley of Mexico Metropolitan Area," Energies, MDPI, vol. 12(5), pages 1-26, March.
    2. Masseran, N. & Razali, A.M. & Ibrahim, K. & Wan Zin, W.Z., 2012. "Evaluating the wind speed persistence for several wind stations in Peninsular Malaysia," Energy, Elsevier, vol. 37(1), pages 649-656.
    3. Joselin Herbert, G.M. & Iniyan, S. & Amutha, D., 2014. "A review of technical issues on the development of wind farms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 619-641.
    4. Kruyt, Bert & Lehning, Michael & Kahl, Annelen, 2017. "Potential contributions of wind power to a stable and highly renewable Swiss power supply," Applied Energy, Elsevier, vol. 192(C), pages 1-11.
    5. Scholz, Teresa & Lopes, Vitor V. & Estanqueiro, Ana, 2014. "A cyclic time-dependent Markov process to model daily patterns in wind turbine power production," Energy, Elsevier, vol. 67(C), pages 557-568.
    6. Perini de Souza, Noéle Bissoli & Cardoso dos Santos, José Vicente & Sperandio Nascimento, Erick Giovani & Bandeira Santos, Alex Alisson & Moreira, Davidson Martins, 2022. "Long-range correlations of the wind speed in a northeast region of Brazil," Energy, Elsevier, vol. 243(C).
    7. Hernández-Escobedo, Q. & Saldaña-Flores, R. & Rodríguez-García, E.R. & Manzano-Agugliaro, F., 2014. "Wind energy resource in Northern Mexico," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 890-914.

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