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Wind speed forecasting in the South Coast of Oaxaca, México

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  • Cadenas, Erasmo
  • Rivera, Wilfrido

Abstract

Comparison of two techniques for wind speed forecasting in the South Coast of the state of Oaxaca, Mexico is presented in this paper. The Autoregressive Integrated Moving Average (ARIMA) and the Artificial Neural Networks (ANN) methods are applied to a time series conformed by 7 years of wind speed measurements. Six years were used in the formulation of the models and the last year was used to validate and compare the effectiveness of the generated prediction by the techniques mentioned above. Seasonal ARIMA models present a better sensitivity to the adjustment and prediction of the wind speed for this case in particular. Nevertheless, it was shown both developed models can be used to predict in a reasonable way, the monthly electricity production of the wind power stations in La Venta, Oaxaca, Mexico to support the operators of the Electric Utility Control Centre.

Suggested Citation

  • Cadenas, Erasmo & Rivera, Wilfrido, 2007. "Wind speed forecasting in the South Coast of Oaxaca, México," Renewable Energy, Elsevier, vol. 32(12), pages 2116-2128.
    • Handle: RePEc:eee:renene:v:32:y:2007:i:12:p:2116-2128
    DOI: 10.1016/j.renene.2006.10.005
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    References listed on IDEAS

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    1. Roulston, M.S. & Kaplan, D.T. & Hardenberg, J. & Smith, L.A., 2003. "Using medium-range weather forcasts to improve the value of wind energy production," Renewable Energy, Elsevier, vol. 28(4), pages 585-602.
    2. 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.
    3. Sfetsos, A., 2002. "A novel approach for the forecasting of mean hourly wind speed time series," Renewable Energy, Elsevier, vol. 27(2), pages 163-174.
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