Wind speed forecasting in the South Coast of Oaxaca, México

Erasmo Cadenas and Wilfrido Rivera

Renewable Energy, 2007, vol. 32, issue 12, 2116-2128

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.

Keywords: Wind speed; Prediction; ARIMA; Neural networks (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (42)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:32:y:2007:i:12:p:2116-2128

DOI: 10.1016/j.renene.2006.10.005

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