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Wind Power Forecast Error Probabilistic Model Using Markov Chains

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Environment, Energy and Climate Change II

Part of the book series: The Handbook of Environmental Chemistry ((HEC,volume 34))

Abstract

Wind forecast is an important consideration in integrating large amounts of wind power into the electricity grid. The wind power forecast error (WPFE) distribution can have a large impact on the confidence intervals produced in wind power forecasting.

The problem of accurately wind energy forecasting has received a great deal of attention in recent years. There are always some errors associated with any forecasting methodology. It is thus necessary for the transmission system operators (TSOs) and the market participants to understand these errors. WPFE has an important role on system balance reserves calculation. As a result of the former, WPFE has an important economic impact in market costs.

In this work, WPFE statistics are examined for Spanish power system over multiple timescales. Comparisons are made between the experimental data in different years and production ranges. The shape of WPFE probability density function (PDF) is found to change significantly with the length of the forecasting timescale and with wind power production range. Additionally, error sources and magnitudes are analyzed to establish their main characteristics. Finally a Markov chain (MC) probabilistic model is constructed using these WPFE data for validation.

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Acknowledgments

This work was supported by the Ministerio de Economía y Competitividad (Spain) through the Research Project Ref. ENE2012-34603, a project cofinanced with FEDER funds.

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Authors and Affiliations

  1. Renewable Energy Research Institute and DIEEAC-EDII-AB, Universidad de Castilla-La Mancha, Albacete, 02071, Castilla-La Mancha, Spain

    S. Martín Martinez, A. Honrubia Escribano, M. Cañas Carretón & E. Gómez Lázaro

  2. Escuela Técnica Superior de Ingenieros Industriales, Universidad de Castilla-La Mancha, Ciudad Real, 13071, Castilla-La Mancha, Spain

    V. Guerrero Mestre

Authors
  1. S. Martín Martinez
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  2. A. Honrubia Escribano
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  3. M. Cañas Carretón
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  4. V. Guerrero Mestre
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  5. E. Gómez Lázaro
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Corresponding author

Correspondence to S. Martín Martinez .

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Editors and Affiliations

  1. CERTES-IUT, The University Paris Est Créteil, Paris Créteil, France

    Gilles Lefebvre

  2. Department of Physical Chemistry, University of Castilla-La Mancha (UCLM), Ciudad Real, Spain

    Elena Jiménez

  3. Department of Physical Chemistry, University of Castilla-La Mancha (UCLM), Ciudad Real, Spain

    Beatriz Cabañas

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© 2014 Springer International Publishing Switzerland

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Martín Martinez, S., Honrubia Escribano, A., Cañas Carretón, M., Guerrero Mestre, V., Gómez Lázaro, E. (2014). Wind Power Forecast Error Probabilistic Model Using Markov Chains. In: Lefebvre, G., Jiménez, E., Cabañas, B. (eds) Environment, Energy and Climate Change II. The Handbook of Environmental Chemistry, vol 34. Springer, Cham. https://doi.org/10.1007/698_2014_303

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