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Integration of Wind Power Production in a Conventional Power Production System: Stochastic Models and Performance Measures

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Handbook of Wind Power Systems

Part of the book series: Energy Systems ((ENERGY))

Abstract

A stochastic programming model for the daily coordination of hydro power plants and wind power plants with pumped storage is introduced, with hourly wind power production uncertainty represented by means of a scenario tree. Historical data of wind power production forecast error are assumed to be available, which are used for obtaining wind power production forecast error scenarios. These scenarios are then combined with information from the weather forecast, resulting in wind power production scenarios. Ex-ante and ex-post measures are considered for assessing the value of the stochastic model: the ex-ante performance evaluation is based on the Modified Value of Stochastic Solution for multistage stochastic programming, introduced independently in Escudero (TOP 15(1):48–66, 2007) and Vespucci (Ann Oper Res 193:91–105, 2012); the ex-post performance evaluation is defined in terms of the Value of Stochastic Planning, introduced in Schütz (Int J Prod Econ, 2009), that makes use of the realized values of the stochastic parameter. Both measures indicate the advantage of using the stochastic approach.

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Acknowledgments

This research was partly supported by the research grants Fondi di Ateneo 2009–2010 of the University of Bergamo (coordinated by M. Bertocchi and L. Brandolini) and by research grant of Accordo Regione Lombardia Metodi di integrazione delle fonti energetiche rinnovabili e monitoraggio satellitare dell’impatto ambientale, CUP: F11J10000200002 (coordinated by A. Fassó). We also acknowledge RSE in Milan, for providing data.

Author information

Authors and Affiliations

  1. Department of Management, Economics and Quantitative Methods, via dei Caniana 2, 24127, Bergamo, Italy

    Maria Teresa Vespucci & Marida Bertocchi

  2. Department of Mathematics, Statistics, Computing and Applications, University of Bergamo, Via Dei Caniana 2, 24127, Bergamo, Italy

    Marida Bertocchi

  3. Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, 7491, Trondheim, Norway

    Asgeir Tomasgard

  4. Department of Information Technology and Mathematical Methods, University of Bergamo, Via Marconi 5a, 24044, Dalmine, BG, Italy

    Mario Innorta

Authors
  1. Maria Teresa Vespucci
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  2. Marida Bertocchi
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  3. Asgeir Tomasgard
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  4. Mario Innorta
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Corresponding author

Correspondence to Maria Teresa Vespucci .

Editor information

Editors and Affiliations

  1. Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

  2. Division of Economics and Business Engineering Hall, Colorado School of Mines, Golden, Colorado, USA

    Steffen Rebennack

  3. Centro Empresarial Rio Praia de Botafogo, Rio de Janeiro, Rio de Janeiro, Brazil

    Mario V. F. Pereira

  4. EnerCoRD - Energy Consulting, Research & Development, Athens, Greece

    Niko A. Iliadis

  5. Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Vijay Pappu

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Vespucci, M.T., Bertocchi, M., Tomasgard, A., Innorta, M. (2013). Integration of Wind Power Production in a Conventional Power Production System: Stochastic Models and Performance Measures. In: Pardalos, P., Rebennack, S., Pereira, M., Iliadis, N., Pappu, V. (eds) Handbook of Wind Power Systems. Energy Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41080-2_5

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  • DOI: https://doi.org/10.1007/978-3-642-41080-2_5

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41079-6

  • Online ISBN: 978-3-642-41080-2

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