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Supply Function Prediction in Electricity Auctions

Author

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  • Matteo Pelagatti

    () (Dipartimento di Statistica, Università degli Studi di Milano-Bicocca)

Abstract

In the fast growing literature that addresses the problem of the optimal bidding behaviour of power generation companies that sell energy in electricity auctions it is always assumed that every firm knows the aggregate supply function of its competitors. Since this information is generally not available, real data have to be substituted by predictions. In this paper we propose two alternative approaches to the problem and apply them to the hourly prediction of the aggregate supply function of the competitors of the main Italian generation company.

Suggested Citation

  • Matteo Pelagatti, 2012. "Supply Function Prediction in Electricity Auctions," Working Papers 20120301, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica.
  • Handle: RePEc:mis:wpaper:20120301
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    File URL: http://www.statistica.unimib.it/utenti/WorkingPapers/WorkingPapers/20120301.pdf
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    Keywords

    electricity auctions; functional prediction; reduced rank regression;

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