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Supply Function Prediction in Electricity Auctions

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Author Info

  • 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.

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File URL: http://www.statistica.unimib.it/utenti/WorkingPapers/WorkingPapers/20120301.pdf
File Function: First version, 2012
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Bibliographic Info

Paper provided by Università degli Studi di Milano-Bicocca, Dipartimento di Statistica in its series Working Papers with number 20120301.

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Length: 11 pages
Date of creation: 01 Mar 2012
Date of revision:
Handle: RePEc:mis:wpaper:20120301

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Web page: http://www.statistica.unimib.it
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Related research

Keywords: electricity auctions; functional prediction; reduced rank regression;

This paper has been announced in the following NEP Reports:

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