Supply Function Prediction in Electricity Auctions
Matteo Pelagatti ()
No 20120301, Working Papers from Università degli Studi di Milano-Bicocca, Dipartimento di Statistica
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.
Keywords: electricity auctions; functional prediction; reduced rank regression (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ene and nep-for
References: Add references at CitEc
Citations Track citations by RSS feed
Downloads: (external link)
http://www.statistica.unimib.it/utenti/WorkingPapers/WorkingPapers/20120301.pdf First version, 2012 (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:mis:wpaper:20120301
Access Statistics for this paper
More papers in Working Papers from Università degli Studi di Milano-Bicocca, Dipartimento di Statistica Contact information at EDIRC.
Series data maintained by Matteo Pelagatti ().