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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Notes
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It can be downloaded (on a daily basis) from the market operator web site www.mercatoelettrico.org.
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Reference [8] solves the problem of optimal bidding when supply functions are step functions with a given number of steps. However, even in this case the optimal predictions of these step functions need not be step functions, as the prices at which the steps take place may be absolutely continuous random variables and this condition makes the expectation of any random step function a continuous function.
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Pelagatti, M. (2013). Supply Function Prediction in Electricity Auctions. In: Grigoletto, M., Lisi, F., Petrone, S. (eds) Complex Models and Computational Methods in Statistics. Contributions to Statistics. Springer, Milano. https://doi.org/10.1007/978-88-470-2871-5_16
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DOI: https://doi.org/10.1007/978-88-470-2871-5_16
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