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Forecast-based scenario-tree generation method

Michal Kaut(michal.kaut***at***sintef.no)

Abstract: Sometimes, the best available information about an uncertain future is a single forecast. On the other hand, stochastic-programming models need future data in the form of scenario trees. While a single forecast does not provide enough information to construct a scenario tree, a forecast combined with historical data doesóbut none of the standard scenario-generation methods is suited to handle this combination. In this paper, we present a new scenario-generation method that combines a single forecast with historical forecast errors. The method is purely data driven and can take into account dependencies between errors of forecasts of different lengths.

Keywords: stochastic programming, scenario generation

Category 1: Stochastic Programming


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Entry Submitted: 03/10/2017
Entry Accepted: 03/10/2017
Entry Last Modified: 03/10/2017

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