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Scenario generation using historical data paths

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

Abstract: In this paper, we present a method for generating scenarios by selection from historical data. We start with two models for a univariate single-period case and then extend the better-performing one to the case of selecting sequences of multivariate data. We then test the method on data series for wind- and solar-power generation in Scandinavia.

Keywords: stochastic programming, scenario generation

Category 1: Stochastic Programming


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Entry Submitted: 02/04/2020
Entry Accepted: 02/04/2020
Entry Last Modified: 02/04/2020

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