Friday, 16:15 - 16:40 h, Room: MA 141

 

Tito Homem-De-Mello
On scenario generation methods for a hydroelectric power system

Coauthors: Vitor L. de Matos, Erlon C. Finardi

 

Abstract:
We study a multi-stage stochastic programming model for hydrothermal energy planning in Brazil, where uncertainty is due to water inflows. We discuss some methods for generation of scenario trees that can be used by an optimization algorithm to solve the problem. Although the original input process is modeled with an periodic auto-regressive model, by making a transformation we can reduce the input process to one that is stage-wise independent. That in turn allows us to proceed with generating scenarios stage-by-stage following the
approach in Mirkov and Pflug (2007). The algorithm we propose hinges on the stage-wise independence property and consists of two phases: first, we generate a scenario tree where the distribution in each stage is approximated by a discrete distribution with large number of points; then, we apply a reduction method to find a distribution with smaller support that minimizes the Wasserstein distance to that discrete distribution. We show how this minimization problem can be solved with a structured binary linear program. Some numerical results are presented to illustrate the ideas.

 

Talk 3 of the invited session Fri.3.MA 141
"Scenario generation in stochastic programming" [...]
Cluster 22
"Stochastic optimization" [...]

 

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