Tuesday, 13:15 - 13:40 h, Room: MA 549


Cosmin Petra
Scalable stochastic optimization of power grid energy systems

Coauthors: Mihai Anitescu, Miles Lubin


We present a scalable approach for solving stochastic programming problems, with application to the optimization of power grid energy systems with supply and demand uncertainty.
Our framework, PIPS, has parallel capabilities for both continuous and discrete stochastic optimizations problems. The continuous solver uses an interior-point method and a Schur complement technique to obtain a scenario-based decomposition. With an aim of providing a scalable solution for problems with integer variables, we also developed a
linear algebra decomposition strategy for simplex methods that is used in a parallel branch-and-bound framework.
We will also discuss application-specific algorithmic developments and computational results obtained on "Intrepid'' Blue Gene/P system at Argonne when solving unit commitment problems with billions of variables.


Talk 1 of the invited session Tue.2.MA 549
"Stochastic programming applications in energy systems" [...]
Cluster 18
"Optimization in energy systems" [...]


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