SC13 Denver, CO

The International Conference for High Performance Computing, Networking, Storage and Analysis

Real-Time Stochastic Optimization of Complex Energy Systems on High Performance Computers.


Authors: Cosmin Petra (Argonne National Laboratory), Olaf Schenk (Universita della Svizzera Italiana), Mihai Anitescu (Argonne National Laboratory)

Abstract: We present a scalable approach that computes in operationally-compatible time the energy dispatch under uncertainty for electrical power grid systems of realistic size with thousands of scenarios. We propose several algorithmic and implementation advances in our parallel solver PIPS-IPM for stochastic optimization problems. The new developments include a novel incomplete augmented multicore sparse factorization implemented within PARDISO linear solver and new multicore- and GPU-based dense matrix implementation. We also adapt and improve the interprocess communication strategy. PIPS-IPM is used to solve 24-hour horizon power grid problems with up to 1.95 billion decision variables and 1.94 billion constraints on "Titan" (Cray XK7) and "Piz Daint" (Cray XC30), where we observe very good parallel inefficiencies and solution times within a operationally defined time interval. To our knowledge, "real-time"-compatible performance on a broad range of architectures for this class of problems has not been possible prior to present work.

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