Optimizing Large-Scale Linear Energy System Problems with Block Diagonal Structure by Using Parallel Interior-Point Methods

Please always quote using this URN: urn:nbn:de:0297-zib-66183
  • Current linear energy system models (ESM) acquiring to provide sufficient detail and reliability frequently bring along problems of both high intricacy and increasing scale. Unfortunately, the size and complexity of these problems often prove to be intractable even for commercial state-of-the-art linear programming solvers. This article describes an interdisciplinary approach to exploit the intrinsic structure of these large-scale linear problems to be able to solve them on massively parallel high-performance computers. A key aspect are extensions to the parallel interior-point solver PIPS-IPM originally developed for stochastic optimization problems. Furthermore, a newly developed GAMS interface to the solver as well as some GAMS language extensions to model block-structured problems will be described.

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Metadaten
Author:Thomas Breuer, Michael Bussieck, Karl-Kien Cao, Felix Cebulla, Frederik Fiand, Hans Christian Gils, Ambros Gleixner, Dmitry Khabi, Thorsten Koch, Daniel Rehfeldt, Manuel Wetzel
Document Type:ZIB-Report
Tag:energy system models; high-performance computing; interior-point methods
MSC-Classification:90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING
CCS-Classification:D. Software
Date of first Publication:2017/12/18
Series (Serial Number):ZIB-Report (17-75)
ISSN:1438-0064
Published in:Operations Research Proceedings 2017