Improving the computational efficiency of stochastic programs using automated algorithm configuration: an application to decentralized energy systems

The optimization of decentralized energy systems is an important practical problem that can be modeled using stochastic programs and solved via their large-scale, deterministic-equivalent formulations. Unfortunately, using this approach, even when leveraging a high degree of parallelism on large hig...

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Vydáno v:Annals of operations research s. 1 - 22
Hlavní autoři: Schwarz, Hannes, Kotthoff, Lars, Hoos, Holger, Fichtner, Wolf, Bertsch, Valentin
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer Nature B.V 2019
Témata:
Algorithms
Alternative energy sources
Automation
Computational efficiency
Computer science
Computing costs
Computing time
Configurations
Formulations
High performance computing
Operations research
Optimization techniques
State of the art
Storage units
Ireland
Germany
ISSN:0254-5330, 1572-9338
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Shrnutí:The optimization of decentralized energy systems is an important practical problem that can be modeled using stochastic programs and solved via their large-scale, deterministic-equivalent formulations. Unfortunately, using this approach, even when leveraging a high degree of parallelism on large high-performance computing systems, finding close-to-optimal solutions still requires substantial computational effort. In this work, we present a procedure to reduce this computational effort substantially, using a state-of-the-art automated algorithm configuration method. We apply this procedure to a well-known example of a residential quarter with photovoltaic systems and storage units, modeled as a two-stage stochastic mixed-integer linear program. We demonstrate that the computing time and costs can be substantially reduced by up to 50% by use of our procedure. Our methodology can be applied to other, similarly-modeled energy systems.
Bibliografie:ObjectType-Article-1
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ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-018-3122-6