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Classification and evaluation of concepts for improving the performance of applied energy system optimization models

Cao, Karl-Kien and von Krbek, Kai and Wetzel, Manuel and Cebulla, Felix and Schreck, Sebastian (2019) Classification and evaluation of concepts for improving the performance of applied energy system optimization models. Energies, 12(24) (2019). Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/en12244656 ISSN 1996-1073

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Official URL: https://www.mdpi.com/1996-1073/12/24/4656

Abstract

Energy system optimization models used for capacity expansion and dispatch planning are established tools for decision making support in both energy industry and energy politics. The ever-increasing complexity of the systems under consideration leads to an increase in mathematical problem size of the models. This implies limitations of today's common solution approaches especially with regard to required computing times. To tackle this challenge many model-based speed-up approaches exist which, however, are typically only demonstrated on small generic test cases. In addition, in applied energy systems analysis the effects of such approaches are often not well understood. The novelty of this study is the systematic evaluation of several model reduction and heuristic decomposition techniques for a large applied energy system model using real data and particularly focusing on reachable speed-up. The applied model is typically used for examining German energy scenarios and allows expansion of storage and electricity transmission capacities. We find that initial computing times of more than two days can be reduced up to a factor of ten while having acceptable loss of accuracy. Moreover, we explain what we mean by “effectiveness of model reduction” which limits the possible speed-up with shared memory computers used in this study.

Item URL in elib:https://elib.dlr.de/129439/
Document Type:Article
Title:Classification and evaluation of concepts for improving the performance of applied energy system optimization models
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Cao, Karl-KienKarl-Kien.Cao (at) dlr.dehttps://orcid.org/0000-0002-9720-0337
von Krbek, KaiKai.Krbek (at) dlr.deUNSPECIFIED
Wetzel, ManuelManuel.Wetzel (at) dlr.dehttps://orcid.org/0000-0001-7838-2414
Cebulla, Felixfelix.cebulla (at) googlemail.comhttps://orcid.org/0000-0001-8819-3780
Schreck, Sebastianschreck.sh (at) gmail.comUNSPECIFIED
Date:2019
Journal or Publication Title:Energies
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:12(24)
DOI :10.3390/en12244656
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Series Name:Electrical Power and Energy System
ISSN:1996-1073
Status:Published
Keywords:Energy systems analysis, Energy system optimization models, Linear programming, Mathematical decomposition, Model reduction, REMix
HGF - Research field:Energy
HGF - Program:Technology, Innovation and Society
HGF - Program Themes:Renewable Energy and Material Resources for Sustainable Futures - Integrating at Different Scales
DLR - Research area:Energy
DLR - Program:E SY - Energy Systems Analysis
DLR - Research theme (Project):E - Systems Analysis and Technology Assessment
Location: Stuttgart
Institutes and Institutions:Institute of Engineering Thermodynamics > Energy Systems Analysis
Deposited By: Cao, Karl-Kien
Deposited On:11 Oct 2019 14:24
Last Modified:16 Dec 2019 15:39

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