001     877631
005     20240709081916.0
024 7 _ |a 10.1016/j.compchemeng.2018.01.023
|2 doi
024 7 _ |a 0098-1354
|2 ISSN
024 7 _ |a 1873-4375
|2 ISSN
024 7 _ |a altmetric:33195634
|2 altmetric
024 7 _ |a WOS:000427486800008
|2 WOS
037 _ _ |a FZJ-2020-02346
082 _ _ |a 660
100 1 _ |a Bahl, Björn
|0 P:(DE-HGF)0
|b 0
245 _ _ |a Rigorous synthesis of energy systems by decomposition via time-series aggregation
260 _ _ |a Amsterdam [u.a.]
|c 2018
|b Elsevier Science
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1592807931_25977
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a The synthesis of complex energy systems usually involves large time series such that a direct optimization is computationally prohibitive. In this paper, we propose a decomposition method for synthesis problems using time-series aggregation. To initialize the method, the time series is aggregated to one time step. A lower bound is obtained by relaxing the energy balances and underestimating the energy demands leading to a relaxed synthesis problem, which is efficiently solvable. An upper bound is obtained by restricting the original problem with the full time series to an operation problem with a fixed structure obtained from the lower bound solution. If the bounds do not satisfy the specified optimality gap, the resolution of the time-series aggregation is iteratively increased. The decomposition method is applied to two real-world synthesis problems. The results show the fast convergence of the decomposition method outperforming commercial state-of-the-art optimization software.
536 _ _ |a 899 - ohne Topic (POF3-899)
|0 G:(DE-HGF)POF3-899
|c POF3-899
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Lützow, Julian
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Shu, David
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Hollermann, Dinah Elena
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Lampe, Matthias
|0 P:(DE-HGF)0
|b 4
700 1 _ |a Hennen, Maike
|0 P:(DE-HGF)0
|b 5
700 1 _ |a Bardow, André
|0 P:(DE-Juel1)172023
|b 6
|e Corresponding author
|u fzj
773 _ _ |a 10.1016/j.compchemeng.2018.01.023
|g Vol. 112, p. 70 - 81
|0 PERI:(DE-600)1499971-7
|p 70 - 81
|t Computers & chemical engineering
|v 112
|y 2018
|x 0098-1354
909 C O |o oai:juser.fz-juelich.de:877631
|p VDB
910 1 _ |a RWTH Aachen
|0 I:(DE-588b)36225-6
|k RWTH
|b 0
|6 P:(DE-HGF)0
910 1 _ |a RWTH Aachen
|0 I:(DE-588b)36225-6
|k RWTH
|b 1
|6 P:(DE-HGF)0
910 1 _ |a RWTH Aachen
|0 I:(DE-588b)36225-6
|k RWTH
|b 2
|6 P:(DE-HGF)0
910 1 _ |a RWTH Aachen
|0 I:(DE-588b)36225-6
|k RWTH
|b 3
|6 P:(DE-HGF)0
910 1 _ |a RWTH Aachen
|0 I:(DE-588b)36225-6
|k RWTH
|b 4
|6 P:(DE-HGF)0
910 1 _ |a RWTH Aachen
|0 I:(DE-588b)36225-6
|k RWTH
|b 5
|6 P:(DE-HGF)0
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 6
|6 P:(DE-Juel1)172023
910 1 _ |a RWTH Aachen
|0 I:(DE-588b)36225-6
|k RWTH
|b 6
|6 P:(DE-Juel1)172023
913 1 _ |a DE-HGF
|b Programmungebundene Forschung
|l ohne Programm
|1 G:(DE-HGF)POF3-890
|0 G:(DE-HGF)POF3-899
|2 G:(DE-HGF)POF3-800
|v ohne Topic
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
914 1 _ |y 2020
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2020-01-14
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2020-01-14
915 _ _ |a WoS
|0 StatID:(DE-HGF)0110
|2 StatID
|b Science Citation Index
|d 2020-01-14
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2020-01-14
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
|d 2020-01-14
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2020-01-14
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1160
|2 StatID
|b Current Contents - Engineering, Computing and Technology
|d 2020-01-14
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b COMPUT CHEM ENG : 2018
|d 2020-01-14
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2020-01-14
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2020-01-14
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2020-01-14
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2020-01-14
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)IEK-10-20170217
|k IEK-10
|l Modellierung von Energiesystemen
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)IEK-10-20170217
980 _ _ |a UNRESTRICTED
981 _ _ |a I:(DE-Juel1)ICE-1-20170217


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21