001     1054234
005     20260211065243.0
024 7 _ |a 10.1016/j.compchemeng.2026.109591
|2 doi
024 7 _ |a 0098-1354
|2 ISSN
024 7 _ |a 1873-4375
|2 ISSN
037 _ _ |a FZJ-2026-01751
082 _ _ |a 660
100 1 _ |a Glücker, Philipp
|0 P:(DE-Juel1)187346
|b 0
|e Corresponding author
245 _ _ |a Unlocking reactive power potential of industrial processes for voltage support through scheduling optimization
260 _ _ |a Amsterdam [u.a.]
|c 2026
|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 1770746394_5904
|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 Demand response of industrial processes generally accounts for active power, but not reactive power which grows in importance for balancing local voltage levels in future electricity grids. We present an optimization-based approach to integrate reactive power into demand response scheduling and derive first estimates on the arising potentials. To this end, we extend a resource-task network scheduling model to account for the reactive power of electrically-powered process tasks, local power converters, and the local power grid. As an illustrative example, we study the multi-step copper production. We find a large achievable range of reactive power provision without compromising production volume or operating cost. Furthermore, we demonstrate how reactive power could be provided as an ancillary service by following a signal. Our results show that penalties or additional investment in compensation devices for power factor correction can be avoided through reactive power control of local power converters. Moreover, we demonstrate that industrial processes with sufficient capacity can alleviate voltage problems in transmission grids. Our work therefore lays the groundwork towards determining the reactive power scheduling potential of power-intensive production processes, and showcases its potential support for the voltage stability of future power grids.
536 _ _ |a 1121 - Digitalization and Systems Technology for Flexibility Solutions (POF4-112)
|0 G:(DE-HGF)POF4-1121
|c POF4-112
|f POF IV
|x 0
536 _ _ |a 1122 - Design, Operation and Digitalization of the Future Energy Grids (POF4-112)
|0 G:(DE-HGF)POF4-1122
|c POF4-112
|f POF IV
|x 1
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Germscheid, Sonja H. M.
|0 P:(DE-Juel1)180409
|b 1
700 1 _ |a Ojeda, Ariana
|0 P:(DE-Juel1)190183
|b 2
|u fzj
700 1 _ |a Benigni, Andrea
|0 P:(DE-Juel1)179029
|b 3
|u fzj
700 1 _ |a Dahmen, Manuel
|0 P:(DE-Juel1)172097
|b 4
700 1 _ |a Pesch, Thiemo
|0 P:(DE-Juel1)142000
|b 5
773 _ _ |a 10.1016/j.compchemeng.2026.109591
|g p. 109591 -
|0 PERI:(DE-600)1499971-7
|p 109591
|t Computers & chemical engineering
|v -
|y 2026
|x 0098-1354
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)187346
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)190183
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)179029
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 4
|6 P:(DE-Juel1)172097
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 5
|6 P:(DE-Juel1)142000
913 1 _ |a DE-HGF
|b Forschungsbereich Energie
|l Energiesystemdesign (ESD)
|1 G:(DE-HGF)POF4-110
|0 G:(DE-HGF)POF4-112
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-100
|4 G:(DE-HGF)POF
|v Digitalisierung und Systemtechnik
|9 G:(DE-HGF)POF4-1121
|x 0
913 1 _ |a DE-HGF
|b Forschungsbereich Energie
|l Energiesystemdesign (ESD)
|1 G:(DE-HGF)POF4-110
|0 G:(DE-HGF)POF4-112
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-100
|4 G:(DE-HGF)POF
|v Digitalisierung und Systemtechnik
|9 G:(DE-HGF)POF4-1122
|x 1
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2025-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2025-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1160
|2 StatID
|b Current Contents - Engineering, Computing and Technology
|d 2025-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2025-11-12
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2025-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2025-11-12
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b COMPUT CHEM ENG : 2022
|d 2025-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2025-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2025-11-12
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2025-11-12
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2025-11-12
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)ICE-1-20170217
|k ICE-1
|l Modellierung von Energiesystemen
|x 0
980 _ _ |a journal
980 _ _ |a EDITORS
980 _ _ |a VDBINPRINT
980 _ _ |a I:(DE-Juel1)ICE-1-20170217
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21