001     917562
005     20240712112855.0
024 7 _ |a 10.48550/ARXIV.2205.14598
|2 doi
024 7 _ |a 2128/33649
|2 Handle
037 _ _ |a FZJ-2023-00764
100 1 _ |a Baader, Florian
|0 P:(DE-Juel1)176974
|b 0
245 _ _ |a Demand Response for Flat Nonlinear MIMO Processes using Dynamic Ramping Constraints
260 _ _ |c 2022
|b arXiv
336 7 _ |a Preprint
|b preprint
|m preprint
|0 PUB:(DE-HGF)25
|s 1673945959_26809
|2 PUB:(DE-HGF)
336 7 _ |a WORKING_PAPER
|2 ORCID
336 7 _ |a Electronic Article
|0 28
|2 EndNote
336 7 _ |a preprint
|2 DRIVER
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a Output Types/Working Paper
|2 DataCite
520 _ _ |a Volatile electricity prices make demand response (DR) attractive for processes that can modulate their production rate. However, if nonlinear dynamic processes must be scheduled simultaneously with their local multi-energy system, the resulting scheduling optimization problems often cannot be solved in real time. For single-input single-output processes, the problem can be simplified without sacrificing feasibility by dynamic ramping constraints that define a derivative of the production rate as the ramping degree of freedom. In this work, we extend dynamic ramping constraints to flat multi-input multi-output processes by a coordinate transformation that gives the true nonlinear ramping limits. Approximating these ramping limits by piecewise affine functions gives a mixed-integer linear formulation that guarantees feasible operation. As a case study, dynamic ramping constraints are derived for a heated reactor-separator process that is subsequently scheduled simultaneously with its multi-energy system. The dynamic ramping formulation bridges the gap between rigorous process models and simplified process representations for real-time scheduling.
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
588 _ _ |a Dataset connected to DataCite
650 _ 7 |a Optimization and Control (math.OC)
|2 Other
650 _ 7 |a FOS: Mathematics
|2 Other
700 1 _ |a Althaus, Philipp
|0 P:(DE-Juel1)180103
|b 1
|u fzj
700 1 _ |a Bardow, André
|0 P:(DE-Juel1)172023
|b 2
|u fzj
700 1 _ |a Dahmen, Manuel
|0 P:(DE-Juel1)172097
|b 3
|e Corresponding author
|u fzj
773 _ _ |a 10.48550/ARXIV.2205.14598
856 4 _ |u https://juser.fz-juelich.de/record/917562/files/2205.14598.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:917562
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)176974
910 1 _ |a RWTH Aachen
|0 I:(DE-588b)36225-6
|k RWTH
|b 0
|6 P:(DE-Juel1)176974
910 1 _ |a ETH Zürich
|0 I:(DE-HGF)0
|b 0
|6 P:(DE-Juel1)176974
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)180103
910 1 _ |a RWTH Aachen
|0 I:(DE-588b)36225-6
|k RWTH
|b 1
|6 P:(DE-Juel1)180103
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)172023
910 1 _ |a ETH Zürich
|0 I:(DE-HGF)0
|b 2
|6 P:(DE-Juel1)172023
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)172097
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
914 1 _ |y 2022
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)IEK-10-20170217
|k IEK-10
|l Modellierung von Energiesystemen
|x 0
980 1 _ |a FullTexts
980 _ _ |a preprint
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)IEK-10-20170217
981 _ _ |a I:(DE-Juel1)ICE-1-20170217


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21