000877624 001__ 877624
000877624 005__ 20240709081916.0
000877624 0247_ $$2doi$$a10.1016/B978-0-12-818634-3.50118-1
000877624 0247_ $$2ISSN$$a1570-7946
000877624 0247_ $$2ISSN$$a2543-1331
000877624 0247_ $$2WOS$$aWOS:000495447200118
000877624 037__ $$aFZJ-2020-02339
000877624 082__ $$a660
000877624 1001_ $$0P:(DE-HGF)0$$aBaumgärtner, Nils$$b0
000877624 1112_ $$a29th European Symposium on Computer Aided Process Engineering$$cEindhoven$$d2019-06-16 - 2019-06-19$$wThe Netherlands
000877624 245__ $$aFrom peak power prices to seasonal storage: Long-term operational optimization of energy systems by time-series decomposition
000877624 260__ $$aAmsterdam [u.a.]$$bElsevier$$c2019
000877624 300__ $$a703 - 708
000877624 3367_ $$2ORCID$$aCONFERENCE_PAPER
000877624 3367_ $$033$$2EndNote$$aConference Paper
000877624 3367_ $$2BibTeX$$aINPROCEEDINGS
000877624 3367_ $$2DRIVER$$aconferenceObject
000877624 3367_ $$2DataCite$$aOutput Types/Conference Paper
000877624 3367_ $$0PUB:(DE-HGF)8$$2PUB:(DE-HGF)$$aContribution to a conference proceedings$$bcontrib$$mcontrib$$s1592766538_26608
000877624 3367_ $$0PUB:(DE-HGF)7$$2PUB:(DE-HGF)$$aContribution to a book$$mcontb
000877624 4900_ $$aComputer Aided Chemical Engineering$$v46
000877624 520__ $$aLong-term operation of energy systems is a complex optimization task. Often, such long-term operational optimizations are solved by direct decomposing the problem into smaller subproblems. However, direct decomposition is not possible for problems with time-coupling constraints and variables. Such time-coupling is common in energy systems, e.g., due to peak power prices and (seasonal) energy storage. To efficiently solve coupled long-term operational optimization problems, we propose a time-series decomposition method. The proposed method calculates lower and upper bounds to obtain a feasible solution of the original problem with known quality. We compute lower bounds by the Branch-and-Cut algorithm. For the upper bound, we decompose complicating constraints and variables into smaller subproblems. The solution of these subproblems are recombined to obtain a feasible solution for the long-term operational optimization. To tighten the upper bound, we iteratively decrease the number of subproblems. In a case study for an industrial energy system, we show that the proposed time-series decomposition method converges fast, outperforming a commercial state-of-the-art solver.
000877624 536__ $$0G:(DE-HGF)POF3-153$$a153 - Assessment of Energy Systems – Addressing Issues of Energy Efficiency and Energy Security (POF3-153)$$cPOF3-153$$fPOF III$$x0
000877624 588__ $$aDataset connected to CrossRef Book Series
000877624 7001_ $$0P:(DE-Juel1)176240$$aShu, David Yang$$b1$$ufzj
000877624 7001_ $$0P:(DE-HGF)0$$aBahl, Björn$$b2
000877624 7001_ $$0P:(DE-HGF)0$$aHennen, Maike$$b3
000877624 7001_ $$0P:(DE-Juel1)172023$$aBardow, André$$b4$$eCorresponding author$$ufzj
000877624 773__ $$a10.1016/B978-0-12-818634-3.50118-1
000877624 909CO $$ooai:juser.fz-juelich.de:877624$$pVDB
000877624 9101_ $$0I:(DE-588b)36225-6$$6P:(DE-HGF)0$$aRWTH Aachen$$b0$$kRWTH
000877624 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)176240$$aForschungszentrum Jülich$$b1$$kFZJ
000877624 9101_ $$0I:(DE-588b)36225-6$$6P:(DE-HGF)0$$aRWTH Aachen$$b2$$kRWTH
000877624 9101_ $$0I:(DE-588b)36225-6$$6P:(DE-HGF)0$$aRWTH Aachen$$b3$$kRWTH
000877624 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)172023$$aForschungszentrum Jülich$$b4$$kFZJ
000877624 9101_ $$0I:(DE-588b)36225-6$$6P:(DE-Juel1)172023$$aRWTH Aachen$$b4$$kRWTH
000877624 9131_ $$0G:(DE-HGF)POF3-153$$1G:(DE-HGF)POF3-150$$2G:(DE-HGF)POF3-100$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bEnergie$$lTechnologie, Innovation und Gesellschaft$$vAssessment of Energy Systems – Addressing Issues of Energy Efficiency and Energy Security$$x0
000877624 9141_ $$y2020
000877624 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2020-01-02
000877624 920__ $$lyes
000877624 9201_ $$0I:(DE-Juel1)IEK-10-20170217$$kIEK-10$$lModellierung von Energiesystemen$$x0
000877624 980__ $$acontrib
000877624 980__ $$aVDB
000877624 980__ $$acontb
000877624 980__ $$aI:(DE-Juel1)IEK-10-20170217
000877624 980__ $$aUNRESTRICTED
000877624 981__ $$aI:(DE-Juel1)ICE-1-20170217