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000889896 1001_ $$0P:(DE-HGF)0$$aBaumgärtner, Nils$$b0
000889896 245__ $$aDeLoop: Decomposition-based Long-term operational optimization of energy systems with time-coupling constraints
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000889896 520__ $$aLong-term operational optimization of energy systems results in challenging, large-scale problems. These large-scale problems can be directly decomposed into smaller subproblems, in the absence of time-coupling constraints and variables. However, time-coupling is common in energy systems, e. g. due to (seasonal) energy storage and peak-power prices. To solve time-coupled long-term operational optimization problems, we propose the method DeLoop for the Decomposition-based Long-term operational optimization of energy systems with time-coupling. DeLoop calculates feasible solutions (upper bounds) by decomposing the operational optimization problem into smaller subproblems. The solutions of these subproblems are recombined to obtain a feasible solution for the original long-term problem. To evaluate the quality of the feasible solutions, DeLoop computes lower bounds by linear programming relaxation. DeLoop iteratively decreases the number of subproblems and employs the Branch-and-Cut procedure to tighten the bounds. In a case study of an energy system, DeLoop converges fast, outperforming a commercial state-of-the-art solver by a factor of 32.
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000889896 7001_ $$0P:(DE-Juel1)176240$$aShu, David Yang$$b1
000889896 7001_ $$0P:(DE-HGF)0$$aBahl, Björn$$b2
000889896 7001_ $$0P:(DE-HGF)0$$aHennen, Maike$$b3
000889896 7001_ $$0P:(DE-HGF)0$$aHollermann, Dinah Elena$$b4
000889896 7001_ $$0P:(DE-Juel1)172023$$aBardow, André$$b5$$eCorresponding author$$ufzj
000889896 773__ $$0PERI:(DE-600)2019804-8$$a10.1016/j.energy.2020.117272$$gVol. 198, p. 117272 -$$p117272 -$$tEnergy$$v198$$x0360-5442$$y2020
000889896 8564_ $$uhttps://juser.fz-juelich.de/record/889896/files/DeLoop_Revised%2013%20January%202020.pdf$$yPublished on 2020-03-03. Available in OpenAccess from 2022-03-03.
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