%0 Conference Paper
%A Baumgärtner, Nils
%A Shu, David Yang
%A Bahl, Björn
%A Hennen, Maike
%A Bardow, André
%T From peak power prices to seasonal storage: Long-term operational optimization of energy systems by time-series decomposition
%V 46
%C Amsterdam [u.a.]
%I Elsevier
%M FZJ-2020-02339
%B Computer Aided Chemical Engineering
%P 703 - 708
%D 2019
%X Long-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.
%B 29th European Symposium on Computer Aided Process Engineering
%C 16 Jun 2019 - 19 Jun 2019, Eindhoven (The Netherlands)
Y2 16 Jun 2019 - 19 Jun 2019
M2 Eindhoven, The Netherlands
%F PUB:(DE-HGF)8 ; PUB:(DE-HGF)7
%9 Contribution to a conference proceedingsContribution to a book
%U <Go to ISI:>//WOS:000495447200118
%R 10.1016/B978-0-12-818634-3.50118-1
%U https://juser.fz-juelich.de/record/877624