TY  - CONF
AU  - Baumgärtner, Nils
AU  - Shu, David Yang
AU  - Bahl, Björn
AU  - Hennen, Maike
AU  - Bardow, André
TI  - From peak power prices to seasonal storage: Long-term operational optimization of energy systems by time-series decomposition
VL  - 46
CY  - Amsterdam [u.a.]
PB  - Elsevier
M1  - FZJ-2020-02339
T2  - Computer Aided Chemical Engineering
SP  - 703 - 708
PY  - 2019
AB  - 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.
T2  - 29th European Symposium on Computer Aided Process Engineering
CY  - 16 Jun 2019 - 19 Jun 2019, Eindhoven (The Netherlands)
Y2  - 16 Jun 2019 - 19 Jun 2019
M2  - Eindhoven, The Netherlands
LB  - PUB:(DE-HGF)8 ; PUB:(DE-HGF)7
UR  - <Go to ISI:>//WOS:000495447200118
DO  - DOI:10.1016/B978-0-12-818634-3.50118-1
UR  - https://juser.fz-juelich.de/record/877624
ER  -