Journal Article FZJ-2021-00504

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DeLoop: Decomposition-based Long-term operational optimization of energy systems with time-coupling constraints

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2020
Elsevier Science Amsterdam [u.a.]

Energy 198, 117272 - () [10.1016/j.energy.2020.117272]

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Abstract: Long-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.

Classification:

Contributing Institute(s):
  1. Modellierung von Energiesystemen (IEK-10)
Research Program(s):
  1. 153 - Assessment of Energy Systems – Addressing Issues of Energy Efficiency and Energy Security (POF3-153) (POF3-153)

Appears in the scientific report 2020
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Medline ; Creative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0 ; Embargoed OpenAccess ; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 5 ; JCR ; NationallizenzNationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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Open Access

 Datensatz erzeugt am 2021-01-20, letzte Änderung am 2024-07-09


Published on 2020-03-03. Available in OpenAccess from 2022-03-03.:
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