Budget-cut: introduction to a budget based cutting-plane algorithm for capacity expansion models
Budget-cut: introduction to a budget based cutting-plane algorithm for capacity expansion models
We present an algorithm to solve capacity extension problems that frequently occur in energy system optimization models. Such models describe a system where certain components can be installed to reduce future costs and achieve carbon reduction goals; however, the choice of these components requires the solution of a computationally expensive combinatorial problem. In our proposed algorithm, we solve a sequence of linear programs that serve to tighten a budget—the maximum amount we are willing to spend towards reducing overall costs. Our proposal finds application in the general setting where optional investment decisions provide an enhanced portfolio over the original setting that maintains feasibility. We present computational results on two model classes, and demonstrate computational savings up to 96% on certain instances.
1373-1391
Singh, Bismark
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Rehberg, Oliver
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Groß, Theresa
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Hoffmann, Maximilian
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Kotzur, Leander
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Stolten, Detlef
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June 2022
Singh, Bismark
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Rehberg, Oliver
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Groß, Theresa
862f262a-b2b0-4923-93f7-237b2977bb05
Hoffmann, Maximilian
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Kotzur, Leander
85ff7749-b85f-423f-815f-41ca2680c449
Stolten, Detlef
80f18944-f5fe-406d-afb9-982c2044db23
Singh, Bismark, Rehberg, Oliver, Groß, Theresa, Hoffmann, Maximilian, Kotzur, Leander and Stolten, Detlef
(2022)
Budget-cut: introduction to a budget based cutting-plane algorithm for capacity expansion models.
Optimization Letters, 16 (5), .
(doi:10.1007/s11590-021-01826-w).
Abstract
We present an algorithm to solve capacity extension problems that frequently occur in energy system optimization models. Such models describe a system where certain components can be installed to reduce future costs and achieve carbon reduction goals; however, the choice of these components requires the solution of a computationally expensive combinatorial problem. In our proposed algorithm, we solve a sequence of linear programs that serve to tighten a budget—the maximum amount we are willing to spend towards reducing overall costs. Our proposal finds application in the general setting where optional investment decisions provide an enhanced portfolio over the original setting that maintains feasibility. We present computational results on two model classes, and demonstrate computational savings up to 96% on certain instances.
Text
s11590-021-01826-w
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More information
Accepted/In Press date: 3 November 2021
e-pub ahead of print date: 29 November 2021
Published date: June 2022
Additional Information:
Funding Information:
We are grateful to Dane Lacey for the modification of the district scenario that we present in Online Appendix A.3. The authors acknowledge the financial support by the Federal Ministry for Economic Affairs and Energy of Germany in the project METIS (project number 03ET4064).
Identifiers
Local EPrints ID: 472743
URI: http://eprints.soton.ac.uk/id/eprint/472743
ISSN: 1862-4472
PURE UUID: 43cfebcd-6dc9-4dd1-81dd-fc2179c49ae3
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Date deposited: 16 Dec 2022 17:35
Last modified: 18 Mar 2024 04:08
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Contributors
Author:
Bismark Singh
Author:
Oliver Rehberg
Author:
Theresa Groß
Author:
Maximilian Hoffmann
Author:
Leander Kotzur
Author:
Detlef Stolten
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