Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/287163 
Year of Publication: 
2021
Citation: 
[Journal:] Optimization Letters [ISSN:] 1862-4480 [Volume:] 16 [Issue:] 5 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2021 [Pages:] 1373-1391
Publisher: 
Springer, Berlin, Heidelberg
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.
Subjects: 
Optimization
Operations Research/Decision Theory
Computational Intelligence
Numerical and Computational Physics, Simulation
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.