Handling of long-term storage in multi-horizon stochastic programs
Michal Kaut ()
Additional contact information
Michal Kaut: SINTEF
Computational Management Science, 2024, vol. 21, issue 1, No 27, 26 pages
Abstract:
Abstract This paper introduces a method for incorporating long-term storage into the multi-horizon modelling paradigm, thereby expanding the scope of problems that this approach can address. The implementation presented here is based on the HyOpt optimization model, but the underlying concepts are designed to be adaptable to other models that utilize the multi-horizon approach. We demonstrate the effects of several formulations on a case study that explores the electrification of an offshore installation using wind turbines and a hydrogen-based energy storage system. The findings suggest that the formulations offer a realistic modelling of storage capacity, without compromising the advantages of the multi-horizon approach.
Keywords: Stochastic programming; Multi-horizon; Modelling (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://link.springer.com/10.1007/s10287-024-00508-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:comgts:v:21:y:2024:i:1:d:10.1007_s10287-024-00508-z
Ordering information: This journal article can be ordered from
http://www.springer. ... ch/journal/10287/PS2
DOI: 10.1007/s10287-024-00508-z
Access Statistics for this article
Computational Management Science is currently edited by Ruediger Schultz
More articles in Computational Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().