An optimisation model for scheduling the decommissioning of an offshore wind farm

Chandra Ade Irawan (), Graham Wall and Dylan Jones
Additional contact information
Chandra Ade Irawan: University of Nottingham Ningbo China
Graham Wall: University of Portsmouth
Dylan Jones: University of Portsmouth

OR Spectrum: Quantitative Approaches in Management, 2019, vol. 41, issue 2, No 7, 513-548

Abstract: Abstract An optimisation model is proposed for scheduling the decommissioning of an offshore wind farm in order to minimise the total cost which is comprised of jack-up vessel, barge (transfer) vessel, inventory, processing and on-land transportation costs. This paper also presents a comprehensive review of the strategic issues relating to the decommissioning process and of scheduling models that have been applied to offshore wind farms. A mathematical model using integer linear programming is developed to determine the optimal schedule considering several constraints such as the availability of vessels and planning delays. As the decommissioning problem is challenging to solve, a matheuristic approach based on the hybridisation of a heuristic approach and an exact method is also proposed to find near optimal solutions for a test set of problems. A set of computational experiments has been carried out to assess the proposed approach.

Keywords: Scheduling; Offshore wind farm; Renewable energy; Matheuristic (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://link.springer.com/10.1007/s00291-019-00546-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:orspec:v:41:y:2019:i:2:d:10.1007_s00291-019-00546-z

Ordering information: This journal article can be ordered from
http://www.springer. ... research/journal/291

DOI: 10.1007/s00291-019-00546-z

Access Statistics for this article

OR Spectrum: Quantitative Approaches in Management is currently edited by Rainer Kolisch

More articles in OR Spectrum: Quantitative Approaches in Management from Springer, Gesellschaft für Operations Research e.V.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().