Use of Markov Decision Processes in the Evaluation of Corrective Maintenance Scheduling Policies for Offshore Wind Farms

Helene Seyr and Michael Muskulus
Additional contact information
Helene Seyr: Department of Civil and Environmental Engineering, Norwegian University of Science and Technology NTNU, NO-7491 Trondheim, Norway
Michael Muskulus: Department of Civil and Environmental Engineering, Norwegian University of Science and Technology NTNU, NO-7491 Trondheim, Norway

Energies, 2019, vol. 12, issue 15, 1-19

Abstract: Optimization of the maintenance policies for offshore wind parks is an important step in lowering the costs of energy production from wind. The yield from wind energy production is expected to fall, which will increase the need to be cost efficient. In this article, the Markov decision process is presented and how it can be applied to evaluate different policies for corrective maintenance planning. In the case study, we show an alternative to the current state-of-the-art policy for corrective maintenance that will achieve a cost-reduction when energy production prices drop below the current levels. The presented method can be extended and applied to evaluate additional policies, with some examples provided.

Keywords: maintenance planning; maintenance strategy; maintenance; corrective maintenance; repair; offshore wind energy; maintenance scheduling; optimization; modeling (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1996-1073/12/15/2993/pdf (application/pdf)
https://www.mdpi.com/1996-1073/12/15/2993/ (text/html)

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:gam:jeners:v:12:y:2019:i:15:p:2993-:d:254448

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().