Development of a Genetic Algorithm Code for the Design of Cylindrical Buoyancy Bodies for Floating Offshore Wind Turbine Substructures

Victor Benifla and Frank Adam
Additional contact information
Victor Benifla: Lehrstuhl für Windenergietechnik, Universität Rostock, Albert-Einstein-Str. 2, 18059 Rostock, Germany
Frank Adam: Lehrstuhl für Windenergietechnik, Universität Rostock, Albert-Einstein-Str. 2, 18059 Rostock, Germany

Energies, 2022, vol. 15, issue 3, 1-24

Abstract: The Levelized Cost of Energy for floating offshore wind must decrease significantly to be competitive with fixed offshore wind projects or even with onshore wind projects. This study focuses on the design optimization of cylindrical buoyancy bodies for floating substructures of offshore wind turbines. The presented work is based on a previously studied buoyancy body design that allows an efficient manufacturing process and integration into different substructures. In this study, an optimization framework based on genetic algorithm is developed to parameterize the buoyancy body’s geometry and optimize its design in terms of cost, considering loads acting on the structure as well as manufacturing and floater specific dimension restrictions. The implementation of the optimization process is detailed, and tested for a given study case. Two structurally different genetic algorithms are considered in order to compare the results obtained and asses the performance of the presented optimization framework.

Keywords: floating offshore wind; buoyancy body; structural analysis; design optimization; genetic algorithm; levelized cost of energy (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: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/3/1181/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/3/1181/ (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:15:y:2022:i:3:p:1181-:d:742944

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 ().