Fast and effective optimisation of arrays of submerged wave energy converters

Junhua Wu, Slava Shekh, Nataliia Y. Sergiienko, Benjamin S. Cazzolato, Boyin Dingt, Frank Neumann, Markus Wagner

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

35 Citations (Scopus)

Abstract

Renewable forms of energy are becoming increasingly important to consider, as the global energy demand continues to grow. Wave energy is one of these widely available forms, but it is largely unexploited. A common design for a wave energy converter is called a point absorber or buoy. The buoy typically floats on the surface or just below the surface of the water, and captures energy from the movement of the waves. It can use the motion of the waves to drive a pump to generate electricity and to create potable water. Since a single buoy can only capture a limited amount of energy, large-scale wave energy production necessitates the deployment of buoys in large numbers called arrays. However, the efficiency of arrays of buoys is affected by highly complex intra-buoy interactions. The contributions of this article are two-fold. First, we present an approximation of the buoy interactions model that results in a 350-fold computational speed-up to enable the use inside of iterative optimisation algorithms, Second, we study arrays of fully submerged three-tether buoys, with and without shared mooring points.

Original languageEnglish
Title of host publicationProceedings of the 2016 Genetic and Evolutionary Computation Conference
EditorsFrank Neumann
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages1045-1052
Number of pages8
ISBN (Electronic)9781450342063
DOIs
Publication statusPublished - 2016
Externally publishedYes
EventThe Genetic and Evolutionary Computation Conference 2016 - Hyatt Regency Denver Tech Center, Denver, United States of America
Duration: 20 Jul 201624 Jul 2016
Conference number: 18th
http://gecco-2016.sigevo.org/index.html/
https://dl.acm.org/doi/proceedings/10.1145/2908812 (Proceedings)

Conference

ConferenceThe Genetic and Evolutionary Computation Conference 2016
Abbreviated titleGECCO 2016
Country/TerritoryUnited States of America
CityDenver
Period20/07/1624/07/16
Internet address

Keywords

  • Evolutionary algorithm
  • Renewable energy
  • Wave energy

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