Layout Optimisation of Wave Energy Converter Arrays

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ID: 116438
2017
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Abstract
This paper proposes an optimisation strategy for the layout design of wave energy converter (WEC) arrays. Optimal layouts are sought so as to maximise the absorbed power given a minimum q-factor, the minimum distance between WECs, and an area of deployment. To guarantee an efficient optimisation, a four-parameter layout description is proposed. Three different optimisation algorithms are further compared in terms of performance and computational cost. These are the covariance matrix adaptation evolution strategy (CMA), a genetic algorithm (GA) and the glowworm swarm optimisation (GSO) algorithm. The results show slightly higher performances for the latter two algorithms; however, the first turns out to be significantly less computationally demanding.
Reference Key
kofoed2017energieslayout Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Pau Mercadé Ruiz,Vincenzo Nava,Mathew B. R. Topper,Pablo Ruiz-Minguela,Francesco Ferri,Jens Peter Kofoed;Pau Mercadé Ruiz;Vincenzo Nava;Mathew B. R. Topper;Pablo Ruiz-Minguela;Francesco Ferri;Jens Peter Kofoed;
Journal energies
Year 2017
DOI
10.3390/en10091262
URL
https://sciprofiles.com/publication/view/7bacb348de9debbeabe88c92ec02841e
Keywords
swarm intelligence wave energy arrays array layout optimisation evolution strategy

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