Layout Optimisation of Wave Energy Converter Arrays
1
Department of Civil Engineering, Aalborg University, Thomas Manns Vej 23, 9220 Aalborg, Denmark
2
Tecnalia Research and Innovation, Energy and Environmental Division, Parque Tecnologico de Bizkaia, 48160 Derio, Spain
3
Basque Centre for Applied Mathematics BCAM, 48009 Bilbao, Spain
4
Institute for Energy Systems, The University of Edinburgh, Edinburgh EH9 3DW, Scotland, UK
*
Author to whom correspondence should be addressed.
Energies 2017, 10(9), 1262; https://doi.org/10.3390/en10091262
Received: 19 July 2017 / Revised: 3 August 2017 / Accepted: 22 August 2017 / Published: 24 August 2017
(This article belongs to the Special Issue Marine Energy)
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.
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MDPI and ACS Style
Ruiz, P.M.; Nava, V.; Topper, M.B.R.; Minguela, P.R.; Ferri, F.; Kofoed, J.P. Layout Optimisation of Wave Energy Converter Arrays. Energies 2017, 10, 1262.
AMA Style
Ruiz PM, Nava V, Topper MBR, Minguela PR, Ferri F, Kofoed JP. Layout Optimisation of Wave Energy Converter Arrays. Energies. 2017; 10(9):1262.
Chicago/Turabian StyleRuiz, Pau M.; Nava, Vincenzo; Topper, Mathew B.R.; Minguela, Pablo R.; Ferri, Francesco; Kofoed, Jens P. 2017. "Layout Optimisation of Wave Energy Converter Arrays" Energies 10, no. 9: 1262.
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