Layout Optimisation of Wave Energy Converter Arrays
AbstractThis 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. View Full-Text
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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.
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 Style
Ruiz, 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.