Layout optimisation of wave energy converter arrays
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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.
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Publisher Copyright: © 2017 by the authors. Licensee MDPI, Basel, Switzerland.
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Array layout , Evolution strategy , Optimisation , Swarm intelligence , Wave energy arrays , Renewable Energy, Sustainability and the Environment , Fuel Technology , Energy Engineering and Power Technology , Energy (miscellaneous) , Control and Optimization , Electrical and Electronic Engineering , SDG 7 - Affordable and Clean Energy
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Mercadé Ruiz , P , Nava , V , Topper , M B R , Minguela , P R , Ferri , F & Kofoed , J P 2017 , ' Layout optimisation of wave energy converter arrays ' , Energies , vol. 10 , no. 9 , 1262 . https://doi.org/10.3390/en10091262