Mercadé Ruiz, PauNava, VincenzoTopper, Mathew B.R.Minguela, Pablo RuizFerri, FrancescoKofoed, Jens Peter2024-07-242024-07-242017Mercadé 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/en100912621996-1073https://hdl.handle.net/11556/3282Publisher Copyright: © 2017 by the authors. Licensee MDPI, Basel, Switzerland.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.enginfo:eu-repo/semantics/openAccessjournal article10.3390/en10091262Array layoutEvolution strategyOptimisationSwarm intelligenceWave energy arraysRenewable Energy, Sustainability and the EnvironmentFuel TechnologyEnergy Engineering and Power TechnologyEnergy (miscellaneous)Control and OptimizationElectrical and Electronic EngineeringSDG 7 - Affordable and Clean Energyhttp://www.scopus.com/inward/record.url?scp=85029370293&partnerID=8YFLogxK