{"title":"A gradient flow approach for combined layout-control design of wave energy parks","authors":"Marco Gambarini, Gabriele Ciaramella, Edie Miglio","doi":"arxiv-2409.10200","DOIUrl":null,"url":null,"abstract":"Wave energy converters (WECs) represent an innovative technology for power\ngeneration from renewable sources (marine energy). Although there has been a\ngreat deal of research into such devices in recent decades, the power output of\na single device has remained low. Therefore, installation in parks is required\nfor economic reasons. The optimal design problem for parks of WECs is\nchallenging since it requires the simultaneous optimization of positions and\ncontrol parameters. While the literature on this problem usually considers\nmetaheuristic algorithms, we present a novel numerical framework based on a\ngradient-flow formulation. This framework is capable of solving the optimal\ndesign problem for WEC parks. In particular, we use a low-order adaptive\nRunge-Kutta scheme to integrate the gradient-flow equation and introduce an\ninexact solution procedure. Here, the tolerances of the linear solver used for\nprojection on the constraint nullspace and of the time-advancing scheme are\nautomatically adapted to avoid over-solving so that the method requires minimal\ntuning. We then provide the specific details of its application to the\nconsidered WEC problem: the goal is to maximize the average power produced by a\npark, subject to hydrodynamic and dynamic governing equations and to the\nconstraints of available sea area, minimum distance between devices, and\nlimited oscillation amplitude around the undisturbed free surface elevation. A\nsuitable choice of the discrete models allows us to compute analytically the\nJacobian of the state problem's residual. Numerical tests with realistic\nparameters show that the proposed algorithm is efficient, and results of\nphysical interest are obtained.","PeriodicalId":501286,"journal":{"name":"arXiv - MATH - Optimization and Control","volume":"152 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - MATH - Optimization and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.10200","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Wave energy converters (WECs) represent an innovative technology for power
generation from renewable sources (marine energy). Although there has been a
great deal of research into such devices in recent decades, the power output of
a single device has remained low. Therefore, installation in parks is required
for economic reasons. The optimal design problem for parks of WECs is
challenging since it requires the simultaneous optimization of positions and
control parameters. While the literature on this problem usually considers
metaheuristic algorithms, we present a novel numerical framework based on a
gradient-flow formulation. This framework is capable of solving the optimal
design problem for WEC parks. In particular, we use a low-order adaptive
Runge-Kutta scheme to integrate the gradient-flow equation and introduce an
inexact solution procedure. Here, the tolerances of the linear solver used for
projection on the constraint nullspace and of the time-advancing scheme are
automatically adapted to avoid over-solving so that the method requires minimal
tuning. We then provide the specific details of its application to the
considered WEC problem: the goal is to maximize the average power produced by a
park, subject to hydrodynamic and dynamic governing equations and to the
constraints of available sea area, minimum distance between devices, and
limited oscillation amplitude around the undisturbed free surface elevation. A
suitable choice of the discrete models allows us to compute analytically the
Jacobian of the state problem's residual. Numerical tests with realistic
parameters show that the proposed algorithm is efficient, and results of
physical interest are obtained.