Optimization Study of Hydraulic Power Take-off System for an Ocean Wave Energy Converter

• URL: http://arxiv.org/abs/2112.09803v1
• Date: Fri, 17 Dec 2021 23:22:56 GMT
• Title: Optimization Study of Hydraulic Power Take-off System for an Ocean Wave Energy Converter
• Authors: Erfan Amini, Hossein Mehdipour, Emilio Faraggiana, Danial Golbaz, Sevda Mozaffari, Giovanni Bracco, Mehdi Neshat
• Abstract summary: This study aims to optimize the PTO system parameters of a pointlinear wave energy converter in the wave scenario in Perth, on Western Australian coasts. Ten optimization algorithms are incorporated to solve the non-linear problem. modified combinations of Genetic, Surrogate, and fminsearch algorithms can outperform the others in the studied wave scenario.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Ocean wave renewable energy is fast becoming a key part of renewable energy industries over the recent decades. By developing wave energy converters as the main converter technology in this process, their power take-off (PTO) systems have been investigated. Adjusting PTO parameters is a challenging optimization problem because there is a complex and nonlinear relationship between these parameters and the absorbed power output. In this regard, this study aims to optimize the PTO system parameters of a point absorber wave energy converter in the wave scenario in Perth, on Western Australian coasts. The converter is numerically designed to oscillate against irregular and multi-dimensional waves and sensitivity analysis for PTO settings is performed. Then, to find the optimal PTO system parameters which lead to the highest power output, ten optimization algorithms are incorporated to solve the non-linear problem, Including Nelder-Mead search method, Active-set method, Sequential quadratic Programming method (SQP), Multi-Verse Optimizer (MVO), and six modified combination of Genetic, Surrogate and fminsearch algorithms. After a feasibility landscape analysis, the optimization outcome is carried out and gives us the best answer in terms of PTO system settings. Finally, the investigation shows that the modified combinations of Genetic, Surrogate, and fminsearch algorithms can outperform the others in the studied wave scenario, as well as the interaction between PTO system variables.

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