  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.

Neural and Evolutionary Computing;Applied Physics