A Novel Hybrid Algorithm for Optimized Solutions in Ocean Renewable Energy Industry: Enhancing Power Take-Off Parameters and Site Selection Procedure of Wave Energy Converters

Ocean renewable energy, particularly wave energy, has emerged as a pivotal component for diversifying the global energy portfolio, reducing dependence on fossil fuels, and mitigating climate change impacts. This study delves into the optimization of power take-off (PTO) parameters and the site selection process for an offshore oscillating surge wave energy converter (OSWEC). However, the intrinsic dynamics of these interactions, coupled with the multi-modal nature of the optimization landscape, make this a daunting challenge. Addressing this, we introduce the novel Hill Climb - Explorative Gray Wolf Optimizer (HC-EGWO). This new methodology blends a local search method with a global optimizer, incorporating dynamic control over exploration and exploitation rates. This balance paves the way for an enhanced exploration of the solution space, ensuring the identification of superior-quality solutions. Further anchoring our approach, a feasibility landscape analysis based on linear water wave theory assumptions and the flap's maximum angular motion is conducted. This ensures the optimized OSWEC consistently operates within safety and efficiency parameters. Our findings hold significant promise for the development of more streamlined OSWEC power take-off systems. They provide insights for selecting the prime offshore site, optimizing power output, and bolstering the overall adoption of ocean renewable energy sources. Impressively, by employing the HC-EGWO method, we achieved an upswing of up to 3.31% in power output compared to other methods. This substantial increment underscores the efficacy of our proposed optimization approach. Conclusively, the outcomes offer invaluable knowledge for deploying OSWECs in the South Caspian Sea, where unique environmental conditions intersect with considerable energy potential.

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

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.

Investigating Wave Energy Potential in Southern Coasts of the Caspian Sea and Evaluating the Application of Gray Wolf Optimizer Algorithm

There is a significantly accelerating trend in the application of the wave energy converters. As a result, it is imperative to adopt a suitable point for implementing these systems. Besides, the Caspian Sea, as one of the most important marine renewable energy sources in Asia, is capable of supplying the coastal areas with a large amount of energy. Therefore, areas around nine ports in the southern coasts of the Caspian Sea were selected to measure their wave energy potential. Initially, the amount of energy on these points was measured using the irregular energy theory. A new approach was developed to compare these points and measure their fitness in supplying the maximum energy using the Grey Wolf optimizer (GWO) algorithm and time history analysis. In this method, the optimal parameters were first extracted from the algorithm for assessing the points within the southern areas of the Caspian Sea. These values were regarded as the assessment indices. Then, the fitness of each point was obtained using the correlation function and the norm vector to present the most optimal point with maximum waver energy exploitation potential. Finally, the side-by-side comparison of the parameters affecting the wave energy showed that an increase or decrease in the wave energy along the southern areas of the Caspian Sea is influenced more by the wave height than the depth on that points. Moreover, the waver energy concentration occurs in the range of Hs = 3 and $T_e$ range is between $0.75\times T_{e_{max}}$ and $0.85\times T_{e_{max}}$.