Advanced Computational and Mathematical Techniques for Wave Energy Converter Systems

This book provides an in-depth examination of the advanced computational and mathematical techniques crucial for the development and optimization of Wave Energy Converter (WEC) systems. As global warming and climate change continue to impact ocean engineering, the need for sustainable and renewable energy sources becomes increasingly urgent. Wave energy, with its vast and largely untapped potential, stands out as a key player in clean power generation. This volume serves as a focal point in marine renewable energies, aligning with the Sustainable Development Goals (SDG-14).

The chapters in this book cover a wide array of topics, showcasing the multifaceted applications of computation and hydrodynamic simulation in ocean engineering. Key concepts include the use of multi-criteria decision-making (MCDM) techniques combined with fuzzy logic theory for optimizing ocean wave energy. The book also presents a systematic assessment of WECs using spherical fuzzy multi-criteria group decision-making techniques. Readers will gain insights into the latest advancements in Computational Fluid Dynamics (CFD) and multi-objective optimization algorithms, which are essential for enhancing wave energy harvesting efficiency. Furthermore, the integration of Artificial Intelligence (AI) for predictive maintenance and fault diagnosis in hybrid solar-wind microgrid systems is thoroughly explored.

This book is designed for researchers, engineers, and practitioners in the fields of marine renewable energies and ocean engineering. It offers cutting-edge insights into the computational and optimization strategies necessary for advancing sustainable maritime transportation and achieving the Sustainable Development Goals (SDG-14). Whether you are a seasoned professional or a newcomer to the field, this book provides the knowledge and tools needed to harness the power of wave energy and contribute to a sustainable future.

Provides advanced mathematics with practical engineering techniques for Wave Energy Converters Including interdisciplinary insights from oceanography, mathematics, and engineering Supporting SDG 14: Life Below Water through marine renewable energies

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Klappentext

This book offers a comprehensive exploration of the advanced computational and mathematical techniques essential for optimizing Wave Energy Converter (WEC) systems. As the demand for sustainable and renewable energy sources intensifies, wave energy emerges as a promising solution with vast untapped potential. This volume serves as a crucial resource for understanding the hydrodynamics, control methods, and numerical modeling necessary to design and enhance WEC systems effectively.

The chapters delve into diverse topics, including the application of multi-criteria decision-making (MCDM) techniques and fuzzy logic theory for optimizing ocean wave energy. Readers will discover how spherical fuzzy multi-criteria group decision-making techniques are employed. The book also highlights advancements in Computational Fluid Dynamics (CFD) and multi-objective optimization algorithms, which are pivotal in improving wave energy harvesting efficiency. Additionally, the integration of Artificial Intelligence (AI) for predictive maintenance and fault diagnosis in hybrid solar-wind microgrid systems is explored.

This book is invaluable for researchers, engineers, and practitioners in marine renewable energies and ocean engineering. It provides cutting-edge insights into the computational and optimization strategies necessary for advancing sustainable maritime transportation and achieving the Sustainable Development Goals (SDG-14).

Inhalt

Fuzzy Multi-Criteria Decision-Making for Oscillating Water Column Optimization.- Assessment of the Functions for Converting Wave to Energy using Spherical Fuzzy Multi-Criteria Group Decision-Making Technique.- AI-Driven Predictive Maintenance and Fault Diagnosis in Hybrid Solar-Wind Microgrids Using Edge Computing for Rural Electrification._ Renewable Energy Sources: An Insight from Geothermal and Wave Energy Converter Systems.- Integration of Artificial Intelligence in Renewable Energy.- Advancing Energy Systems with CFD from Renewable Technologies to Nuclear Reactor Safety.- Multi-Objective Optimization Algorithms for Wave Energy Harvesting Efficiency.- The evolution of Computational Fluid Dynamics (CFD) simulation models on Wave Energy Converter (WEC).- Computational Study on Singularly Perturbed 1D Transport Equations with Space Delay Argument.- Control Strategies for Wave Energy Converter System.- AI-Powered Grid Optimization for Renewable Energy Integration.- Hydrogen Energy Generation for Sustainable Future Technologies.- Artificial Intelligence and Computational Mechanics in Wave Energy Converter Systems.- Tethering Artificial Intelligence for Enhancing Renewable Energy: Innovations and Challenges.