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Optimization in Control Systems Engineering for Renewable Energy: Harnessing Soft Computing and Optimization Models for Water-Based Renewables
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Author(s): C. V. Suresh Babu (Hindustan Institute of Technology and Science, India), Kalyan Kumar V. L. (Hindustan Institute of Technology and Science, India), Kathari Hima Kishore (Hindustan Institute of Technology and Science, India)and Doni Dhas A. (Hindustan Institute of Technology and Science, India)
Copyright: 2025
Pages: 34
Source title:
Modern SuperHyperSoft Computing Trends in Science and Technology
Source Author(s)/Editor(s): Florentin Smarandache (University of New Mexico, USA)and Priyanka Majumder (Techno College of Engineering, Agartala, India)
DOI: 10.4018/979-8-3693-6875-6.ch010
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Abstract
This study aims to explore the integration of soft computing and optimization models in enhancing the efficiency of renewable energy systems. Employing a multi-disciplinary approach, the research utilizes advanced algorithms, including genetic algorithms and artificial intelligence techniques, to optimize resource allocation and improve decision-making processes. Key findings indicate that hybrid renewable energy systems (HRES) significantly enhance energy reliability and sustainability while minimizing environmental impacts. The study concludes that the application of AI and soft computing methodologies can lead to more robust and adaptive energy management solutions, ultimately contributing to a sustainable energy future. The implications of this research highlight the necessity for continued innovation in renewable energy technologies and the importance of ethical considerations in AI deployment.
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