Artificial Intelligence-based Renewable Energy Systems: Standards, Communication Systems, and Data Networks provides a comprehensive guide to integrating AI into renewable energy systems, addressing both fundamental principles and practical applications. Sections explore the evolution of AI in energy-efficient systems, advanced applications, architectural frameworks, standards, and distributed renewable energy networks while also delving into data communication systems, including networking protocols, advanced learning techniques, blockchain applications, big data analytics, green communication solutions, cybersecurity, and privacy challenges. Combining theoretical foundations with practical insights, this book offers students, researchers, and engineers a holistic perspective on AI communication and data networks for renewable energy systems.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. i 4. Table of Contents - p. iii 5. Series Volumes - p. ii 6. Copyright - p. iv 7. Contributors - p. xiii 8. About the editor - p. xv 9. About the series - p. xvii 10. About the series editors - p. xix 11. Part I. Artificial intelligence evolution in energy efficient systems and its fundamental concepts - p. P1 12. Chapter 1. Artificial intelligence-based energy efficiency solutions: A new paradigm of connected networks - p. 3 13. Chapter 2. Advanced AI applications in renewable energy systems - p. 23 14. Chapter 3. Architectural frameworks for AI in renewable energy systems - p. 45 15. Chapter 4. Standards and policies for AI in renewable energy systems - p. 71 16. Chapter 5. Distributed renewable energy networks in the AI era - p. 93 17. Part II. Data communication systems for AI in renewable energy systems - p. P2 18. Chapter 6. Networking and protocols for AI renewable energy networks - p. 117 19. Chapter 7. Advanced learning techniques for AI in renewable energy - p. 137 20. Chapter 8. Blockchain applications in AI renewable energy systems - p. 169 21. Chapter 9. Big data analytics for AI renewable energy networks - p. 193 22. Chapter 10. Green communication solutions for AI renewable energy networks - p. 221 23. Chapter 11. Cybersecurity in AI-based renewable energy networks - p. 235 24. Chapter 12. Privacy and trust challenges in AI renewable energy systems - p. 261 25. Index - p. 281
Artificial Intelligence-based Renewable Energy Systems: Standards, Communication Systems, and Data Networks provides a comprehensive guide to integrating AI into renewable energy systems, addressing both fundamental principles and practical applications. Sections explore the evolution of AI in energy-efficient systems, advanced applications, architectural frameworks, standards, and distributed renewable energy networks while also delving into data communication systems, including networking protocols, advanced learning techniques, blockchain applications, big data analytics, green communication solutions, cybersecurity, and privacy challenges. Combining theoretical foundations with practical insights, this book offers students, researchers, and engineers a holistic perspective on AI communication and data networks for renewable energy systems.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. i 4. Table of Contents - p. iii 5. Series Volumes - p. ii 6. Copyright - p. iv 7. Contributors - p. xiii 8. About the editor - p. xv 9. About the series - p. xvii 10. About the series editors - p. xix 11. Part I. Artificial intelligence evolution in energy efficient systems and its fundamental concepts - p. P1 12. Chapter 1. Artificial intelligence-based energy efficiency solutions: A new paradigm of connected networks - p. 3 13. Chapter 2. Advanced AI applications in renewable energy systems - p. 23 14. Chapter 3. Architectural frameworks for AI in renewable energy systems - p. 45 15. Chapter 4. Standards and policies for AI in renewable energy systems - p. 71 16. Chapter 5. Distributed renewable energy networks in the AI era - p. 93 17. Part II. Data communication systems for AI in renewable energy systems - p. P2 18. Chapter 6. Networking and protocols for AI renewable energy networks - p. 117 19. Chapter 7. Advanced learning techniques for AI in renewable energy - p. 137 20. Chapter 8. Blockchain applications in AI renewable energy systems - p. 169 21. Chapter 9. Big data analytics for AI renewable energy networks - p. 193 22. Chapter 10. Green communication solutions for AI renewable energy networks - p. 221 23. Chapter 11. Cybersecurity in AI-based renewable energy networks - p. 235 24. Chapter 12. Privacy and trust challenges in AI renewable energy systems - p. 261 25. Index - p. 281
