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Artificial Intelligence for Reliability and Maintainability of Energy Systems
- 1st Edition - April 1, 2025
- Editors: Fausto Pedro Garcia Marquez, René Vinicio Sánchez Loja, Mayorkinos Papaelias
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 4 7 2 2 - 4
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 4 7 2 3 - 1
Artificial Intelligence for Reliability and Maintainability of Energy Systems prepares students, researchers, and industry engineers to design and maintain reliable, sustai… Read more
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Request a sales quoteArtificial Intelligence for Reliability and Maintainability of Energy Systems prepares students, researchers, and industry engineers to design and maintain reliable, sustainable energy systems using state-of-the-art AI techniques. The book provides a clear foundation in the fundamentals of power systems statistics and reliability, including resilience principles and strategies, practical applications, and real-world solutions. It covers a wide range of renewable sources, including biomass and biomethane, solar, and hybrid-renewable systems. The AI tools presented cover forecasting, the Internet-of-Things, machine learning, digital twin technology, and big data analysis, with a variety of applications to avoid power outages, minimize disruption, and accurately assess system resilience.
Including case studies and details methodology for practical techniques, this book helps energy systems engineers and researchers to provide a stable and consistent power supply in the face of climate change challenges and the energy transition.
Including case studies and details methodology for practical techniques, this book helps energy systems engineers and researchers to provide a stable and consistent power supply in the face of climate change challenges and the energy transition.
- Provides a foundation of the fundamental principles and strategies for reliability and resilience
- Introduces the readers to a toolbox of AI methodologies with a variety of applications
- Leverages clear chapter objectives, worked problems, and detailed case studies to support real-world solution-building
Researchers, industry professionals, and higher-level undergraduate/graduate students in energy grids and artificial intelligence integration
1. Intelligent energy system with climate protective visions
2. Computer vision, energy and society
3. Computer vision for human factors in energy related activities
4. Computer vision for life-cycle assessment of energy & decarbonization roadmaps
5. Computer vision safety, reliability and ethics for energy
6. Automation of science discovery related to energy materials and chemistry
7. Data-driven design of energy materials and systems
8. Data science for energy applications
9. Digital twin or big data analytics of complex energy processes/systems
10. Hybrid data-driven and physical modelling for energy related problems
11. Hardware for data collections in energy systems
12. Internet-of-things and cyber-physical energy systems
13. Intelligent control of energy systems
14. Virtual reality applied to energy and environment
15. Current State of energy systems
16. Artificial Intelligence and Machine Learning implications to energy systems
17. Weather forecasting using Artificial Intelligence
18. Intelligent Energy storage
19. Modelling and Simulation of Power Electronic Circuits
20. Control methods in Renewable energy systems
21. Role of Artificial Intelligence in Power Quality Management and Stability Analysis
22. Integration of microgrids
23. Rooftop photovoltaic systems
24. Biomass and biogas
25. Renewable energy systems and technologies education
26. Evolutionary Intelligence in Renewable energy
27. Smart Energetic Management
28. Energy efficient lighting systems
29. Scope of Artificial Intelligence based solar energy system
30. Role of Artificial Intelligence in environmental sustainability
31. Integration of Artificial Intelligence with biomethanation
32. Hybrid renewable energy system and Artificial Intelligence
33. Renewable energy and sustainable developments
2. Computer vision, energy and society
3. Computer vision for human factors in energy related activities
4. Computer vision for life-cycle assessment of energy & decarbonization roadmaps
5. Computer vision safety, reliability and ethics for energy
6. Automation of science discovery related to energy materials and chemistry
7. Data-driven design of energy materials and systems
8. Data science for energy applications
9. Digital twin or big data analytics of complex energy processes/systems
10. Hybrid data-driven and physical modelling for energy related problems
11. Hardware for data collections in energy systems
12. Internet-of-things and cyber-physical energy systems
13. Intelligent control of energy systems
14. Virtual reality applied to energy and environment
15. Current State of energy systems
16. Artificial Intelligence and Machine Learning implications to energy systems
17. Weather forecasting using Artificial Intelligence
18. Intelligent Energy storage
19. Modelling and Simulation of Power Electronic Circuits
20. Control methods in Renewable energy systems
21. Role of Artificial Intelligence in Power Quality Management and Stability Analysis
22. Integration of microgrids
23. Rooftop photovoltaic systems
24. Biomass and biogas
25. Renewable energy systems and technologies education
26. Evolutionary Intelligence in Renewable energy
27. Smart Energetic Management
28. Energy efficient lighting systems
29. Scope of Artificial Intelligence based solar energy system
30. Role of Artificial Intelligence in environmental sustainability
31. Integration of Artificial Intelligence with biomethanation
32. Hybrid renewable energy system and Artificial Intelligence
33. Renewable energy and sustainable developments
- No. of pages: 300
- Language: English
- Edition: 1
- Published: April 1, 2025
- Imprint: Elsevier
- Paperback ISBN: 9780443247224
- eBook ISBN: 9780443247231
FG
Fausto Pedro Garcia Marquez
Fausto Pedro García Márquez works as a Professor and as Director of the Ingenium Research Group at the Universidad De Castilla-La Mancha, Spain. He is an Honorary Senior Research Fellow at Birmingham University, UK, and a Lecturer at the Postgraduate European Institute. He has published more than 150 papers and 31 books (Elsevier, Springer, Pearson, McGraw-Hill, Intech, IGI, Marcombo, AlfaOmega). He has been Principal Investigator in 4 European projects, 6 national projects, and more than 150 projects for universities, companies, and other institutions. His main interests are: Artificial Intelligence, Maintenance, Management, Renewable Energy, Transport, Advanced Analytics, and Data Science.
Affiliations and expertise
Professor, Universidad De Castilla-La Mancha, SpainRL
René Vinicio Sánchez Loja
René Vinicio Sánchez Loja is a Professor at the Universidad Politécnica Salesiana, Ecuador, working mainly in areas related to the automation of sequential processes. In 2014, he founded the Research and Development Group in Industrial Technologies, and Overseas invited Ph.D. at Chongqing Technology and Business University, China. He is a senior member of IEEE. He has extensive experience in the organization of conferences, implementation of technological projects, management and execution of research projects; currently he has more than 60 publications in Web of Science. His current focus is in the areas of project management, condition-based maintenance, engineering education and industry 4.0 especially for SMEs.
Affiliations and expertise
Professor, Universidad Politécnica Salesiana, EcuadorMP
Mayorkinos Papaelias
Mayorkinos Papaelias is a Reader in NDT and Condition Monitoring in the School of Metallogy and Materials at the University of Birmingham, UK. Dr Papaelias leads the research activity in Non-Destructive Testing and Structural Health Condition Monitoring at the Birmingham Railway Centre for Research and Education and conducts research in structural health condition monitoring of wind turbine towers, and advanced condition monitoring of wind turbine gearboxes and rotating machinery. He served as a technical consultant to TWI, ENGITEC, Innovative Technology and Science Ltd, and Instituto de Soldadura e Qualidade. He is editor of two books on fault detection and condition monitoring, and has contributed chapters to books in fault detection and rail inspection. Mayorkinos is chairman of the Education Committee of the International Society for Condition Monitoring of the British Institute of Non-Destructive Testing.
Affiliations and expertise
Reader in NDT and Condition Monitoring, School of Metallogy and Materials, University of Birmingham, UK