Overview

Advanced Analytics for Reliability and Resilience of Energy Systems prepares students, researchers, and industry engineers to design and maintain reliable, sustainable energy systems using state-of-the-art AI techniques. This 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. The AI tools presented range across forecasting, the Internet-of-Things, machine learning, digital twin technology, and big data analysis, with a variety of applications to avoid power outages, minimise disruption, and accurately assess system resilience. Including case studies and details methodology for practical techniques, Advanced Analytics for Reliability and Resilience of Energy Systems 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

Full Product Details

Author:   Fausto Pedro Garcia Marquez (Professor, Universidad De Castilla-La Mancha, Spain) ,  René Vinicio Sánchez Loja (Professor, Universidad Politécnica Salesiana, Ecuador) ,  Mayorkinos Papaelias (Reader in NDT and Condition Monitoring, School of Metallogy and Materials, University of Birmingham, UK)
Publisher:   Elsevier - Health Sciences Division
Imprint:   Elsevier - Health Sciences Division
Weight:   0.450kg
ISBN:  

9780443247224

ISBN 10:   0443247226
Pages:   300
Publication Date:   23 January 2026
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Forthcoming
Availability:   Not yet available  
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Table of Contents

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

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Author Information

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. 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. 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.

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