Advanced Analytics for Reliability and Resilience of Energy System - Brossura

Brossura

ISBN 10: 0443247226 ISBN 13: 9780443247224

Casa editrice: Elsevier, 2026

Riassunto

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. The book provides a clear foundation in the fundaments 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 outrages, minimize disruption, and accurately assess system resilience.

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Informazioni sugli autori

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 numerous papers and books with international publishers of repute, and has been involved as a principal investigator in numerous international projects. 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.

Dalla quarta di copertina

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. The book provides a clear foundation in the fundaments 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 outrages, minimize disruption, and accurately assess system resilience.

Key Features:

• 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

Dettagli dell'edizione

• Editore: Elsevier
• Data di pubblicazione: 2026
• Lingua: Inglese
• ISBN 10: 0443247226
• ISBN 13: 9780443247224
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 484
• Redattore: Garcia Marquez
• Contatto del produttore: non disponibile
• Persona responsabile: LSWR Group; b.criscuolo@lswr.it; ; Via Spadolini, 7; Milano; Italia