Mayorkinos Papaelias – författare

Approx.200 pagesApprox.200 pages

Non-Destructive Testing and Condition Monitoring Techniques in Wind Energy looks at the complex and critical components of energy assets and the importance of inspection and maintenance to ensure their high availability and uninterrupted operation. Presenting the main concepts, state-of-the-art advances and case studies, this book approaches the topic by considering it as an integral part of the overall operation of any wind energy project. Linking the essential NDT subject with its sub disciplines, the book uses computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques to support analysis of prognostic problems with defined constraints and requirements.

This book is the first of its kind and will provide useful insights to industrial engineers and scientists, academics and students in the possibilities that NDT and condition monitoring technologies can offer.

Presents advances in Non-Destructive Techniques and Condition Monitoring Systems applied in the energy industry Provides case studies in Fault Detection and Diagnosis and Prognosis for critical variability Offers technical maintenance actions for the observation and analyses of inspection, monitoring, testing, diagnosis, prognosis and active maintenance actions in wind

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 transitionProvides a foundation with the fundamental principles and strategies for reliability and resilienceIntroduces the readers to a toolbox of AI methodologies with a variety of applicationsLeverages clear chapter objectives, worked problems, and detailed case studies to support real-world solution-building

Designing reliable and maintainable energy systems is crucial for ensuring efficiency, longevity, and sustainability in energy production, distribution, and consumption. Reliability focuses on minimizing failures and ensuring continuous operation under varying conditions, while maintainability emphasizes ease of inspection, repair, and upgrades. A well-designed energy system integrates robust components, predictive maintenance strategies, and advanced monitoring technologies to reduce downtime and operational costs. By prioritizing both reliability and maintainability, engineers can develop resilient energy infrastructures that support modern demands while minimizing environmental impact and lifecycle costs.Designing Reliability and Maintainability of Energy Systems is a guide to enhancing the resilience and reliability of modern energy infrastructures. Chapters present fundamental principles of reliability and resilience and new artificial intelligence applications, such as predictive maintenance, advanced analytics, and digital twin technologies for improved efficiency and sustainability in energy systems. Clear chapter objectives, worked problems, and case studies are included to demonstrate real-world applications of these technologies.This book is valuable for researchers, industry professionals, engineers, and advanced undergraduate and graduate students focused on energy grids, power system reliability, and AI-driven solutions for sustainable infrastructure.

Provides a foundation with the fundamental principles and strategies for reliability and resilienceIntroduces the readers to a toolbox of AI methodologies with a variety of applicationsLeverages clear chapter objectives, worked problems, and detailed case studies to support real-world solution-building

It also addresses the financial aspects of renewable energy projects and analyzes their profitability, covering the most relevant topics for engineers, economists, managers and scientists who are actively involved in renewable energy research and management.

It also addresses the financial aspects of renewable energy projects and analyzes their profitability, covering the most relevant topics for engineers, economists, managers and scientists who are actively involved in renewable energy research and management.