Artificial 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.

• 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