Elsevier Advanced Analytics for Reliability and Resilience of Energy System

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 Provides a foundation with 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