Advanced Energy Management: Digitalization and AI for the Internet of Energy presents the latest advances in the fields of distributed renewable systems, advanced controls, and energy management of nonlinear energy behaviours. The book addresses the problems of energy resilience under extreme climate and extreme events and presents new applications for energy-efficient, low-carbon and energy-reliable cities. The book explains how energy management is used in multi-energy systems for improved power dispatch, fast response, dynamic ageing, techno-economic performance. The introduction provides a comprehensive overview of artificial intelligence applications for renewable energy systems. The subsequent sections delve into various aspects, such as the interconnection between climate change and multi-energy systems, the role of big data and digitalization in sustainable energy supply, the integration of renewable energy sources, and the application of machine learning in power forecasting, demand predictions, and energy storage. Following this, the book explains demand-side management and grid-response controls in integrated energy management systems (IEMSs), and energy management systems (EMSs) in integrated energy systems and power grid with artificial intelligence. Dedicated chapters review peer-to-peer and blockchain-based energy sharing and trading, dynamic pricing and decision making in distributed energy markets, as well as city-scale energy resilience and robustness with distributed energy systems. Finally, the ethical, regulatory, and policy considerations of applying artificial intelligence in energy systems and energy management are discussed, and detailed Sustainability and Environmental Impact Analyses are presented. Advanced Energy Management: Digitalization and AI for the Internet of Energy is an invaluable reference for students, researchers, and industry professionals seeking advanced energy management strategies, and will be of interest to anyone involved in carbon neutrality solutions.

• Presents the latest developments and future trends in advanced energy management following sustainable energy supply-transmission-distribution with energy storage
• Explains the fundamentals of how AI can facilitate a low-carbon transition through sustainable energy and storage
• Includes case studies and real-world applications of advanced energy management with AI and digitalization