Advanced Energy Management: Digitalization and AI for the Internet of Energy explores recent advancements in distributed renewable systems, advanced controls, and energy management of nonlinear energy behaviors. The book addresses energy resilience amid extreme climates and events, presenting new applications for energy-efficient, low-carbon, and reliable cities. It details the role of AI in renewable energy systems, including power dispatch, fast response, dynamic aging, and techno-economic performance. This introduction provides a comprehensive overview of AI applications in renewable energy systems. The book delves into the interconnection between climate change and multi-energy systems, big data's role in sustainable energy supply, and much more.

It also covers demand-side management, grid-response controls in Integrated Energy Management Systems (IEMSs), and Energy Management Systems (EMSs) in integrated energy systems and power grids with AI. Additionally, the book reviews peer-to-peer and blockchain-based energy sharing, dynamic pricing, decision-making in distributed energy markets, city-scale energy resilience, and robustness with distributed energy systems. Ethical, regulatory, and policy considerations of AI in energy management and detailed Sustainability and Environmental Impact Analyses are discussed.