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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.
List of contents
1. Introduction to Artificial Intelligence for Energy and multidisciplinary research for Carbon Neutrality Transition
2. Interconnection among climate change, performance response and anti-climate change strategies of multi-energy systems
3. Big data and energy digitalization for sustainable energy supply-transmission-distribution with energy storages
4. Integration of Renewable Energy Sources
5. Internet of Thing (IoT) technologies for internet of energy (IOE)
6. Machine learning for power forecasting on renewable systems
7. Machine learning for demand predictions of buildings and transportations
8. Machine learning for energy storage I-thermal & electrical & hydrogen energy storages
9. Demand-side management and grid-response controls in Integrated energy management systems (IEMSs)
10. Energy management systems (EMSs) in integrated energy systems with artificial intelligence 11. Energy management systems (EMSs) in power grid
12. Peer-to-peer (P2P) energy sharing and trading, dynamic pricing and decision making in distributed energy markets
13. Blockchain-based power trading security and privacy protection
14. City-scale energy resilience and robustness with distributed energy systems
15. Ethical Considerations and Societal Impact of AI in Energy Systems
16. Frontier regulatory and policy of advanced energy management for carbon neutrality transition
17. Case studies and real-world applications of advanced energy management with AI and digitalization
18. Sustainability and Environmental Impact Analysis
19. Prospects, technical challenges, and future research directions on advanced energy management with artificial intelligence
About the author
Yuekuan Zhou is an Assistant Professor of Sustainable Energy and Environment at the Hong Kong University of Science and Technology (Guangzhou), China. His research aims at achieving smart zero-energy and zero-carbon district energy systems for carbon neutrality and climate change mitigation, via cleaner power production, energy-efficient system design and operation, innovation in smart energy integration, multi-objective optimization on nonlinear dynamic behaviours with artificial intelligence. Asst. Prof. Zhou has published more than 80 papers on these topics in international, peer-reviewed journals. His current research interests include latent thermal storage, electrochemical battery, hydrogen and pumped hydro storages in zero-energy buildings, life-cycle carbon-neutral buildings, peer-to-peer energy trading and inter-city energy migration energy network with a hydrogen economy.
