Advanced Energy Management

Digitalization and AI for the Internet of Energy

AvYuekuan Zhou

Häftad, Engelska, 2026

Del i serien Advances in Intelligent Energy Systems

1 826 kr

Kommande

Beskrivning

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 behaviors. 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 multienergy systems for improved power dispatch, fast response, dynamic aging, and techno-economic performance.

This book 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

Produktinformation

Utgivningsdatum:2026-06-01
Mått:152 x 229 x undefined mm
Vikt:450 g
Format:Häftad
Språk:Engelska
Serie:Advances in Intelligent Energy Systems
Antal sidor:290
Förlag:Elsevier Science
ISBN:9780443340291

Utforska kategorier

Energiteknik inom Naturvetenskap och teknik
Artificiell intelligens inom Data och IT

Mer om författaren

Dr. Yuekuan Zhou is an Associate Proffessor at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China. His research aims at achieving smart zero-energy and zerocarbon 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 contributed to numerous publications in 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.

Innehållsförteckning

1. Introduction to Artificial Intelligence for Energy and multidisciplinary research for Carbon Neutrality Transition2. Interconnection among climate change, performance response and anti-climate change strategies of multi-energy systems3. Big data and energy digitalization for sustainable energy supply-transmission-distribution with energy storages4. Integration of Renewable Energy Sources5. Internet of Thing (IoT) technologies for internet of energy (IOE)6. Machine learning for power forecasting on renewable systems7. Machine learning for demand predictions of buildings and transportations8. Machine learning for energy storage I-thermal & electrical & hydrogen energy storages9. 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 grid12. Peer-to-peer (P2P) energy sharing and trading, dynamic pricing and decision making in distributed energy markets13. Blockchain-based power trading security and privacy protection14. City-scale energy resilience and robustness with distributed energy systems15. Ethical Considerations and Societal Impact of AI in Energy Systems16. Frontier regulatory and policy of advanced energy management for carbon neutrality transition17. Case studies and real-world applications of advanced energy management with AI and digitalization18. Sustainability and Environmental Impact Analysis19. Prospects, technical challenges, and future research directions on advanced energy management with artificial intelligence