Advanced Energy Management
Digitalization and AI for the Internet of Energy
Will be published approx. on 26. June 2026
Book
Paperback/Softback
290 pages
978-0-443-34029-1 (ISBN)
Description
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.
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.
More details
Series
Language
English
Place of publication
Philadelphia
United States
Target group
Professional and scholarly
College/higher education
Dimensions
Height: 229 mm
Width: 152 mm
Weight
450 gr
ISBN-13
978-0-443-34029-1 (9780443340291)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Person
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.
Content
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
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