Produktbild: Artificial Intelligence in Energy Systems
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Artificial Intelligence in Energy Systems

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.10.2026

Herausgeber

Zhuang Tian + weitere

Verlag

Elsevier

Seitenzahl

350

Maße (L/B)

22.9/15.2 cm

Gewicht

449 g

Sprache

Englisch

ISBN

978-0-443-44552-1

Beschreibung

Portrait

Dr. Zhuang Tian is a researcher based at Northwestern Polytechnical University, China, where he is a member of the research team working on energy system modeling, control, and energy management, covering multiple areas such as wind energy and fuel cells. Dr. Tian has published numerous articles in reputed international journals and has been involved in several book publications.

Prof. Daming Zhou is a Full Professor at Northwestern Polytechnical University, China, and a recipient of China’s National Youth Talent Program. His primary research areas include energy system modeling, control, and energy management, with over 10 years of research in wind energy, fuel cells, and other renewable energy technologies, currently as research team leader. Prof. Zhou has published more than 40 high-impact papers, with over 1,800 citations, and has authored four monographs. He holds eight patents.

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.10.2026

Herausgeber

Verlag

Elsevier

Seitenzahl

350

Maße (L/B)

22.9/15.2 cm

Gewicht

449 g

Sprache

Englisch

ISBN

978-0-443-44552-1

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Artificial Intelligence in Energy Systems
  • 1. Artificial Intelligence in Wind Energy Systems and Future Energy Ecology. Frontiers and Synergies
    2. Adaptive Control Methods of Intelligent Control Theory in Wind Energy Systems
    3. Data-Driven Intelligent Forecasting and Optimization Scheduling of Wind Energy Resources
    4. Intelligent Fault Diagnosis and Strategies for Hydrogen Energy Systems
    5. Intelligent Energy Management and Fault Prevention in Multi-Energy Complementary Microgrids
    6. Collaborative Optimization and Management Strategies in Distributed Multi-Energy Systems
    7. AI-Based Multi-Energy Grid Management and Load Control Strategies
    8. Intelligent Scheduling and Optimization Technologies in Multi-Energy Grid Systems
    9. Coordinated Scheduling and Fault Recovery Mechanisms in Dynamic Power Grids
    10. Conclusion. The Vision and Challenges of Intelligent Energy Futures