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In Artificial Intelligence Empowered Smart Energy Systems, the editors along with a team of distinguished researchers deliver an original and comprehensive discussion of artificial intelligence enabled smart energy systems. The book offers a deep dive into AI’s integration with energy, examining critical topics like renewable energy forecasting, load monitoring, fault diagnosis, resilience-oriented optimization, and efficiency-driven control.
The contributors discuss the real-world applications of AI in smart energy systems, showing you AI’s transformative effects on energy landscapes. It provides practical solutions and strategies to address complicated problems in energy systems.
The book also includes:
- A thorough introduction to cybersecurity, privacy, and virtual power plants
- Comprehensive demonstrations of the effective leveraging of AI technologies in energy systems
- Practical discussions of the potential of AI to create sustainable, efficient, and resilient energy systems
- Detailed case studies and real-world examples of AI’s implementation in smart energy systems
Perfect for researchers, data scientists, and policymakers, Artificial Intelligence Empowered Smart Energy Systems will also benefit graduate and senior undergraduate students in both the tech and energy industries.
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Qiang Yang, PhD, is a Full Professor at the College of Electrical Engineering at Zhejiang University, China. He is a Senior Member of the IEEE and a Distinguished Member of the China Computer Federation. His primary research interests include smart energy systems, learning-based optimization and control.
Gang Huang, PhD, is an Assistant Professor at the College of Electrical Engineering at Zhejiang University, China. He is a Senior Member of the IEEE and a Senior Member of the China Computer Federation. His primary research interests include artificial intelligence for power and energy systems.
