Zhang / Song / Chen Reliable Non-Parametric Techniques for Energy System Operation and Control

Fundamentals and Applications of Constraint Learning and Safe Reinforcement Learning Methods
1. Auflage 2025
ISBN: 978-0-443-36493-8
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, 350 Seiten

Reihe: Advances in Intelligent Energy Systems

Reliable Non-Parametric Techniques for Energy System Operation and Control: Fundamentals and Applications of Constraint Learning and Safe Reinforcement Learning Methods, a new Volume in the Advances in Intelligent Energy Systems, is a comprehensive guide to modern smart methods in energy system operation and control. This book covers fundamental concepts and applications in both deterministic and uncertain environments. It addresses the challenge of accuracy in imbalanced datasets and the limitations of measurements. The book delves into advanced topics such as safe reinforcement learning for energy system control, including training-efficient intrinsic-motivated reinforcement learning, and physical layer-based control, and more. Other chapters cover barrier function-based control and CVaR-based control for systems without hard operation constraints. Designed for graduate students, researchers, and engineers, this book stands out for its practical approach to advanced methods in energy system control, enabling sustainable developments in real-world conditions. - Bridges the gap between theory and practice, providing essential insights for graduate students, researchers, and engineers - Includes visual elements, data and code, and case studies for easy understanding and implementation - Provides the latest release in the Advances in Intelligent Energy Systems series, bringing together the latest innovations in smart, sustainable energy

Hongcai Zhang is currently an Assistant Professor with the State Key Laboratory of Internet of Things for Smart City and the Department of Electrical and Computer Engineering at the University of Macau, China. Prior to this, he was a postdoctoral scholar with the University of California, USA, from 2018-2019. His current research interests include Internet of Things for smart energy, optimal operation and optimization of power and transportation systems, and grid integration of distributed energy resources. He has published over 70 JCR Q1/Q2 journal papers with 3 identified as ESI highly cited papers, and is an Associate Editor for IEEE Transactions on Power Systems and the Journal of Modern Power Systems and Clean Energy.

Autoren/Hrsg.

Zhang, Hongcai

Song, Yonghua

Chen, Ge

Yu, Peipei