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This book delves into modeling, multi-cluster interactive dispatch, and multi-energy coordination in distributed energy grid clusters, focusing on the integrated operation and scheduling of electricity, heating, and gas systems. It introduces innovative methods such as physical information fusion, multi-energy system modeling, and cloud-edge collaborative computing. Through numerous case studies and simulations, it validates strategies like hierarchical control, rolling optimization, and real-time adjustments. The book also explores market trading strategies using game theory and competitive pricing models. It concludes with an analysis of the technological trends and challenges facing distributed energy networks, serving as a reference for researchers, engineers, and graduate students in the energy internet field.
List of contents
Overview of Distributed Energy Grid Clusters.- Modeling Techniques for the Operation of Distributed Energy grid clusters.- Distributed Energy Network Cluster Thermal Electric.
About the author
Lu Tianguang is a Professor at Shandong University, Deputy Director of Shandong Provincial Key Laboratory of Digital Intelligent Energy Innovation, Associate at Harvard University, IEEE Senior Member, and Chartered Engineer (CEng). He is mainly engaged in the research of key technologies such as intelligent sensing and operation optimization of low-carbon power systems, intelligent power distribution hierarchical regulation and control, and grid integration of renewable energy. He has published over 80 papers on different journals, including Nature Communications (Frist Author). He was a recipient of the Distinguished Young Scholar of China Frontiers of Engineering in 2023 (issued by Chinese Academy of Engineering), and the Harvard University Certificate of Distinction in Teaching in 2019. He is an Associate Editor of the IEEE Transactions on Power Delivery and the CSEE Journal of Power and Energy Systems.
Summary
This book delves into modeling, multi-cluster interactive dispatch, and multi-energy coordination in distributed energy grid clusters, focusing on the integrated operation and scheduling of electricity, heating, and gas systems. It introduces innovative methods such as physical information fusion, multi-energy system modeling, and cloud-edge collaborative computing. Through numerous case studies and simulations, it validates strategies like hierarchical control, rolling optimization, and real-time adjustments. The book also explores market trading strategies using game theory and competitive pricing models. It concludes with an analysis of the technological trends and challenges facing distributed energy networks, serving as a reference for researchers, engineers, and graduate students in the energy internet field.
