Control and Communication for Demand Response with Thermostatically Controlled Loads

The book focuses on control and communication for demand response with thermostatically controlled loads. This is achieved by providing in-depth study on a number of major topics such as load control, optimization strategies, communication network model, resource allocation methods, system design, implementation, and performance evaluation. Two major cost modeling methods are established in detail, which are cost modeling based on Taguchi Loss Function and cost modeling based on regulation errors. The comprehensive and systematic treatment of issues in optimization strategies and resource allocation for demand response are one of the major features of the book, which is particularly suited for readers who are interested to learn solutions in control and communication. The book can benefit researchers, engineers, and graduate students in fields of control theory, automation, communication engineering and economics, etc.

Addresses control and communication for demand response in theory Provides in-depth establishment of two major cost modeling methods Studies major optimization strategies and resource allocation methods

Auteur

Kai Ma received the B. Eng. degree in Automation and Ph.D. degree in Control Science and Engineering from Yanshan University, China in 2005 and 2011, respectively. In 2011, he joined Yanshan University. From 2013 to 2014, he was a postdoctoral research fellow in Nanyang Technological University, Singapore. He is currently a professor and director of the Department of Automation, School of Electrical Engineering, Yanshan University, China. His research interests include demand response in smart grid and resource allocation in communication networks.

Pei Liu received the B. Eng. degree in Automation from the Yanching Institute of Technology, China, in 2016, and the Ph.D. degree in Control Science and Engineering from Yanshan University, China in 2022. She is currently a postdoctoral research fellow in Tsinghua University, China. Her research interests include demand response in smart grid, resource allocation in communication networks, and communication security.

Jie Yang received her B. Eng. degree in Electrical Engineering and Automation from the Yanshan University in 2006, the Master degree in Control Theory and Control Engineering from Yanshan University in 2009, and the Ph.D. degree in Control Science and Engineering from Tianjin University in 2015. She is currently an associate professor in Yanshan University. Her research interests include economical dispatch in power systems.

Xinping Guan was a Professor and the Dean of Electrical Engineering with Yanshan University, Qinhuangdao, China. He is currently a Chair Professor with Shanghai Jiao Tong University, Shanghai, China, where he is the Dean of Electronic Information and Electrical Engineering and the Director with the Key Laboratory of Systems Control and Information Processing, Ministry of Education of China. As a Principal Investigator, he has completed or is currently performing research on many national key projects. He is the leader of the prestigious Innovative Research Team of the National Natural Science Foundation of China. He is an Executive Committee member of the Chinese Automation Association Council and the Chinese Artificial Intelligence Association Council. He has authored or co-authored 4 research monographs, over 270 papers in IEEE TRANSACTIONS and other peer-reviewed journals, and numerous conference papers. His current research interests include industrial cyberphysical systems, wireless networking and applications in smart city and smart factory, and underwater sensor networks. Mr. Guan was a recipient of the First Prize of the Natural Science Award from the Ministry of Education of China in 2006 and 2016 and the Second Prize of the National Natural Science Award of China in 2008, the IEEE TRANSACTIONS ON FUZZY SYSTEMS Outstanding Paper Award in 2008, the National Outstanding Youth award honored by the NSF of China, the Changjiang Scholar by the Ministry of Education of China, and the Statelevel Scholar of the New Century Bai Qianwan Talent Program of China.

Contenu
Introduction.- Switched Control Strategies of Aggregated Commercial HVAC Systems for Demand Response.- Hybrid control strategy of Aggregated TCLs for Demand Response.- Fuzzy Neural Network Control strategy of TCLs for Demand Response.- Optimal Control of TCLs Consumer Cost Based on Tracking Differentiator.- Optimizing Regulation of Aggregated TCLs Based on Multi-Swarm PSO.- Communication Network and Cost Modeling.- Bandwidth Allocation for Cooperative Relaying Network.- Distributed Power Allocation and Relay Selection for Cooperative Relaying Network.- Centralized Power Allocation and Relay Selection for Cooperative Relaying Network.- Interference Management and Power Control for Cognitive Radio Network.- Power Allocation for a Relaying-Based Cognitive Radio Network.- Spectrum Allocation and Power allocation for a Relaying-Based Cognitive Radio Network.