Authoritative and highly comprehensive guide on how emerging technologies can address various challenges in different sectors of smart cyber-physical power systems
Smart Cyber-Physical Power Systems explores the transformative role of emerging technologies in addressing the multifaceted challenges within smart cyber-physical power systems. Employing cutting-edge techniques through artificial intelligence (AI), machine learning (ML), big data, blockchain, information theory, quantum computing, IoT, and beyond, this book offers insights into the integration, operation, and optimization of modern power systems, from design of distributed energy resources to stability, reliability, cybersecurity and control. To aid in reader comprehension, hundreds of figures and tables are included throughout.
This book begins with an overview of cyber-physical power systems, including fundamentals, challenges, and solutions. It then moves on to explain the basic structure of traditional and smart cyber-physical power systems, their modeling, architecture, and other preliminaries, and how information flow has changed power system structures and presented modern power systems with new challenges.
Diving deeper, further chapters meticulously discuss specific applications and case studies. Topics include the operation and control of microgrids, enhancing energy efficiency in smart buildings through IoT integration, and innovative home energy management systems powered by artificial neural networks. The book also ventures into cutting-edge research such as the application of deep learning algorithms for solving optimal power flow problems and the challenges in active distribution networks.
With contributions from highly qualified members of the field, Smart Cyber-Physical Power Systems also discusses topics including: *Innovative Energy Management and Smart Grids: Chapters cover a range of topics from global demand response strategies to the intricacies of smart city energy infrastructure as a cyber-physical system of systems, managing interconnected microgrid systems, integration of Internet of Energy and smart building technologies as well as the pivotal role of electric vehicles in modern energy ecosystems. *Resilience and Security in Power Systems: Discussions on the resilience, reliability, and security of cyber-physical power systems, including cutting-edge solutions for cyber-resiliency, cyber-attack detection, anomaly mitigation, and privacy-preserving measures in modern power systems. *Advanced Applications of AI and Machine Learning: Explore the application data science, artificial intelligence, machine learning and quantum computing in optimizing power system operations, solving optimal power flow, addressing protection challenges, enhancing energy trading, and forecasting with chapters dedicated to emerging technologies such as information theory, quantum computing, digital twins and reinforcement learning. *Future Trends and Innovations: Delve into emerging technologies and future trends, including the transformative potential of augmented reality (AR), virtual reality (VR), and the Metaverse in modern power systems. Explore the role of blockchain in energy trading, the impact of advanced communications technology, and how development and embedded systems, DevOps, MLOps, and edge computing are revolutionizing the design, operation, and engagement with power systems.
Smart Cyber-Physical Power Systems is an ideal resource on the subject for professors, researchers, and graduate students in electrical power engineering, smart grids, and energy fields, as well as professionals in R&D departments of companies and industries related to energy, smart homes/cities, and renewable energy resources.
Welcome to the exploration of smart cyber-physical power systems (CPPSs), where challenges are met with innovative solutions, and the future of energy is shaped by the paradigms of AI/ML, big data, blockchain, IoT, quantum computing, information theory, edge computing, Metaverse, DevOps, and more.
Ali Parizad, PhD, is a Postdoctoral Associate at the Advanced Research Institute (ARI) of Virginia Polytechnic Institute and State University, VA, USA. Leveraging his extensive academic background, he served as a Senior Data Scientist in the IDA Data Science & Machine Learning (DSML) Department at Shell Energy. He holds the position of Staff Power Systems Machine Learning Engineer at Thinklabs AI, where he tackles critical challenges in power systems with cutting-edge AI applications.
Hamid Reza Baghaee, PhD, is an Associate Research Professor at Amirkabir University of Technology, Tehran, Iran.
Saifur Rahman, PhD, is the founding director of the Advanced Research Institute at Virginia Tech, where he is the Joseph R. Loring Professor of Electrical and Computer Engineering.
