Digital Twins for Smart Grid Optimization

The concept of the Digital Twin (DT) a dynamic digital representation of a physical system has become increasingly relevant in the modernization of power systems and smart grids. As energy infrastructures evolve toward higher levels of automation, intelligence, and integration with renewable energy sources, digital twins offer a powerful platform for simulation, optimization, and predictive analytics across the entire energy value chain.
This edited volume provides a comprehensive and up-to-date exploration of Digital Twin technologies for modern smart grids, covering the fundamental architectures, enabling communication infrastructures, optimization methodologies, intelligent control strategies, cybersecurity, artificial intelligence, and real-time energy management. The book explores how Digital Twins convert conventional power systems into smart, data-driven cyber-physical ecosystems with continuous monitoring, predictive analytics, autonomous decision-making, and resilient operation alongside emerging challenges of renewable energy, distributed energy resources, electric vehicles, interoperability, and secure digital infrastructures.
Written by leading academics and experts from industry, the book combines theoretical contributions with description of practical models, optimization frameworks, mathematical formulations, and case studies of real-world implementations. The individual chapters contain the latest contributions to the discipline, including of IoT, 5G/6G communications, machine learning, risk-aware optimization, closed-loop control, trustworthy Digital Twin architecture for next generation power systems.
Written for researchers and graduate students, practicing engineers, and industry professionals, this book will serve as both a comprehensive reference and practical resource to develop intelligent, resilient, secure, and sustainable Digital Twin-enabled smart grid solutions to usher in this new evolution of modern energy systems.