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Full Description
This book offers a comprehensive, interdisciplinary exploration of how edge computing is transforming smart grids from real-time data processing and microgrid energy management to intelligent algorithms for predictive demand response and energy optimization. It bridges cutting-edge technologies such as blockchain, federated learning, mobile crowd computing, and 5G-enabled MEC, while addressing crucial challenges in cybersecurity, anomaly detection, and resource allocation. It delves into the core principles and architectures of edge-enabled smart grids, illustrating how real-time data processing, decentralized resource management, and localized control are transforming traditional energy infrastructures. With a special emphasis on microgrid energy optimization, predictive demand response, and AI-driven decision-making, this book highlights the pivotal role of intelligent algorithms deployed at the network edge in ensuring efficiency, scalability, and low-latency performance. It offers an insightful analysis of cybersecurity vulnerabilities, anomaly detection frameworks, and real-time threat mitigation strategies from the edge computing perspective. Whether you're a researcher, engineer, or energy professional, this book equips you with the insights and tools needed to design, implement, and secure next-generation smart grid systems driven by edge intelligence.
