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Jha / Appasani / Bizon

Edge Computing for Smart Grid

Medium: Buch
ISBN: 978-3-032-31470-3
Verlag: Springer
Erscheinungstermin: 09.11.2026
vorbestellbar, Erscheinungstermin ca. November 2026

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.


Produkteigenschaften


  • Artikelnummer: 9783032314703
  • Medium: Buch
  • ISBN: 978-3-032-31470-3
  • Verlag: Springer
  • Erscheinungstermin: 09.11.2026
  • Sprache(n): Englisch
  • Auflage: Erscheinungsjahr 2026
  • Serie: Power Systems
  • Produktform: Gebunden
  • Seiten: 303
  • Format (B x H): 155 x 235 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

Edge Computing in Smart Grids: Applications, Technologies, and Challenges.- The Role of SGs and the IoT in Enabling Eco-friendly Automation Solutions.- Multi-tier edge computing for IoT-based smart grids: Latency-aware data processing and resource management.- Prosumers’ Advantages in Smart Grid using Edge Computing.- Smart Microgrid Energy Management Using Edge Computing.- Decentralized Intelligence in Smart Grids: The Role of Edge Computing and Federated Learning.- Machine Learning on a Power Budget: Energy-Efficient Techniques for the Smart Grid Edge.- Digital Twins Based on Edge Computing for Smart Grid Applications.- Edge Computing and Machine Learning for Anomaly Detection in Smart Grids.- Edge-Centric Architectures for Secure and Sustainable Hybrid Energy Management.- Potential Benefits of Edge Computing for Smart Grid and Distributed Systems.