Vol. 1 No. 1 (2025)

Articles

Digital Twin Dynamics in Smart Energy Grids: Advanced Integration and Practical Implementations

Published 2025-08-25

  • Emily Rodriguez

Emily Rodriguez
Department of Electrical Engineering, Stanford University, Stanford, California, United States

Abstract

Smart energy grids are undergoing a profound transformation driven by the integration of renewable energy sources, distributed generation, and advanced monitoring systems. Digital twin dynamics has emerged as a critical enabler in this evolution, offering real-time simulation, optimization, and predictive capabilities. This paper focuses on the advanced integration of digital twins in smart energy grids, exploring key technologies such as real-time data synchronization between physical grids and their virtual replicas, AI-driven load forecasting, and cybersecurity enhancement through twin-based threat detection. Through case studies from urban and rural smart grid deployments, the research demonstrates how digital twin dynamics improves grid stability, reduces energy loss, and facilitates the seamless integration of renewable energy. The findings highlight the potential of digital twins to address the complexities of modern energy systems and pave the way for more resilient and sustainable energy networks.

Keywords

Digital twin dynamics; Smart energy grids; Renewable energy integration; AI-driven forecasting; Cybersecurity

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