Advances in Digital Twin Deployment for Real-Time Asset Monitoring and Optimization in Power Transmission Systems
DOI:
https://doi.org/10.32628/CSEIT251234Keywords:
Digital Twin, Power Transmission Systems, Real-Time Monitoring, Predictive Maintenance, Renewable Integration, Grid OptimizationAbstract
The integration of digital twin technology into power transmission systems marks a significant evolution in the way grid assets are monitored and optimized. This paper explores recent advances in the deployment of digital twins, emphasizing their role in enabling real-time, data-driven decision-making and enhancing operational resilience. Beginning with a discussion on the structural architecture of digital twins, the study outlines their core components—virtual models, sensor networks, and cyber-physical synchronization—and how they interoperate with existing infrastructure through standardized communication protocols. The paper then delves into the real-time monitoring capabilities of digital twins, highlighting their ability to support condition-based maintenance, detect anomalies through embedded AI/ML models, and provide actionable insights via immersive visualization tools. Further, the study examines optimization functionalities such as dynamic line rating, energy flow simulations, and renewable energy integration, demonstrating how digital twins improve both short-term efficiency and long-term grid planning. Despite their transformative potential, challenges remain, including data quality concerns, cybersecurity risks, cost constraints, and interoperability issues. The paper concludes by recommending future research priorities and policy interventions, including standardization efforts, investment incentives, and workforce development, to promote widespread and sustainable adoption. Overall, the deployment of digital twins represents a pivotal step toward intelligent, adaptive, and future-ready power transmission networks.
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