Digital Twin Modeling of Fiber Optic Telecom Infrastructure for Proactive SCADA Network Resilience in Power Transmission Utilities

Abstract

This study investigated the effectiveness of digital twin modeling in enhancing the resilience of fiber optic telecom infrastructure supporting SCADA systems in power transmission utilities through a quantitative, simulation-based approach. A digital twin framework was developed to replicate real-time network conditions and evaluate performance under both baseline and optimized scenarios. The dataset consisted of 120 simulated network segments characterized by key performance indicators including latency, packet loss, bandwidth utilization, signal attenuation, and recovery time. Descriptive analysis revealed a baseline mean latency of 48.6 ms and packet loss of 2.1%, with recovery time averaging 18.9 minutes. Following digital twin-based optimization, latency was reduced to 34.2 ms, packet loss declined to 0.9%, and recovery time improved to 9.7 minutes, representing improvements of 29.6%, 57.1%, and 48.7%, respectively. Bandwidth utilization showed improved stability with reduced variance, indicating more efficient load balancing across network segments. Inferential statistical analysis confirmed that these improvements were statistically significant at p < 0.05, with effect sizes indicating moderate to large practical impact, particularly for recovery time (η² = 0.52) and packet loss (η² = 0.46). Regression analysis demonstrated strong relationships between latency, packet loss, and network reliability, with packet loss exhibiting the highest influence (β = -0.67). Sub-group analysis further revealed that high-load segments experienced the greatest performance gains, with latency decreasing from 62.7 ms to 41.3 ms and packet loss from 3.4% to 1.5%. Multi-point failure scenarios showed substantial resilience improvement, with recovery time reduced from 26.4 minutes to 13.2 minutes. The findings confirmed that digital twin integration significantly enhanced SCADA communication performance by enabling real-time monitoring, predictive analytics, and adaptive network optimization. This study provided strong quantitative evidence that digital twin modeling is an effective approach for improving telecom network reliability, operational stability, and resilience in power transmission utilities.