Reliability analysis of distribution automation control systems considering 5G communication latency

Abstract

Distribution automation control increasingly relies on 5G access, edge computing, and network slicing to connect feeder terminal units, intelligent electronic devices, sectionalizing switches, distributed energy resources, and inspection sensors. However, control reliability is not determined by average communication availability alone. Tail latency, packet loss, edge-processing delay, and deadline mismatch can turn a delivered command into an invalid automation action. This paper develops a latency-aware reliability analysis method for 5G-enabled distribution automation. The end-to-end command delay is decomposed into queueing, radio access, core forwarding, edge processing, and device-processing components, and the resulting delay distribution is mapped to command-validity probability. A modified IEEE 33-node feeder is then used to quantify the impact of nominal 5G, congested 5G, and protected slicing with mobile edge computing. The empirical results show that, under congested 5G, the P95 command delay rises from 13.5 to 43.2 ms and SAIDI increases from 40.1 to 50.3 min/customer, whereas slicing plus edge computing reduces SAIDI to 38.9 min/customer. The framework also supports optical-inspection-assisted automation scenarios in which camera, LiDAR, or thermal records share communication infrastructure with protection commands.