This study investigates the electromagnetic surges induced by nearby lightning strikes on high-voltage overhead transmissionlines, using Rusck’s analytical model as a foundational framework. The work focuses on characterizing over voltages generated through inductive coupling between a vertically oriented lightning channel and conductors suspended at various heights above ground level. The main objective is to quantify the peak induced voltages as functions of lateral strike distance (from 10 to 5,000 meters), lightning current amplitude (20 kA to 300 kA), and geometric configuration of the transmission line. Applied to the 208 km Ngo-Djiri line in the Congo Basin an area subject to high thunderstorm frequency the results reveal a steep hyperbolic decrease in induced voltage with increasing distance from the strike point, consistent with electromagnetic field theory. A linear relationship between lightning current and induced voltage is observed, validating the model’s reliability in high-amplitude regimes. For typical configurations, overvoltages remain below the 1050 kV insulation level of 220 kV systems. However, in extreme cases involving high current ( 200kA) and close proximity ( 50m), induced voltages can exceed this threshold, suggesting the need for enhanced protection measures. Beyond theoretical modeling, this study highlights the relevance of Rusck’s approach for African networks, where simplified models are essential due to limited measurement data and resource constraints. It also outlines practical directions for future research, including integration of real soil resistivity, capacitive coupling effects, and multi-conductor asymmetry into the modeling framework. The results advocate for adaptive insulation coordination and protection schemes tailored to regions with high lightning activity. Ultimately, the work contributes to strengthening the resilience of HV infrastructures in tropical environments by providing a deterministic, scalable, and physically interpretable methodology for lightning-induced surge prediction and mitigation.
Gomba et al. (Tue,) studied this question.