The report addresses several aspects related to power system vulnerability, including component vulnerability models, system vulnerability indices and uncertainty propagation in vulnerability models.

A model is proposed to quantify overhead line span vulnerability to flashovers due to excessively reduced insulation distances caused by concurrent factors (e.g. large OHL wire swings due to wind, “increased sags” due to wet snow sleeves). The model solves an optimization problem to get the worst geometric configuration of wires, computes the relevant critical flashover voltage (under specified weather conditions) and the flashover probability.

Simulations on a small set of OHL’s in a portion of the Italian EHV/HV grid affected by frequent flashovers show that the model is selective, i.e. able to select exclusively the lines which underwent recorded faults in the past, and robust, i.e. using a smaller amount of data does not affect significantly its outcomes, which is important for an extensive application also in areas where Lidar data are available with lower update rates.

A model is also proposed to simulate the vulnerability of tower foundations to mechanical instability induced by riverbank erosion. Given the river flow speed and height, the erosion on the river channel is quantified, identifying the critical conditions for riverbank collapse with potential instability of the terrain under the tower foundations. The model accounts for different soil types and different distances of foundations from the riverbank.

Moreover, analytical models are described to quantify respectively the mechanical vulnerability of wind turbine (WT) towers to strong wind and the effect of prolonged droughts on the maximum generation capacity of thermal units with CLC (Closed Loop Cycle) and OLC (Open Loop Cycle) cooling systems.

Then, a methodology is proposed to compute probabilistic “system vulnerability” (SV) indexes defined in the previous research year to assess system degradation as a function of threat features (e.g. extension, severity). Simulations show that the weighted average SV index is a good indicator of system vulnerability to threat scenarios.

Finally, a method is proposed to propagate parameter uncertainties in the asset vulnerability models for the Terna-RSE resilience methodology: a distribution of line span failure return periods (RP) in case of strong wind is found under uncertain initial tensions for the wires. Simulations on wind threat indicate the method effectiveness and the variety of line span behaviours, in terms of RP uncertainty.