Given the increasing frequency and severity of extreme weather events in recent years, transmission network planning and operation cannot be carried out without considering these factors.

To address this, a joint project between the Italian TSO, Terna, and RSE S.p.A. developed a risk-based methodology for assessing the resilience of the power system within the context of network planning.

This methodology aims to define a resilience indicator that captures the benefits of network reinforcement operations in terms of increased resilience, as required by the Italian energy regulator’s cost-benefit analysis (CBA).

The two main indicators of the methodology are the return period for outages at each substation connected to the transmission network and the Expected Energy Not Served (EENS) due to interruptions.

The return period of a substation depends on the network’s level of interconnection and the return periods of the power lines. The resilience benefit is evaluated as the difference in EENS indicators before and after implementing the network operations.

The article describes the implementation of the methodology in a professional tool, its validation against real data, and its application to a portion of the transmission network through a case study.

Following the methodology presentation, the validation process of the overhead line (OHL) vulnerability model is detailed. The validation consists of two phases: the first compares the wet snow loads calculated from a reanalysis dataset with the loads recorded during significant snowfall. The second validation phase is based on a statistical comparison between the return periods of interruptions (in terms of the average number of failures) due to wet snow events, as calculated by the methodology—combining the vulnerability model with the aforementioned reanalysis dataset—and the empirical return periods of power line interruptions derived from available historical fault event data.

Finally, a simple case study illustrates an application of the methodology, showing the process of identifying the network portions at the highest risk of interruption due to severe weather events and selecting operations based on cost-benefit criteria.