Probabilistic impact assessment of lightning strikes on power systems incorporating lightning protection design and asset condition

Lightning strikes may result in widespread power outages with long supply interruption times and severe impacts to economy and society. To prevent this from happening now and in the future, power system planning and operation practices must be revisited so that the probability of outages caused by lightning strikes can be reduced. In this context, this article presents a probabilistic framework for impact assessment of lightning strikes on the grid which investigates power system exposure to lightning strikes. This new framework incorporates information about failure rates attributed to lightning protection system design and asset condition together with the probability of lightning activity over time for a probabilistic impact assessment of lightning strikes on the grid. Notably, the probability of lightning activity is conditioned by information about weather patterns and seasons obtained through collaboration with the Met Office. Furthermore, it is demonstrated in the reduced 29-bus Great Britain transmission system model with weather data collected from 2010 to 2019 and validated against historical fault data recordings provided by the National Grid’s Transmission System Performance Reports and by the National Fault Interruption Reporting Scheme. Therefore, the framework is envisaged to assist power system planners to investigate best design and maintenance practices and grid modernization interventions and power system operators to deploy smart operational measures that reduce the probability of power outages caused by lightning strikes. [Display omitted] •Probabilistic impact assessment of lightning strikes on the grid over time.•Probability of lightning activity based on UK’s Met Office adopted practices.•Lightning protection failure rates given by design criteria and asset condition.•Power transmission components of concern: overhead lines and outdoor substations.•Validation through comparison with historical data of power outages in the UK.