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Probabilistic reliability assessment of power systems is an ongoing field of research, particularly in the development of tools to model the probability of exogenous threats and their potential consequences. This paper describes the application of a weather-dependent failure rate model to a region of the Icelandic transmission system, using 10 years of weather data and overhead line fault records. The studied failure rate model is compared with a constant failure rate model, in terms of variability and how well the models perform in a blind test over a 2 year period in reflecting the occurrence of outages. The weather-dependent and constant failure rate models are used as input to a state-of-the-art risk assessment tool to determine the sensitivity of such software to weather-dependent threats. The results show the importance of weather-dependent contingency probabilities in risk estimation, and in quantitative assessment of maintenance activities. The results also demonstrate that inclusion of weather dependence in power system reliability assessments affects the overall distribution of risk as a positively skewed distribution, with high-risk periods occurring at low frequency.

This paper presents a probabilistic methodology for assessing power system resilience, motivated by the extreme weather storm experienced in Iceland in December 2019. The methodology is built on the basis of models and data available to the Icelandic transmission system operator in anticipation of the said storm. We study resilience in terms of the ability of the system to contain further service disruption, while potentially operating with reduced component availability due to the storm impact. To do so, we develop a Monte Carlo assessment framework combining weather-dependent component failure probabilities, enumerated through historical failure rate data and forecasted wind-speed data, with a bi-level attacker-defender optimization model for vulnerability identification. Our findings suggest that the ability of the Icelandic power system to contain service disruption moderately reduces with the storm-induced potential reduction of its available components. In other words, and as also validated in practice, the system is indeed resilient.

Abstract-Reliability of electrical transmission systems is presently managed by applying the deterministic N-1 criterion, or some variant thereof. This means that transmission systems are designed with at least one level of redundancy, regardless of the cost of doing so, or the severity of the risks they mitigate. In an operational context, the N-1 criterion provides a reliability target but it fails to accurately capture the dynamic nature of shortterm threats to transmission systems. Ongoing research aims to overcome this shortcoming by proposing new probabilistic reliability criteria. Such new criteria are anticipated to rely heavily on component failure rate calculations. This paper provides a threat modelling framework, using the Icelandic transmission system as an example, highlighting the need for improved data collection and failure rate modelling. The feasibility of using threat credibility indicators to achieve spatio-temporal failure rates, given minimal data, is explored in a case study of the Icelandic transmission system. The paper closes with a discussion on the assumptions and simplifications that are implicitly made in the formulation, and the additional work required for such an approach to be included in existing practices. Specifically, this paper is concerned only with short term and real-time management of electrical transmission systems.