Abstract
Abstract
This paper presents a Probabilistic Risk Assessment (PRA) framework for estimating the risk of power system operation under planned outages. The uncertainty in nodal injections and consumptions is represented by scenarios drawn from a copula model that are evaluated via Monte Carlo simulation. For each scenario, the impact of both ordinary and exceptional contingencies is computed via a cascading failure model, which captures the evolution of events after the initial contingencies. The probability of these contingencies is estimated using a Markov chain model. A risk assessment tool is developed to summarize the results in traffic-light risk indicators, informing outage planners about the risk associated with planned outages. By utilizing a realistic case-study, we demonstrate that the developed PRA framework allows planners to identify critical outages that should be rescheduled when they pose unacceptable levels of risk.
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@article{Berti2026probabilistic,
title = {A probabilistic risk assessment framework to estimate power system risks for outage planning},
author = {Davide Berti and Davood Raoofsheibani and Blazhe Gjorgiev and Roberto Rocchetta and Giovanni Sansavini},
journal = {Electric Power Systems Research},
year = {2026},
doi = {10.1016/j.epsr.2026.113761},
url = {https://doi.org/10.1016/j.epsr.2026.113761}
}
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