A Probabilistic Risk Assessment Framework To Estimate Power System Risks For Outage Planning

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.