Probabilistic Prioritization as an Improvement for Risk-based Contingency Screening Methods

The process of dynamic risk assessment in power systems is commonly based on the analysis of both, probabilities and costs for a set of critical contingencies. Increasing the accuracy of this process requires processing many contingencies possibly with the help of time-domain simulations (TDS), which are highly time consuming and computationally expensive, but allow providing reliable results. This paper introduces probabilistic prioritization (PP) as a method to select critical N-k contingencies and provide an efficient identification of the critical ones by a reduction of the number of TDS. Although PP pays attention only to probabilities of contingencies, it utilizes the concept of risk accuracy, in order to provide a stopping criterion for TDS used to assess the costs resulting from particular contingencies. Moreover, the PP method is general and may be applied in other risk assessment processes. The extended IEEE39 system was used to investigate the PP method and the results show that the reduction of the TDS number is around 31% for PP, when compared with a reference case, where contingency filtering was not applied.