A Reasoning Approach Based on Pattern Graph for Analyzing the Risk of Power Outage Propagation

This paper proposes a pattern graph-enabled approach to accurately and comprehensively assess the risk of outage propagation patterns among branches. First, we propose a modeling strategy that captures the risk level of a correlation accurately by considering the likelihood of its outage that is associated with another branch outage. Furthermore, we construct a pattern graph by identifying and linking the virtual paths to estimate the risk level of a correlation and calculate the risk level of inexplicit correlations hidden within the cascading outage dataset, we construct a pattern graph by identifying and linking the virtual paths to estimate the risk level of a correlation. The simulation results for the IEEE 39-bus system show that the proposed method can effectively reveal the propagation risk of correlations with a simple and accurate reasoning process.