Real-time estimation of propagation of cascade failure using branching process

Cascading is characterized by a sequence of line trips and load sheds which may lead to major system collapse or even blackout resulting in huge economic losses. In the absence of on-site measurement, it has always remained a challenge to form an accurate model to capture this cascading phenomena considering the complexity of the interconnected network. An alarm or a prediction in advance will save the system from complete collapse which has motivated to propose an accurate dynamic model replicating the propagation of cascading using real-time data. Branching Process is one such model which captures the cascade dynamics by grouping the propagation of line failures into stages. This paper proposes a real-time cascade data generation using RT-Lab and a novel grouping technique to evaluate Branching Process parameters. The proposed methodology is compared with the standard empirical distribution and the results are validated.