Performance analysis of MMF-based transmission network fault diagnosis via randomized hybrid simulations

In this paper, a hybrid simulation study is carried out on the 68-bus 16-machine test system to assess the performance of a recently developed fault diagnosis scheme using multiple-model filters (MMF) built on partitioned electric network models. Our main interest lies with the effectiveness of a secondary protection system, in which diagnosis plays a key role in enabling reliable and timely recovery from misoperations in the conventional primary protection. The hybrid simulation involves both event — driven and time — driven dynamics with arrivals of transmission short-circuit faults as independent Poisson processes among transmission lines and the fault location uniformly distributed along the short-circuited line. This paper reports only on the dependability enhancement through the diagnosis scheme, which is measured by the probability of successful fault diagnosis by the secondary protection given that the primary protection has failed to diagnose the fault.