Fault Section Estimation for Power Networks Using Logic Cause-Effect Models

A graphic modeling approach for fast fault section estimation via Boolean rule matrix transformations is proposed in this paper. This study extends matrix-based inference in fault diagnosis from radial distribution networks to mesh transmission networks. The proposed approach offers a clear framework, rapid reasoning, and has no problem of convergence and parameter setting during the diagnosis procedure. Furthermore, the required data used for inference can be obtained online from existing supervisory control and data-acquisition/energy-management systems without installing dedicated measurement devices, which reduces extra hardware investment and makes it more feasible to power utilities. By testing three different types of transmission networks, the proposed approach showed some clear merits over existing methods.