Skip to Main Content
Various transmission line fault location algorithms have been proposed in the past depending on the measurements available. These algorithms perform well when the measurements utilized are accurate; they may yield erroneous results when the measurements contain considerable errors. In some cases, there are redundant measurements available for fault location purposes, and it may be possible to design an optimal estimator for the fault location based on nonlinear estimation theories. This paper aims at proposing a possible method for deriving an optimal estimate of the fault location that is capable of detecting and identifying the bad measurement data, minimizing the impacts of the measurement errors and thus significantly improving the fault location accuracy. The solution is based on the distributed parameter line model and thus fully considers the effects of shut capacitances of the line. Since field data are not available, case studies based on simulated data are presented for demonstrating the effectiveness of the new method.