Distance Protection Functions Based on the Conic Section Equation and the Bayesian Inference: Implementation and Tests with Field Data

This paper discusses an implementation and testing of two innovative methods for transmission lines distance protection against real-world fault events. This study's contribution is to encourage the testing and validation of protection solutions proposed in the scope of theoretical research with field data and compare them with the responses of commercial devices by showing how this allows for further conclusions and discussing the practical applicability of the new solutions. Given the large volume of field data recorded daily, this practice is possible in the modern power industry. The first method uses impedance calculation based on the Lissajous figure analysis, formed by the intersection of voltage and current signals in quadrature. The second method, in its turn, utilizes a least-squares approach to estimate impedances combined with a Bayesian Inference criterion. Both algorithms employ direct analysis of the voltage and current signals in time-domain without the need for phasor estimations. This work compares the methods and evaluates their performance against the responses of distance protection functions from different commercial devices on eight recent field fault events on Brazilian transmission lines with varying voltage levels. The conventional phasor-based protection is also consid-ered in the comparisons to provide a comprehensive analysis.