Transmission Line Distance Protection Algorithm Based on Bayesian Inference

Abstract

This paper presents a distance protection method based on estimating the resistances and inductances seen by the relay using a least-squares (LS) approach combined with the application of Bayesian inference (BI) to determine fault probabilities in the protected zone over time. The use of BI in the presented algorithm increases the security and reliability of the LS-based line protection approach, which, although fast, may yield impedance estimates with numerical inaccuracies and therefore configures a solution capable of detecting faults internal to the protected zone rapidly and dependably. The authors tested the proposed algorithm using data sets obtained from transmission line fault simulations performed in Alternative Transients Program (ATP), which considered noisy measurements, current transformer (CT) saturation, capacitive-coupling voltage transformer (CCVT) transients, switching onto fault, close-in faults, frequency variations, uncertainties in the line’s parameters, and power swings. Furthermore, the authors tested the presented method against measurements recorded by field protection equipment during seventy-nine actual fault events on four existing 500 [kV] lines. The results indicate that the proposed algorithm is a fast, secure, and reliable distance protection solution and that using BI to the LS-based distance protection approach increases security while maintaining fast fault detection.