Accurate Fault Classifier and Locator for EHV Transmission Lines Based on Artificial Neural Networks

Table 11

Comparison of ANN-based fault classification and location schemes.

Algorithms suggested	Fault classifier inputs	Fault locator inputs	FIA range (°)	𝐿𝑓 range (%)	𝑅𝑓 range (Ω)	%Error range	Response time
Joorabian et al. [22]	Five consecutive samples of three-phase currents and voltages	Five consecutive samples of three-phase currents and voltages	0–90°	0–94%	0–100	0.0397% to 0.4123%	Not indicated
Mahanty and Gupta [10]	Five consecutive samples of three-phase currents	Five consecutive samples of three-phase currents and voltages	0–90°	0–82%	0–200	0.0007% to 4.45%	Not indicated
Jiang et al. [31]	Negative-sequence components of three-phase currents and voltages quantities	Negative-sequence components of three-phase currents and voltages quantities	Not indicated	Not indicated	Not indicated	0.41% to 0.54%	1.28 cycles
Yadav and Thoke [32]	No method for fault classification	Three consecutive samples of three-phase currents and voltages	Not indicated	0–90%	0–100	0.052% to 1.5693%	1.5 cycles
Proposed scheme	Four consecutive samples of three-phase currents	Magnitudes of fundamental components of three-phase currents and voltages	0–360°	0–96%	0–200	0.0175% to 0.3041%	1 cycle time from inception of fault