A Novel HVDC Double-Terminal Non-Synchronous Fault Location Method Based on Convolutional Neural Network

• Published in: IEEE transactions on power delivery Vol. 34; no. 3; pp. 848 - 857
• Main Authors: Lan, Sheng, Chen, Mou-Jie, Chen, Duan-Yu
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 1-D CNN; Artificial neural networks; Computer simulation; Convolution; Convolutional neural networks; Data transmission; Electric power transmission; Fault location; Grounding; high resistance fault; Hilbert-Huang Transform; HVdc system; HVDC transmission; Inverters; Machine learning; Neural networks; Rectifiers; Repair & maintenance; Time synchronization; Transmission lines; Traveling waves; unsynchronized two-end measurement

Due to the difficulty in locating high-resistance grounding faults, this paper proposes a novel fault location method for HVdc transmission lines by considering double-end unsynchronized using Hilbert-Huang transform and one-dimensional convolutional neural network (1D-CNN). After the fault signal i...