Thesis Format
Monograph
Degree
Doctor of Philosophy
Program
Electrical and Computer Engineering
Supervisor
Ajaei, Firouz B.
Abstract
Detecting High-Impedance Faults (HIFs) are challenging due to their low short-circuit current magnitude. An undetected HIF may jeopardize human safety and cause arcing and fire ignition. Therefore, HIFs must be detected and cleared in a timely manner to ensure human safety and to avoid fire hazards. The conventional relays and protection systems often fail to reliably detect and clear HIFs. Moreover, the existing HIF detection methods: (i) often mis-detect non-HIF disturbances as HIF, (ii) typically fail to detect HIFs in a timely manner, (iii) typically are unable to detect HIFs distant from the relay location (Remote HIFs).
This thesis focuses on developing fast and reliable methods for detecting High-Impedance Arcing Faults, hereafter referred to as High-Impedance Faults, in medium-voltage AC distribution systems. The proposed HIF detection methods, which are based on digital signal processing and machine learning techniques, are evaluated using various case studies including (i) simulated HIFs on seven different fault surfaces, (ii) simulated non-HIF scenarios such as capacitor switching, operation of nonlinear loads, and transformer energization, (iii) recorded HIF signals obtained from experimental HIF tests on four different fault surfaces. The time-domain simulation studies are conducted on the IEEE 13-node test feeder using the PSCAD/EMTDC software. The study results indicate that the proposed HIF detection methods (i) can detect all investigated HIF scenarios under 200 ms, which is well-below the typical HIF detection speed reported in the literature, (ii) are sensitive to remote HIFs, (iii) do not cause false tripping against non-HIF scenarios (iv) are computationally efficient.
Summary for Lay Audience
A High-Impedance Fault (HIF) typically occurs when a highly resistive object such as a tree branch serves as a current path between an energized primary conductor and the ground. An HIF may also occur if an energized broken conductor falls and contacts a high-impedance surface such as sand, asphalt, cement, grass, or reinforced concrete. The HIF current typically is too low to cause any damage to the power system equipment. However, undetected HIF may cause arcing and fire ignition, which may impose a threat to human safety. Therefore, HIFs must be detected in a timely manner to preserve human safety and to avoid any arcing and fire ignitions. Due to the low HIF current, the conventional protection systems are unable to reliably detect and clear HIFs. Moreover, the existing HIF detection methods are either fail to detect HIFs or require high computational resources. Hence, are not compatible for real time HIF detection. The purpose of this thesis is to present fast, reliable, and computationally efficient HIF detection methods that can be used for real time HIF detection. The proposed HIF detection methods are tested through various case studies including (i) simulated HIFs on seven different fault surfaces, (ii) simulated various non-HIF scenarios such as capacitor switching, operation of nonlinear loads, and transformer energization, (iii) experimental field HIFs on four different fault surfaces.
Recommended Citation
Hojatpanah, Farnam, "Fast and Reliable High-Impedance Fault Detection in AC Distribution Systems" (2024). Electronic Thesis and Dissertation Repository. 9987.
https://ir.lib.uwo.ca/etd/9987