1 / 12

DETECTION OF HIGH IMPEDANCE FAULTS USING ARTIFICIAL NEURAL NETWORKS

DETECTION OF HIGH IMPEDANCE FAULTS USING ARTIFICIAL NEURAL NETWORKS. By Ibrahim El-Amin Mohammad H. Al-Mubarak. May 2003. Problem Definition. High Impedance Fault (HIF) is a fault on primary distribution (PD) system that cannot be detected by conventional O/C protection

borka
Download Presentation

DETECTION OF HIGH IMPEDANCE FAULTS USING ARTIFICIAL NEURAL NETWORKS

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. DETECTION OF HIGH IMPEDANCE FAULTS USING ARTIFICIAL NEURAL NETWORKS By Ibrahim El-Amin Mohammad H. Al-Mubarak May 2003

  2. Problem Definition • High Impedance Fault (HIF) is a fault on primary distribution (PD) system that cannot be detected by conventional O/C protection • 95% of faults on PD feeders occur on O/H lines • Undetected HIFs may result in public hazard and property damage • Primary motivator to design HIF detectors is public safety

  3. Problem Statement and Paper Objective • O/C relays are set to operate for currents between 125-200% of the normal load current • HIFs draw currents in the range of 0-100 A • Objective of paper is to develop an ANN based HIF detector that can also: • Locate the HIF • Distinguish HIFs from normal switching events • Identify the faulty phase

  4. Feeder Simulation with EMTP Fault Diagnosis Data Scaling and Preprocessing ANN Trainging and Testing Solution Approach

  5. Feeder Simulation • EMTP is used because • It can handle switch closing and opening (ideal for transient analysis or fault simulation) • It can simulate unbalanced systems (e.g. single line to ground faults) • Simulation is for 5 cycles (83.33 ms) at a sampling rate of 0.2778 ms • 300 samples/phase for each case, i.e. 1800 samples to represent the 3 phases of the current and voltage waveforms

  6. Feeder Simulation (Cont’d)

  7. Feeder Simulation (Cont’d) Phase-C Current Waveform for Load-4 and C1 Switching

  8. Designing and Testing the ANN ANN Targets

  9. Comparison Between the Three ANN Designs

  10. Test Results of the ANN Designs w.r.t. Targets

  11. Test Results of the ANN Designs w.r.t. Targets 1 3 2 1 3 4 2

  12. Conclusions • Out of the eight design versions, four are promising for HIF diagnosis applications. These are D1F, D2B, D3R & D3B • Design D3R is the best because • 100% accuracy for all test cases and all targets • 100% accuracy for mid-span HIF cases, for extended feeder cases, for varying fault impedance cases and for varying transmission line impedance cases • All errors are for lightly loaded feeder cases, but none of them is in detecting the HIF occurrence • The design fails to distinguish between two fault events but succeeds in not false-indicating a HIF for normal system operation or vice versa

More Related