Abstract
The authors propose a new fault location method that uses a neural network to analyze the distribution pattern of the ground wire current along the power line. This method is able to locate the fault section even for secondary power lines with complicated configurations. The method is based on the inference process, i.e., human experts will analyze the distribution pattern of the current amplitude and phase angle. In locating fault sections, higher precision than ordinary three-layer neural network or the expert system of previous development can be obtained. The proposed neural network comprises three sets of three-layer neural networks which follow the back-propagation learning procedure. The 1st and 2nd neural networks calculate the candidate-1 and candidate-2 for the fault section using current amplitude and phase angle distribution patterns, respectively. The 3rd neural network then performs final fault location using these candidates and a current amplitude distribution pattern. The results evaluated with all possible fault causes indicate that the new method is precise to as high as 98.4 percent even when the measured values differ by 30 percent from predicted ones with EMTP.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
