Abstract
This paper presents a recurrent neural network-based technique to identify the direction of a fault on a transmission line. The network uses samples of voltage and current signals to learn the hidden relationship existing in the input patterns. The proposed small size recurrent network has been implemented on a digital signal processor board and its behavior is investigated on a physical power system model. Details of implementation and the experimental studies are given and analyzed in the paper. Performance studies results show that the proposed approach is able to detect the direction of a fault on a transmission line rapidly and correctly. It shows that the proposed network is robust, fast and accurate.
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.
