Abstract
Precise fault location in distribution network is one of the most important applications among intelligent monitoring and outage management tasks used for realization of self-healing networks. The data gathered from various intelligent sensors installed throughout the power system could be utilized for smart approaches to locating faults, helping the system restoration, reducing outage time and improving system reliability. Since the distribution network is radial, with multiple laterals connected to the main feeder, faults at various locations may lead to the same voltages and currents observed at the substation. In other words, using the substation measurements to calculate the fault location, multiple failure states are possible. In this paper, Markov decision process is used as a tool for the determination of the faulted feeder section and its isolation from the grid. The algorithm is based on transition probabilities among states obtained from intelligent sensors and tested on a radial distribution network with 3 sectionalizers.
Sign-in/Register to access full text options 
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.
