Abstract
As electrification deepens and the society relies more and more on electricity, dependability and safety standard of the power distribution system becomes higher and higher. What is more, to minimize carbon emission, high percentage of renewable energy resources penetration is becoming a reality, which further complicates the distribution system. Because of equipment failure, construction mistake and other causes, power system faults are inevitable. Fault section identification and fault isolation is a critical mission in distribution system operation [1]. As the distribution system develops and evolves, two main ways to accomplish this goal were established: (a) Substation overcurrent relay detects the fault and the corresponding substation breaker isolates the fault. Then trial-and-error method is used to identify and isolate the fault section; (b) Distributed sensors are deployed in the distribution system. Distribution system automation software in the operation center then collects fault information sent from all the distributed sensors. Operation stuff make a judgement on the fault section and fault isolation is done on a remote control or manual operation fashion. These methods leave a lot of room for improvements, which will be elaborated in section II. In this paper, integrated usage of fundamental frequency signals and traveling waves signals is done for fault detection and fault type identification in distributed sensors. And then an automatic fault section identification algorithm is introduced. This algorithm does not require human intervention, which reduces outage time, saves manual efforts and also lays the foundation for automatic electricity restoration.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: 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.