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Conference Paper

Faulty Feeder Identification Technology for Reduced Outage Zone in Smart Grids

This research proposes a novel technique using grid-connected converters for faster and reliable detection of faults in smart PV systems connected to low-voltage distribution grids. The method improves fault detection speed by 33%, enhancing grid reliability during abnormal voltage conditions.
Year
2022
Faulty Feeder Identification Technology for Reduced Outage Zone in Smart Grids

Faulty Feeder Identification Technology utilizing Grid-Connected Converters for Reduced Outage Zone in Smart Grids

Abstract:

For penetration of more renewable and EVs in future smart grids, reliable infrastructure using grid-connected converters (GCCs) are needed. One of the main concerns for grid reliability is outage management during unpredictable faults. By using intelligent monitoring and multi-functional control by GCCs, utilities can perform timely faulty feeder detection and isolation to reduce outage zones. Utilities relatively deal with short-circuit faults but suffer from detection failure during high-impedance faults (HIFs) which largely occur due to vegetation or tree contact. Locations of 70-80% of such HIFs remain unknown due to high fault resistances and low levels of fault current. Similar detection failures are reported in neutral ineffectively grounded distribution grids. In this research, advanced GCCs are utilized for safer, faster, reliable faulty feeder identification with no additional cost. Novel technique using GCCs as power source to inject multiple frequency components and employing computationally intensive algorithms is proposed. Developed algorithm is verified by simulation analysis in MATLAB and found to perform 33% faster detection for HIF conditions.

Published in: 2022 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)

Date of Conference: 24-28 April 2022 

Date Added to IEEE Xplore12 July 2022 

ISBN Information:

Electronic ISBN:978-1-6654-3775-2

Print on Demand(PoD) ISBN:978-1-6654-3776-9

ISSN Information: 

  • Electronic ISSN: 2472-8152 
  • Print on Demand(PoD) ISSN: 2167-9665 

DOI: 10.1109/ISGT50606.2022.9817553

Publisher: IEEE

Conference Location: New Orleans, LA, USA

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