Title :
Leveraging substation automation for faulted segment identification
Author :
Ning Kang ; Mousavi, Mirrasoul J.
Author_Institution :
Corp. Res. Center, ABB, Raleigh, NC, USA
Abstract :
This paper discusses the potential for identifying faulted segment(s) on single phase distribution laterals using limited IED (Intelligent Electronic Device) data from digital substations. Identifying faulted segment(s) in a timely manner speeds up fault isolation and restoration processes contributing to greater system reliability. Achieving this objective with minimum data requirements in terms of fault measurements lends itself in practice to a cost-effective solution that can be further used to optimize the requirements for feeder sensor placement. The methodology utilizes fundamental frequency current magnitudes from feeder head in conjunction with an approximate sequence model of the multiphase feeder including single-phase and double-phase line segment. The proposed methodology was evaluated on actual circuits and data from field-recorded faults demonstrating the extent with which IED data from substations alone can be fully leveraged to identify faulted segments for isolation purposes in real-time.
Keywords :
approximation theory; control engineering computing; fault location; optimisation; power engineering computing; sensor placement; substation automation; cost-effective solution; fault isolation process; fault location; fault measurements; fault restoration process; faulted segment identification; feeder sensor placement; frequency current magnitudes; intelligent electronic device; limited IED data; minimum data requirements; multiphase feeder head; multiphase feeder sequence model; single phase distribution laterals; substation automation; Circuit faults; Current measurement; Fault location; Impedance; Resistance; Substations; Distribution system; fault location; faulted segment identification; multiphase line modeling; sequence components;
Conference_Titel :
PES General Meeting | Conference & Exposition, 2014 IEEE
Conference_Location :
National Harbor, MD
DOI :
10.1109/PESGM.2014.6939908