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Non‐intrusive sensing method of the phasor of system voltage for partial discharge diagnostics
Author(s) -
Li Fei
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2019.1836
Subject(s) - phasor , partial discharge , overhead (engineering) , phasor measurement unit , voltage , electric power transmission , global positioning system , electronic engineering , computer science , system of measurement , overhead line , transmission line , electrical engineering , engineering , electric power system , physics , telecommunications , power (physics) , quantum mechanics , astronomy
This study presents a non‐intrusive sensing method to obtain the phasor of system voltage of overhead lines for a mobile partial discharge diagnostics platform; with the phasor, partial discharges detected by the mobile platform can be characterised by statistical phase‐resolved patterns. Firstly, finite‐element analysis simulations were conducted to understand the relations between overhead lines of different configurations and the electric field underneath. With an electric field sensor, the phasor of system voltage can be derived with the aid of a second measurement unit for system frequency. The two measurement units are synchronised by two GPS receivers with 1 pulse per second (PPS) accuracy. The method is based on the wide area measurement principle and was verified by laboratory experiments. Then, the methodology has been deployed in the 132/275/400 kV substation and underneath single‐circuit overhead lines in the field. The phasor of system voltage on an overhead transmission line can be successfully derived, and phase‐resolved partial discharge information can be calculated. This non‐intrusive and mobile methodology is effective and efficient for practical field measurements. The method eliminated the needs of connecting to an on‐site system voltage, and this is of great importance for diagnostics research carried out by mobile platforms.

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