Electric Power ›› 2024, Vol. 57 ›› Issue (9): 181-193.DOI: 10.11930/j.issn.1004-9649.202309031

• Key Technologies of Urban Power Grid for New Power System • Previous Articles     Next Articles

Multiple Characteristics Criterion Based Incipient Fault Detection of Distribution Systems

Anning WANG1(), Rongqi FAN1, Yang ZHANG2(), Jiachao LIU3, Wei HU3, Shimin ZHONG3, Ke JIA2   

  1. 1. State Grid Shandong Electric Power Company, Jinan 250001, China
    2. School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
    3. State Grid Shandong Electric Power Company Qingdao Power Supply Company, Qingdao 266002, China
  • Received:2023-09-07 Accepted:2023-12-06 Online:2024-09-23 Published:2024-09-28
  • Supported by:
    This work is supported by Science and Technology Project of State Grid Shandong Electric Power Company (No.520602220002).

Abstract:

The fault characteristics of the new distribution system have changed significantly under the high proportion of new energy access, with variable operation modes and limited short-circuit currents. In this regard, arc-type early faults are the signs of short-circuit in the power system.The effective identification of early faults in advance can avoid the problem of short-circuit faults, which is difficult to jump off. Based on the equivalent model of early faults, the paper analyses the electrical quantity characteristics and temperature characteristics of the fault arc, and proposes an arcing high-resistance fault detection method that combines the current and temperature characteristics at the same time. The method integrates the speed of electrical signals and the high sensitivity and reliability of thermal signals, and then based on the composite characteristic quantity fault parameter identification criteria to detect the early faults. The effectiveness of the proposed method is verified comprehensively by simulation in PSCAD, field data and fault test in labs.

Key words: new distribution system, incipient fault, fault detection, arc modelling, composite eigenvalue criterion