1078 / 2019-05-20 13:56:18
Comparative Study of Algorithms for Fast Identification Power Frequency Short-circuit Current in Short Data Window
short-circuit current,amplitude identification,effect comparison,application range
全文录用
Fan Xie / School of Electrical Engineering, Xi’an Jiaotong University
Shaogui Ai / Electric Power Research Institute, State Grid Ningxia Electric Power CO. LTD.
Hanhua Zhang / Electric Power Research Institute, State Grid Ningxia Electric Power CO. LTD.
Yongning Huang / Electric Power Research Institute, State Grid Ningxia Electric Power CO. LTD.
Tengfei Liu / School of Electrical Engineering, Xi’an Jiaotong University
Zhiguo Hao / School of Electrical Engineering, Xi’an Jiaotong University
For limiting the short-circuit current level, the rapid identification of the power frequency short-circuit current in a short-window is the key to fast and accurate response. This paper analyzes the transient characteristics of short-circuit faults, while introduces the basic principles of phaselet algorithm, least squares algorithm and extended Prony algorithm. Based on the transmission system simulation data, this paper analyzed the accuracy and calculated amount of the three algorithms, and explored the influences of three factors such as fault-point voltage phase, sampling frequency and data window length. Synthesizing performance comparison and theoretical analysis, the application range of the three algorithms is divided. The research results provide a reference for the selection of the short-window fast algorithm for identifying power frequency short-circuit current.
重要日期
  • 会议日期

    10月21日

    2019

    10月24日

    2019

  • 10月13日 2019

    摘要录用通知日期

  • 10月13日 2019

    初稿截稿日期

  • 10月14日 2019

    初稿录用通知日期

  • 10月24日 2019

    注册截止日期

  • 10月29日 2019

    终稿截稿日期

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