• DocumentCode
    3448421
  • Title

    Modeling of TCC-based protective devices

  • Author

    Li, Jun ; Butler-Purry, Karen L. ; Benner, Carl

  • Author_Institution
    Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
  • Volume
    1
  • fYear
    2003
  • fDate
    7-12 Sept. 2003
  • Firstpage
    150
  • Abstract
    Accurate fault location information helps operator and utility personnel to expedite service restoration, reduce outage time, operating cost and customer complaints. The power system automation lab (PSAL) at Texas A & M University has developed three modules to locate faults in radial distribution systems. These modules use a fuzzy logic approach in which each module computes a possibility value for each line section in a distribution system. Possibility values represent the possibility a line section has a fault. By aggregating these possibility values, the final possibility value for each section can be computed. In order to develop an aggregation method and verify the validity of the three modules, data that represent currents and voltages measured at the substation of a radial distribution system during fault conditions are needed. Also system information such as equipment parameters, protective device settings and phase distribution of line sections must be known. Because this information is not publicly available from a real system, generating this data through simulation of a radial distribution system with protective devices is required. One difficulty in this simulation is the lack of models in existing circuit simulation software such as ATP and MATLAB for protective devices controlled by time-current characteristics (TCC). This paper proposes a method to model TCC-based protective devices. SIMULINK and SimPowerSystems (SPS) blockset of MATLAB were used to model the system. S-functions, special type functions that interact with SIMULINK´s equation solvers, were used to model the protective device control logic. The IEEE 34-bus test feeder was used to show the validity of the modeling method. The results show the modeling methodology works accurately.
  • Keywords
    fault location; fuzzy logic; power distribution faults; power distribution protection; power engineering computing; IEEE 34-bus test feeder; MATLAB; S-functions; SIMULINK; SimPowerSystems; aggregation method; circuit simulation software; equipment parameters; fault location; fuzzy logic approach; phase distribution; power system automation lab; protective device control logic; protective devices; radial distribution systems; time-current characteristics; Circuit faults; Circuit simulation; Costs; Fault location; MATLAB; Mathematical model; Personnel; Power system modeling; Power system protection; Power system restoration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transmission and Distribution Conference and Exposition, 2003 IEEE PES
  • Print_ISBN
    0-7803-8110-6
  • Type

    conf

  • DOI
    10.1109/TDC.2003.1335173
  • Filename
    1335173