Interaction between Arc and Network in the Itrv-Regime

  • W. Hermann
  • K. Ragaller
Part of the Earlier Brown Boveri Symposia book series (EBBS)


A theoretical study of the intensive interaction between a SF6-circuit breaker and the high voltage network during the itrv-regime is presented. The influence on the recovery voltage of the time variation of the arc voltage and the arc current before and after current zero are analyzed using as an example the normal short line fault. The tools for a theoretical study of the interaction are described: a physical arc model which is applicable to the thermal interruption mode and a simplified circuit representation of the network situation in which an itry appears.

The variations of current and voltage across the circuit breaker in the close neighbourhood of current zero are presented for the tf and the slf with different types of itrv. It is shown that the inherent voltage oscillation of the itry is transformed to a steadily increasing variation on a strongly reduced voltage level.

Different network configurations yielding an itry are calculated to explore the consequences of the superimposed itry wave on the current limit of a circuit breaker. Tests are simulated using existing test standards for a short line fault as well as proposed values for the itry to determine the influence of the itry on the range of application of a circuit breaker. It turns out that a SF6 circuit breaker which masters the slf according to present test standards, has no problem in mastering tests including itry according to an IEC-proposal. In some cases the breaking limit is even raised compared to present slf test specifications.

The influence of the quantitaties which mainly determine the effect of the itry on a circuit breaker, the time to the first peak and the value of the reflecting capacitance is analyzed.


Circuit Breaker Thermal Limit Ohmic Heating Fault Current Source Side 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1978

Authors and Affiliations

  • W. Hermann
    • 1
  • K. Ragaller
    • 1
  1. 1.Brown Boveri & Company Ltd.BadenSwitzerland

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