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Failure risk analysis under switching surges in power transmission systems

Electric Power Systems Research • 2018
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Publication Information
Authors A.H. Hamzaa, Samy M. Ghaniaa, Ahmed M. Emamb, Ahmed S. Shafya
Keywords Insulation coordination Insulation failure Risk analysis Switching overvoltages Transmission lines insulation
Journal Electric Power Systems Research
Publisher Electric Power Systems Research
Volume Electric Power Systems Research 166 (2019) 190–198
Issue Not Available
Pages Not Available
publication.type International
Paper Link Open Link
Supplementary Materials Not Available
Abstract
The insulation of the power transmission systems is exposed to stresses not only during normal operating but also
by the transient overvoltages. Transient overvoltages are originated by different sources such as lightning,
switching and faults. The switching surges have become dominant factor in the insulation design of Extra High
Voltages and Ultra High Voltages systems. Insulation failure probability under transient surges is the main
impressive concern in the studies of insulation coordination and failure risk. In this paper the failure risk of
insulation under switching overvoltages generated during energization of unloaded transmission line are computed
using the statistical approach. In the calculation, both the statistical characteristics of the overvoltages and
statistical distribution of insulation flashover probabilities are tackled. The statistical distributions of energization
overvoltages on a typical 500 kV transmission-line are derived from the results of 100 energization
cases with statistical switching using Alternate Transient Program (ATP). The most important factors affecting
the insulation flashover probabilities and the failure risk are demonstrated. The effects of number of towers in
parallel, the switching overvoltages profile, the front time of the overvoltages waveform and the non-standard
atmospheric conditions on the failure probability are investigated. Failure risk analysis is analyzed using different
probability distribution scheme