Abstract

Gas-insulated metal-enclosed switchgear (GIS) is an important switching equipment in modern power system. Since GIS equipment has a fully enclosed structure, once failure occurs, it will always be followed by a huge economic loss and an adverse social impact. On-site lightning impulse (LI) test is very important to improve the quality of the GIS equipment since it is particularly sensitive to some fixed insulation defects formed in the transportation and installation process. The on-site LI waveform, restricted by the large load capacitance and impulse generator inherent inductance, has a long wavefront time T f compared with standard LI, called non-standard LI. The non-standard LI test has been carried out in the field. But its insulation defect detecting effectiveness is not clear. In this paper, a generating system of impulses with different waveform parameters, including double-exponential impulses with different wavefront times in the range of 0.08 ∼ 23.5 μs and an oscillating LI with wavefront time around 10 μs, was established. The insulation characteristics of SF 6 gas gap with highly inhomogeneous electric field under impulses with different waveform parameters were investigated. Experimental results showed that the insulation defects detecting effectiveness of oscillating LI with long T f around 10 μs is lower than that of standard LI. According to the voltage-time characteristic, it can be inferred that the T f plays an important role in the insulation defect detection. Prospective voltage is introduced to evaluate the insulation defects detecting effectiveness first. The insulation defect detecting effectiveness using the impulse test is reflected in the value of the prospective voltage. The prospective voltage-time characteristics confirm the conclusion that with the increase of impulse voltage T f , the detection effectiveness for GIS insulation is reduced. Consequently the standard or impulse LI test with T f < 1.56 μs is to be preferred for installation detection, because it offers a greater probability of detecting insulation defects.

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