Statistical Analysis And Application Of Characteristic Gas In Power Transformer Oil

Power transformer is one of the main electrical equipment in power system, and its operation will directly affect the reliability and safety of power system.. Because of the complexity of power transformer structure and the variety and randomness of fault cause, fault phenomenon and fault mechanism, it makes the fault diagnosis of power transformer more difficult.. Therefore to the transformer insulation fault diagnosis, at the present stage through on a regular basis in transformer oil dissolved gas analysis experiment was conducted and a preliminary analysis of the operation situation of transformer and fault development trend. According to the transformer to carry out maintenance work. This paper mainly through all kinds of actual transformer fault case, the three ratio method in transformer insulation fault diagnosis application, and to explore in transformer oil dissolved gas on-line monitoring system application status and existing problems. In Tangshan power supply company as an example, the transformer equipment to carry out condition based maintenance of equipment, combined with chromatographic and charged detection data to carry out equipment condition evaluation. It is pointed out that only the three ratio coding combined with other equipment test data comprehensive analysis in order to draw the true state of equipment, and can not simply be various gas component content dividing three ratio is obtained, should pay attention to the various features of the gas component of growth, draw the correct operation of the equipment. The statistical data of on-line monitoring device for large transformer oil chromatogram spectroscopy. It is found that the dispersion data of online monitoring device greatly, and with the data offline has certain gap. But by contrast to previous off-line data statistics found in the transformer oil chromatogram spectrum on-line monitoring device working normally under the premise, on-line monitoring data although and laboratory DGA data differences, but can reflect the development trend of transformer fault, and can be used as a transformer condition based maintenance of a good auxiliary means.