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Reference: ISH2017_520

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Online insulation monitoring system for gas insulated transformer



Gas Insulated Transformer (GIT) becomes more and more popular in large cities with high population density because of its good performance in terms of fire prevention and explosion protection, etc. GIT is designed with large safety margin, which gives rise to the fact that very few GIT failures have been reported. We traced three failure cases only in the last 30 years in China. However, as the gas insulated transformers in service reach their designed lifetime, online insulation monitoring systems are required to extend their service with enough security margins. This paper has addressed the problems on what to monitor, how to monitor, and how to interpret the monitoring data. A fault model was designed with defects to represent various insulation failure conditions such as hot spots and partial discharges. And the insulation of GIT are included in the defect models. Each defect is implemented separately so that each can be easily inserted into or dismounted from the GIT in test. For each defect, proper monitoring sensors and instruments are designed in the experimental monitoring system. Test data are recorded for further analysis, including the temperature at the defects, the decomposed gas components and concentration, and the partial discharge data. The partial discharge signals come from high frequency sensor on coupling capacitor, ultra high frequency sensors on the tank, and acoustic sensors on the tank. In the study, defects were turned on one by one and the associated signals were recorded and associated with each phenomenon. Such information was fused into an expert system to generate the general criteria for each defect during the operation of normal GIT. Such information and criteria can be used for online monitoring and status evaluation of GIT in service. With that information, gas insulated transformers can continue their service in power grid until the end of their lives.

File Size: 389,2 KB

Pages NB: 6

Year: 2017

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