Research And Application Of State Detection And Warning System For Electric Disconnector In Substation

Electric disconnectors, mostly outdoor type in substation, are usually exposed to severe external environment such as strong light and rain in the air, which often occur corrosion and clamping stagnation of drive mechanism. The clamping stagnation can produce a rotation angle loss, resulting the improper position of the switch and the severe heating problem. More seriously, it may also cause cracks porcelain, and even rupture, leading to equipment failure. i.e., the events “4.10” and “4.11” causing large area blackouts in power grid of Guangdong province are both induced by the defects of the electric disconnectors for the insufficient monitoring.In addition to the above-mentioned mechanical transmission problems, the problems of the electric limit switch operating mechanism dead, broken gear teeth, improper maintenance debugging mechanism position, the motor internal fault and lack of equal power sources, which will bring instability of opening and closing operation. Thus, these will cause great difficulties of operation and maintenance to meet the safe system operation.At present, a lot of research has been performed for monitoring and condition-based maintenance of substation transformers, circuit breakers and capacitive equipment, but few studies were investigated related to the isolation switch. To effectively determine the presence of abnormal defects of the disconnector, and to ensure its normal operation, there is an urgent need for condition monitoring and early warning of the mechanical transmission and electric operation.Therefore, this paper will study condition monitoring and early warning system of the electric disconnector. The dynamic data of anomalies defects are incorporated with the static data of maintenance and machine account in the condition monitoring. The comparative analysis of status data are then conducted under normal operating conditions and abnormal fault conditions, which can determine whether or not there is an abnormality of the disconnector. By analyzing data trends of the disconnector, we can predict the development trend of failures, make active decisions to prevent occurrence of unexpected problems before the isolation switch failure. The health level of the disconnector will be enhanced, which will be helpful to the safety of the power grid.