Study On The Condition Assessment And Fault Diagnosis For Power Transformer Mainly Based On Power-on State Variables

Transformer is one of the most important devices in electrical power system. So transformer’s reliability directly affects the security and stability of the power system. Taking scientific and reasonable maintenance for transformer is a very effective way to keep the power system in a good condition. Condition Based Maintenance(CBM) is to maintain a equipment with the most suitable way according to its state, and nowadays this kind of maintenance works best and is widely used. Conditon assessment and fault dignosis are the key basis and vital step for CBM. At present, there are plenty methods of conditon assessment and fault diagnosis. But many of them exist some problems, including too long power-off time for transformer, too large workload of assessment and diagnosis, too weak operability and so on. In order to try best to solve these problems, this paper takes a study on the condition assessment and fault diagnosis for power transformer mainly based on power-on state variables. The main contents include:(1)Deeply analysed the power-on state variables of transformer. Firstly introduce every power-on state variable and the state characteristics they express. Then the transformer faults are classified broadly and detailedly respectively, and the power-on and power-off state variables for both classification way are provided and analysed. After that, the relation between fault modes and power-on state variables are particularly studied.(2)Built the model of condition assessment for power transformer mainly based on power-on state variables. This model includes dynamic assessment, regular assessment and precise assessment.In the dynamic assessment, the boundary values of dissolved gas in oil for every voltage grade are estimated according to the monitored gas data of transformers in Gansu province in 2013 and the statistic data of transformers’faults and defects throughout the country. And then different fuzy membership functions are built based on these boundary values. In regular assessment and precise assessment, weights that vary with the changing state variables are created by introducing the dynamic weight based on inverse entropy theory.(3)Built the model of fault diagnosis for power transformer mainly based on power-on state variables. This model includes two step, primary diagnosis and precise diagnosis. In primary diagnosis transformer’s faults are broadly classified into three classes, thermal fault and electrical fault, deformation fault, damp fault and contamination fault. In the precise diagnosis of thermal fault and electrical fault, Rough Set theory(RS) is used to simply the process and reduce the number of power-off state variables that need to be used.(4)Proved that the models of assessment and dianosis are useful and practical by using a transformer case. Condition assessment and diagnosis are made for a faulty transformer by using the models built in this paper. Then the results are compared with pratical situation.