State assessment method for transformer under DC bias based on gray cloud model

In order to evaluate the influence of DC bias on the operating state of transformer, a state assessment method for transformer based on gray cloud model is proposed. Firstly, the method determines the maximum and minimum values, the distortion rate and the DC component of the magnetizing current as the evaluation indicators, and uses a modified analytical hierarchy process to clarify the weight of each indicator in the evaluation. Meanwhile, considering that single unqualified indicator being covered by the qualified indicators possibly, the variable weight theory is used to increase weight of unqualified indicators dynamically. Finally, the gray cloud model is used to calculate the index clustering coefficient to determine what operating state the transformer is in. The simulation model is used to obtain the magnetizing current under the influence of different DC bias. Using above data to evaluate the operating state of transformer, the effectiveness of method is verified.