表征绕组特征的参数与绕组变形关系的仿真

Simulation of the Relation between the Characterization Parameters of the Winding and the Winding

为了提升变压器绕组变形判别精度,研究了表征绕组特征的参数与绕组变形关系的仿真方法。利用有限元方法建立表征绕组特征的参数与绕组变形关系的双绕组、同芯式变压器漏磁场模型,通过二维泊松方程混合边值的有限元解分析变压器绕组漏磁场,利用最小二乘算法基于所建立变压器漏磁场模型辨识可表征绕组特征的漏电感参数,通过所获取漏电感值与实际漏电感值相比实现变压器绕组变形判别。通过有限元方法建立变压器绕组仿真模型并分析表征绕组特征的参数与绕组变形关系,仿真结果可知,该方法可有效辨识表征绕组特征的漏电感参数,依据表征绕组特征参数与绕组变形关系实现变压器高压与低压绕组变形的精准判别,判别精度高达99%以上,实验效果表明利用表征绕组特征的漏电感参数在线监测绕组变形具有可行性。

In order to improve the accuracy of transformer winding deformation discrimination,the simulation of the relationship between the parameters characterizing the winding characteristics and the winding deformation is studied.The finite element method is used to establish the double-winding,concentric transformer leakage magnetic field model that characterizes the relationship between the winding characteristics and the winding deformation.The two-dimensional Poisson equation mixed boundary value finite element solution is used to analyze the transformer winding leakage magnetic field,and the least square algorithm is also used.Based on the established transformer leakage magnetic field model,the leakage inductance parameters that can characterize the characteristics of the winding are identified,and the obtained leakage inductance value is compared with the actual leakage inductance value to realize the transformer winding deformation judgment.The finite element method is used to establish a transformer winding simulation model and analyze the relationship between the parameters characterizing the winding characteristics and the winding deformation.The simulation results show that this method can effectively identify the leakage inductance parameters characterizing the winding characteristics,realize the high voltage of the transformer based on the relationship between the characterizing winding characteristic parameters and the winding deformation,and provide accurate discrimination with low-voltage winding deformation.The discrimination accuracy is more than 99%.Experimental results show that it is feasible to monitor winding deformation online by using leakage sensing parameters which characterize winding characteristics.