倒置式油浸电流互感器受潮过程微水含量动态推演方法

Dynamic Deduction Method of Moisture Content of Inverted Oil Immersed Current Transformer During Damp Process

为在可测特征量的基础上研究受潮过程中电流互感器内部微水的分布及扩散规律,该文提出了一种受潮过程中电流互感器内部微水含量动态推演方法。首先,建立了220k V倒置式油浸电流互感器电-热-流多物理场耦合三维仿真模型,利用有限元分析和多物理场耦合分析等方法,得到了受潮过程中电流互感器内部温度场以及微水含量分布规律;然后,通过分析环境温度对微水扩散的影响,建立了电流互感器内部油纸绝缘中微水含量与取油阀处绝缘油微水含量间的关联关系,并在此基础上,建立了基于回归决策树算法的倒置式油浸电流互感器内绝缘微水含量动态推演模型;最后,搭建了LVB-220W3倒置式油浸电流互感器实验平台,来验证仿真及动态推演模型的有效性。研究结果表明:本文提出的电流互感器内绝缘微水含量动态推演模型计算结果与实验结果的最大偏差为2.51%,可为油纸绝缘设备运维和检测提供一种新的思路。

In order to study the distribution and diffusion law of moisture in the current transformer(TA) during the damp process on the basis of measurable characteristics, this paper proposes a dynamic deduction method of moisture content in the TA during the damp process. Firstly, a three-dimensional simulation model of electric-thermal-fluid multi-physics coupling for 220 kV inverted oil-immersed current transformer(IOCT) is established. By using the finite element analysis and multi-physics coupling analysis, the temperature field and the distribution law of moisture content in the IOCT during the damp process are obtained. Then, by analyzing the influence of ambient temperature on the moisture diffusion, the correlation between the moisture content in the oil-paper insulation inside the IOCT and the moisture content of the insulating oil at the oil intake valve is established. On this basis, the dynamic deduction model of internal insulation moisture content of IOCT based on regression decision tree algorithm is established. Finally, the experimental platform of LVB-220 W3 IOCT is built to verify the validity of the simulation and dynamic deduction model. The results show that the maximum deviation between the calculation results of the dynamic deduction model and the experimental results is 2.51%, which can provide a new idea for the operation, maintenance and detection of oil-paper insulation equipment.