基于泄漏电流的绝缘子污秽状态预警方法的研究

Warning Method of Insulator Contamination Based on Leakage Current

随着大气污秽程度的增加和超高压和特高压电网的建设和运行,污闪事故严重威胁电力系统的安全运行。为了实时地监测绝缘子表面的污秽程度,科学地预测和评判污闪的潜在威胁,文中通过对ZS-35绝缘支柱加压,在相同盐密和湿度下采集泄漏电流,提取泄漏电流幅值、有效值、等效脉冲以及环境参量相对湿度作为的输入参量,建立了基于径向基神经网络的污秽绝缘子的污秽等级评定模型和污闪预警模型,结果用实验室测得的数据对模型进行了验证,证明了该模型的准确性。

To monitor the pollution level of the insulator surface in time for EHV and UHV power grids and accurately evaluate the potential harm of pollution flashover, voltage was applied upon a ZS-35 insulator to extract the amplitude, RMS value and equivalent pulses of leakage current as well as the environmental parameter relative humidity as input parameters of neural network, so a pollution level evaluation model of polluted insulator and a flashover warning model were established based on radial basis function neural network. The results of the models coincide well with the data measured experimentally, verifying the accuracy of the models.