Impact of noise related waveforms on long term field leakage current measurements

Abstract

Leakage current (LC) monitoring is widely employed in order to investigate electrical surface activity on high voltage (HV) insulators. Long term field monitoring is required in order to obtain an actual view of the phenomena. Therefore any monitoring system is bound to encounter data size problems. A number of solutions have been proposed to address this problem by extracting different values from the measured waveforms as a performance indication. However, a parameter that is fully representative of the waveform is yet to be determined. Hence, measuring and storing of the actual LC waveform is still required on sites for research and monitoring purposes. In addition, field related noise can result to misinterpretation of the actual activity. In this paper, a number of 26089 waveforms, recorded in a 150 kV Substation on four different post insulators that are part of the grid, are investigated. The monitoring period exceeded six years. Different techniques are applied and evaluated on the data set, employing simple numeric criteria and more advanced techniques such as Fourier and Wavelet analysis. Results are presented towards addressing the problems of noise and data size. The study objective is the incorporation of the results in improved leakage current monitoring systems.