Search

Partial discharge (PD) is the symptom of insulation breakdown in power equipment. The high rising steepness of PD current radiates electromagnetic waves which can be coupled with antenna. In this study, an antenna array is applied to PD detection and localisation in air-insulated substations, in which the locations of PD sources are found with time difference of arrival localisation algorithm. The influences of antenna deployment including the size, aspect ratio and shape of antenna array on localisation accuracy are systematically investigated. Three approaches including Cramér–Rao lower bound, numerical simulation of root of mean square error and experiments are adopted to evaluate the localisation accuracy. Three kinds of antenna arrays with diamond, rectangle and Y shapes are designed for locating the coordinates of PD sources. Their localisation performances are compared by these evaluation approaches, and the optimum antenna configurations for coordinate estimation are derived. The results indicate that the optimum array is dependent on aspect ratio of array size. If the aspect ratio is higher than 0.5, the rectangle array gives minimum localisation error and wide bearing ranges with low error. For array with aspect ratio smaller than 0.25, the diamond array is optimum among the three shapes. [ABSTRACT FROM AUTHOR]

Ultra-high-frequency (UHF) method is regarded as an effective approach for partial discharge (PD) detection in gas insulated substation (GIS). The feature parameters representing UHF signal characteristics can be extracted from its waveform, and applied to PD source classification and mixed signals separation. In this study, an UHF signal feature extraction algorithm based on cumulative energy (CE) technique is proposed. The CE functions in time domain (TCE) and frequency domain (FCE) are calculated from UHF waveforms and their fast Fourier transform spectrums, respectively. The mathematical morphology gradient (MMG) operation is applied to TCE and FCE to characterise their rising behavior. The feature parameters including width, area and sharpness are extracted from CEs and MMGs in both time and frequency domain. Moreover, the extracted features are applied to UHF signals classification and mixed signals separation. First, experiments on four kinds of typical defects in a 252 kV GIS are performed, and the classification performance of the extracted features is examined with the acquired signals. Second, by clustering the extracted features with fuzzy maximum-likelihood algorithm, mixed UHF signals originated from multiple PD sources are successfully separated. The results indicate that the proposed features are effective for representing UHF signal characteristics. [ABSTRACT FROM AUTHOR]