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The finite-difference time-domain (FDTD) method has been widely used for analyzing the EM wave propagation property of partial discharge (PD). However, many studies use Gaussian pulse as the excitation source, which shows few theoretical relations with the EM wave generation mechanism of PD. To simulate the EM wave generated by PD, the electric field distortion caused by the streamer discharges is analyzed. The finite element method (FEM) is used to calculate the fluid model to get the electric distribution alongside the charged air gap. This distorted electric field obtained from the fluid model is applicable as an excitation source of EM wave, which also explains its generation mechanism caused by the time-varying electric field. Because of the limitations of FEM, such as one frequency response and the huge computation complexity for large electric size. FDTD method is a useful tool to approximate Maxwell's curl equations and simulate the EM wave generated by the distorted electric field. In contrast to typical FDTD applications with one excitation, several excitation points should be chosen to simulate the distorted electric field, and they are evenly distributed alongside the streamer path since the EM wave is emitted by a charged gap rather than a point. Thus, this paper proposes a hybrid method that combines FEM and FDTD for the whole process simulation of the EM wave caused by PD. A positive streamer under two types of electrodes is simulated and the frequency spectrums of generated EM time-domain waveforms are also obtained. The proposed method simulates the EM radiation of PDs digitally, which provides a reference for PD monitoring. [ABSTRACT FROM AUTHOR]

To monitor the insulation deterioration of power equipment and realize prompt fault warning systems in air-insulated substations, in this study, we propose a multiple signal classification (MUSIC) algorithm-based partial discharge (PD) localization method with an angle of arrival (AOA) and ultrahigh frequency (UHF)-received signal strength indicator (RSSI). Compared with traditional UHF time-difference-based techniques, this RSSI-based AOA localization method is a more economical solution. In addition, by comparing the measured RSSI vector to a prebuilt reliable reference data set, the MUSIC method can effectively locate the direction of the PD source with high accuracy. Compared with the method that directly determines the smallest RSSI values by several sensors, this method can accomplish localization by fewer sensors without impeding accuracy. Furthermore, the interpolation method was adopted to improve the precision of the relationship curve of AOA/RSSI, which it did with a limited number of sensors. Laboratory tests were conducted to verify the accuracy of the proposed method, and most of the localization errors were less than 1°, which indicates its potential application in the prompt identification of faults regarding the insulation deterioration of power equipment in substations. [ABSTRACT FROM AUTHOR]