Localization of multiple partial discharge sources in air-insulated substation using probability-based algorithm

Ultra-high-frequency (UHF) sensing technique has been introduced to detect and localize partial discharge (PD) sources in air-insulated substation (AIS). This paper presents a probability-based algorithm to localize multiple PD sources which may occur simultaneously in different power equipment. Assuming that the time difference of arrival (TDOA) between all pairs of antennas in a array are normally distributed, the probability density function (PDF) of PD source coordinates can be obtained by substituting the linearized form of time difference equations into PDFs of TDOAs. When large number of PD signals are recorded, the joint PDF (JPDF) can be calculated from the product of PDF of each TDOA. Then the PD coordinates to be solved are regarded as with highest probability, and can be solved by taking the derivative of JPDF. In the case of multiple PD sources, mixed UHF signals are separated by clustering the TDOA vectors with K Means clustering method. PD experiments are performed to test the presented algorithm, and the localization accuracy of proposed algorithm is compared with other typical methods such as Newton-Raphson, Particle Swarm Optimization and plane intersection method. The results indicate that the probability-based localization algorithm reasonably integrates the TDOAs of continuous signal sequence, which can effectively reduce the influence of TDOA estimation errors and improve the localization accuracy.