Power cables are very critical in electrical power systems as power cables failure can interrupt the electrical flow due to unexpected power failure. There are a few sorts of partial discharge (PD) estimations gadgets in the market. For instance, PD can be distinguished by utilizing Rogowski coil (RC) sensors in the disconnected procedure. The current issue PD signal does not usually occur as a single source. Thus, the analysis of multiple PD sources is required to ensure that the cable insulation is in a healthy condition. PD location technique based on multiple signals in 11kV underground power cable was conducted in this research to estimate the accurate location of the PD signal. Modelling of single power cable in a distance of 10km with the RC sensor is installed at several distances to capture the PD signal that travels along the power cable. By selecting the distance between six RC sensors and synchronous multiple PD signal, the design of the power system has been constructed by using EMTP-ATP software. Multi-point technique based on time difference of arrival (TDOA) was performed in the single line power cable to obtain the PD location. The measurement using multi-point of RC sensor technique is preferred based on the conditions due to the value of velocity elimination. Based on the results, the accurate location of PD Source 1 is detected 501 m along RC sensor A1 to RC sensor A3. In contrast, PD source 2 has been detected 2800.15 m along RC sensor A4 to RC sensor A6 with the percentage error of 0.2% and 0.0053%, respectively. The findings show that the location of multiple PD signal that occurred along the line cable can be detected accurately by using the multi-point technique and TDOA. Hence, the performance of the power system has been improved.

According to partial discharge (PD) damage in the electrodes that are not entirely bridging, the presence of PD in the high voltage (HV) power cable might lead to insulation failure. PD defects can damage cross-linked polyethylene (XLPE) cables directly, which is one of the most critical electrical issues in the industry. Poor workmanship during cable jointing, aging, or exposure to the surrounding environment is the most common cause of PD in HV cable systems. As a result, the location of the PD signals that occur cannot be classified without identifying the multiple PD signals present in the cable system. In this study, the artificial neural network (ANN) based feedforward back propagation classification technique is used as a diagnostic tool thru MATLAB software in which the PD signal was approached to determine the accuracy of the location PD signal. In addition, statistical feature extraction was added to compare the accuracy of classification with the standard method. The three-point technique is also an approach used to locate PD signals in a single line 11 kV XLPE underground power cable. The results show that the statistical feature extraction had been successful classify the PD signal location with the accuracy of 80% compared to without statistical feature extraction. The distance between PD signals and the PD source affected the result of the three-point technique which proved that a lower error means a near distance between them.