Medium voltage underground cables are widely used in urban area as distribution power lines due to their advantages over overhead cables. Underground cables may suffer from partial discharge because of insulation degradation after certain period of time. In this paper, an improved multi-end partial discharge location algorithm called segmented correlation trimmed mean algorithm is proposed. The algorithm uses segmented correlation technique and trimmed mean data filtering technique to enhance the accuracy of partial discharge location algorithm. The algorithm had been tested in MATLAB environment which consists white Gaussian noise. First, discrete wavelet transform is carried out to suppress noisy signals. Next, segmented correlation technique is applied to the de-noised segmented partial discharge signals. Segmented correlation technique has manipulates partial discharge signals by performing cross correlation process on segmented partial discharge signals in order to reduce memory usage and algorithm execution time. Lastly, trimmed mean data filtering technique is applied to the estimated partial discharge location values to estimate new partial discharge location value. Trimmed mean data filtering technique does statistical process control on estimated partial discharge location values in order to minimize the error of estimated partial discharge location. The segmented correlation trimmed mean algorithm had been compared with the existing multi-end correlation-based algorithm. The result shown that the segmented correlation trimmed mean algorithm has better accuracy than multi-end correlation-based algorithm.

Partial discharge (PD) is one of the most popular failure or breakdown that can happen at high voltage (HV) equipment. PD is the fault that causes the insulation breakdown occurred between two electrodes. It happened or occurred because of the improper insulation, ageing, environment effect and manufacturing defects. The loss of the power will affect consumer and system operation. One of the technique that can measure or detect the PD is by using ultra high frequency (UHF) method for HV equipment insulation condition monitoring and assessment. In this paper, the application of UHF method have been reviewed as the best method to detect PD in transformer, GIS and cable. The UHF method for every electrical equipment is described in order to detect the PD and the laboratory result shows that this method can be considered as suitable technique. Based on this review, the new design in UHF sensor is required in order to improve the sensitivity and bandwidth for PD detection in HV equipment. The valuable parameter such as size and PD frequency range can be used for early stage of designing new the UHF sensor.

In this paper, a series of investigations on sensitivity and bandwidth for four types of Rogowski coil (RC) sensors was demonstrated. The proposed RC sensor design using acrylonitrile butadiene styrene material carries the advantages, such as lighter weight, robust, and higher temperature resistance. The prototype development first was carried out with the assistance of Solidwork 3D computer aided design software and MakerBot 2X 3D printer. Subsequently, the sensors were modeled and simulated using electromagnetic transient program-alternative transient program software environment based on the lumped parameter identification. A single-end measuring technique was used to locate the PD signal on the three-phase medium voltage underground cross-link polyethylene insulated power cable with a 240-mm ² nominal area copper conductor. In order to verify the results achieved from the simulation, an experiment was carried out. This experiment was repeated concurrently for each design of the RC sensors. In order to achieve the best PD detection, the precise selection for the best sensor is paramount. In this case, the results indicated that certain geometrical shape performed better with regard to the detection of the PD signal.

This paper presents de-noising of PD signal using three different techniques; ANN, FFT and DWT. The objective of this paper is to yield the PD signal from the disturb signal which is the combination of PD and noise signal. These signals are generated using EMTP-ATP simulation environment. This research used the straightforward procedure in the de-noising technique. The accuracy of the de-noising is based on the calculation of SNR. The result of this research shows ANN is the best de-noising technique as the calculated SNR is the highest with 0.635938, followed by FFT technique with SNR of 0.452903 and lowest SNR is DWT with -0.154054.

Partial discharge (PD) is an electrical discharge which is one of the most critical breakdown factor that is affecting the electrical equipment. The loss of the power will affect consumers and system operation. High voltage (HV) transformer is one of the equipment’s subjected to phenomena PD. In this paper reviews an application of acoustic methods in transformer and piezoelectric sensors application on PD detection in HV transformer. Based on this review, the new design in acoustic sensor is required in order to improve the sensitivity and bandwidth for PD detection at HV transformer. The valuable parameter such as materials, size, and PD frequency range were discussed in this paper and can be used for early stage on designing new acoustic sensor. This detection method given some benefits on preventing the power electrical system from breakdown.