HV Cable Intelligent Sensing IoT Technology and Application

In view of the challenges faced by the current HV cable O&M management, such as the growth of equipment scale, the severe security situation, the lack of comprehensive perception on equipment status, and the ability of intelligent analysis and decision-making to be improved, it was proposed to build a HV cable intelligent sensing IoT based on new sensors such as intelligent earthing box, PD intensive care unit, intelligent ground landmark and face recognition system for terminal stations, so as to comprehensively improve the quality and efficiency of HV cable O&M management. A pilot project was built in Hongqiao area in Shanghai, forming typical application scenarios such as IoT intelligent disposal, integration of monitoring and detection data in terminal stations, panoramic intelligent patrol inspection for ensuring power supply.

Reliable detection of pulse arrival time for partial discharge location in HV cable based on improved Allen-Bear algorithm

In multi-sensor data based partial discharge (PD) source location in high voltage (HV) cable, poor reliability of detection of pulse arrival time against noises, waveform distortion, amplitude attenuation is the major barriers to practical application. In this paper, an improved Allen-Bear PD pulse detection algorithm, which combines the advantage of the characteristic functions of the two time-window energy ratio based detection algorithms, is proposed for robust PD location. The most critical contribution of proposed method is the extension of frequency domain component compared to the characteristic functions of the original algorithm. Simulation and physical experiment results demonstrate that the proposed method not only ensures the detection accuracy of the PD pulse arrival time, but also improves the reliability under harsh practical scenarios. It performs significantly better than the existing detection algorithm in terms of anti-noise, anti-waveform distortion, time window length variation, etc. It has significant value for practical applications.

Autonomous Analysis of Infrared Images for Condition Diagnosis of HV Cable Accessories

Infrared thermography has been used as a key means for the identification of overheating defects in power cable accessories. At present, analysis of thermal imaging pictures relies on human visual inspections, which is time-consuming and laborious and requires engineering expertise. In order to realize intelligent, autonomous recognition of infrared images taken from electrical equipment, previous studies reported preliminary work in preprocessing of infrared images and in the extraction of key feature parameters, which were then used to train neural networks. However, the key features required manual selection, and previous reports showed no practical implementations. In this contribution, an autonomous diagnosis method, which is based on the Faster RCNN network and the Mean-Shift algorithm, is proposed. Firstly, the Faster RCNN network is trained to implement the autonomous identification and positioning of the objects to be diagnosed in the infrared images. Then, the Mean-Shift algorithm is used for image segmentation to extract the area of overheating. Next, the parameters determining the temperature of the overheating parts of cable accessories are calculated, based on which the diagnosis are then made by following the relevant cable condition assessment criteria. Case studies are carried out in the paper, and results show that the cable accessories and their overheating regions can be located and assessed at different camera angles and under various background conditions via the autonomous processing and diagnosis methods proposed in the paper.

Measuring the Voltage Dependence of Current Transformers

A setup has been developed to determine the voltage dependence of the ratio error and phase displacement of current transformers (CTs) used for medium- or high-voltage (HV) applications. A shielded HV cable is used to protect the reference CT for the voltage applied to the CT under test. As a first step, a method was developed to determine and correct for the effect of the leakage current through this cable on the ratio error and phase displacement of the reference CT for voltages up to 24 kV.

Measuring the Voltage Dependence of Current Transformers

A setup has been developed to determine the voltage dependence of the ratio error and phase displacement of current transformers (CTs) used for medium- or high-voltage (HV) applications. A shielded HV cable is used to protect the reference CT for the voltage applied to the CT under test. As a first step, a method was developed to determine and correct for the effect of the leakage current through this cable on the ratio error and phase displacement of the reference CT for voltages up to 24 kV.