Search

If an R.M.U. (Ring Main Unit) cubicle is installed, operated and maintained in accordance with current standards and the manufacturer's instructions, the likelihood of internal arcing is reduced, but should not be completely ignored. This article outlines the experimental situations in which arcing can occur and the catastrophic effects seen if R.M.U. is not properly designed for this type of damage. This type of failure can be caused by a fault, abnormal operating conditions or a malfunction and represents a danger during its installation and to persons present. The situations in which this type of failure can occur are presented and experimentally analysed: bi-phase internal arcing in the connections compartment, three-phase internal arcing in the switching compartment, internal arcing in the fuse compartment and single-phase arcing between a phase and the switchgear enclosure. [ABSTRACT FROM AUTHOR]

The basic requirements for the design of a switchgear for main 35–220 kV step-down substations are reliability and efficiency. Switchgear circuits are chosen depending on the number of supply and transit lines and transformers, the substation's place in the power supply system, and the area that can be allocated under the substation construction. The substation switchgear's reliability depends on the circuit type and the equipment to be installed. When designing, as a rule, standard substation switchgear circuit solutions are chosen with often unreasonably overstated reliability indicators and, as a consequence, capital costs. This paper explores the issues of automated choice of the best option for the 35–220 kV substation switchgear circuit, considering its structural reliability and additional costs for the area allocated under the electrical unit. A distinctive feature of the work is a comprehensive accounting of the reliability indicators of the substation and the influence of the layout of switchgear circuits as a whole on the performance indicators of future electrical installations. The developed technique is used at the pre-design stages and allows for reducing further capital, maintenance, and repair costs for electrical units by up to 14.5%. The developed approach is implemented in the original TER CAD software product. [ABSTRACT FROM AUTHOR]

To improve the insulation diagnosis of a medium-voltage (MV) switchgear, we have developed a four-terminal surface current sensor and a method to estimate the direction of partial discharge occurrence. In this method, the accuracy of the direction estimation is improved by referring only to the direct wave, and the error due to noise can be suppressed by calculating the outputs of the four terminals. The experimental results demonstrate that the detection characteristics of the sensor concur well with the theoretical characteristics derived from the detection principle. Additionally, we conducted an experiment using the developed sensor and the new method to detect the surface current generated due to partial discharge occurring in a rectangular enclosure. The results demonstrate that the occurrence direction could be estimated even for a rectangular enclosure. Furthermore, the propagation attenuation of the surface current at the corners of the enclosure was large, exhibiting an attenuation 0.25 times for the worst case. Finally, it was confirmed that noise removal using a wavelet transform could reduce the direction estimation error of the discharge occurrence by approximately half. [ABSTRACT FROM AUTHOR]

In the authors' previous research, a new method for partial discharge detection in the switchgear based on near-field detection was proposed. The content of this paper is the continuation of the authors' previous research. In order to realize the reasonable layout of the near-field magnetic field probe for partial discharge detection in the switchgear, this paper simulates and analyzes the influence of the internal structure of the switchgear on the near-field propagation characteristics of the electromagnetic wave signal generated by partial discharge, and determines the installation position of the near-field probe in the switchgear. Firstly, the propagation characteristics of electromagnetic wave signals in the different media of the switchgear are analyzed, and the switchgear model is established. Then, based on the finite difference time domain method, the influence of different devices in the switchgear on the near-field propagation of the partial discharge electromagnetic wave signal is simulated. The simulation results show that the current transformer, insulator, busbar and cabinet all obviously attenuate the amplitude of the near-field electromagnetic wave signals generated by partial discharge, and the insulator causes obvious signal distortion. Finally, it is determined that the near-field probe can be installed on the inner wall or the right wall near the bottom plate of the switchgear. [ABSTRACT FROM AUTHOR]

In power energy distribution networks, switchgear is considered critical equipment. This is because the act of monitoring the operation and condition of switchgear, as well as performing the required corrective maintenance on any potentially problematic equipment, is critical. A single event may harm thousands of customers over time and pose a significant risk to operational staff. Many considerations must be put in place before using outages to switch down the system since they may raise maintenance costs and disrupt the power supply to users. As a result, proper interpretation of switchgear status evaluations is critical for the early identification of possible faults. Existing ultrasound condition-based monitoring (CBM) diagnostic testing techniques require the tester to manually interpret test data. This study aims to review the status of the recent development of CBM techniques with faults in switchgear. The current trend in electrification will be toward the safety and sustainability of power grid assets, which involves an evaluation of the electrical systems' and components' health and grids for medium-voltage distribution. This work provides a current state-of-the-art evaluation of deep learning (DL)-based smart diagnostics that were used to identify partial discharges and localize them. DL techniques are discussed and categorized, with special attention given to those sophisticated in the last five years. The key features of each method, such as fundamental approach and accuracy, are outlined and compared in depth. The benefits and drawbacks of various DL algorithms are also examined. The technological constraints that hinder sophisticated PD diagnostics from being implemented in companies are also recognized. Lastly, various remedies are suggested, as well as future research prospects. [ABSTRACT FROM AUTHOR]

When an arc fault occurs in a medium-voltage (MV) metal enclosed switchgear, the arc heats the filling gas, resulting in a pressure rise, which may seriously damage the switchgear, the building it is contained in, or even endanger maintenance personnel. A pressure rise calculation method based on computational fluid dynamics (CFD) has been put forward in this paper. The pressure rise was calculated and the arc tests between the copper electrodes were performed in the container under different gap lengths by the current source. The results show that the calculated pressure rise agrees well with the measurement, and the relative error of the average pressure rise is about 2%. Arc volume has less effect on the pressure distribution in the container. Arc voltage Root-Mean-Square (RMS) has significant randomness with the change of arc current, and increases with the increase of gap length. The average arc voltage gradients measure at about 26, 20 and 16 V/cm when the gap lengths are 5, 10 and 15 cm, respectively. The proportion (thermal transfer coefficient kp) of the arc energy leading to the pressure rise in the container is about 44.9%. The pressure is symmetrically distributed in the container before the pressure wave reaches the walls and the process of the energy release is similar to an explosion. The maximum overpressure in the corner is increased under the reflection and superimposition effects of the pressure wave, but the pressure waves will be of no importance any longer than a few milliseconds in the closed container. [ABSTRACT FROM AUTHOR]

Currently, the existing condition-based maintenance (CBM) diagnostic test practices for ultrasound require the tester to interpret test results manually. Different testers may give different opinions or interpretations of the detected ultrasound. It leads to wrong interpretation due to depending on tester experience. Furthermore, there is no commercially available product to standardize the interpretation of the ultrasound data. Therefore, the objective is the correct interpretation of an ultrasound, which is one of the CBM methods for medium switchgears, by using an artificial neural network (ANN), to give more accurate results when assessing their condition. Information and test results from various switchgears were gathered in order to develop the classification and severity of the corona, surface discharge, and arcing inside of the switchgear. The ultrasound data were segregated based on their defects found during maintenance. In total, 314 cases of normal, 160 cases of the corona, 149 cases of tracking, and 203 cases of arcing were collected. Noise from ultrasound data was removed before uploading it as a training process to the ANN engine, which used the extreme learning machine (ELM) model. The developed AI-based switchgear faults classification system was designed and incorporated with the feature of scalability and can be tested and replicated for other switchgear conditions. A customized graphical user interface (GUI), Ultrasound Analyzer System (UAS), was also developed, to enable users to obtain the switchgear condition or classification output via a graphical interface screen. Hence, accurate decision-making based on this analysis can be made to prioritize the urgency for the remedial works. [ABSTRACT FROM AUTHOR]

This paper presents the results of a comparative analysis of the dielectric strength of disconnecting vacuum interrupters operating on air and helium. The breakdown voltage Ud was measured in the pressure range from 8.0 × 10−4 Pa to 3.0 × 101 Pa for air and from 8.0 × 10−4 Pa to 7.0 × 102 Pa for helium, while varying the interelectrode distance from 1.0 to 5.0 mm. Dedicated laboratory workstations were used to determine the actual pressure values in the vacuum interrupters tested and to precisely measure and record the dielectric strength results of the test object. It was found that the helium-filled vacuum interrupter maintains its full dielectric strength in significantly larger pressure ranges, while the air-filled vacuum interrupter loses its insulating properties. Thus, it is possible to make vacuum interrupters based on the working medium associated with pure helium, with larger working pressure ratings. Under such conditions, it is easier to maintain the tightness of the device and to limit cut-off currents and overvoltages associated with vacuum switchgear. [ABSTRACT FROM AUTHOR]