Grease Quality Issues on Middle Voltage Switchgear: Corrosivity, Resistivity, Safety and Ageing

Grease products recommended by OEM for conventional 11kV switchgears are generally trusted. Some disadvantages might however exist among them or their supply could be insufficient and lead to use of non-OEM-recommended grease. This paper reports analysis methods to evaluate both types of grease that were recently used in the switchgears at local electrical distribution stations owned by Tenaga Nasional Berhad. Hardened, greenish and severely irritating greases probably caused by incompatible compounding, electrochemical reaction, and hazardous components, respectively, were among common problems faced by workers. Eight physical tests and four chemical tests were conducted on 10 grease samples using thermogravimetry, switchgear rig, gas chromatography and infrared spectroscopy besides other equipment and standard methods. Grease stability, oil bleeding, flammability of grease droplet and dropping point were among the characteristics determined in the analyses. The results reveal copper corrosion, chemical change, instable and inconsistent grease, and toxics in grease, which surprisingly included the OEM-recommended one. ABSTRAK: Produk gris yang disyorkan oleh Pengeluar Peralatan Asal (OEM) bagi gear-suis konvensional 11 kV secara umumnya dipercayai ramai. Kemungkinan terdapat kekurangan pada produk-produk tersebut ataupun bekalan gris mereka yang tidak mencukupi telah mendorong kepada penggunaan gris yang tidak disyorkan oleh OEM. Kaedah analisis kajian ini melaporkan tentang kedua-dua jenis gris yang kebelakangan ini digunakan oleh Tenaga Nasional Berhad pada gear-suis di stesen pencawang elektrik. Gris mengeras, berlumut dan menjengkelkan mungkin disebabkan oleh sebatian bahan yang tidak sesuai, tindak balas elektrokimia dan komponen yang tidak selamat, masing-masing adalah antara masalah yang dihadapi oleh para pekerja. Lapan ujian fizikal dan empat ujian kimia telah dijalankan pada 10 sampel gris menggunakan termogravimetri, pemakai gear-suis, kromatografi gas dan spektroskopi inframerah selain alatan lain dan kaedah-kaedah piawai. Antara ciri-ciri yang dikaji dalam analisis ini adalah kestabilan gris, sifat lelehan minyak, sifat mudah terbakar titisan gris dan takat rendah gris. Hasil kajian mendapati gris ini menyebabkan tembaga terhakis, sifat kimia berubah, sifat gris yang tidak stabil dan mudah berubah, dan juga beracun memberi kejutan kerana pihak OEM tetap mengesyorkan gris jenis ini

Partial discharge in medium and high voltage electrical devices

Partial discharges (PD) are small electrical sparks or pulses that occur within the insulation of medium and high voltage electrical devices. These pulses will partially bridge the gap between phase insulation to ground or phase to phase insulation. These discharges erode insulation and eventually result in insulation failure. There are three types of discharges for insulation that are internal discharges, corona and surface discharge

Using diagnosis gas analysis as a tool for power transformer maintenance

The importance of Diagnosis Gas Analysis (DGA) has been recognized by electrical industry nowadays as one of the tools for power transformer maintenance to monitor the performance of transformers and provide early information about the health of a transformer. The lifespan of a transformer depends on the condition of the transformer oil. Transformer problem causes an increase in temperature of transformer components, thereby increasing the temperature of the insulating. When the oil is exposed to heat, it will result in the formation of a number of gases dissolved in transformer oil. The purpose of this research is to investigate the relationship between dissolved gases in transformer oil and its relationship to the damages suffered by the transformer. This research used oil samples taken from a number of power transformers installed in Tenaga Nasional Berhad, an electrical utility company in Malaysia. Oil samples were sent to a laboratory for analysis. This research is aimed at finding the causes and consequently identify damages to the components by using five methods of interpretation using the DGA namely Rogers Ratio Method, Doernenburg Ratio Method, IEC Method Ratio, CIGRE Ratio Method and Duval Triangle Method Ratio Method. Three actual cases are discussed in this thesis based on the investigation and repair works on 132kV and 275kV transformers. It is found that DGA can be used to locate defects in the components of the transformer

Trending of SF6 decomposition by-products characteristics under artificially induced PD in GIS

This work aims to study the decomposition of Sulfur Hexafluoride (SF6) and describe the energy of partial discharge (PD). It is also aimed to identify feature or key gases generated under the activity of discharge induced by artificially introduced insulation defects. Different configurations of four types of defects were used in the discharge chamber, and the analysis of decomposition components were employed to detect the PD. The variation of decomposition by-products along the stress duration under different levels of PD energy were studied, and key gases generated under each type of defect have been proposed. A series of experiments have been conducted using experimental platform including testing equipment, discharge chamber and PD measurement equipment. The applied voltage was gradually increased beyond the PD inception voltage after each sampling throughout the energisation duration to study the correlation of discharge energy with concentration and amount of generated products. Decomposition by-products, detected using Fourier transform infrared spectroscopy (FTIR), have been analyzed to reveal the relationship with the energy of PD. Results have shown that products such as SO2F2, SOF2, CO2 and C3F8 were generated by some defect configurations at different rates, and sulfur-containing products are more stable and correlated with the PD level. Analyses of the characteristics of decomposition by-products can be used to effectively assess the condition of SF6 gas insulated equipment (GIE)

Design of GIS defects for partial discharge induced SF6 decomposition

In this paper the experimental setup including the design of artificial defects to implement the partial discharge (PD) study on sulfur hexafluoride (SF) decomposition is discussed. This work aims to clarify the steps of the experimental arrangement followed to obtain decomposition results under PD of three categories of insulation artificial defect. The experimental method is explained from the design stage until the sample analysis stage, including the experimental platform and procedures. The design details include the amount and configuration of defects used, testing platform, aging time and power ratings. The experimental procedures include the design, test platform, equipment utilized, atmospheric conditions, and sample analyses. The proposed procedures suggest that valid and reliable results could be achieved through a series of experiments on SF decomposition that emulate the actual defects in a real gas insulated switchgear (GIS) chamber. This work can be useful in providing testing procedures applied to study the decomposition of SF under the presence of PD sources

Investigation of SF6 decomposition under partial discharge induced by protrusion defect

The aim of this paper is to compare the decomposition characteristics of sulfur hexafluoride, using the study of decomposition by-products, under AC partial discharge of three protrusion defect configurations. This comparison can reveal the influence of quantity, size, and material of the protrusion defect on the insulation status of GIS and demonstrate the most severe configuration by analyzing the by-products. In literature, previous researchers have shown that there is a direct relationship between the generated products and the amount of PD. In this analysis, the effect of each configuration was achieved by using the important relationship between the concentration of decomposition products and the concentration ratio of SOF/SOF with the level of PD along with the stress duration. Using a coaxial gas chamber, an experimental platform was set up using various artificial protrusion defects to simulate partial discharge initiation in GIS. The applied voltage was gradually increased from the initial discharge until the breakdown over the aging cycle. Gas samples were obtained every 18 hours and byproduct gases were detected using Fourier transform infrared spectroscopy. Results show that the amount and concentration of products and the SOF/SOF ratio have shown interesting trends. It is concluded that the severity of the defect increases with the increase of the quantity and size of the defect. The study of the impact of protrusion, as the common form of defect in GIS, reveals the partial discharge severity in terms of produced by-product gases, and their concentrations are directly related to the configuration of the protrusion defect

Grease quality issues on middle voltage switchgear: corrosivity resistivity safety and ageing.

Grease products recommended by OEM for conventional 11kV switchgears are generally trusted. Some disadvantages might however exist among them or their supply could be insufficient and lead to use of non-OEM-recommended grease. This paper reports analysis methods to evaluate both types of grease that were recently used in the switchgears at local electrical distribution stations owned by Tenaga Nasional Berhad. Hardened, greenish and severely irritating greases probably caused by incompatible compounding, electrochemical reaction, and hazardous components, respectively, were among common problems faced by workers. Eight physical tests and four chemical tests were conducted on 10 grease samples using thermogravimetry, switchgear rig, gas chromatography and infrared spectroscopy besides other equipment and standard methods. Grease stability, oil bleeding, flammability of grease droplet and dropping point were among the characteristics determined in the analyses. The results reveal copper corrosion, chemical change, instable and inconsistent grease, and toxics in grease, which surprisingly included the OEM-recommended one

Classification of partial discharge sources by SF6 decomposition by-products

This paper studies the decomposition characteristics of Sulfur hexafluoride (SF6) under partial discharge (PD) of three common types of defects in gas-insulated switchgear, and classifies the type of defect based on the byproducts. To extract the effect of each defect on insulation gas, the decomposition characteristics under partial discharge of two protrusion, free conducting particles and fixed conducting particles defect configurations were studied. The generated products and their concentrations were used as feature parameters in the support vector machine (SVM) algorithm in Python environment to predict the type of defect causing the PD. The artificial defects were designed and placed in a coaxial gas chamber simulating a GIS configuration. During the stress cycle of up to 126 hours, the applied voltage was regularly increased in steps and hence higher PD levels were measured. Gas samples were collected every 18 hours and were analyzed using Fourier transform infrared (FTIR) spectroscopy gas analyzer. Results have shown that the decomposition of SF6 under the three defects are not the same and the SVM was successfully able to identify the type of the defect based on the supplied gas concentrations

Fault Classification System for Switchgear CBM from an Ultrasound Analysis Technique Using Extreme Learning Machine

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