Improvement of distribution transformer fault analysis using FRA method

The distribution transformers are one of the most expensive components in the electrical power distribution system. During its lifetime, distribution transformers are exposed to several failures. For this reason, it is crucial to continuously monitor its condition. Frequency Response Analysis (FRA) is an advanced electrical test, which is commonly employed to investigate the transformer’s main winding. Moreover, it has been shown to be sensitive to non-mechanical changes such as winding insulation. The measured FRA result needs to be compared with the previous measurement to identify any variation between them. The variation will indicate mechanical changes in the transformer. However, interpreting the variation to determine the type, location, and severity of the suspected failure, requires expertise. For this reason, further understanding of the damage detecting characteristic of FRA is required. In this study, an electrical circuit model is developed based on 33/11kV, 1MVA distribution transformer to investigate the influence of various changes in the winding RLC values on the frequency response. The model is also used to simulate other failures such as winding deformation, bushing and short circuit faults. In addition, the tap changer fault and weakness of clamping structure are also investigated by examining an 11/0.433 kV, 500KVA distribution transformer. Additionally, the transformer ageing and degradation of winding’s insulation is also investigated using different FRA measurement configuration. Findings show that tap changer coking and clamping faults affect the frequency response at less than 2kHz. FRA capacitive inter-winding shows isolation in between 2kHz to 20kHz due to transformer ageing. The frequency response shifting towards lower frequencies at 20kHz to 2MHz due to winding insulation degradation. Also, in this study, the method or interpretation scheme for FRA is obtained. It is a guideline in the form of a flowchart, which is proposed for the first time and helps the engineers in having a better interpretation of FRA results. In conclusion, this study is to improve the understanding on the distribution transformers faults detection using FRA method

Pollution flashover characteristics of coated insulators under different profiles of coating damage

Based on experiments and numerical analysis techniques, this paper aims to investigate the influence of the four different coating damage profiles on the performance of coated 33 kV porcelain insulator strings under polluted and clean surface conditions. The performance of the insulators coated with room temperature vulcanizing (RTV) under partial coating damage and undamaged coating was evaluated. The influence of humidity on pollution flashover was taken into consideration. The ring-shaped, fan-shaped, and random-shaped coating was applied following coating damage. The results showed that the flashover characteristic of the RTV-coated insulators had a significant difference as compared to the normal insulators. Electrical characteristics such as the flashover voltage, critical current, and surface resistance were significantly affected by coating damage distribution and humidity level on the insulators’ surface. The electric field and potential difference were analyzed as well using the finite element method (FEM). The initiation of the arc was observed to appear at the area of insulators where the electric field was the highest. It was also observed that different coating distributions of pollution and humidity levels resulted in a change in the surface pollution layer resistance and an uneven distribution of the electric field. This indicates that the coated insulators’ parameters are directly related to the coating damage distribution on the insulator surface, particularly in the presence of humidity

Interpretation of Frequency Response Analysis for Fault Detection in Power Transformers

Frequency response analysis (FRA) is a method of monitoring a power transformer’s mechanical integrity. However, identifying the type of fault and its severity by comparing measured responses is still challenging and mostly relies on personnel expertise. This paper is taking one step forward to standardize the FRA interpretation process by proposing guidelines based on various international standards and FRA case studies. In this study, the FRA signature is divided into three regions: low-, mid- and high-frequency regions. The deviation from the fingerprint signature for various faults is classified into small, large, and no variations, based on the calculation of the correlation coefficient. The proposed guidelines are developed based on the frequency regions, and the level of variation is represented using a simple arrow method to simplify the interpretation process. A case study is conducted on a three-phase 11/0.433 kV, 500 kVA distribution transformer with a short circuit winding fault to validate the proposed guidelines

Frequency Response Analysis for Three-Phase Star and Delta Induction Motors: Pattern Recognition and Fault Analysis Using Statistical Indicators

This paper presents a new investigation to detect various faults within the three-phase star and delta induction motors (IMs) using a frequency response analysis (FRA). In this regard, experimental measurements using FRA are performed on three IMs of ratings 1 HP, 3 HP and 5.5 HP in normal conditions, short-circuit fault (SC) and open-circuit fault (OC) conditions. The SC and OC faults are applied artificially between the turns (Turn-to-Turn), between the coils (Coil-to-Coil) and between the phases (Phase-to-Phase). The obtained measurements show that the star and delta IMs result in dissimilar FRA signatures for the normal and faulty windings. Various statistical indicators are used to quantify the deviations between the normal and faulty FRA signatures. The calculation is performed in three frequency ranges: low, middle and high ones, as the winding parameters including resistive, inductive and capacitive components dominate the frequency characteristics at different frequency ranges. Consequently, it is proposed that the boundaries for the used indicators facilitate fault identification and quantification

Interpretation of Frequency Response Analysis for Fault Detection in Power Transformers

Frequency response analysis (FRA) is a method of monitoring a power transformer’s mechanical integrity. However, identifying the type of fault and its severity by comparing measured responses is still challenging and mostly relies on personnel expertise. This paper is taking one step forward to standardize the FRA interpretation process by proposing guidelines based on various international standards and FRA case studies. In this study, the FRA signature is divided into three regions: low-, mid- and high-frequency regions. The deviation from the fingerprint signature for various faults is classified into small, large, and no variations, based on the calculation of the correlation coefficient. The proposed guidelines are developed based on the frequency regions, and the level of variation is represented using a simple arrow method to simplify the interpretation process. A case study is conducted on a three-phase 11/0.433 kV, 500 kVA distribution transformer with a short circuit winding fault to validate the proposed guidelines

Understanding power transformer frequency response based on model simulation

Frequency Response Analysis (FRA) has been approved and there is an increased interest in performing electric power transformers tests. The drawback of using the FRA method is that there is no available recognized standard to interpret the obtained results, which depend on personal expertise. For further understanding of the FRA signature of power transformers faults, it was recommended to use lumped or distributed circuit approaches, therefore understanding the fault effect on the FRA signature. This study presents a power transformer model and simulates its FRA. Also, the effect of reducing the model electrical circuit RLC parameters was investigated. The effect of each parameter was determined in the FRA spectrum. The results show a significant change in a specific region for each parameter

Pollution flashover under different contamination profiles on high voltage insulator: Numerical and experiment investigation

This work aimed to study the influence of contamination profiles and humidity on flashover electrical characteristics of polluted insulators. Firstly, the flashover tests on cap and pin glass insulators under four pollution levels represented by salinity were conducted. Eight artificial contamination profiles based on the solid layer method have been modeled for the selected insulators. The numerical analysis has been used to determine the insulator electrical characteristics such as potential, electric field, and power dissipation under proposed contamination profiles using finite element methods (FEM). Next, the power dissipation has been simulated with consideration of thermal stress propagation in locations with high power. Finally, flashover voltage gradient tests have been conducted under various humidity and contamination profiles. The values of the flashover voltage gradient due to pollution were determined as the percentage of the value of the flashover voltage gradient in the clean condition which was identified as the reference point. The numerical model indicated that the initiation of arc generally occurs at area in which the electric field and power dissipation is maximum. It was also observed from experimental results that the flashover voltage gradient under different contamination profiles has different values depends on the location and dimension of the pollution region

Frequency Response Analysis for Three-Phase Star and Delta Induction Motors: Pattern Recognition and Fault Analysis Using Statistical Indicators

This paper presents a new investigation to detect various faults within the three-phase star and delta induction motors (IMs) using a frequency response analysis (FRA). In this regard, experimental measurements using FRA are performed on three IMs of ratings 1 HP, 3 HP and 5.5 HP in normal conditions, short-circuit fault (SC) and open-circuit fault (OC) conditions. The SC and OC faults are applied artificially between the turns (Turn-to-Turn), between the coils (Coil-to-Coil) and between the phases (Phase-to-Phase). The obtained measurements show that the star and delta IMs result in dissimilar FRA signatures for the normal and faulty windings. Various statistical indicators are used to quantify the deviations between the normal and faulty FRA signatures. The calculation is performed in three frequency ranges: low, middle and high ones, as the winding parameters including resistive, inductive and capacitive components dominate the frequency characteristics at different frequency ranges. Consequently, it is proposed that the boundaries for the used indicators facilitate fault identification and quantification

Investigating and Modeling Ageing Effects on Polymeric Insulator Electrical Properties

Polymeric insulators, in particular silicone rubber (SIR) are lightweight, have good hydrophobicity characteristics, and are easy to carry and install. They are commonly used for outdoor insulation in power lines. However, pollution, UV radiation, temperature, discharge, wetness, and stress can cause them to degrade over time, losing their electrical properties. Therefore, evaluating the ageing and degradation of polymeric insulators under different conditions becomes crucial. This paper investigates the ageing effects of the polymeric insulators with differences in pollution, applied voltage, hydrophobicity class, and geometrical structures of insulators. The investigation includes the experimental tests of the insulators’ electrical properties such as leakage current and flashover voltage, after assessing the initial characteristics of insulators based on their age and supply voltage. In addition, the aged polymeric insulator model based on an equivalent circuit model was developed to determine the leakage current and breakdown voltage of aged insulators. Moreover, an artificial neural network model is carried out to predict the critical leakage current and flashover voltage of the insulator under the ageing effect. The experiment results were used to validate the accuracy of the proposed models; with an aggregate error of less than 10%, the proposed models appeared to be satisfactory. These models can serve as a scholarly resource for designing, operating, and maintaining insulators, especially in polluted environments