Oil-impregnated Paper Bushing Research Articles

Evaluating the insulation condition of oil‐impregnated paper bushings based on the time constant database

AbstractAssessing the insulation condition of oil‐impregnated paper (OIP) bushings is necessary to guarantee the safe operation of power transformers. Moisture is the main threat to the insulation of OIP bushings. Therefore, accurately estimating their moisture value is crucial to keep power systems running smoothly. However, it has been suggested that the ageing status of OIP bushings should be considered while assessing the moisture. Dielectric frequency‐domain spectroscopy (FDS) has been extensively employed for assessing insulation condition of OIP insulations due to its benefits. A new approach was proposed to assess the insulation condition of OIP bushings using FDS results. Various OIP samples with various moisture levels and degrees of polymerisation (DP) were selected. The extended Debye model (EDM) parameters related to each sample were calculated using their tanδ − f curve. A time constant database (TCD) was created using the obtained time constants of EDM, which includes the dominant time constant and time constant related to the R0 – C0 branch, and their corresponding insulation condition. Then, a method was introduced based on the created TCD to estimate the insulation condition of OIP bushings. The results showed that the average relative error of moisture and DP estimation is 8.33% and 6.32%, respectively.

Influence of Typical Defects on Insulation and Gas Production Characteristics of Oil-Impregnated Paper Bushing

Influence of Typical Defects on Insulation and Gas Production Characteristics of Oil-Impregnated Paper Bushing

Assessing the moisture content of oil‐impregnated paper bushings with a simple and fast method

AbstractPower outages can cause harm to both society and individual health. Among the crucial elements of power systems, power transformers play a vital role, and their failures can lead to incidents and disruptions. According to statistics, almost 50% of the explosions and fires in the power transformer are caused by oil‐impregnated paper (OIP) bushing failures. Moreover, moisture is a crucial factor that affects the health of OIP bushings, and assessing the moisture level in OIP bushings is vital to guarantee the safety of power systems. While the frequency‐domain dielectric spectroscopy (FDS) method has been widely used to assess the moisture content of OIP bushings on‐site, it has the disadvantage of requiring a long measurement time. Therefore, a novel technique was proposed in this study that involves measuring the OIP bushing dissipation factor (tanδ) at 1 Hz to estimate the moisture content in a significantly shorter time. Five samples of OIP with various moisture levels have been selected, and an equation based on the OIPs' value of tanδ at 1 Hz was proposed to assess the moisture level of OIP bushings. Furthermore, the validity of the proposed method was successfully verified, proving its precision and time efficiency.

Investigation on Hot Spot Temperature of Resin-Impregnated Paper High-Voltage Bushing Based Upon Dielectric Loss

The resin impregnated paper high voltage bushing (RHB) has explosion-proof and flame-retardant advantages compared with the oil-impregnated paper bushing. However, the RHB failure is frequently caused by high temperatures, so it is essential to investigate the hot spot temperature of the transformer RHB. Thus, the multi-physics field simulation model of the transformer RHB is developed. Furthermore, the hot spot temperature distribution pattern is obtained. In terms of the transformer RHB temperature rise test, the transformer RHB frequency domain spectroscopy (FDS) is carried out under load and oil temperature variables. In addition, relationships between the transformer RHB hot spot temperature and FDS curves are established. It is illustrated that the inversion method of the transformer RHB hot spot temperature is based on the dielectric loss tangent integral. According to the tanδ curves, the dielectric loss tangent integral and the square of the dielectric loss tangent integral are used as the characteristic parameters for the inversion of the transformer RHB hot spot temperature. The results show that both characteristic parameters have a well-fitting exponential correlation with the transformer RHB hot spot temperature. In addition, this conclusion enables non-destructive measurement of the transformer RHB hot spot temperature to improve the thermal reliability of its operation.

An Enhanced X Model of Oil-Impregnated Paper Bushings Including Axial and Radial Nonuniform Thermal Aging

The X model is a conventional tool of frequency domain spectroscopy (FDS) technology for assessing the insulation state of oil-impregnated paper (OIP) bushings. However, the accuracy and applicability of the X model are questionable because it overlooked the effect of non-uniform thermal ageing, and there are no models and mathematical formulas that can be applied to non-uniform thermal-aged OIP bushings. To solve this issue, an enhanced X model is proposed by considering the radial and axial non-uniform thermal ageing of OIP bushings. The enhanced X model’s mathematical formula was deduced initially. Then, the complex relative permittivity (CRP) of three types of non-uniform thermally aged OIP bushings was tested. Comparing the calculated CRP based on the enhanced X model to the laboratory-measured CRP reveals that the average relative error of the real part and imaginary part of the CRP are 7.24% and 10.94%, respectively, which indicates that the accuracy and practicability of the enhanced X model are good. It is anticipated that the contributions will provide a theoretical foundation for the state assessment of the OIP bushings under non-uniform thermal ageing.

Estimation of Hot-Spot Heating in OIP Transformer Bushings Due to Geomagnetically Induced Current

This paper studies the temperature distribution in the transformer bushing in the presence of Geomagnetically Induced Current (GIC). The thermal stress can significantly affect the transformer bushing reliability and lifespan. However, the existing research works have focused on thermal modeling of transformer bushing due to loading, and the impact of GIC on this valuable apparatus has not been investigated yet. In this paper, the hot-spot temperature (HST) in an oil-impregnated paper (OIP) bushing is studied during the GIC. The harmonic currents at various GIC levels are obtained from the EMTP-RV time-domain simulations using a detailed topological transformer model. Based on a frequency-dependent model of the bushing resistance, the total power loss is calculated by taking into account the GIC, load current, and harmonic currents. Subsequently, the temperature distribution in the modeled bushing is obtained from the finite-element method (FEM), considering all thermal mechanisms, including fluid flow, internal convection, and thermal conduction. In addition, a Thermal Equivalent Circuit (TEC) is developed for the bushing that replicates the FEM results. The simulation results reveal that the bushing HST may exceeds the recommended permissible temperature of the IEEE bushing standard. This situation may result in bushing insulation deterioration and reduction of the bushing lifespan.

A Method for Discriminating the Moisture Status of OIP Bushing Based on Dissado-Hill and GWO-HMM Model

An accurate discrimination on moisture status of oil-impregnated paper (OIP) bushings is crucial for the maintenance and replacement schedule of bushings. Based on frequency-domain spectroscopy (FDS) measurement and Dissado–Hill (DH) relaxation model, this article proposes a hybrid approach of hidden Markov model and gray wolf optimization (GWO-HMM) for MS estimation of bushings subjected to the ununiform moisture distribution and dynamic time-series modeling. First, simulation models of moisture diffusion and FDS of the OIP bushing were constructed using finite element modeling approach. Then, the GWO algorithm was employed to explore dielectric parameters influenced by moisture in the DH model. Then, the GWO-HMMs was adopted as a classification tool to discriminate the MS of the simulation and experimental data of the bushings. Classification results confirm that the average identification accuracies of the proposed method are 97.17% and 96.81% over these two datasets, which demonstrates the effectiveness of the proposed moisture estimate method for OIP bushings.

Insulation Performance and Simulation Analysis of SiO2-Aramid Paper under High-Voltage Bushing.

The long-term safe and stable operation of oil-impregnated paper (OIP) bushings is of great significance to the operation of power systems. With the growth of OIP bushing, its internal insulation will gradually decay. Aramid insulation paper has excellent thermal aging characteristics and its insulation performance can be improved by using nano-modification technology. In this paper, the nano-SiO2 particles were used as the modified additives, and the modified aramid insulation paper was prepared through four steps: ultrasonic stirring, fiber dissociation, paper sample copying and superheated calendering. The microscopic physical morphology and chemical components of the insulation specimens before and after modification were analyzed by atomic force microscopy (AFM), scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS), and an OIP bushing model based on the modified aramid insulation paper was constructed and its electric field distribution was analyzed. The simulation results show that the use of SiO2-modified aramid insulation paper can improve the electric field distribution of OIP bushings and increase the operating life of power transformers.

Partial Discharge Detection and Diagnosis of Transformer Bushing Based on UHF Method

Bushings are essential components in a power transformer where incipient partial discharge (PD) activities and its detection and diagnosis cannot be ignorant. In this paper, an oil-impregnated paper (OIP) bushing is modeled to investigate that the oil gaps between the flange and condenser body in a typical OIP bushing provide a feasible path to trace the electromagnetic signal. As a non-destructive method, UHF (Ultra High Frequency) is proposed to detect 4 typical inside and outside PD defects of 110 kV bushings. To analyze the parameters of different defects, not only phase-resolved partial discharge (PRPD) is presented, but also 16 detailed time-domain and frequency-domain parameters of UHF signal are involved. Then feature extraction and selection are conducted through comparative principal component analysis (PCA) and extremely randomized trees (ET) algorithms. It is revealed that the selected features are representative and ET greatly reduces the amount of data whilst ensuring high accuracy. Fault diagnosis for bushing is finally achieved via support vector machine (SVM) with the selected features. The presented work of bushing PD detection based on UHF sensors provides a complete solution for the bushing diagnosis in potential field application and maintenance.

Online recognition method of partial discharge pattern for transformer bushings based on small sample ultra-micro-CNN network

Oil impregnated paper bushing is the key equipment connecting a transformer and a power grid. Insulation deterioration may cause partial discharge, which poses a great threat to the safe operation of power systems. In order to realize the online diagnosis for partial discharge and automatic identification of insulation defects of transformer bushings, an ultra-micro-convolutional neural network with only more than 3000 parameters is designed, which adaptively extracts partial discharge characteristics based on small samples, so as to judge the defect category and the reasons. The accuracy rate can reach 97.1%, the computational complexity is lower, the real-time performance is stronger, and it can be easily deployed on various embedded platforms.

An IGBA Algorithm-Based Curve Reconstruction Method of Frequency-Domain Dielectric Spectroscopy for OIP Bushing With Nonuniform Moisture Distribution

Oil-impregnated paper (OIP) bushing is essential equipment in traction power supply systems, and its moisture status is directly related to the power transmission of high-speed railway. Also, the moisture distribution in the OIP bushing insulation is usually nonuniform. The frequency-domain dielectric spectroscopy (FDS) method is now widely accepted as the most potential method for evaluating the moisture status of the OIP traction bushing with nonuniform moisture distribution. However, as far as the FDS curve reconstruction of field bushing is concerned, it remains a challenge. In this article, based on the extended Debye model, a new curve reconstruction method (including equivalent circuit and mathematical models) of the bushing dielectric response is proposed. Then, the reconstruction method is converted into a mathematical problem of programming optimization. Based on the advantages of metaheuristic algorithms such as simplicity, flexibility, derivative-free mechanism, and local optimal avoidance, an improved metaheuristic algorithm was used to address the optimization problem. Finally, the proposed method was tested on bushing samples and real bushings. The research shows that the proposed method of curve reconstruction can well characterize the FDS curves of the traction bushing insulation with the nonuniform moisture distribution.

A High-Precision Diagnosis Method for Damp Status of OIP Bushing

An accurate assessment of the damp status of oil-impregnated paper (OIP) bushings is crucial for the power industry to make informed decisions on the maintenance and replacement schedule of bushings. This article proposes a hybrid of the convolutional neural network (CNN) and the hidden Markov model (HMM) for estimating the damp status (i.e., moisture level and moisture source) of bushings especially when nonuniform moisture distribution exhibits in the bushing. First, simulation models of moisture diffusion and frequency-domain spectroscopy (FDS) of the OIP bushing were constructed using the finite element modeling (FEM) approach. Then, CNN was employed to extract informative features from FDS results of the OIP bushing, which is sensitive to both concentrations and sources of moisture. Finally, HMMs were further utilized as a strong stability tool to recognize the damp status of OIP bushings. The proposed method was implemented to identify the bushing damp status using both simulation data and real-life measurements. Identification results demonstrate that the proposed method has high accuracy in determining the moisture level and moisture source of the OIP bushing insulation.

The mathematical model of dissipation factor with temperature–frequency effect for oil-impregnated paper bushings

The accuracy of insulation defect diagnosis based on the dielectric spectrum response is severely influenced by temperature for oil-impregnated paper bushing. The dielectric loss (tan δ) mathematical model with a temperature–frequency factor to restrict the application of the frequency domain dielectric spectrum (FDS) for insulation diagnosis is not clear. In this paper, five temperatures are selected to study the frequency temperature characteristic of the FDS and polarization current for oil-impregnated paper bushing. The experimental results show that the temperature has different effects on the lower frequency (0.001 Hz–1 Hz) and higher frequency (1000 Hz–10 kHz) of FDS. With the increasing temperature, the lower frequency tan δ of 1 mHz–1 Hz shows a better pattern of exponential growth, while the higher frequency tan δ at 1 kHz–10 kHz shows the declining law with the rising temperature. With the increasing temperature, the polarization current shows a better pattern of exponential growth, while resistance obviously shows the declining law of the exponential pattern. The FDS curve of oil-impregnated paper bushings can be amended by the mathematical model of tan δ for the dielectric response on site for accuracy diagnosis.

A Diagnostic Method for Moisture Intrusion Fault in OIP Bushing

Oil-impregnated paper (OIP) bushing is essential equipment in power substations, and moisture intrusion is one of the major faults during its operation. In this article, a method is proposed to diagnose the moisture intrusion fault by the hidden Markov model (HMM) and the shuffled frog-leaping algorithm (SFLA). First, HMM is employed to characterize the probabilistic relationship between the moisture states and frequency-domain spectroscopy (FDS). Then, SFLA is adopted to optimize the locatable results of moisture intrusion point (MIP) in the bushing. Next, extensive simulated data are used for parameter training in the HMM-SFLA model library, with cross-validation for optimal parameters' configuration of HMM and SFLA. Finally, the proposed method was validated by experiment in laboratory and field measurements. The results show that the proposed method can effectively diagnose the MIP of OIP bushings.

Transformer Bushing Thermal Model for Calculation of Hot-Spot Temperature Considering Oil Flow Dynamics

Thermal stress plays a prominent role in the reliability of bushings and contributes to the reliability of power transformers, especially during overload conditions. Thus, exploring the temperature distribution in the bushings is essential. This paper proposes a new thermal model to estimate the hotspot temperature (HST) of oil-impregnated paper (OIP) bushings, based on a modified thermal-electrical analogy model. The proposed model is developed based on the finite element method (FEM) to accurately model all fluid flow and internal convection as well as the thermal conduction mechanism. To this end, convection thermal resistances are defined, and their nonlinear characteristics are calculated for different overloading conditions. The proposed approach is applied on a 245 kV, 800 A OIP bushing to analyze not only the normal loading condition but also short-term overloading beyond the rated current. In addition, the oil flow condition with different load currents and transformer top oil temperatures (TTOT) are investigated. The results show a consistent temperature rise with the typical test conditions with no identified problematic situation. However, during overloading, the temperature rise exceeds beyond the permissible limits recommended by IEEE C57.19. Hence, the overloading of transformers may deteriorate the bushing insulation and reduce its lifetime.

Frequency Domain Spectroscopy for Non-Uniformly Distributed Moisture Detection in Transformer Bushings

Frequency domain spectroscopy (FDS) has been widely used to evaluate the moisture fault of oil-impregnated paper (OIP) bushings. However, there is no reliable method for the location detection of moisture faults in bushings, which frequently initiate its insulation failure. In this study, we developed a distributed FDS measurement method for OIP bushings with two taps. Three times FDS will be measured to acquire the FDS parameters from 0.001 Hz to 10 kHz between the rod (a) and end foil (c), rod and second end foil (b), and second end foil and end foil at room temperature over time. The results show that the $C_{1mHz} /C_{10kHz}$ ratio of $C_{ab}$ is more sensitive for detection of the inner damp layer. The rate of $C_{1mHz} /C_{10kHz}$ of $C_{bc}$ is more sensitive to the outer layer damp bushings. The layer ratios of complex capacitance ( $V_{12}/V_{1}$ and $V_{2}/V_{1}$ ) are key features for the detection of non-uniformly distributed moisture for a capacitance bushing.

Insulation Defect Diagnostic Method for OIP Bushing Based on Multiclass LS-SVM and Cuckoo Search

Frequency-domain dielectric spectrum (FDS) is an effective testing method to reflect the changes of internal insulation status of oil-impregnated paper (OIP) bushing. In field application, the results of FDS test can be both affected by aging defects and damp defects, then the internal insulation defects of OIP bushing cannot be diagnosed in detail, which is an issue of discrimination of multiclass classification. To solve this problem, a method to diagnose the internal insulation defects of OIP bushing is proposed based on multiclass least square support vector machines (LS-SVMs) optimized by cuckoo search (CS) algorithm. First, the multiclass LS-SVM parameters are optimized by the CS algorithm. Then, the training data set is used to train the multiclass LS-SVM model, and the test data set is used for model testing. The experimental results show that the proposed method can effectively diagnose the internal insulation defects in detail, i.e., aging defects and damp defects. In addition, in the proposed method, the CS algorithm is better than the genetic algorithm and particle swarm optimization algorithm, and the convergence rate of the CS algorithm is faster than the other two algorithms.

PD Defect Monitoring for Oil-Impregnated Paper Bushing by Measuring the Inner Pressure

When the inner insulation of oil-impregnated paper bushing breaks down in service, gases decomposed by oil and paper may cause an explosion. The explosion of bushing occurs from time to time because of the lack of an effective monitoring method. In order to provide an effective online monitoring method for the bushing to avoid explosion, this paper presents a method to monitor the PD defect in bushing by measuring the inner pressure of bushing. In this paper, the relationship of variation between characteristic gases content and inner pressure is studied, the effect of inner temperature on inner pressure is analyzed and the method for reducing this effect is also presented, and the monitoring method is proved to be useful by PD tests on a real bushing. The results show that the inner pressure increases obviously due to the generation of characteristic gases by internal discharge in oil-impregnated paper bushing, and the pressure increases with the deterioration of the discharge; although the inner pressure has a great influence on the inner pressure, the influence can be reduced or eliminated greatly by the method of common-mode rejection. According to the results, the internal discharge defect of the oil-impregnated paper bushing can be detected by monitoring the pressure, and the bushing explosion can be avoided.

The Mechanism and Diagnosis of Insulation Deterioration Caused by Moisture Ingress into Oil-Impregnated Paper Bushing

The healthy state of insulation in oil-impregnated bushings is traditionally evaluated by tanδ and capacitance at power frequency and mostly at 10 kV in the test standard. However, there has frequently been insulation accidents induced by moisture ingress (MI) for bushings that have passed the standard. The mechanism and new diagnostic features for MI into bushings were not distinct enough and an accurate test method is urgently needed research. To address this technical gap, a bushing model with a transparent sheath was designed and an ultrasonic humidifier device was adopted to simulate the environment of MI in bushings and recorded by digital camera. The parameters of dielectric dissipation factor, capacitance, partial discharge (PD), frequency domain response, and moisture content in oil were measured at room temperature with time. The results presented that both the increment dissipation factor at low frequency of 0.001 Hz and the increment dissipation factor of 1.2 Um could be used for detecting the earlier insulation defect of oil-impregnated paper (OIP) bushings. The phase resolved partial discharge (PRPD) can serve as the diagnostic basis of the severe state (S3) of insulation deterioration caused by MI into bushings around the phases of 0–117°, 151–303°, and 325–360°. The research findings would provide a useful reference for the condition diagnosis and maintenance of OIP bushings. Especially, the increment detection of Frequency Domain Spectroscopy (FDS) at the frequency of 1 mHz and 10 kHz was recommended firstly for the operative bushings in real sites.

A Parameterization Approach for the Dielectric Response Model of Oil Paper Insulation Using FDS Measurements

To facilitate better interpretation of dielectric response measurements—thereby directing numerical evidence for condition assessments of oil-paper-insulated equipment in high-voltage alternating current (HVAC) transmission systems—a novel approach is presented to estimate the parameters in the extended Debye model (EDM) using wideband frequency domain spectroscopy (FDS). A syncretic algorithm that integrates a genetic algorithm (GA) and the Levenberg-Marquardt (L-M) algorithm is introduced in the present study to parameterize EDM using the FDS measurements of a real-life 126 kV oil-impregnated paper (OIP) bushing under different controlled temperatures. As for the uncertainty of the EDM structure due to variable branch quantity, Akaike’s information criterion (AIC) is employed to determine the model orders. For verification, comparative analysis of FDS reconstruction and results of FDS transformation to polarization–depolarization current (PDC)/return voltage measurement (RVM) are presented. The comparison demonstrates good agreement between the measured and reconstructed spectroscopies of complex capacitance and tan δ over the full tested frequency band (10−4 Hz–103 Hz) with goodness of fit over 0.99. Deviations between the tested and modelled PDC/RVM from FDS are then discussed. Compared with the previous studies to parameterize the model using time domain dielectric responses, the proposed method solves the problematic matching between EDM and FDS especially in a wide frequency band, and therefore assures a basis for quantitative insulation condition assessment of OIP-insulated apparatus in energy systems.