Polarization And Depolarization Current Research Articles

Residual LSTM-based short duration forecasting of polarization current for effective assessment of transformers insulation

The empirical application of polarization and depolarization current (PDC) measurement of transformers facilitates the extraction of critical insulation-sensitive parameters. This technique, rooted in time-domain dielectric response analysis, forms the bedrock for parameterization and insulation modeling. However, the inherently time-consuming nature of polarization current measurements renders them susceptible to data corruption. This article explores deep-learning-based short-duration techniques for forecasting polarization current to address this limitation. By incorporating spatial shortcuts, the residual long short-term memory (LSTM) network facilitates the seamless propagation of spatial and temporal gradients. Furthermore, the relative forecasting assessment of the proposed residual LSTM model’s performance is made against traditional LSTM, attention LSTM, gated recurrent units (GRU), and convolutional neural network (CNN) models. Thus, optimal model selection strategies are evaluated based on their capability to capture extended dependencies and short-term information present in the data. In addition, the Monte Carlo dropout prediction is employed to estimate uncertainty in polarization current forecasts. The findings demonstrate that the proposed residual LSTM network model for polarization current forecasting yields the lowest error metrics and maintains prediction consistency over the testing duration. Thus, the proposed approach significantly reduces PDC measurement time, providing an effective means to develop proactive maintenance strategies for evaluating the insulation condition of transformers.

DC Electric Field Effect on Conductivity and Interface Charge of Oil-Paper Insulation

Understanding the effect of electric field strength on conductivity and interface charge is very important for the converter transformer design, operation and maintenance. This paper studies the DC electric field effect sensitivity on conductivity and interface charge of “liquid–solid” oil-paper insulation. Firstly, polarization and depolarization current (PDC) and conductivity of mineral oil, oil-immersed pressboard and “liquid–solid” oil-paper insulation is measured. secondly, interface charge characteristics is calculated. Last, the influence mechanism of DC electric field and moisture on interface charge density and conductivity is analyzed. Results show that PDC curve of mineral oil increases with electric field, while mineral oil conductivity decreases and then increases with DC electric field strength. PDC curve and conductivity of oil-immersed pressboard and “liquid–solid” oil-paper insulation increases with moisture content and DC electric field. Nevertheless, “liquid–solid” oil-paper insulation with low moisture content increases rapidly and then tends to be stable, while that with high moisture content keeps increasing exponentially. Interface charge density of “liquid–solid” oil-paper insulation increases with DC electric field strength and decreases with moisture content. Compared with interface charge density calculated by Maxwell-Wagner Equation (M-W Equation), error percentage in low moisture content is high, indicating that interface charge density effect on converter transformer “liquid–solid” oil-paper insulation should be taken into consideration in structure design and operation maintenance.

Determination of Dielectric Models Based on Effective Multi-Exponential Fittings

In high-voltage (HV) transmission and distribution systems, HV apparatuses are subjected to electrical, thermal, and mechanical stresses that deteriorate the insulation performance. The polarization and depolarization current (PDC) measurement is an effective tool used for evaluating insulation performances. The depolarization current represented by the summation of the discharge currents with the different time constants can be utilized for the development of the dielectric model based on the extended Debye’s model (EDM). This paper presents effective techniques for determining the dielectric model. Iterative approaches with predetermination of the time constants and least squares methods (either linear ordinary or percentage ones) were utilized to fit the depolarization current in the form of multi-exponential functions. The fitting parameters determined by the proposed method with the linear ordinary least squares (OLLS) method and provided by commercial software agree very well only in the high current and beginning range. Application of the linear percentage least squares (PLLS) method shows better accuracy than that of the OLLS method, and the deviation from the measured one in the low current range and the late measuring time were reduced significantly. The fitted current by this proposed technique with the PLLS method agrees well with the measured current throughout the whole recording time, even in the low current and late time range. From the accurately fitted currents, the dielectric model and the dielectric loss factors can be determined precisely, and the insulation condition of HV equipment can be evaluated properly.

Thermal Aging-Based Degradation Parameters Determination for Grid-Aged Oil Paper Insulation

Elevated thermal stress-related aging is significant on the oil-impregnated paper (OIP) used as insulation in high-pressure gas cables (HPGCs). The aim of this article is to develop a cheap alternative for lab dielectric measuring and characterizing temperature-dependent parameters for OIP. First, this article derives the operating thermal conditions of the grid-aged cable based on IEC standards after analyzing the loading data using machine learning techniques to determine the elevated temperature levels for the experiments. Second, a novel lab-fabricated inexpensive electronics circuit is developed for polarization and depolarization current (PDC) measurements which can be adapted for such measurements over expensive commercial devices. From the measured parameters, an extended three-branch Debye model is optimized using a developed error function approach based on the Akaike information criterion (AIC) and goodness of fit. The model indicated a reduction in the branch resistance with temperature elevation and aging, whereas the branch capacitance revealed an increasing trend. The resultant relaxation time (RC) showed a decrease overall. Last, a short-duration frequency domain spectrum was analyzed and extrapolated to obtain parameters for a wide range of frequencies and fit in a Cole–Cole model, derived for oil-paper insulation. The time constants obtained from this model also confirmed a reducing trend across the temperature and aging variations and the model parameter, the alpha coefficient showed a decreasing trend. Last, the effect of the measured dielectric parameters is reflected with breakdown values to investigate the effect of temperature on the electrical life of insulation.

Quantitative Evaluation of Thermal Ageing State of Cross-Linked Polyethylene Insulation Based on Polarization and Depolarization Current

The widespread use of cross-linked polyethylene (XLPE) as insulation in cables may be attributed to its outstanding mechanical and dielectric properties. In order to quantitatively evaluate the insulation status of XLPE after thermal ageing, an accelerated thermal ageing experimental platform is established. Polarization and depolarization current (PDC) as well as elongation at break of XLPE insulation under different ageing durations are measured. XLPE insulation state is determined by the elongation at break retention rate (ER%). Based on the extended Debye model, the paper proposed the stable relaxation charge quantity and the dissipation factor at 0.1 Hz to evaluate the insulation state of XLPE. The results show that the ER% of XLPE insulation decreases with the growth of ageing degree. The polarization and depolarization current of XLPE insulation will increase obviously with thermal ageing. Conductivity and trap level density will also increase. The number of branches of the extended Debye model increases, and new polarization types appear. Stable relaxation charge quantity and dissipation factor at 0.1 Hz proposed in this paper have a good fitting relationship with ER% of XLPE insulation, which can evaluate the thermal ageing state of XLPE insulation effectively.

Reinforcement Learning-Based Genetic Algorithm for Aging State Analysis of Insulating Paper at Transformer Hotspot

The aging state evaluation of insulating paper at the transformer hotspot is a pain point in the industry. To address this issue, the modified dielectric response (MDR) model and the reinforcement learning based genetic algorithm (RLGA) are proposed to analyze the aging state of insulating paper at hotspot. Firstly, the aging state related polarization and depolarization currents (PDC) of transformer insulation are collected. Then the MDR model is reported to describe the PDC property of insulating paper. The RLGA is later proposed to search the optimal model parameters defined in MDR to characterize the aging state of insulating paper at hotspot. Verification results present the feasibility and validity of extracted optimal model parameters for aging analysis. Furthermore, the quantitative correlation between these parameters and the aging state of hotspot is analyzed. Regarding this, the present work provides a potential method for obtaining aging information of insulating paper at hotspot.

Assessing Aging Status and Type of XLPE Cable Insulation With a Graphic Approach Based on PDC Measurement

The polarization and depolarization current (PDC) measurement has been widely used to assess the aging degree of cross-linked polyethylene (XLPE) cables. However, the aging type identification of XLPE cables has not been fully considered. In this study we conduct PDC measurement on thermal-aged and water tree-aged XLPE cable samples respectively, upon which a graphical approach to assess the insulation condition and distinguish the aging type of XLPE cables is proposed. First, to designate the evaluation indexes of the insulation condition, multiple PDC measurement based dielectric parameters are considered. Then, to reflect the sensitivity of each evaluation index to the condition of XLPE cable, a combined weighting method based on the group fuzzy analytic hierarchy process (GFAHP) and entropy method (EM) is introduced. Furthermore, the improved radar chart method (RCM) based graphical approach is proposed to comprehensively and intuitively characterize the evaluation indexes. Finally, the aging degree of the XLPE cable samples is quantitatively assessed by calculating the area of the polygon in the chart. Simultaneously, utilizing the position of the areal coordinate and the shape characteristic parameter of the polygon, the thermal-aged and water tree-aged samples are effectively distinguished.

Aging State of Stator Bar Insulation Based on the Entropy Weight and Dielectric Response Methods

This article describes a novel research method for evaluating the aging state of the primary insulation material of large generator stator bars based on combining dielectric response methods with the entropy weight method. Vacuum pressure impregnation (VPI) epoxy-mica insulation specimens subjected to different electrical aging time periods were characterized via frequency domain spectroscopy (FDS), polarization and depolarization current (PDC), and thermal stimulated depolarization current (TSDC) tests. The comprehensive characteristic (VPI) parameters obtained by calculating the characteristic dielectric response parameters using the entropy weight method were used to describe the aging state of the VPI epoxy-mica insulation. The results show that during electrical aging, microcosmic structural variations within the insulation directly manifested as changes in the characteristic dielectric response parameters and indirectly affected the comprehensive evaluation parameters of the entropy weight method.

Improving the polarisation and depolarisation current measuring method to avoid ground wire interference

The ground wire is significantly interfered by the current above 1 μA in the industrial field during the traditional polarisation and depolarisation current (PDC) measurement. This paper explains a method to test PDC from high-voltage wire using a principle of equipotential picoammeter, which is completely isolated from the ground wire and connected in series with the high voltage wire. In this method, a device is designed with a multi-range automatic switching function. The device can automatically switch the test range current from 1 pA to 10 mA with a resolution of 1 pA. To demonstrate the device and effectiveness of this new method, the traditional and the proposed new device are used to test the PDC of cable samples in the laboratory as well as in an industrial environment. It is worth noting that there is almost no interference on the Earth wire in the laboratory environment but massive interference in the industrial environment using a traditional method of PDC measurement from ground or Earth wire. The new method of high-voltage testing can efficiently eliminate the interference and accurately measure PDC in a strong industrial interference environment. Furthermore, the wiring of this new method and device is relatively simple, which is convenient for industrial applications.

Polarization and Conduction Characteristics of Mineral Oil and Natural Ester Mixed with Nanoparticles

Mineral oil (MO) has been widely used in transformers because of its reasonable price and acceptable properties. Currently, alternative liquid insulations have been proposed with some excellent properties. Therefore, the mineral oil characteristics need to be enhanced for high performance to compete with such alternative liquid insulations. This paper aims to study the power frequency dielectric dissipation factor (tanδ) along with polarization and depolarization current (PDC) characteristics of the mineral oil-based nanofluid and natural ester (NE)-based nanofluid. Besides, Fourier-transform infrared spectroscopy (FT-IR) measurement of the test specimen was performed. Titanium dioxide (TiO2) and zinc oxide (ZnO) with 0.01% and also 0.03% volume concentration were used to mix with the unmodified liquid to create liquid insulation-based nanofluid. Then, unmodified mineral oil, unmodified natural ester, mineral oil-based nanofluid, and natural ester-based nanofluid were comparatively investigated. Tanδ at power frequency and the PDC characteristics of such liquids were examined. For PDC measurement, TiO2 clearly affected the polarization current and conduction loss factor, whereas ZnO evidently impacted the depolarization current and polarization loss factor. In the case of FT-IR test results, there was no significant change when the modified insulating liquid was compared with those of the unmodified insulating liquid.

Effects of Temperature Gradient Induced Aging and Moisture Distribution on Dielectric Response Measurement for Transformer Insulation

Internal temperature distribution of an oil-immersed transformer is not uniform, resulting in an axial moisture gradient. Thus, the internal insulating paper ages unevenly with the synergetic impact of temperature and moisture. To examine the aging characteristics and moisture dispersion mechanism of insulating paper in a nonuniform system. A discretized aging kinetic model is proposed to analyze the nonuniform aging impact of insulating paper. Then, dielectric response spectroscopy (DRS), including frequency-domain spectroscopy (FDS) and polarization and depolarization current (PDC), is measured to illustrate the effect of nonuniform effect on the DRS test. Findings indicate that: 1) temperature gradient is a more important factor in nonuniform aging of paper than moisture distribution; 2) both the amplitude of FDS and PDC decrease as the moisture distribution becomes more uniform; and 3) the conductance of insulating paper with diverse nonuniform moisture content and aging degrees can be interpreted by the proposed mathematical model, in which the identified parameters are positively correlated with the deterioration degree of internal insulation materials.

Dielectric analysis of degraded stator bars of a hydro generator

This paper presents the investigation of dielectric analysis of degraded stator bars by Polarization and Depolarization Current (PDC) measurement. The stator bars obtained from the 30-year in-service synchronous machine were divided into two groups. The first group was the unmodified stator bars. The second group was the simulated degradation stator bars which were composed of the thermal stress stator bars, conductive tap abrasion stator bars, multiple air cavity stator bars, multiple oil filled stator bars and multiple water filled stator bars. PDC test experiment was performed with the stator bar samples. PDC test results were analyzed in time domain and in frequency domain with the derived parameters i.e. Rdc, real and imaginary part of complex capacitance, C ratio, conduction loss factor and polarization loss factor. It was found that PDC shapes obtained from the conductive tape abrasion stator bar and multiple water filled cavity stator bar were clearly different from that of the unmodified stator bar. For other case studies, the derived parameters showed the usefulness in analysis the degraded stator bar characteristics. For example, the increase in the imaginary capacitance and conduction loss factor can be observed from most cases of degraded stator bar test results.

Aging assessment method of oil–paper composite insulation based on repeated polarization current characteristics

To explore the aging assessment method of the oil–paper insulation in power transformers, the polarization and depolarization current (PDC) characteristics of oil–paper composite insulation samples are investigated under high applied voltage. Based on the asymmetry of polarization absorption current and depolarization current and the polarity effect of insulation pressboard, the repeated polarization current test method is proposed. A novel aging characteristic parameter, which is the ratio of the normalized charge for the first polarization and the normalized charge for the second polarization, is extracted. The difference between the decay rates of the first polarization current and the second polarization current increases at first and then decreases with the polarization time, and decreases with increasing aging degree of the pressboard. The more serious the insulation aging is, the smaller the variation range of aging characteristic parameter with polarization time is, and the closer the value is to 1. With decrease in the DP, the maximum of aging characteristic parameter changes in a decreasing trend. The aging condition of the oil–paper composite insulation can be assessed by the repeated polarization current method and the relationship between the aging characteristic parameter and the polarization time.

Depolarization Ratio Index (DRI) as alternative method in identifying oil-filled transformer internal faults

Dissolved gas analysis is the most common and well-established method used in identifying internal faults of power transformers. However, an onsite analysis using this method accuracy still need to be improved while the laboratories analysis process takes longer time. New alternative onsite and online method are most urgently need to be studied. Power transformer faults identification based on extended application of polarization and depolarization current (PDC) measurement data on oil sample from in-service power transformer was investigated in this research. The changes in the molecular properties of the insulating oil due to different fault conditions found had influenced the initial time response of the PDC measurement (from 0 to 100 s). In this research, the unique characteristic pattern of each condition was determined by a single unique numerical dimensionless quantity known as depolarization ratio index (DRI). DRI is used to express the changes of depolarization current shape with different fault conditions. The ratio of depolarization current between 5/100 and 10/100 s was found to have a better correlation at least more than 90% on the incipient fault in power transformer. Indeed, the DRI at 5/100 also was observed has higher accuracy especially on units with normal, overheating and arcing condition. In addition, a graphical representation of DRI value at 5/100 and 10/100 s was proposed for fault recognition in power transformer. Both DRI and graphical representation are well validated, and the proposed interpretation techniques have accuracy of more than 90% and able to identify and classify the normal, overheating and arcing condition of the in-service power transformer.

Influence of Cable Temperature Rise on PDC Method Test Results of Water Tree Aged Cables

There is a certain temperature rise in the field running cable because of the load bearing. To study the influence of cable temperature rise on the polarization and depolarization current (PDC) method, 10kV XLPE short cables were accelerated aging three months by water needle electrode method, and the PDC method was used to test the new and aged cables under constant humidity. The polarization and depolarization current of the cable samples was analyzed, and the conductivity and low frequency dielectric loss spectra were obtained and inspected. The results show that: in the experiment selected test temperature, the change laws of conductivity of the new and aged cables are the same, and the conductivity gradually rose after a slight drop in 40 °C; in the dielectric loss spectrum, the polarization of the new sample is low and the polarization loss changes little with temperature, and the dielectric loss is mainly affected by the conductivity, so the test result is clearly divided into two regions. And water tree aged samples have strong polarization and are obviously affected by temperature, so their low frequency dielectric loss showed the trend of first rising and then decreasing and the maximum appeared at 60 °C.

Estimation of de‐trapped charge for diagnosis of transformer insulation using short‐duration polarisation current employing detrended fluctuation analysis

Researchers have shown that the value of charge carriers, de-trapped from the oil–paper interface of power transformer insulation, is useful in carrying out the diagnosis. However, the evaluation of the de-trapped charge requires the analysis of polarisation–depolarisation currents. Being an off-line time-consuming process, the measurement and analysis of polarisation and depolarisation current (PDC) data are not practically advantageous. The study presents a detrended fluctuation analysis-based technique to estimate the magnitude of normalised de-trapped charge using the polarisation current measured for a short duration. Using the proposed technique, the requirement of measuring the complete PDC data, for diagnosis purposes, can be eliminated. Further, the technique also eliminates the requirement of depolarisation current which in turn facilitates a reduction in equipment shutdown time. The applicability of the proposed technique is tested on the data obtained from several real-life power transformers.

ANN based temperature compensation for variations in polarization and depolarization current measurements in transformer

Nowadays, more than a quarter of the faults that occur in oil-filled transformers are due to the aging and deterioration of their oil-paper insulation. Therefore, condition assessment of the oil-paper insulation of oil-filled transformers, which are installed in the power grids, is very important. One of the non-destructive methods, which are currently used to distinguish the insulation condition, is polarization and depolarization current (PDC) technique. Factors such as oil conductivity, paper conductivity, moisture content, temperature and insulation aging alter PDC test results. This paper proposes a method based on artificial neural network (ANN) integrated genetic algorithm to modify the effect of temperature variation in the results of PDC tests. For this purpose, PDC tests are performed on two different transformers at temperatures of 22 °C, 30 °C, 40 °C, 50 °C, 60 °C and 70 °C with the help of Megger-IDAX 300 device, which is capable of performing PDC tests up to 70 °C. To achieve the desired temperatures, the transformers are placed in the thermal furnace and with special thermal cables; the terminals of the devices are connected to the transformers inside the furnace. According to the results of depolarization current, which are measured at different temperatures, the parameters of the insulation model have been estimated by using genetic algorithm (GA). The insulation model parameters corresponding to 22 °C temperature in each transformer are selected as target parameters. Insulation model parameters related to higher temperatures are applied as inputs to the artificial neural network (ANN). This is done in order to train the ANN. The purpose of artificial neural network training is to transmit parameters related to higher temperatures on target parameters. Finally, with the help of the transferred model parameters, the polarization and depolarization current curves are drawn and transferred on the target curves (curves of 22 °C). The transfer error is calculated by the mean square error (MSE) index. Comparison of the proposed model results with the traditional method, which is based on the Arrhenius equation, in correcting the effect of temperature on the PDC test results, confirms the prediction accuracy of the proposed method.

Performance Assessment of Oil-Immersed Cellulose Insulator Materials Using Time–Domain Spectroscopy under Varying Temperature and Humidity Conditions

The measurement of polarization and depolarization currents (PDC) based on time–domain response is an effective method for state assessment of cellulose insulation material in oil-immersed electrical equipment. However, the versatility of the data obtained at different temperatures is limited because of the temperature dependence of the PDC. In this respect, the universal conversion of PDC data at different temperatures is an essential aspect to improve the accuracy of the determination of insulating properties of cellulose materials immersed in the oil. Thus, an innovative temperature conversion method based on polarization time-varying current (PTC, obtained by multiplying the polarization current and time) is proposed in this article. In the current work, the PTC data at different temperatures are obtained from the oil-immersed cellulose pressboards with different moisture. Afterwards, the functional model based on the power series theory is used to simulate the PTC data, through which the coefficients of the power series are found related to the test temperature of the PTC and the moisture content (mc%) of the oil-immersed cellulose pressboards. Furthermore, the functional relationship among moisture, test temperatures, and the feature parameter calculated by these coefficients is established. Thus, the PTC data at various temperatures can be calculated by the established function. The potential application ability of the proposed method is verified by comparing the calculated results with the measured results obtained from the various samples.

The Investigation of Insulation Performance Evaluation of the Large Electrical Rotating Machine in Frequency Domain

The insulation structure of winding in a large electrical rotating machine consists of epoxy resin and mica material. The insulation structure is composed of many junctions. The insulation problems generate different kinds of signals, such as electromagnetic waves, which may get released from the non-perfect characteristics of the enclosure. This signal may interfere with the functioning of other nearby electronic devices. Therefore, maintaining an excellent condition of the insulation system of the machine is very important. For a condition monitoring of this insulation as proposed in this research, it is taken into consideration the results of the polarization and depolarization current (PDC) measurement of the test sample, and the stator winding rated 13.8 kV was investigated. The experiments were conducted under different thermal stresses, i.e., 25°C (the room temperature) and 100°C (the operation temperature). The test samples were divided into three types: I. haft-overhang, II. overhang and III. full stator bar. From the PDC measurement data record, the complex capacitance and polarization losses (ion migration polarization, slow relaxation polarization and interfacial polarization) were calculated. It was found that the aging of the insulation related to the complex capacitance and polarization losses can be contributed for research in future wireless technology.

Development and application of HVDC Cable polarization/depolarization current detecting instrument

In order to test the insulation state of 6kV XLPE cable reliably, the system design and related test work are carried out in this paper. High voltage excitation source, weak current test module, data acquisition system, communication, power supply and other hardware design work are described. The control of high voltage signal, switching of measurement mode, data acquisition of current and software design of man-machine interface are introduced. Finally, the designed test instrument is presented, and the field test results show that the home-made polarization and depolarization current (PDC) instrument can be used for testing, and the overall test performance is relatively good.