Power Transformer Insulation Research Articles

Assessment of UHF Frequency Range for Failure Classification in Power Transformers.

Ultrahigh-frequency (UHF) sensing is one of the most promising techniques for assessing the quality of power transformer insulation systems due to its capability to identify failures like partial discharges (PDs) by detecting the emitted UHF signals. However, there are still uncertainties regarding the frequency range that should be evaluated in measurements. For example, most publications have stated that UHF emissions range up to 3 GHz. However, a Cigré brochure revealed that the optimal spectrum is between 100 MHz and 1 GHz, and more recently, a study indicated that the optimal frequency range is between 400 MHz and 900 MHz. Since different faults require different maintenance actions, both science and industry have been developing systems that allow for failure-type identification. Hence, it is important to note that bandwidth reduction may impair classification systems, especially those that are frequency-based. This article combines three operational conditions of a power transformer (healthy state, electric arc failure, and partial discharges on bushing) with three different self-organized maps to carry out failure classification: the chromatic technique (CT), principal component analysis (PCA), and the shape analysis clustering technique (SACT). For each case, the frequency content of UHF signals was selected at three frequency bands: the full spectrum, Cigré brochure range, and between 400 MHz and 900 MHz. Therefore, the contributions of this work are to assess how spectrum band limitation may alter failure classification and to evaluate the effectiveness of signal processing methodologies based on the frequency content of UHF signals. Additionally, an advantage of this work is that it does not rely on training as is the case for some machine learning-based methods. The results indicate that the reduced frequency range was not a limiting factor for classifying the state of the operation condition of the power transformer. Therefore, there is the possibility of using lower frequency ranges, such as from 400 MHz to 900 MHz, contributing to the development of less costly data acquisition systems. Additionally, PCA was found to be the most promising technique despite the reduction in frequency band information.

Transformer oil electrical–thermal characteristics analysis and evaluation

Transformer oil plays the role of heat dissipation and insulation in power transformers, and its electrical and thermal characteristics are directly related to the stable operation of the transformer. At the same time, it is important to master the electric–thermal characteristics of transformer oil for transformer state evaluation, latent fault prediction, and maintenance planning. Based on this, the gas production rule and electrical characteristics of transformer oil under accelerated aging are studied in this paper. First, the experimental platform for power transformer aging is established to accelerate the aging of power transformers. Second, the accelerated aging transformer oil is taken as the research object, and the power frequency, DC, lightning, and gas chromatography are measured and analyzed. Finally, a transformer oil aging evaluation model is established, which takes into account four factors: carbon and oxygen gas factors in transformers, life loss factors calculated by hotspot temperature, hydrocarbon gas factors dissolved in transformer oil, and oil quality factors, and conducts aging evaluation. The conclusion shows that the T parameter proposed in this paper can effectively evaluate the quality of transformer oil. When T is less than or equal to 0.6, there is no aging of the oil. When T is greater than 0.6 and less than 1, the transformer oil has been aging, but it is not manifested. Those are parameters whose chromatography and breakdown voltage are not far beyond the IEEE standard. When T = 1, the aging of oil with significant changes in gas content and breakdown voltage can be observed. When T is greater than 1, the oil has undergone serious aging.

Investigating the effects of corrosion parameters on the surface resistivity of transformer’s insulating paper using a two-level factorial design

The integrity of the insulation in oil-filled power transformers, shunt reactors, and high voltage bushings can be affected when copper dissolves in the insulating oil and then deposits onto the paper insulation. The presence of dissolved copper in the oil increases dielectric losses, while copper deposition significantly improves the conductivity of the paper insulation. Various factors, including temperature, oxygen, sulfur groups, passivators, and ageing time, have been found to contribute to the acceleration of corrosion activity in transformer insulating oils. Unfortunately, there is a lack of extensive research focused on systematically analysing and measuring the impact of corrosion-related factors on the dissolution of copper in transformer insulating oils and the deposition of copper onto solid insulation surfaces (Kraft paper). Therefore, this study aims to thoroughly examine the effects of corrosion factors on copper and sulfur deposition on Kraft paper insulation when it is submerged in transformer mineral oil (TMO). Using a two-level (2k) factorial design, we investigated three crucial factors: i) oil temperature, ii) elemental sulfur concentration, and iii) ageing time. It is worth mentioning that the results obtained from the two-level factorial design indicate that the surface resistivity is primarily affected by the temperature of the oil. This factor alone explains a significant 38.68% of the observed variation. In order to improve predictability, a regression model was created to estimate the surface resistivity of TMO-impregnated paper insulation. This model takes into account factors such as oil temperature, elemental sulfur concentration, and ageing time.

A Reviewed Turn at of Methods for Determining the Type of Fault in Power Transformers Based on Dissolved Gas Analysis

Since power transformers are the most important pieces of equipment in electricity transmission and distribution systems, special attention must be paid to their maintenance in order to keep them in good condition for a long time. This paper reviews the main steps in the process of diagnosing the health of power transformer insulation, which involves the science of analysing the gases dissolved in power transformer oil for effective identification of faults. An accurate diagnosis of incipient faults is favourable to sustainable development and necessary to maintain a reliable supply of electricity. The methods presented for fault diagnosis in mineral-oil-immersed power transformers are divided into analytical and graphical methods and have been found to be simple, economical and effective. After describing the methods, both their strengths and weaknesses were identified, and over the years, the methods were complemented to provide highly accurate information, validated by field inspections. This paper focuses on practical information and applications to manage maintenance based on accurate and up-to-date data. The contents of this paper will be of particular use to engineers who manufacture, monitor and/or use high-power transformers in the energy sector, as well as to undergraduate, master’s and PhD students interested in such applications.

A study on electro-thermal-physical properties of mixed mineral oil and vegetable oil as an alternative for liquid insulation in power transformers

ABSTRACT The power transformer plays a crucial role in the power system’s network for distributing power. The efficient operation of power transformers is mainly based on the efficient liquid insulation used for cooling purposes. Mineral Oil (MO) derived from petroleum is traditionally used for insulation in power transformers. However, its lower thermal degradation and thermal conductivity may influence the performance of the transformer. The non-degradable property and low flash and fire points also affect environmental safety. The aforementioned attributes encouraged researchers to propose an alternative transformer oil for power transformers. In literature, various studies have been carried out to analyze Vegetable Oil (VO) as an alternative to petroleum-based MO; However, due to high viscosity, acidity may affect the performance of the transformer. Hence, this article proposes mixed MO with VO as an alternative for liquid insulation in power transformers. This study uses different ratios of coconut oil, palm oil and sunflower oil for investigation with MO. The experimental results show that the electrical, thermal, and physical properties of mixed transformer oil are better than those of MO and VOs. The results show that a higher proposition of VO has shown better performance. The thermal conductivity of mixed VOs with MO has increased by 6–10% compared to the MO. Both flash and fire points of mixed VO with MO increased by 50–70% compared to MO. The load has been performed to analyze the efficiency and operating temperature of the transformer; results show that the mixed VO with MO combination has 32.3% higher efficiency and 16 ∘ C lower operating temperature compared to MO. Further, the various aging characteristics of the transformer oil are also discussed in this study.

Novel Method Using Transformer Moisture Equilibrium for Removal of Absorbed Moisture from Cellulose Paper Insulation in Power Transformers

Novel Method Using Transformer Moisture Equilibrium for Removal of Absorbed Moisture from Cellulose Paper Insulation in Power Transformers

Transformer hot spot temperature estimation through adaptive neuro fuzzy inference system approach

Transformer performance and efficiency can be enhanced by effectively address the properties of its insulation system. The power transformer insulation system weakens as a result of operational thermal stresses brought on by dynamic loading and shifting environmental patterns. Winding hot spot temperature is a crucial metric that must be maintained below the prescribed limit while power transformers are operating so as to maintained power system reliability. This is due to the fact that, among other variables, the time-dependent aging effect of insulation depends on transitions in hot spot temperatures. Due to the non‐linear nature of the conventional mathematical models used to determine these temperatures, and complexity of thermal phenomena, investigations still need to be exercised to fully understand the variables that associate with hot spot temperature computation with minimum error. This paper explores the possibilities of enhancing top oil and hot spot temperature estimation accuracy through the use of an adaptive neuro-fuzzy inference (ANFIS) technique. The paper presents an adaptive neuro fuzzy model to approximate the hot spot temperature of a mineral oil-filled power transformer based on loading, and established top oil temperature. Initially, a sub-ANFIS top oil temperature estimation model based on loading and ambient temperature as inputs is established. Using a hybrid optimization technique, the ANFIS membership functions were fine-tuned throughout the training process to reduce the difference between the actual and anticipated outcomes. The correctness and reliability of the created adaptive neural fuzzy model have been verified using real-world field data from a 60/90MVA, 132 kV power transformers under dynamic operating regimes. The ANFIS model results were validated against field measured values and literature-based electrical-thermal analogous models, establishing a precise input-output correlation. The developed ANFIS model achieves the highest coefficient of determination for both TOT and HST (0.98 and 0.96) and the lowest mean square error (7.8 and 10.3) among the compared thermal models. Correct determination of HST can help asset managers in thermal analysis trending of the in-service transformers, helping them to make proper loading recommendations for safeguarding the asset.

Exploring the electrical properties of pressboard and kraft paper insulation in power transformers: A dielectric spectroscopy and principal component analysis approach

<p>We explored the aging effects on insulating materials used in power transformers through dielectric spectroscopy. Frequency domain spectroscopy (FDS) was conducted for both aged and new Kraft paper and pressboard samples to determine their dielectric properties across a temperature range of 40–100 ℃ for pressboard and 40–70 ℃ for Kraft paper. Principal component analysis (PCA) was employed to classify the data, identify key factors contributing to variance, and elucidate the relationships between different parameters. The analysis revealed positive correlations between conductivity and frequency, as well as between permittivity and tan delta, with distinct differences in behavior observed between aged and new samples at lower frequencies. Additionally, the impact of temperature was evident, with increased temperature leading to an upward shift in dielectric behavior. At lower temperatures, aging had a reduced effect on the materials' properties. These findings provide significant insights into the dielectric behavior and aging mechanisms of insulation materials in power transformers.</p>

A Time-domain Fractional Element Model for Aging Condition Analysis of Hot-spot Region Insulation in Power Transformer

A Time-domain Fractional Element Model for Aging Condition Analysis of Hot-spot Region Insulation in Power Transformer

Markers of cellulose insulation ageing: Calculation of total methanol quantity in the internal insulation of power transformers

The methods of calculation of methanol quantity in the internal insulation of power transformers (PT) based on the values of its concentration in transformer oil (TO) are considered. The total methanol quantity formed during the operation of PTs allows estimating the degree of degradation of cellulose insulation. We are considering the models for calculation of the total methanol quantity in PT on the base of: literature data characterizing the methanol balance in the cellulose-oil system; data on the reduction of methanol concentration after TO replacement during total overhaul. The errors analysis on the base of the results of calculations using the models showed that their value can reach 30%. Reduction of errors in the calculation results should be based on a deeper study of the kinetics of methanol sorption processes by cellulose and taking into account the structural features of different types of cellulose insulation in the particular PT. The considered models can be recommended for estimation of total quantity of any dissolved decomposition products of cellulose insulation in TO, which can become an important indicator of technical condition of PT.

Nanodielectric Fluids for Power Transformer Insulation and Cooling: A Review Identifying Challenges and Future Research Needs

Nanodielectric Fluids for Power Transformer Insulation and Cooling: A Review Identifying Challenges and Future Research Needs

Power Transformers Insulation Faults Identification with DGA: A Molecular Dynamics-Assisted Method

Power Transformers Insulation Faults Identification with DGA: A Molecular Dynamics-Assisted Method

An Evaluation and Correlation Study of Oil and Solid Insulation in Power Transformers using Composite Index Considering Operating Age

An Evaluation and Correlation Study of Oil and Solid Insulation in Power Transformers using Composite Index Considering Operating Age

K2CO3‐loaded γ‐Al2O3 for acid removal in waste transformer oil

AbstractTransformer oil plays a critical role in ensuring the insulation and normal operation of power transformers. However, during operation, the transformer oil would undergo oxidation and degradation, leading to the formation of acids and polar compounds that increase its acidity and degrade its performance. Hence, the recycling and regeneration of aged transformer oil is an essential practice in transformer maintenance, contributing significantly to the extension of a transformer's operational lifespan and the reduction of potential risks. Adsorption separation is a preferred method for regeneration, offering simplicity and high efficiency. This study focuses on impregnated γ‐Al2O3 as an adsorbent for acidity removal in waste transformer oil. We conducted static adsorption experiments to investigate the optimal loading amount of the active component and the best calcination temperature for acid removal. XRD technique is employed to monitor the phase changes of the carrier during the calcination process. BET analysis is used to observe variations in the specific surface area and pore volume of the adsorbent during the modification process. DTG‐TGA is utilized to assess the weight loss during the calcination process. FTIR is employed to observe changes in functional groups during modification and adsorption processes. Along with these investigations, a study is also carried out to assess the dynamic acid removal performance of the acid‐removing adsorbent loaded into a fixed bed. The findings contribute to the development of sustainable methods for regenerating transformer oil, ensuring efficient and environmentally friendly operations.

Research on Changes in the Phase Shift Angle and Admittance of the Cellulose–Bio-Oil Composite under the Influence of Increasing Moisture during the Long-Term Operation of Power Transformers

In this study, the temperature–frequency dependencies of the pressboard–bio-oil–water nanoparticle composite’s fundamental parameters—phase shift angle and admittance—were examined using the Frequency Domain Spectroscopy method. Measurements were conducted in a frequency range of 10−4 Hz to 5 × 103 Hz at temperatures ranging from 293.15 K to 343.15 K, with a step of 10 K. The temperature stabilization accuracy was less than ±0.05 K. A total of 15 Arrhenius plots were determined for various phase shift angle values, from which 15 values and the average activation energy of relaxation time were determined. Similarly, the values of the activation energy of admittance relaxation time and the activation energy of admittance were determined. It was established that all three average values are identical within the bounds of uncertainty. Based on 45 values, a generalized activation energy was determined, with a value of ΔW ≈ (1.032 ± 0.0196) eV. Using the generalized activation energy value, the phase shift angle curves determined for all temperatures were recalculated to a temperature of 293.15 K. It was found that after conversion, all curves perfectly overlap. A similar operation was carried out for the frequency dependencies of admittance. In this case, too, the recalculated dependencies perfectly match. This means that the shape of the frequency dependencies of the phase shift angle and admittance depends solely on the moisture content in the pressboard–bio-oil–water nanodrop composite. The position of the curves in doubly logarithmic coordinates depends only on temperature and is determined by the generalized activation energy Using the generalized activation energy determined in this study will allow for the development of accurate methods for estimating moisture content in cellulose insulation of power transformers containing bio-oil. This will contribute to the detection of critical moisture content, which is about 5% by weight, and to the elimination of the risk, associated with such a high moisture content, of catastrophic failure of power transformers.

Investigating Aging Characteristics of Oil-Immersed Power Transformers' Insulation in Electrical-Thermal-Mechanical Combined Conditions.

The condition and health of large oil-immersed power transformers' insulation have a direct impact on the safety and stability of the power grid. Therefore, it is crucial to investigate the aging characteristics of oil-paper insulation in power transformers. In this study, we developed a computational model for reclosing current calculation and multiphysics coupling models for magnetic-circuit-force, electrostatic field, and temperature field simulations. The calculated aging resulted in a mechanical stress of 8.71 MPa, an electric field strength of 2.26 × 106 V/m, and a temperature of 113.7 °C. We conducted combined electrical-thermal-mechanical aging tests on the oil-paper insulation and measured various insulating paper performance parameters at different aging stages. Our study revealed that both the mechanical and electrical properties of the insulating paper deteriorated in both aging groups. However, the changes were more pronounced in the electrical-thermal-mechanical aging group compared to the electrical-thermal aging group, indicating that mechanical stress accelerated the aging process of the insulating paper. In the early stages of aging, the rate of performance changes in the electrical-thermal aging group was similar to that in the electrical-thermal-mechanical aging group. However, as the aging time increased, the degradation of performance induced by mechanical aging became more significant. This suggests that the insulating paper's resistance to mechanical damage, specifically short-circuit resistance, noticeably decreased after prolonged aging.

Aging analysis of non-edible natural ester oil–paper insulation under various conditions

Natural esters have emerged as a viable and sustainable alternate for liquid insulation in power transformers. However, the natural esters currently used for transformer applications are extracted from edible sources, leading to concerns about their impact on the food supply. In order to overcome this issue, studies on the dielectric properties of non-edible natural esters have received a lot of attention in industries as alternative dielectric liquids for power transformers. In this research work, non-edible natural esters, namely Jatropha oil, Karanja oil, and Mahua oil are taken for analysis. Cellulose materials are impregnated with these oil samples, further, the samples are aged at 130 °C up to 28 days. Different dielectric, mechanical, physical and chemical parameters are measured and analyzed after every 7 days of aging. When comparing the results, karanja oil performed better than others.

Distributed Characteristics of Free Metallic Particles in Flowing Transformer Oil Under DC and AC Voltages

Transformer oil is inevitably contaminated by metallic particles during manufacturing and operation, which will accumulate in the oil gap and poses a serious threat to the oil insulation in power transformer. However, the distributed characteristics of particles in oil channels will be influenced by oil flow. In this paper, a circulation flow device of transformer oil was established and the distributed characteristics of metallic particles in flowing oil were obtained under DC (direct current) and AC (alternative current) voltages respectively. It was found that particle counts between parallel plate electrodes and rod-plane electrodes would decrease monotonously with increasing flow velocities under DC application, whereas the concentration between spherically capped electrodes would increase slightly first and then decline. When the electrodes were energized by AC voltage, the reduction of the particle concentration was more significant with the addition of flow velocities. What’s more, the temporal changes of particle amount under different conditions were obtained. Then the impacts of flow velocities and applied voltages on particle distribution were discussed based on the force analysis on metallic particles.

The Application of Selected Hierarchical Clustering Methods for Classification the Acoustic Emission Signals Generated by Partial Discharges

The paper presents the results of the application of the hierarchical clustering methods for the classification of the acoustic emission (AE) signals generated by eight basic forms of partial discharges (PD), which can occur in paper-oil insulation of power transformers. Based on the registered AE signals from the particular PD forms, using a frequency descriptor in the form of the power spectral density (PSD) of the signal, their representation in the form of the set of points on plane XY was created. Next, these sets were subjected to analysis using research algorithms consisting of selected clustering methods. Based on the suggested numeric performance indicators, the analysis of the degree of reproduction of the actual distribution of points showing the particular time waveforms of the AE signals from eight adopted PD forms (PD classes) in the obtained clusters was carried out. As a result of the analyses carried out, the clustering algorithms of the highest effectiveness in the identification of all eight PD classes, classified simultaneously, where indicated. Within the research carried out, an attempt to draw general conclusions as to the selection of the most effective hierarchical clustering method studied and the similarity function to be used for classification of the selected basic PD forms.

Potential Characterization of Bush Mango Oil for Application in Transformer Insulation

In recent times, the suitability of some oils from edible fruits as a replacement for mineral oils used in transformers has been proven in different literature. The use of edible oils as transformer insulation fluid gives rise to the concept of green insulation in transformers. Research in the use of edible oil in the production of transformer oil has been one of the major researches in high voltage engineering. The existence of paucity of knowledge on the use of bush mango oil as dielectric fluid in transformers led to the idea of this research work. Therefore, this study focuses on the investigation of the suitability of using Irvingia Gabonensis Oil (IGO) for insulation in power transformers. From the series of analyses conducted, it has been established that the Irvingia Gabonensis (Bush Mango) oil is not suitable for transformer insulation oil. This is because the biobased green oil produced presented characteristics that are not suitable to match the standards recommended by the International Electrochemical Commission (IEC) and the American Society for Testing and Materials (ASTM).