Transformer Oil Research Articles

Ultra-low concentration detection of dissolved C2H2 in oil using fixed-frequency RF-assisted calibration-free wavelength modulation spectroscopy

The monitoring sensitivity of dissolved C2H2 in transformer oil is crucial to ensuring the safe operation of electric power systems. A highly sensitive sensor system based on fixed-frequency radio frequency assisted calibration-free wavelength modulation spectroscopy (FF-RF-WMS-2f/1f) for dissolved C2H2 in transformer oil was developed and evaluated. Lowering the headspace sampling pressure to 0.1 atm effectively increased the outgassing ratio and detection signal of dissolved C2H2, while also reducing background interference. By employing a novel fixed-frequency RF-assisted modulation technique, we effectively suppressed the amplitude and influence of optical fringes and improved the system’s linear fitting R-squared value for gas-phase concentration from 0.9997 to 0.9999. Furthermore, the minimum detection limit (MDL), as calculated by Allan deviation, was reduced from 8.58 ppb to 4.36 ppb, while the optimal integration time increased slightly from 62 s to 79 s. The equivalent MDL for dissolved C2H2 reached 0.9 ppb. The comparative experiments showed that the error was less than 0.2 ppm or 8 %, the relative standard deviations (RSDs) of continuous measurement were less than 3 %, and the RSD at ultra-low concentration was less than 8 %. The experiments verified the high sensitivity and accuracy of the sensor system, making it suitable for ultra-low concentration dissolved C2H2 detection in transformer insulating oil.

The relationship between power of arc discharge in transformer oil and peak value of the shock wave

The relationship between power of arc discharge in transformer oil and peak value of the shock wave

Surface reaction mechanisms research of Cun and Pdn (n=1–3) clusters modified MoSTe for fault gases in oil-immersed transformers

Efficient detection and timely resolution of internal faults within synthetic ester oil transformers are imperative for ensuring the stability of power systems. This paper proposes the utilization of MoSTe monolayer modified with Cun and Pdn (n=1–3) clusters for detecting internal fault gases (C2H2, C2H4, and CH4) in transformers. The adsorption mechanism and electronic properties of target gases on the modified substrate surface are systematically studied through density functional theory analysis of adsorption energy, density of states, and deformation charge density. The results indicate that TMn clusters possess the capability to enhance the reactivity of the MoSTe surface, leading to varying degrees of improvement in conductivity and adsorption capacity. Different target gases exhibit distinct adsorption characteristics, with the modified monolayer showing strong adsorption capabilities for C2H2 and C2H4. The calculation of work function and recovery time further reveal the promising potential of Pdn-MoSTe monolayer as resistive gas sensing materials for detecting C2H2 and C2H4, while Cun-MoSTe monolayer are also identified as high-quality candidates for C2H4 sensing materials. This study is expected to facilitate the practical application of MoSTe monolayer in the field of transformer operational state monitoring, providing new insights for exploring novel gas sensing materials.

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.

Adsorption and detection analysis of metal clusters (Pt3, Rh3) modified WTe2 monolayers to dissolved gases (CO, CO2, H2, C2H2) in transformer oil: A density functional theory study

Gas sensors are the key equipment in transformer fault online monitoring systems, and developing new and efficient gas sensing materials is an important prerequisite for breaking through existing monitoring performance. Herein, the first-principles density functional theory (DFT) is employed to study the adsorption and gas-sensing performance of two metal atomic clusters (Pt3 and Rh3) anchored on a WTe2 monolayer (C-WTe2) for four typical fault characteristic gases (CO, CO2, H2, and C2H2). These results suggest that four gases can stably bind to C-WTe2 and exist in the form of chemical adsorption due to the high adsorption energy. Also, Rh3-WTe2 exhibits high selectivity and repeatability towards CO and CO2 due to its strong response and fast recovery characteristics when used in resistive sensors; Pt3-WTe2 can detect and distinguish the four types of gases due to the significant and differentiated changes in work function when used in work function sensors. Therefore, both Pt3-WTe2 and Rh3-WTe2 monolayers are promising gas-sensing materials for the dissolved gases detection in oil. This investigation sheds light on devices of designing metal atomic cluster anchored WTe2-based gas sensor for improved transformer fault monitoring performances.

Study of the methanogenic potential of used grease and bleaching earth by conversion into biogas: The case of a wastewater treatment plant and a refinery

The structure from which this study was carried out is a food processing company specializing in the transformation of crude palm oil into table oil. In order to comply with environmental standards when discharging the refinery's wastewater, it has its own wastewater treatment unit. The aim of this study is to contribute to environmental protection by recovering grease and bleaching earth through biogas production by anaerobic digestion. The characterization provided us with moisture, dry matter and volatile solids contents the values obtained are 32.31%, 67.69% and 97.57% respectively. In the same order, those for bleaching earth are 1.80%, 98.20% and 59.97%. The values obtained during the characterization of the bleaching earth are not conducive to good anaerobic digestion. To optimise biogas production from fat, we used inoculums such as cattle dung and broiler droppings. Biodegradability tests carried out with different proportions of substrates and inoculums led to the conclusion that the presence of a large quantity of microorganisms is necessary for optimum biogas production. In addition, the grease produced a good quantity of biogas when co-digested with the inoculums. The cumulative volume of biogas obtained over 30 days with the grease was 445 ml. The highest quantity of biogas obtained by optimising gas production is 780 ml.

Theoretical Study of Dissolved Gas Molecules in Transformer Oil Adsorbed on Intrinsic and TM (Ta, V)-Doped MoTe2 Monolayer.

In this paper, CH4, C2H2, H2, and CO adsorbed on intrinsic MoTe2 monolayer and transition metal atom (Ta, V)-doped MoTe2 monolayer have been investigated with density functional theory based on first-principles study. The adsorption energy, geometries, band structures, and density of states of four gases (CH4, C2H2, H2, and CO) adsorbed on the MoTe2 and doped MoTe2 surfaces were analyzed. The results shown that the gas adsorption performance of transition metal atom (Ta, V)-doped MoTe2 monolayers is more superior than that of intrinsic MoTe2, and the adsorption energy and charge transfer of the adsorbed gases on the TM-MoTe2 monolayer are significantly increased in comparison with both sides. Among them, Ta-MoTe2 has the largest Eads value in the adsorbed CO system with a very small adsorption distance, as well as a more suitable recovery time of CO at room temperature, so Ta-MoTe2 can be a candidate material for CO detection. New atoms were introduced during the doping process, which increased the carrier density and carrier mobility of the material, thus improving the charge transfer at the surface of the material. which provides a direction for the gas-sensitive properties of metal Ta-modified MoTe2 materials.

Research on discharge characteristics of synthetic ester-paper insulation under power frequency and low frequency

Abstract Synthetic ester insulating oil transformer has broad application prospects in offshore wind power low-frequency power transmission. This paper carried out discharge tests on synthetic ester-paper insulated used sharp plate electrodes at a power frequency of 50 Hz and a low frequency of 17 Hz based on the pulse current method. The research results show that some basic characteristics do not change under 50 Hz and 17 Hz, that is, the discharge is distributed near the voltage peak in a peak shape. The main differences are that the positive peak characteristics at 17 Hz tend to be blurred; the positive maximum discharge amount, and discharge times show an overall downward trend; the phase-resolved partial discharge pattern (PRPD) and the statistical map (n-φ, n-q) have the same overall shape, but different distribution ranges. The test results can be used as a reference for partial discharge pattern identification and insulation design in synthetic ester low-frequency transformers.

Biodiesel Prepared Through Silver Doped Blended Heterogeneous Catalyst and Soybean Oil

Biodiesel amalgamate with silver doped nickel and calcium blended oxide catalyst & soybean oil. Alkaline earth metal calcium and the use of nickel blended oxide integrated and optimized throughout a blending process that after silver doped in differing percentages to research the outcome of prepared catalysts on the change oil to FAME. Catalytic characteristics such as surface area, energy band difference, crystallinity, morphology, and the composition of prepared samples explored utilizing different BET, FTIR, XRD, SEM, and EDX methods. Silver doped 20 percent NiO-CaO blended oxide catalyst defined with a distinctive weight percentage of silver 2wt percent Ag found to be most viable with 80 percent transformation of oil. The optimized response variable for the change of biodiesel was alcohol to oil proportion 15:1, response temperature 64oC, and catalytic converter stacking 05wt percent. This prepared catalyst has added significance as a blended catalyst for biodiesel generation. Key Words: FAME, Transesterification, Silver, Mixed Oxide, Catalyst

Enhancing Power Transformer Oil Quality Weight Factor using A Genetic Algorithm

Power transformers are critical to electrical power systems but are prone to failures due to factors such as heat, electricity, chemical reactions, mechanical stress, and adverse environmental conditions. Moni-toring the insulating oil effectively is key to preventing these failures. A major challenge in this process is determining the optimal weights for the oil quality index, which lacks a standardized benchmark and often relies on subjective expert assessments. To reduce expert bias and subjectivity, this research utilizes a genetic algorithm to optimize the weightings for five essential parameters: color, water content, break-down voltage (BDV), interfacial tension (IFT), and acidity. The algorithm operates through three stages: crossover, mutation, and selection, and analyzes data from 504 oil tests across various transformers. The mean absolute percentage error (MAPE) is used as the fitness value to assess the algorithm's effective-ness. The optimization process determined the best conditions as 132 iterations, a population size of 180, a crossover rate of 0.2, and a mutation rate of 0.8. These parameters achieved an average MAPE of 1.799% over ten trials, indicating high accuracy. This research not only optimizes the weighting of the oil quality index but also significantly reduces the need for expert input and subjective judgments in trans-former maintenance. The findings are expected to improve the efficiency and reliability of power trans-formers, thereby minimizing failures and associated economic costs.

Adsorption sensitivity and sensing performance of Au-doped Ti3C2O2 gas sensor for fault characteristic gases in power transformer

By analyzing the compositions and concentration of dissolved gases in power transformer oil, it is possible to effectively identify and predict the types and degrees of internal faults in oil-immersed transformers. This technology is currently an important method for fault diagnosis and prevention of large oil-immersed power transformers. This study established two different adsorption systems, namely Ti3C2O2 and Ti3C2O2 doped with Au atom, for the detection of four fault characteristic gases (CO, CO2, C2H4, CH4) in power transformer oil. The research results indicate that Ti3C2O2 exhibits inadequate adsorption capabilities for the above gases. The maximum adsorption energy is only −0.440 eV, which belongs to physical adsorption. After doping with Au atoms, the adsorption sensitivity of Ti3C2O2 for the above gases was significantly improved, with a significant increase in adsorption energy and charge transfer. The average adsorption energy has increased by 435%, and the minimum adsorption energy is also −0.660 eV. The adsorption process changed from physical adsorption to chemical adsorption. These research results provide a theoretical basis for Au-doped Ti3C2O2 gas sensor in detecting fault characteristic gases in power transformer.

Adsorption behavior of Rh-VSe2 monolayer upon dissolved gases in transformer oil and the effect of applied electric field

Dissolved gas analysis (DGA) in transformer oil is an effective method to monitor the operating status of transformers. Based on fundamental principles, the adsorption behavior of decomposed gases from transformer oil (CO, CH4, C2H2, C2H4, and C2H6) on intrinsic and Rh-doped VSe2 monolayers is examined. The adsorption structure, adsorption energy, charge transfer, density of state, electron density difference, work function, and desorption properties are discussed to evaluate the potential applications of VSe2 monolayers as scavengers and gas-sensing materials for transformer oil decomposed gases. The results show that Rh dopant can be stably adsorbed on the surface of VSe2 monolayer, and the minimum binding energy is −4.957 eV. The adsorption behavior of oil-dissolved gases on the intrinsic VSe2 monolayer is weak. The sensing performance of VSe2 monolayer for oil-dissolved gas molecules is significantly enhanced after the introduction of Rh dopant. The sensing performance of Rh-VSe2 monolayer for CO, C2H2, C2H4 and C2H6 gases is stronger than that of CH4. Furthermore, in order to improve the applicability of the Rh doped VSe2 monolayer for the detection of oil-dissolved gases molecules. The effect of electric field on the sensing properties of gas molecules on Rh doped VSe2 monolayers is also investigated. Finally, the desorption performance of the system is evaluated based on the transition state theory and Van’t-Hoff-Arrhenius expression. The findings of the study not only disclose the method by which the Rh doped VSe2 monolayer detects the breakdown gasses in transformer oil, but they also offer theoretical recommendations for the advancement of VSe2-based sensors and scavengers.

Adsorption of dissolved gases (CO, H2, CO2) produced by partial discharge in converter transformer oil by CuO(1, 2) and Ag2O(1, 2) clusters doped with MoTe2: A DFT study

Density functional theory (DFT) was used to analyze the effect of (CuO)n, (Ag2O)n (n=1, 2) cluster-doped MoTe2 on the three gases (CO, H2 and CO2) adsorption performance and characteristics. MoTe2 has large bond length and low binding energy, which can simultaneously achieve high sensitivity to target molecules and excellent reversibility at room temperature. By analyzing the modified MoTe2, compared with the initial MoTe2, the reduced energy band structure of band gap, the increased adsorption energy, more charge transfer, and the increased conductivity of DOS, all reflect that the doping of metal oxides enhances the adsorption and sensing performance of MoTe2 for the three gases. The adsorption capacity of CuO-MoTe2 and (Ag2O)2-MoTe2 for the three gases is: CO>H2>CO2, while the adsorption capacity of (CuO)2-MoTe2 and Ag2O-MoTe2 for the three gases is: CO>CO2>H2. Finally, the adsorption effects of the four modifications were compared and feasibility analyzed through molecular orbitals, recovery time, sensitivity and work function, and corresponding conclusions were drawn. The results of this study provide a theoretical basis for detecting dissolved gases in oil generated by partial discharge of converter transformers.

Research on the online monitoring technique for transformer oil level based on ultrasonic sensors

AbstractIn order to solve the problem of remote oil level measurement for unmanned transformers, this paper proposes an online monitoring technology for transformer oil level based on ultrasonic sensors. Subsequently, a finite element model and experimental testing platform were constructed to analyse and verify the influencing factors of the transformer oil level sensors. The results indicated that there is a lower measurement error at 140 kHz in the ultrasonic frequency range of 20–320 kHz, which can be selected as the recommended frequency. The impurities in the oil and the thickness of the tank wall have a slight impact on the accuracy of oil level measurement, and can lead to a decrease in the signal‐to‐noise ratio of the echo. Furthermore, as the speed of sound increases by about 4 m/s, for every 1°C increase in oil temperature, it is necessary to calibrate the measurement results based on the oil temperature. The test results of actual experimental transformers showed that the designed online monitoring device can achieve high‐precision monitoring of transformer oil level, with a relative error generally less than 3%.

BiPLS-RF: A hybrid wavelength selection strategy for laser induced fluorescence spectroscopy of power transformer oil

In this paper, a method for indirect diagnosis of transformer faults based on the fluorescence spectrum and characteristic wavelength screening of transformer oil has been proposed. Specifically, a hybrid strategy (BiPLS-RF) for establishing the fluorescence spectrum feature screening of transformer oil using backward interval partial least squares (BiPLS) and random forest (RF) has been proposed. Aiming at the problem of transformer fault diagnosis, the laser induced fluorescence (LIF) spectroscopy of transformer oil in different states was first collected, and it is found that the fluorescence spectrum intensity of normal transformer oil was stronger than that of faulty transformer oil. Then the characteristic bands of the original fluorescence spectra were screened by BiPLS. It is found that when the original fluorescence spectra were divided into 15 sub-intervals, the minimum root mean squares error of cross-validation can be obtained by selecting 3 sub-intervals (including 411 wavelengths). On this basis, RF was employed to further screen the characteristic wavelengths and realized the identification of the fluorescence spectrum. It is found that in the RF model composed of 54 trees, the selected 196 characteristic wavelengths of the fluorescence spectrum can minimize the analysis error (0.56%). In addition, the selected characteristic wavelength information was fed into other common classifiers to construct a fluorescence spectrum identification model, which further proved the effectiveness of BiPLS-RF for wavelength selection for LIF spectroscopy of power transformer oil. The results show that it is feasible to use BiPLS-RF to screen the characteristic wavelength of LIF spectroscopy and apply it to transformer fault diagnosis, which provides a new solution for transformer fault diagnosis.

New Short-Circuited Coaxial Method Implementation for Complex Permittivity Measurement of Power Transformer Oils

The investigation into the dielectric properties of transformer oils has been a focal point in both historical and contemporary electric insulation technology as high-voltage applications have greatly benefited from the continuous research efforts in this field. The dielectric permittivity is one of the factors to be negotiated when discussing the electric insulation of any material. This work aims to showcase a new short-circuited coaxial cable method to evaluate the complex dielectric permittivity of palm, sunflower and rapeseed oil and review other previously used measurement techniques. Mainly, the test was performed using a sample holder that represents a short-ended coaxial cable filled with the test material which is connected to one port of a vector network analyser. The measurements of the input impedance for various oil samples were conducted at frequencies ranging from 1 MHz to 10 MHz. The technique uses the value of the input impedance which depends on the reflected signals from the test sample to the network analyser, consequently, the value of the dielectric permittivity and dielectric loss have been calculated using the short circuit impedance formula which involves numerical methods to get the results which shows that this method can be used as an alternative to investigate the oils insulation parameters as it provides smooth results for permittivity without any divergence, ensuring more reliable and consistent measurements as well as providing high accuracy in determining the permittivity of materials.

Ti3C2Tx (T = F, O, OH) as a sensor for dissolved gas in transformer oil: A theoretical study

Power transformer is the hub of power grid energy transmission, and its safe and reliable operation is very important to power grid. In this paper, based on density functional theory, Ti3C2Tx (T = F, O, OH) material was used as sensing material. The adsorption models of Ti3C2Tx and dissolved characteristic gases (H2, CH4, C2H4, C2H6, C2H2, CO, and CO2) in transformer oil are constructed. The adsorption distance, bond length change, adsorption energy, charge transfer and density of states (DOS) of the adsorption system were analyzed. The results showed that the gases can adsorb on the surface of Ti3C2Tx spontaneously. Specifically, CO2, CO, C2H2 and C2H4 exhibit a strong adsorption effect on Ti3C2(OH)2, forming hydrogen bonds or chemical bonds, accompanied by large charge transfer and adsorption energy, indicating Ti3C2(OH)2 shows a good sensing performance for these gases.

Investigation on the combined effect of the hydrogen premixing and nanoparticle mixed pyrolysed oil of transformer oil waste in engine characteristics

In the world, the waste of one situation is the perfect requirement for the other situation. The value addition of the waste can produce new products which contribute to different applications. The electrical grid system produced the transformer oil wastes based on their use and capacity. This waste can be converted into useful applications in the CI engine by pyrolysis at 480 °C. This Pyrolysed oil of transformer oil waste (POTOW) is blended with diesel as a 1:3 contribution by volume for improved fuel properties. But it produced lesser performance. Therefore, the nanoparticles of Titanium dioxide and Silicon dioxide are added to the blend to generate the nano fuel. Enhanced performance and emission reduction are tried with 2–6 lpm hydrogen induction with the nano fuel in a 5.2 kW CI engine. Even though nanofuel produced better results, hydrogen induction was used to increase performance with reduced engine emissions further. At full load, 6 lpm hydrogen induction with the nanofuel produced 10.4% higher brake thermal efficiency, nearly 40% drop in CO, 39% drop in the UHC, and 22.22% drop in the smoke emission but 28% higher NOx emission compared to the petroleum diesel. Therefore, this combination is recommended for the CI engine operation with higher performance with reduced emissions and the transformer oil waste reduction in the environment of this application.

New Insights into Gas-in-Oil-Based Fault Diagnosis of Power Transformers

The dissolved gas analysis of insulating oil in power transformers can provide valuable information about fault diagnosis. Power transformer datasets are often imbalanced, worsening the performance of machine learning-based fault classifiers. A critical step is choosing the proper evaluation metric to select features, models, and oversampling techniques. However, no clear-cut, thorough guidance on that choice is available to date. In this work, we shed light on this subject by introducing new tailored evaluation metrics. Our results and discussions bring fresh insights into which learning setups are more effective for imbalanced datasets.

Adsorption of dissolved gases on the TM (Pt, Pd) doped XP(X=In, Ga): A DFT study

Using 2D materials to detect dissolved gases in transformer oil can effectively evaluate the operating status of power systems. In this study, the Pt and Pd atoms are used to modify InP and GaP monolayers for detecting the target gases (C2H2, C2H4, CH4). The band gaps of modified structures are reduced and became more compact compared to the original substrates. The adsorption characteristics of the target gases on the modified substrates are systematically analyzed through adsorption parameters, DCD and DOS. The adsorption effect of the modified InP monolayers on the target gases is ranked as: C2H2>C2H4>CH4. The adsorption capacity of the modified GaP monolayers to the target gases is: C2H4>C2H2>CH4, however the adsorption capacity of the Pd-GaP/gases system is consistent with that of the modified InP monolayers. The sensitivity and recovery time of every gas adsorption systems are further analyzed. In addition, this study provides a theoretical direction for exploring the application prospects of InP and GaP monolayers in the evaluation of operating conditions of oil-immersed transformers.