Search Results (118)

Power transformer insulation systems, composed of liquid and solid insulators, are continuously exposed to thermal and electrical stresses that degrade their performance over time and may lead to premature failure. Since these stresses are unavoidable during operation, selecting effective insulating materials is critical for long-term reliability. In this study, Kraft insulation paper was used as the solid insulator and impregnated with three different liquids: mineral oil and two natural esters (NE1204 and NE1215), to evaluate their stability under simultaneous thermal and electrical stress. The degradation behavior of the oil-impregnated papers was assessed using frequency-domain dielectric spectroscopy (FDS) and Fourier-transform infrared spectroscopy (FTIR), enabling early fault detection. Comparative analyses were conducted to evaluate the withstand capability of each liquid type during operation. Results revealed strong correlations between FTIR indicators (e.g., oxidation and hydroxyl group loss) and dielectric parameters (permittivity and loss factor), confirming the effectiveness of this combined diagnostic approach. Post-aging breakdown analysis showed that natural esters, particularly NE1215, offered superior preservation of insulation integrity compared to mineral oil. Differences between the two esters also highlight the role of chemical composition in insulation performance. This study reinforces the potential of natural esters as viable, eco-friendly alternatives in thermally and electrically stressed applications. Full article

This paper presents the design, development, and characterization of a low-cost and environmentally friendly high-voltage divider optimized for on-site calibration up to 850 kV. Unlike traditional dividers that rely on oil or SF₆ for insulation, both of which pose environmental risk and regulation issues, the proposed system uses modular construction with commercial off-the-shelf components and natural air insulation, minimizing environmental impact and facilitating transport, calibration, and maintenance. Despite using air insulation, the divider demonstrates excellent uncertainty performance. Characterization results show frequency linearity better than 0.2% up to 100 kHz and a bandwidth exceeding 10 MHz, making it suitable for the measurement of a wide range of voltage types. Static and dynamic performance evaluations confirm reliable scale factor stability and low measurement uncertainty: 0.01% for DC (550 kV), 0.3% for AC (405 kV), and 0.7% for impulses such as 1.2/50 µs (850 kV). The system offers a practical and sustainable solution for high-voltage measurements, meeting growing industrial and European environmental demands. Full article

In this paper, results of comparative studies on the positive lightning impulse breakdown voltage (LIBV) and accelerating voltage (V_a) of six insulating liquids of different chemical composition are presented. This paper discusses the behavior of uninhibited naphthenic mineral oil (UMO), inhibited naphthenic mineral oil (IMO), natural ester (NE), synthetic ester (SE), and two modern dielectric fluids: bio-based hydrocarbon (BIO) and inhibited liquid produced using Gas-to-Liquids (GTL) technology. Measurements are taken in a point-to-sphere electrode system for two selected gap distances: 25 mm (which is suggested by the IEC 60897 standard) and 40 mm. After analyzing the obtained results, it is noted that positive LIBV does not differ significantly between the tested liquids. Noticeable differences are observed, however, for V_a. The lowest values of this parameter characterize ester liquids, which is consistent with the common knowledge in this field. In addition, the obtained values of LIBV and V_a are used to evaluate the maximum values of electric field intensity through the application of simulations for each specific case based on the finite element method. These simulations confirm that, for a given parameter, maximum electric field stress is on similar level, regardless of the gap distance. This proves that the breakdown and appearance of fast discharges are determined by specific field conditions. Full article

Transformers are essential for voltage regulation and power distribution in electrical systems, and monitoring their top-oil temperature is crucial for detecting potential faults. High oil temperatures are directly linked to insulation degradation, a primary cause of transformer failures. Therefore, accurate oil temperature prediction is important for proactive maintenance and preventing failures. This paper proposes a hybrid time series forecasting model combining ARIMA, LSTM, and XGBoost to predict transformer oil temperature. ARIMA captures linear components of the data, while LSTM models complex nonlinear dependencies. XGBoost is used to predict the overall oil temperature by learning from the complete dataset, effectively handling complex patterns. The predictions of these three models are combined through a linear-regression stacking approach, improving accuracy and simplifying the model structure. This hybrid method outperforms traditional models, offering superior performance in predicting transformer oil temperature, which enhances fault detection and transformer reliability. Experimental results demonstrate the hybrid model’s superiority: In 5000-data-point prediction, it achieves an MSE = 0.9908 and MAPE = 1.9824%, outperforming standalone XGBoost (MSE = 3.2001) by 69.03% in error reduction and ARIMA-LSTM (MSE = 1.1268) by 12.08%, while surpassing naïve methods 1–2 (MSE = 1.7370–1.6716) by 42.94–40.74%. For 500-data-point scenarios, the hybrid model (MSE = 1.9174) maintains 22.40–35.53% lower errors than XGBoost (2.4710) and ARIMA-LSTM (3.6481) and outperforms naïve methods 1–2 (2.8611–2.9741) by 32.97–35.53%. These results validate the approach’s effectiveness across data scales. The proposed method contributes to more effective predictive maintenance and improved safety, ensuring the long-term performance of transformer equipment. Full article

Known as the “white oil”, lithium is a key raw material to support strategic emerging industries and future industrial development. Zabuye Salt Lake is the only one in Tibet, China that has so far realized the industrialization of lithium extraction from the salt lake brine. The green and low-cost lithium extraction technology by using the salinity-gradient solar pond (SGSP) adopted has always been paid much attention by lithium-related practitioners and researchers. In order to improve the lithium yield and grade of a single crystallization pond, the cross-year brine mixing method can be used to increase the initial temperature and CO₃²⁻ concentration of the raw brine for making the SGSP. The premise is to ensure that the summer brine with low Li⁺ and high CO₃²⁻ prepared in the previous year could be stored safely for overwintering with a minimal change in brine composition, for use in brine mixing in February and March of the next year, which can be realized by using the SGSP. In this paper, two experiments of brine storage for overwintering were carried out in the Zabuye mining area, Tibet in 2020 and 2021 by using the large-scale SGSP with an area of nearly 4000 m². The results show that during the operation of the SGSP in winter, the brine temperature in the lower convective zone (LCZ) can still rise to more than 20 °C and remain relatively stable, indicating that the coverage of surface ice layer not only has an effect of heat preservation and insulation on the SGSP, but also plays a positive role in the thermal storage capacity of the SGSP. The vertical distributions of brine temperature, density and salinity in the pond showed the ideal gradient curves increasing from top to bottom, and the concentrations of Li⁺ and CO₃²⁻ in the brine only decreased slightly. The structure of the salinity-gradient layer tended to stabilize faster when the brine filling depth was larger, but the boundary between the upper convective zone (UCZ) and the non-convective zone (NCZ) was relatively blurred. It is completely feasible to store the brine for overwintering by using the SGSP in the Zabuye mining area, and the experimental results could be directly scalable to larger industrial applications. It can not only provide high-quality raw brine for cross-year brine mixing, but also reduce the pressure of brine production, and a small amount of lithium mixed salt collected is helpful to increase the output of a single crystallization pond. Additionally, the potential challenges of maintaining the SGSP system during extreme winter conditions are described, and effective measures and suggestions are proposed to make the technology feasible in diverse climates. Full article

The power transformer is one of the most important parts of a power system. The transformer oil in a transformer not only increases its insulation strength, but also helps its cooling. Cellulose particles are one of the main factors affecting the breakdown characteristics of transformer oil, and the withstand voltage test can effectively detect the quality of transformer oil. Therefore, the withstand voltage test on transformer oil with different cellulose particle content levels in the laboratory can determine the breakdown characteristics of transformer oil and the method of improving the insulation strength of power transformers. However, there is lack of a set of effective preparation and test methods of transformer oil for laboratory use in the industry. Based on national standards and engineering practice, this paper puts forward a method of preparing transformer oil with different cellulose particle content levels in the laboratory and a method of the withstand voltage test on transformer oil in the laboratory, which can improve the efficiency and the scientificity of such experiments. Full article

To eliminate the problem of the aging of cellulose insulation in the manufacturing stage, a new drying method is being developed based on the use of methanol vapors. Previous studies have shown that the complete removal of methanol from the cellulose insulation after the drying process is very difficult. Therefore, it is necessary to check how the remaining methanol after drying affects the properties of both the cellulose materials and mineral oil. To conduct such studies, it is necessary to know the methanol content in oil that can be expected depending on its initial content in the cellulose materials and the temperature of the insulation system. Therefore, the main goal of this work is to develop methanol equilibrium curves for oil–paper insulation. To achieve the assumed goal, three-stage studies were conducted. A gas chromatograph equipped with a flame ionization detector was used in all stages of these studies. The gas partition coefficient between oil and air was determined for a temperature of 70 °C. The key experimental finding was the development of methanol equilibrium curves for oil–paper insulation. Thanks to this achievement, it is possible to estimate the methanol content in cellulose materials and mineral oil depending on the insulation temperature. Such data are necessary, among others, to plan appropriate studies aimed at assessing the impact of methanol content on the dielectric and physicochemical properties of these materials, important from the point of view of the operation of power transformers. Full article

Defining the copper-based catalysts that are responsible for the catalytic behaviour of oil-paper insulation systems and implementing effective regulation are of great significance. Accelerated ageing experiments were conducted to reveal variations in copper scales and deterioration in insulation properties. As ageing progressed, TEM images demonstrated that copper species were adsorbed and aggregated on the fibre surface in the form of nanoparticles (NPs). The scale of NPs exhibited a continuous increase, from 27.06 nm to 94.19 nm. Cu(I) and Cu(II) species were identified as the active sites for inducing intense free radical reactions, which significantly reduced the activation energy, making the insulating oil more susceptible to oxidation. The role of the antioxidant di-tert-butyl-p-cresol (DBPC) in extending the insulation life was regulated by determining the optimal addition time based on variations in the interfacial tension. After the second addition of DBPC, the ageing rates of the dissipation factor, acidity, micro-water and breakdown voltage in the Cu+DBPC group decreased by 28.8%, 43.2%, 52.9% and 46.7%, respectively, compared to the Cu group. This finding not only demonstrates the crucial role of DBPC in preventing the copper-based catalyst-induced oxidation of insulating oil, but also furnishes a vital foundation for enhancing the long-term stability of transformer insulation systems. Full article

Three-dimensional printing technology continues to evolve, enabling new applications in manufacturing. Extensive research in the field of biomimetics underscores the significant impact of the internal geometry of building envelopes on their thermal performance. Although 3D printing holds great promise for improving thermal efficiency in construction, its full potential has yet to be realized, and the thermal performance of printed building components remains unexplored. The aim of this paper is to experimentally examine the thermal insulation characteristics of prototype cellular materials created using 3D additive manufacturing technologies (SLS and DLP). This study concentrates on exploring advanced thermal insulation solutions that could enhance the energy efficiency of buildings, cooling systems, appliances, or equipment. To this end, virtual models of sandwich composites with an open-cell foam core modeled after a Kelvin cell were created. They were characterized by a constant porosity of 0.95 and a pore diameter of the inner core of the composites of 6 mm. The independent variables included the different material from which the composites were made, the non-uniform number of layers in the composite (one, two, three, and five layers) and the total thickness of the composite (20, 40, 60, 80, and 100 mm). The impact of three independent parameters defining the prototype composite on its thermal insulation properties was assessed, including the heat flux (q) and the heat transfer coefficient (U). According to the experimental tests, a five-layer composite with a thickness of 100 mm made of soybean oil-based resin obtained the lowest coefficient with a value of U = 0.147 W/m²·K. Full article

In most industrialized countries, power transformers built several decades ago are approaching the end of their operational lifespan. The ongoing energy transition, focused on developing 100% renewable energy sources and accelerating global transportation electrification, further exacerbates these assets. Combined with rising electricity demand, there is an increasing risk of critical transformers’ degradation acceleration. In this context, understanding the aging mechanisms of the insulation system inside these essential assets, which form the core of every energy network, becomes paramount for today’s managers and engineers responsible for their operations. The acids generated through oil oxidation can be classified into two categories: low molecular weight acids (LMAs), which are inherently more hydrophilic and consequently have a greater impact on the degradation rate of solid insulation through hydrolysis, and high molecular weight acids (HMAs), which do not significantly contribute to the degradation of paper insulation. This study specifically addresses the impact of acids generated through oil oxidation—focusing on LMAs. New oil samples were infused with different ratios of LMAs before impregnation. The impregnated paper samples underwent thermal aging at 115 °C. Different physicochemical and dielectric properties were investigated. The investigations revealed that oils blended with formic acid exhibited more adverse effects on the insulation system compared to other LMAs. This information is essential for industry professionals seeking to mitigate the risks associated with transformer degradation and extend the lifespan of these critical assets during the energy transition. Full article

Partial discharge is a fault that occurs at the site of insulation defects within a transformer. Dual instances of partial discharge origination discharging simultaneously embody a more intricate form of discharge, where the interaction between the discharge sources leads to more intricate and unpredictable insulation damage. Conventional piezoelectric transducers are magnetically affixed to the exterior metal tank of transformers. The ultrasonic signals emanating from partial discharge undergo deflection and reverberation upon traversing the windings, insulation paperboards, and the outer shell, resulting in signal attenuation and thus making it difficult to detect such faults. Furthermore, it is challenging to distinguish between simultaneous discharges from dual partial discharge sources and continuous discharges from a single source, often leading to missed detection and repairs of fault points, which increase the maintenance difficulty and cost of power equipment. With the advancement of MEMS (Micro-Electro-Mechanical System) technology, fiber-optic ultrasonic sensors have surfaced as an innovative technique for optically detecting partial discharges. These sensors are distinguished by their minute dimensions, heightened sensitivity, and robust immunity to electromagnetic disturbances. and excellent insulation properties, allowing for internal installation within power equipment for partial discharge monitoring. In this study, we developed an EFPI (Extrinsic Fabry Perot Interferometer) optical fiber ultrasonic sensor that can be installed inside transformers. Based on this sensor array, we also created a partial discharge ultrasonic detection system that estimates the directional information of single and dual partial discharge sources using the received signals from the sensor array. By utilizing the DOA (Direction of Arrival) as a feature recognition parameter, our system can effectively detect both simultaneous discharges from dual partial discharge sources and continuous discharges from a single source within transformer oil tanks, meeting practical application requirements. The detection methodology presented in this paper introduces an original strategy and resolution for pinpointing the types of partial discharges occurring under intricate conditions within power apparatus, effectively distinguishing between discharges from single and dual partial discharge sources. Full article

In general, a high voltage (HV) substation can be made up of multiple insulation subsystems: an air insulation subsystem (AIS), gas insulation subsystem (GIS), liquid insulation subsystem (power transformers), and solid insulation subsystem (power cables), all of them with their grounding structures interconnected and linked to the substation earth. Partial discharge (PD) pulses, which are generated in a HV apparatus belonging to a subsystem, travel through the grounding structures of the others. PD analyzers using high-frequency current transformer (HFCT) sensors, which are installed at the connections between the grounding structures, are sensitive to these traveling pulses. In a substation made up of an AIS, several non-critical PD sources can be detected, such as possible corona, air surface, or floating discharges. To perform the correct diagnosis, non-critical PD sources must be separated from critical PD sources related to insulation defects, such as a cavity in a solid dielectric material, mobile particles in SF6, or surface discharges in oil. Powerful diagnostic tools using PD clustering and phase-resolved PD (PRPD) pattern recognition have been developed to check the insulation condition of HV substations. However, a common issue is how to determine the subsystem in which a critical PD source is located when there are several PD sources, and a critical one is near the boundary between two HV subsystems, e.g., a cavity defect located between a cable end and a GIS. The traveling direction of the detected PD is valuable information to determine the subsystem in which the insulation defect is located. However, incorrect diagnostics are usually due to the constraints of PD measuring systems and inadequate PD diagnostic procedures. This paper presents a diagnostic procedure using an appropriate PD analyzer with multiple HFCT sensors to carry out efficient insulation condition diagnoses. This PD procedure has been developed on the basis of laboratory tests, transient signal modeling, and validation tests. The validation tests were carried out in a special test bench developed for the characterization of PD analyzers. To demonstrate the effectiveness of the procedure, a real case is also presented, where satisfactory results are shown. Full article

2-Furaldehyde (2-FAL) is one of the main by-products of the degradation of hemicellulose, which is the solid material of the oil–paper insulating system of oil-filled transformers. For this reason, it has been suggested as a marker of the degradation of the insulating system; sensing devices for 2-FAL analysis in a wide concentration range are of high interest in these systems. An optical sensor system is proposed; this consists of a chemical chip, able to capture 2-FAL from the insulating oil, coupled with a surface plasmon resonance (SPR) probe, both realized on multimode plastic optical fibers (POFs). The SPR platform exploits gold nanofilm or, alternatively, a double layer of gold and silicon oxide to modulate the sensor sensitivity. The capturing chip is always based on the same molecularly imprinted polymer (MIP) as a receptor specific for 2-FAL. The system with the SPR probe based on a gold nanolayer had a higher sensitivity and a lower detection limit of fractions of μg L⁻¹. Instead, the SPR probe, based on a double layer (gold and silicon oxide), has a lower sensitivity with a worse detection limit, and it is suitable for the detection of 2-FAL at concentrations of 0.01–1 mg L⁻¹. Full article

In order to reveal the migration and evolution of gas molecules in the actual oil–paper insulation composite system of transformer from the molecular level, the diffusion behavior of seven gas molecules (H₂, CO, CO₂, CH₄, C₂H₂, C₂H₄, C₂H₆) generated during the operation and aging of oil-immersed transformers in the oil–paper composite insulation system is studied by molecular dynamics. Firstly, based on the molecular dynamics software, the model of the oil–paper composite insulation system and the gas molecule model is constructed. In order to compare and analyze the diffusion properties of gas molecules in a single medium, a single model of insulating oil and cellulose is also constructed. Then, the diffusion coefficients of gas molecules in the insulating oil, cellulose, and oil–paper insulating composite system are simulated and calculated. And the differences in the diffusion properties of gas molecules in the three insulating mediums are discussed. Finally, the microscopic mechanism of diffusion of different gas molecules in the three mediums is analyzed. The simulation results show that among the three mediums, the diffusion coefficient of H₂ is the largest, while the diffusion coefficients of the other gas molecules are not very different. The diffusion coefficients of the seven gas molecules are the smallest in the oil-immersed paper composite insulation system, followed by cellulose, while the diffusion coefficients are the largest in mineral oil. It indicates that the diffusion of gas molecules is inhibited in oil–paper insulation systems where the insulating paper is completely immersed in oil. This is mainly due to the fact that the insulating oil completely penetrates into the paper, filling the pores and voids between the fibers, resulting in a reduction in the transition vacancies of the intermediate gas molecules, which hinders the diffusion of the gas molecules. Full article

Partial discharge (PD) is one of the major causes of insulation accidents in oil-immersed transformers, generating a large number of signals that represent the health status of the transformer. In particular, acoustic signals can be detected by sensors to locate the source of the partial discharge. However, the array, type, and quantity of sensors play a crucial role in the research on the localization of partial discharge sources within transformers. Hence, this paper proposes a novel sensor array for the specific localization of PD sources using COMSOL Multiphysics software 6.1 to establish a three-dimensional model of the oil-immersed transformer and the different defect types of two-dimensional models. “Electric-force-acoustic” multiphysics field simulations were conducted to model ultrasonic signals of different types of PD by setting up detection points to collect acoustic signals at different types and temperatures instead of physical sensors. Subsequently, simulated waveforms and acoustic spatial distribution maps were acquired in the software. These simulation results were then combined with the time difference of arrival (TDOA) algorithm to solve a system of equations, ultimately yielding the position of the discharge source. Calculated positions were compared with the actual positions using an error iterative algorithm method, with an average spatial error about 1.3 cm, which falls within an acceptable range for fault diagnosis in transformers, validating the accuracy of the proposed method. Therefore, the presented sensor array and computational localization method offer a reliable theoretical basis for fault diagnosis techniques in transformers. Full article