Hot Spot Temperature Research Articles

Research on multi-physical field analysis and assessment technique of virtual connection defects in cluster cable joints based on digital twin technology

As the “blood vessels” and “nerves” of the power grid, cables are important carriers for transmitting electric energy, and their failures will affect the safe and stable operation of the power grid. In this paper, a digital twin model of thermal characteristics is constructed for 10 kV YJV×400 cluster cable and its joint model. Based on the multi-physical field coupling analysis method, the fluid field, temperature field and current-carrying capacity of the cluster cable are analyzed. The temperature rise and airflow distribution characteristics of the joint and its external insulation when the defect of joint false connection occurs are analyzed. Based on the fuzzy analytic hierarchy process (FAHP), weights are assigned to the locations of multiple measurement points of the cable external insulation, and the temperature distribution of each measurement point is combined with the digital twin technology to calculate the hot spot temperature of the cable, so as to assess the defects of the joints of the cables. The digital twin platform is used for real-time monitoring of cable status and assessment of defects. The temperature rise experiments of cables under different carrying capacity and joint defects show that this method can accurately and efficiently calculate hot spot temperatures and assess defects of joints in cluster cables.

Estimation Method of Remaining Life and Hot Spot Temperature According to Real-Time Transformer Load Pattern Process

Estimation Method of Remaining Life and Hot Spot Temperature According to Real-Time Transformer Load Pattern Process

DISTRIBUTION TRANSFORMER LIFE LOSS ANALYSIS ON JTM 20 KV DUE TO AMBIENT TEMPERATURE AND LOADING

A continuously operating transformer will inevitably undergo a temperature rise, with the iron core and copper coil as the primary sources of heat generation. The maximum temperature occurring in these components, also known as the hottest spot temperature, is the hottest point. It is essential to maintain a regular flow of temperature within safe limits to prevent any damage. The objective of this study is to estimate the remaining life of the distribution transformer at Tanjungpura University by analyzing its life shrinkage under JTM 20 kV's ambient temperature and loading conditions. To achieve this, transformer loading and top oil temperature were measured for one week. The Montsinger equation was utilized for calculating the transformer aging rate, while a service life of 20 years was assumed as per IEC 60354. Based on findings from research conducted at 4 locations, it was observed that the transformer experiences varying loads with temperature increases exclusively on weekdays from Monday to Friday. The age shrinkage values for each transformer were as follows: 0.0728 p.u, 0.0493 p.u, 0.0044 p.u, and 0.0043 p.u. Considering these research outcomes, the estimated remaining lifespan of the Tanjungpura University distribution transformer is long, and the transformer is in good condition.

Hotspot Temperature Prediction of Relay Protection Equipment Based on a Physical-Model-Aided Data-Driven Method

Relay protection equipment (RPE) is a type of automation equipment aiming to protect power systems from further damage caused by local faults. It is thus important to ensure the normal operation of RPE. As the power density of electronic components continuously increases, the overheating problem of RPE cannot be neglected. Given the difficulties in implementing direct measurement and predicting development trends of RPE temperature, a novel hotspot temperature monitoring method for RPE was proposed, which is a data-driven method. The generative adversarial network, aided by a physical model, is used to address small samples. Afterwards, a stacked ensemble model established based on random forests was used to predict the hotspot temperature of the RPE. Experiment results show that the proposed method can effectively predict hotspot temperature of RPE with the predictive error lower than 2%. And comparative results demonstrate the superiority of the proposed method compared to other methods.

Temperature Hotspot Detection on Printed Circuit Boards (PCBs) Using Ultrasonic Guided Waves-A Machine Learning Approach.

This paper addresses the challenging issue of achieving high spatial resolution in temperature monitoring of printed circuit boards (PCBs) without compromising the operation of electronic components. Traditional methods involving numerous dedicated sensors such as thermocouples are often intrusive and can impact electronic functionality. To overcome this, this study explores the application of ultrasonic guided waves, specifically utilising a limited number of cost-effective and unobtrusive Piezoelectric Wafer Active Sensors (PWAS). Employing COMSOL multiphysics, wave propagation is simulated through a simplified PCB while systematically varying the temperature of both components and the board itself. Machine learning algorithms are used to identify hotspots at component positions using a minimal number of sensors. An accuracy of 97.6% is achieved with four sensors, decreasing to 88.1% when utilizing a single sensor in a pulse-echo configuration. The proposed methodology not only provides sufficient spatial resolution to identify hotspots but also offers a non-invasive and efficient solution. Such advancements are important for the future electrification of the aerospace and automotive industries in particular, as they contribute to condition-monitoring technologies that are essential for ensuring the reliability and safety of electronic systems.

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.

Improving Dynamic Thermal Characteristics of Power Transformers Using an Earth-Oil Heat Exchanger

A significant aspect affecting the power transformer’s performance and lifetime is the maximum temperature within the machine. This research estimates the top-oil temperature (TOT), bottom-oil temperature (BOT), and hot-spot temperature (HST) for a 2500 kVA oil natural air natural (ONAN) distribution transformer with or without an earth-oil heat exchanger (EOHE). The differential equations of the thermal models are solved using the Runge-Kutta fourth-order method. MATLAB code is used to simulate the created models. The present model takes into account how oil properties such as dynamic viscosity, thermal conductivity, and density change with temperature. The IEEE model is used for model validation. The estimated findings are of high accuracy compared with the others. Results show that the maximum reductions in the HST, TOT, and BOT due to EOHE are 48.82%, 41.93%, and 29.59%, respectively. The use of EOHE decreases the temperature of the transformer oil as well as increases the transformer’s lifetime.

Theoretical Study of Liquid Flow and Temperature Distribution in OF-Cooled Power Transformers

The objective of the paper is to analyse the effects of various geometrical and operating parameters on the liquid flow distribution in OF-cooled power transformers. Our investigation includes two cases: one with a simplified winding geometry and another that closely resembles the actual winding geometry. The analyses were carried out using computational fluid dynamics (CFD) and custom, internally developed thermo-hydraulic models. Our findings confirm that buoyancy forces rather than the pump drive the liquid flow within the windings of an OF-cooled power transformer. The results also show that the liquid flow distribution, which is influenced by the winding geometrical properties and liquid properties, has a significant impact on the hot-spot temperatures of the windings. The comparison between the results of the CFD simulations and the results of the simple model demonstrates a high level of agreement in calculating both the mass flow rates and temperatures.

Photovoltaic hotspots: A mitigation technique and its thermal cycle

In the rapidly evolving field of solar energy, Photovoltaic (PV) manufacturers are constantly challenged by the degradation of PV modules due to localized overheating, commonly known as hotspots. This issue not only reduce the efficiency of solar panels but, in severe cases, can lead to irreversible damage, malfunctioning, and even fire hazards. Addressing this critical challenge, our research introduces an innovative electronic device designed to effectively mitigate PV hotspots. This pioneering solution consists of a novel combination of a current comparator and a current mirror circuit. These components are uniquely integrated with an automatic switching mechanism, notably eliminating the need for traditional bypass diodes. We rigorously tested and validated this device on PV modules exhibiting both adjacent and non-adjacent hotspots. Our findings are groundbreaking: the hotspot temperatures were significantly reduced from a dangerous 55 °C to a safer 35 °C. Moreover, this intervention remarkably enhanced the output power of the modules by up to 5.3%. This research not only contributes a practical solution to a longstanding problem in solar panel efficiency but also opens new pathways for enhancing the safety and longevity of solar PV systems.

Numerical study of the cooling capacity of several alternative liquids in zig-zag cooling system of a power transformer

Mineral oil is the usual coolant of the power Transformers. Nonetheless, the high risk of fire of this liquid due to its low ignition point and its scarce biodegradability has promoted the development of dielectrics alternative fluids with better physical-chemical properties. However, these new liquids have to be as good coolants as mineral oil in order to maintain the power transformer performance. This numerical study analyzes the coolant capacity of some of these new commercial liquids (a natural ester, a synthetic ester, and a silicone oil) by using the zig-zag cooling system of the low voltage winding of a real power transformer. Two types of thermal-fluid studies (parametric and time-dependent studies) have been made by using a 3D model of this system. The comparison of temperatures obtained from the parametric study (different inlet flow rates) allow us to say that the worst coolant is the silicone oil. Also, it can be say that a significant increase in the inlet flow rate produces mild drops of hot-spots temperatures and no modification in the initial temperature distribution. For the time dependent study (25% of overload during 1 hour), the hot-spot temperature exceed the limits, which negatively affects the aging speed of the insulating paper and therefore the transformer lifetime.

A numerical study on effect of intra and inter spaced winding configuration on performance of oil forced transformer cooling system

The present work aims at investigating, numerically, the heat transfer characteristics of transformer cooling system under forced circulation for three different winding configurations. The purpose of a transformer cooling system is to keep the hot spot temperature within the critical value for a long life of transformer, which increases with enhanced cooling of transformer windings. Thus, two different winding configurations are modeled by providing space within the windings (an intra-space model) and in between the windings (an inter-space model) to improve the fluid-solid interaction. A conventional winding, without spacing, is also modeled for comparative study. A 315 kVA, 3-phase core type transformer is taken as the base model from which the winding and core specifications are obtained analytically. Parameters chosen to measure the influence of winding configuration are local temperature distribution in the windings and core and maximum transformer temperature. Results are obtained for all three models with varying space for various cooling mediums like naphthenic oil, silicon oil, and synthetic ester oil at flow velocities ranging from 0.72 m/s to 2.16 m/s. It is observed that the gap between the windings, interspacing, decreases the secondary winding temperatures, while it increases the core and primary winding temperatures. However, the intra spacing configuration finds a drop in local temperatures at all locations of the transformer windings and core. The enhanced heat dissipation to the cooling agent, with intra spacing winding configuration, reduces the maximum transformer temperature. Contrasting to the above, the inter-space model has an adverse effect on maximum temperature at all widths of space considered. Quantitatively, the space within the transformer reduces the maximum temperature by 5% in comparison with the space between the windings. The increased velocity of the cooling medium, Naphthenic oil, from 0.72 m/s to 2.16 m/s reduces the maximum temperature by 4.5 units. The study made to know the role of cooling medium discloses that the synthetic ester oil shows better performance for reducing temperature values due to its highly viscous nature.

Research on magnetic-fluid-thermal-stress multi-field bidirectional coupling of high speed permanent magnet synchronous motors

Due to the fact that high speed permanent magnet synchronous motors (HSPMSM) are direct drives instead of using gears, they have technical and economical advantages in many applications. In this paper, a 150 kW, 30,000 r/min HSPMSM was used as research object, for which a magnetic-fluid-thermal-stress multi-field coupling model was developed and solved. Motor losses were obtained from electromagnetic analysis and were applied as heat source. Subsequently, the temperature and fluid distribution were solved according to given heat source characteristics and cooling structure. Based on this, the rotor stress distribution influenced by the temperature load was further obtained. On the other hand, the effect of temperature change on conductor resistivity, permanent magnet remanence, cooling medium thermophysical properties, and loss characteristics, which in turn affect temperature and stress distribution, was considered. The bidirectional coupling of multi-fields was achieved by iterative calculations in the "forward" and "reverse" cycles. The results showed that the hotspot temperature increased by 14.19 % and the tangential stress in permanent magnet increased by 5.28 % compared to the unidirectional coupling. Finally, an experiment platform was built, and tests were conducted. The results showed that the temperature obtained by bidirectional coupling was closer to the experimental result.

Research on temperature rise characteristics and hot spot temperature inversion method of oil-immersed transformer based on coupling of magnetic-fluid-thermal field

The hot spot temperature is an important factor affecting the operation state and insulation life of oil-immersed transformer. It is of great value to carry out multi-physical field coupling simulation research on magnetic-fluid-thermal field of oil-immersed transformer and accurately calculate and predict the hot spot temperature of transformer for transformer service life evaluation. In this paper, the oil immersed transformer is taken as the research object, and five characteristic parameters of the hysteresis model are obtained by using PSO optimization algorithm according to the experimental magnetic characteristics data of the core material and the classical J-A hysteresis model, A 3D simulation model of magnetic-fluid-thermal field is established based on the electrical and structural parameters of the oil-immersed transformer. Combined with the magnetic characteristics of the core material, the thermal field and the surrounding fluid distribution of the transformer core and winding are obtained by two-way coupling method. On this basis, in order to accurately reflect the correlation between the hot spot temperature of the transformer winding and the temperature of the oil tank wall, the selection position of the characteristic temperature point of the transformer tank wall is determined by streamline analysis method, and the hot spot temperature of the oil-immersed transformer is retrieved by support vector machine method. The results show that the prediction accuracy of the hot spot temperature reaches 0.998, and the inversion method has a high enough accuracy. It provides theoretical basis and technical support for real-time monitoring of hot spot temperature in oil-immersed transformer windings.

Simulation calculation of fluid field- thermal field of oil-immersed transformer and optimization of winding structure parameters

The optimization method of winding structure parameters of oil-immersed transformer is proposed to reduce the hot spot temperature of transformer and the metal conductor consumption based on the coupling calculation method of electromagnetic-fluid-thermal. Firstly, according to the electrical and structural parameters of the oil-immersed transformer, a 3D simulation model is established by using finite element software, and the distribution of the thermal field and the fluid field around the transformer as well as the fluid field and thermal field of the low-voltage winding are obtained. In order to accurately reflect the temperature rise distribution characteristics of the low-voltage winding, a 2D model of the low-voltage winding of the transformer was established considering the calculation efficiency and accuracy, and the thermal field and fluid field distribution of the two low-voltage winding models were compared and analyzed. The temperature error was less than 5.98?, which verified the accuracy of the equivalent model. On this basis, the hot spot temperature of low voltage winding under different structural parameters is obtained by combining the Latin hypercube experiment design and thermal field simulation method, and the response surface model of winding hot spot temperature and structural parameters is established. Taking the hot spot temperature of low voltage winding and the amount of metal conductor as optimization objectives, combined with the response surface model, the optimal solution set of Pareto is obtained by using NSGS-? optimization algorithm, and two kinds of optimal design results are obtained on the Pareto front surface. The results show that the hot spot temperature is reduced by 4.16% and the metal conductor consumption is reduced by 13.79% in scheme 1; the hot spot temperature is reduced by 0.51% and the metal conductor consumption is reduced by 28.46% in scheme 2. The research results have important guiding significance for the optimization of oil-immersed transformer.

Research on temperature rise calculation and hot spot temperature inversion method for oil immersed transformer based on magnetic - thermal - fluid

The hot spot temperature of oil-immersed transformer winding is an important factor affecting the aging of material insulation. In this paper, a magnetic field simulation model is established based on the electrical and structural parameters of the oil-immersed transformer, and the loss distribution characteristics of each wall of the transformer core, winding and fuel tank are accurately calculated by using the finite element simulation software. The simulation model of transformer fluid- thermal field is established, the simulation results of transformer thermal field are obtained, and the temperature distribution of oil-immersed transformer core and winding and the flow velocity around it are obtained. According to the simulation results of thermal field, the characteristic temperature measuring points with strong correlation between tank wall and winding temperature were determined. The inversion models of tank wall and winding hot spot temperature were established by using the support vector regression and BP neural network algorithm respectively by central composite design method. The results show that the correlation coefficient of support vector regression algorithm in predicting winding hot spot temperature reaches 0.98, and the relative error between the model predicted value and the real value is less than 8%, which is more accurate than BP neural network. The above research provides the theoretical basis and technical support for real-time monitoring of oil-immersed transformer winding hot spot temperature.

Formation of fast-ignition hotspots and propagartion of burning waves in pre-compressed isochoric plasmas

The formation and evolution of hotspots is important for achieving ignition and high energy gain in inertial fusion process. However, most of relevant studies are carried out on pre-compressed plasmas with an isobaric configuration, the evolution of the hotspot in a plasma with an isochoric configuration is rarely studied. In this paper, a semi-analytical model is developed to describe the evolution of the hotspot boundary and propagation of fusion burning waves for a high-density pre-compressed plasma with an isochoric configuration in the double-cone ignition scheme. For the shock wave, the strong shock wave approximation and the quasi-isobaric approximation are reasonable. The quasi-isobaric approximation shows that as the plasma density behind the shock wave increases, the plasma temperature decreases. Because of these, the range of <inline-formula><tex-math id="M4">\begin{document}$ {\mathrm{\alpha }} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231474_M4.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231474_M4.png"/></alternatives></inline-formula>-particles decreases rapidly behind the shock wave, forming an <inline-formula><tex-math id="M5">\begin{document}$ {\mathrm{\alpha }} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231474_M5.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231474_M5.png"/></alternatives></inline-formula>-particle absorption peak. Therefore, considering that the hotspot is the main region where <inline-formula><tex-math id="M6">\begin{document}$ {\mathrm{\alpha }} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231474_M6.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231474_M6.png"/></alternatives></inline-formula>-particles are produced and deposited, the position of the shock peak can be used to identify the boundary of the hotspot in a high-density plasma with an isochoric configuration. It also shows that a “self-regulating burning process” exists in the burning process of the isochoric hotspot, most of <inline-formula><tex-math id="M7">\begin{document}$ {\mathrm{\alpha }} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231474_M7.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="5-20231474_M7.png"/></alternatives></inline-formula>-particles are deposited in the stable region and behind the shock, and finally, transport through the shock peak and heat the cold fuel, resulting in the temperature rising. In the high-density hotspots of plasma with an isochoric configuration, the deposition of α-particles behaves as an obvious non-uniform distribution effect. By analyzing the non-uniform deposition of α-particles, the deposition rate of α-particles at the edge of spherical uniform hotspot is calculated, then the temperature and density evolution of the isochoric hotspot can be well described. The model can be used to estimate the Lawson parameter of the hotspots at the end of the early stage of ignition. It is found that a lower fast electron energy is more beneficial to ignition and high gain operation of fusion plasma. It is also shown that the high density of the hotspots in the isochoric plasma will lead to a higher fusion burning rate, which can offset the negative influence of the shock wave and even achieve higher energy gain. The semi-analytical model is verified by the hydrodynamic simulations of O-SUKI-N.

A Semi-Analytic Model for Temperature Distribution Prediction and Hotspot Tracking in SPMSM and Its Application for Improved Multiphysics Multiobjective Optimization Design

A Semi-Analytic Model for Temperature Distribution Prediction and Hotspot Tracking in SPMSM and Its Application for Improved Multiphysics Multiobjective Optimization Design

Initial Temperature Determination for RealTime Thermal Models in Permanent Magnet Synchronous Machines

Initial Temperature Determination for RealTime Thermal Models in Permanent Magnet Synchronous Machines

Research on Inversion Model of Winding Hot Spot Temperature of 10-kV Oil-Immersed Three-Dimensional Coiled Core Transformer

Research on Inversion Model of Winding Hot Spot Temperature of 10-kV Oil-Immersed Three-Dimensional Coiled Core Transformer

Improved cryogenic stability by thermal insulation between forced-flow gas-cooled REBCO conductors in fusion magnets

A key design feature is presented to improve the cryogenic stability of forced-flow gas-cooled HTS conductors for fusion magnets. In order to realize the compact and economic fusion system, a variety of conductors are under development with stacked REBCO tapes so that the high-field magnets can operate at 20–30 K with the internal flow of helium gas. Thermal-hydraulic analysis is typically based on 1-D models under a prescribed thermal load along the conductors. In this study, the effect of thermal interaction between adjacent conductors in a winding pack is rigorously considered for the analysis. In a double pancake with single cooling loop, it is evidently verified that the conductor temperature may rise to a peak at inner layers, seriously affecting current sharing and thermal stability. The analytical results are useful in predicting the temperature and location of hot spot in terms of a dimensionless parameter, NTU. In theory, the gas-cooled magnet can be thermally stable by either infinitely increasing or infinitesimally decreasing the thermal interaction between conductors. In practice, however, the thermal insulation to minimize the contact between inbound and outbound flows in a double pancake is proposed as an effective way to improve the cryogenic stability.