The cable intermediate joint plays a crucial role in power cable systems, as its temperature directly impacts insulation performance and longevity. Predicting temperature accurately poses challenges for operation and maintenance. This study introduces a model for electromagnetic‐thermal coupling of a 110 kV single‐core high voltage cable, enabling numerical simulation to determine temperature distributions within the cable body and middle joint. By employing a hybrid orthogonal design approach, training and test samples are generated from simulated temperature field data. Conductor current, ambient temperature, convective heat transfer coefficient, and insulation thermal conductivity coefficient of the intermediate joint are chosen as variables to compile the dataset. An inverse model‐based prediction method is developed using a firefly‐optimized BP neural network algorithm. Results demonstrate that the optimized model exhibits a correlation coefficient of 0.99, surpassing the prediction accuracy of traditional optimized BP neural networks. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

The long-term operation of oil-immersed transformers causes rapid internal temperature rise, which may lead to accidents such as transformer burning, which has a certain impact on the safe and reliable operation of the power grid. This paper uses finite element simulation to establish a 3-D circuit-magnetic field model based on transformer parameters, accurately calculating core and winding losses. The calculated loss is loaded into the simulation model of the flow temperature field, and the distribution characteristics of the temperature field and flow field of the transformer core and winding are obtained accurately by analyzing the heat transfer mode of the transformer. Through central composite design and range analysis, optimal winding geometry parameters minimizing hot spot temperature are determined. In order to further reduce the temperature rise of the transformer, the principle of enhanced heat dissipation is used, and the cooling module is attached to the radiator of the transformer model, with its shape, position, installation method, and quantity optimized via heat-flow coupling calculations to obtain the optimal scheme to minimize the hot spot temperature of the transformer. The results show that the hot spot temperature of the oil-immersed transformer can be reduced from 78.1 degrees C to 60.7 degrees C, and the hot spot temperature can be reduced by 22.3%. The aforementioned research provides a new idea and reference for oil immersed transformer to reduce temperature rise and improve heat dissipation performance.

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, a 3-D 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. Considering the calculation efficiency and accuracy, a 2-D model of transformer low-voltage winding is established, and the thermal field and flow field distribution of the two models are compared and analyzed. The temperature error was less than 5.98 degrees C, which verified the accuracy of the equivalent model. On this basis, combined with Latin hypercube experiment design and thermal field simulation method, 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, the optimal solution set of Pareto is obtained by using NSGS-II 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 Scheme1 and 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.

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 algorithm according to the experimental magnetic characteristics data of the core material and the classical Jiles-Atherton (J-A) hysteresis model, A 3-D 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.

The oil-immersed transformer is a crucial power equipment in power system, which is prone to abnormality or failure under long running. In order to improve the level of operation and maintenance and ensure the safe and reliable operation of the power grid, it is necessary to diagnose the fault of the oil-immersed transformer in time. Most of the traditional fault vibration methods are off-line detection, and are easily disturbed by mechanical deterioration. In order to solve the above problems, this paper established a 3D electromagnetic and stress coupling simulation model of oil-immersed transformer by finite element simulation software. The vibration characteristics of oil-immersed transformer core winding are obtained, and at the same time, this paper obtained the vibration signals at different positions on transformer core winding and oil tank. According to the vibration signal of the transformer, the best measuring point position of the tank wall is proposed to accurately reflect the vibration characteristics of the transformer. The signal data is preprocessed by CEEMDAN decomposition method, and the signal data is classified by GWO-BP composite classification algorithm. This paper proposed an online transformer fault diagnosis method based on vibration signal, which achieves the purpose of accurately diagnosing oil-immersed transformer faults. The test results show that in the case of oil-immersed transformers the accuracy of the proposed transformer fault diagnosis method is more than 93%, which provides important guiding significance for the safe and stable operation of the transformer. (c) 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

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 back propagation 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 back propagation neural network. The aforementioned research provides the theoretical basis and technical support for real-time monitoring of oil-immersed transformer winding hot spot temperature.

The challenges of noise and temperature rise of air-core reactor have always been the hot issues concerned by scholars on account of its long-term exposure to electromagnetic-thermal-force multi-physics fields. In this paper, a simulation model of three-dimensional electromagnetic-structure-sound and fluid-temperature fields is established on COMSOL according to design parameters of reactor, and the results of sound and temperature fields with and without sound-insulation device are obtained. At first, the sound pressure level and temperature rise distribution characteristics are analyzed, and by combining the central composite design and finite simulation results, the results of sound and temperature fields are acquired with different parameters of sound-insulation device. Then, a neural network model is established,which constructs a correlation between the sound pressure level and the hot temperature of the reactor with sound insulation device. Subsequently, the sensitivity analysis technique is accustomed to derive the influence of the structure parameters on the sound pressure level and the hot temperature. Finally, the multi-island genetic algorithm is applied to obtain the optimal parameters of sound insulation device. The optimization results show that the sound pressure level and the hot temperature of the reactor are decreased by 13.9 dB and 26.3 ℃, respectively, under the optimal parameters. Thus,the optimization method has important reference significance for the parameter optimization of sound-insulation device.

The oil-immersed transformer is an important part of power system operation, and the distribution of its iron core vibration characteristics is of great significance for the safe and stable operation of the transformer. To study the law of vibration characteristics of transformers under normal operating conditions, this paper analyzes the vibration characteristics of transformer cores under actual conditions. The principle of magnetic field and vibration characteristics are analyzed, the model of an oil-immersed three-phase transformer considering clamps is established, and the magnetic flux density distribution and stress distribution of the transformer core part is studied. Meanwhile, the maximum stress distribution area of the iron core is obtained at the connection angle between the iron yoke and the iron core column, the vibration displacement of the maximum stress distribution area is extracted, and the distribution law of the vibration characteristics of the iron core is obtained. This research provides a reference for the subsequent optimal design of the vibration displacement of the transformer.

The overall structure of an oil-immersed transformer is complex. Its heat dissipation process includes thermal convection, thermal conduction, and thermal radiation, so it is difficult to obtain its detailed temperature field distribution characteristics. The simulation model developed in this paper to establish the flow-temperature field coupling of a 20 kV oil-immersed transformer is obtained after analyzing transformer losses and heat transfer. In addition, the distribution of the temperature field of the oil-immersed transformer as well as the analysis of the law of the transformer temperature field distribution are obtained. The result indicates that the hot point temperature of the transformer is 63.73 ℃ while the hot point is distributed at about 1/3 from the upper end inside the low voltage winding.

由于SF6气体的温室效应,以C4F7N、C5F10O、C6F12O和HFO-1234ze(E)等气体为代表的新型环保替代气体得到了广泛的关注,但对于这些气体分子在局部过热或放电状态下导致设备内部温度升高时的分解机理还缺乏研究.为了进一步探究新型环保气体替代SF6气体的可行性,本文以HFO-1234ze(E)分子为例,基于ReaxFF反应分子动力学方法和密度泛函理论,从微观层面模拟研究了HFO-1234ze(E)分子和不同温度下20％HFO-1234ze(E)/80％CO2混合气体的分解现象.结果发现:HFO-1234ze(E)分子存在着7种不同的分解路径,且CO2中的C=O会最先分解;而HFO-1234ze(E)中的C—F键和C=C双键焓值较高,断裂较为困难,随着温度的升高,发生分解的时间也越早.当温度低于2000 K时,HFO-1234ze(E)/CO2混合气体几乎都不会发生分解;当温度为2000 K时,HFO-1234ze(E)分子不会发生分解,CO2分子会迅速发生分解;当温度为2600 K以上时,温度每上升2000 K,HFO-1234ze(E)分子就会多分解5个左右,CO2分子就会多分解35个左右,直到最后基本完全分解.混合气体主要分解产生CO、O2、C2O2、HF、CF4、C2F6、C3F6和C3H3F3等各类自由基,其中:CO为有毒气体、HF为强腐蚀性气体,应采取措施对其含量进行监测;其他分解产物的化学性质均较为稳定且对环境无害,并仍然具有一定的绝缘能力.以上表明20％HFO-1234ze(E)和80％CO2混合气体在一定程度上可以完全替代SF6气体,这也为进一步研究其他新型环保混合气体提供了理论依据和工程指导.

According to the design parameters of dry-type air core reactor with equal high and heat flow， a three-dimensional fluid field-temperature field coupling simulation model is established. Considering the influence of spider arm on reactor temperature rise， the detailed temperature field and flow field distribution characteristics of reactor are obtained.The simulation results show that the temperature rise of each encapsulated coil in reactor is basically the same. The heat dissipation characteristics between the coil and the air duct are obtained by extracting the temperature and velocity distributions along the axial direction of the coil and the air duct. On this basis， the internal coil-air duct unit is selected to reflect the overall temperature rise of the reactor， combined with the experimental correlation of vertical pipe convection heat transfer， the reactor temperature rise calculation method is deduced. Based on the inductance conservation and structural equation of reactor， the relationship between the amount and loss of reactor metal conductor and the overall shape proportion of encapsulated coil， airway width and encapsulated number is constructed， and the influence rules of each structural parameter on the amount of reactor metal conductor are analyzed. Taking the amount of metal conductor of reactor as the optimization objective， the optimal structural parameters of the coil are obtained by multi-island genetic algorithm.The optimization results show that the optimization method can significantly reduce the amount of metal conductor under the condition of ensuring the constant inductance and temperature rise of reactor and meeting the requirements of loss， which provides important guiding significance for the optimal design of reactor.

Due to the greenhouse effect of SF6 gas, new environmentally friendly substitute gases represented by C4F7N, C5F10O, C6F12O, and HFO-1234ze(E) have received widespread attention. However, there is still a lack of research on the decomposition mechanism of these gas molecules when the internal temperature of the equipment increases due to local overheating or discharge conditions. To further investigate the feasibility of using new environmentally friendly gases to replace SF6 gas, more researches are needed. This article takes HFO-1234ze(E) molecules as an example and uses the ReaxFF reactive molecular dynamics method and density functional theory to simulate and study the decomposition of HFO-1234ze(E) molecules and 20%HFO-1234ze(E)/80%CO2 mixture gases at different temperatures from a microscopic perspective. The results show that HFO-1234ze(E) molecules have seven different decomposition pathways, and the C=O bond in CO2 decomposes first. The C—F and C=C bonds in HFO-1234ze(E) have higher enthalpy values, making them difficult to break. As the temperature increases, the time of decomposition occurs earlier. When the temperature is below 2 000 K, HFO-1234ze(E)/CO2 mixture gas will hardly decompose. However, when the temperature reaches 2 000 K, HFO-1234ze(E) molecule remains stable, while CO2 molecule rapidly decomposes. At temperatures above 2 600 K, for every 2 000 K increase in temperature, about 5 more HFO-1234ze(E) molecules decompose, and about 35 more CO2 molecules decompose, until complete decomposition is reached. The mixture gas mainly decomposes into various free radicals such as CO, O2, C2O2, HF, CF4, C2F6, C3F6, and C3H3F3, among which CO is a toxic gas and HF molecules are strongly corrosive. Measures should be taken to monitor their content. The chemical properties of other decomposition products are relatively stable and environmentally friendly, and still have a certain insulating capacity. This indicates that the mixture of 20%HFO-1234ze(E) and 80%CO2 can completely replace SF6 gas to a certain extent, providing a theoretical basis and engineering guidance for further research on other new environmentally friendly mixed gases.

The main reasons for the vibration of iron core reactor include the Maxwell force of the iron core and the magnetostrictive effect of the silicon steel sheet. To accurately establish the magnetostrictive model of silicon steel sheet,the magnetostrictive model is established based on the secondary domain transition model of soft magnetic materials combined with the Jiles-Atherton hysteresis model, and adaptive simulated annealing（ASA） algorithm was used to extract multiple parameters in the model. Based on confirming the validity of the magnetostrictive model, the multi-physics simulation software is used to construct the vibration calculation model of the dry-type iron-core reactor considering the magnetostrictive model. The vibration distribution characteristics of the iron core are analyzed, and an optimization model that can accurately predict the vibration displacement of the iron core is established by combining the Latin hypercube sampling and the Kriging model. In the case of balancing the electromagnetic and vibration characteristics of the core reactor, the amount of metal conductors on the core is minimized, and the optimal structure of the core of the reactor is obtained. The characteristics of the reactor model before and after optimization are compared and analyzed. The results show that, after optimization, the amount of metal conductors in the core of the reactor is reduced by 9.21%; the inductance error is only 0.31%; the vibration of the core is reduced by 18.18%, which meets the electromagnetic and vibration requirements of the reactor.

The loss and the amount of metal conductors are the key factors to be considered in the optimization design of the dry-core reactor. In order to effectively reduce the loss and cost, this paper proposed a multi-objective optimization method for the dry-core reactor based on the multi-physical field simulation and the VIKOR decision. Firstly, the dry-core reactor was taken as the research object, and the magnetic field-flow field-temperature field model was established. The loss density of the core and the coil obtained from the magnetic field calculation was used as the heat source, and the reactor temperature distribution was obtained through the fluid-thermal coupling calculation; Then the magnetic field-structure field model was established. Taken the electromagnetic force calculated based on the magnetic field as the stress item, the vibration displacement distribution of the core and coil were calculated. The temperature rise and vibration displacement results of the core reactor under different structural parameters were obtained by combining the finite element simulation and the Latin hypercube test design. In order to further simplify the optimization process, the sensitivity analysis method was used to reduce the dimension of parameters. The agent model among the design parameter, the temperature rise and the vibration was established considering key parameters. The multi-objective genetic algorithm was used to obtain the Pareto frontier solution set that meets the performance requirements of the reactor. Considering the conflict between the amount of metal conductor and the loss of the reactor, the VIKOR comprehensive decision method was introduced. On the basis of determining the weight of the optimization objective, the benefit ratio of the Pareto solution set was calculated. The optimal design parameter combination was determined by the minimum benefit ratio. The correctness of the optimization design method was verified by simulation. Compared with that before optimization, the consumption of iron core and coil metal conductors of the optimized iron core reactor decreases by 3.0% and 16.6% respectively with the loss increased by 4.4%. At the same time, the temperature rise and vibration decreases by 7.4% and 16.7% respectively on the basis of meeting the design requirements. The proposed method can effectively improve the performance and provide guidance for the optimization design of reactors.

以铁心电抗器线圈作为研究对象,以均衡电磁、温升及振动特性,提高金属材料利用率为目的,进行了优化设计.首先采用电磁场-温度场-结构场多物理场耦合有限元方法分析了电抗器线圈的结构参数对电磁、温升及振动的影响.根据分析结果,结合正交试验法对线圈结构进行优化设计,在均衡电抗器电磁、温升及振动特性的情况下使绕组导体用量最小化,获得铁心电抗器线圈的最佳结构参数.为了验证优化设计方法的正确性,将优化前后的模型进行性能比较,结果表明,优化后铁心电抗器线圈的导体用量与优化前相比减少了16.8％,且电感偏差仅为0.6％;线圈的最大温升降低了7.3％,内层线圈的振动位移增加了14.3％,外侧线圈的振动大小不变,满足了电抗器对于电磁、温升及振动的要求.

In this paper, a fluid-thermal coupled finite element model is established according to the design parameters of dry type air core reactor. The detailed temperature distribution can be achieved, the maximum error coefficient of temperature rise is only 6% compared with the test results of prototype, and the accuracy of finite element calculate method is verified. Taking the equal height and heat flux design parameters of reactor as research object, the natural-convection cooling performance of reactor with and without the rain cover is investigated. It can be found that the temperature rise of reactor is significantly increased when adding the rain cover, and the reasons are given by analyzing the fluid velocity distribution of air ducts between the encapsulation coils. In order to reduce the temperature rise of the reactor with the rain cover, the optimization method based on the orthogonal experiment design and finite element method is proposed. The six factors of the double rain cover are given, which mainly affect the temperature rise of reactor, and the five levels are selected, the influence curve and contribution rate of each factor on the temperature rise of reactor are analyzed. The results show that the contribution ratio of the parameter H1, L1, and L2, are obviously higher than the parameter H2, L3, and ?, so the more attention should be paid in the design of double rain cover. Meanwhile, the optimal structural parameters of rain cover are given based on the influence curves, and the temperature rise is only 43.25?. The results show that the optimization method can reduce the temperature rise of reactor significantly. In addition, the temperature distribution of inner encapsulations coils of reactor are basically the same, the current carrying capacity of coils can be fully utilized, which provides an important guidance for the optimization design of reactor.

In this paper, the three‐dimensional fluid field‐temperature field coupled model of air core reactor is established, the detailed temperature field distributions of reactor can be obtained, and the reason about the temperature rise of reactor is significant increased when adding the rain cover is given by analyzing the flow velocity of fluid in the air ducts. Considering the natural air cooling no longer meets the temperature rise requirement of the reactor, the forced air cooling is performed by installing ventilation duct and fan at the bottom of the reactor, combined with the finite element method and central composite experimental design method (CCD), the influence of structure parameters of rain cover and ventilation duct on the temperature rise of reactor are analyzed, meanwhile, the response surface model is established, which reflects the relationship between the temperature of reactor and the structure parameter of rain cover and ventilation duct, and the optimal design parameters can be obtained based on the quantum genetic algorithm, the maximum temperature of the reactor is only 59.3°C, the difference between the prediction of response surface and simulation result is only 0.1°C, and the correctness of the optimization method is validated, which provides an important guiding significance for the safe and stable operation of reactor in the system. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

In this paper, the CFD model is established for the low voltage winding region of an oil-immersed transformer according to the design parameters, and the detailed temperature distribution within the region is obtained by numerical simulation. On this basis, the response surface methodology is adopted to optimize the structure parameters with the purpose of minimizing the hot spot temperature. After a sequence of designed experiments, the second-order polynomial response surface and the support vector machine response surface are established, respectively. The analysis of their errors shows that the support vector machine response surface can be better used to fit the approximation. Finally, the particle swarm optimization algorithm is employed to get the optimal structure parameters of the winding based on the support vector machine response surface. The results show that the optimization method can significantly reduce the hot spot temperature of the winding, which provides a guiding direction for the optimal design of the winding structure of transformers.

In this paper, a coupled flow-thermal field simulation model is established based on the parameters of the transformer. Then the distribution of the flow and thermal fields are obtained. The results show that oil backflow occurs to varying degrees at the top and bottom of the transformer. In addition, with the formation of backflow, the hot spot temperature of the transformer increases. Through the combination of orthogonal experiments and finite element method, the geometric structure of winding oil passage is selected as the optimization variable. The law between the winding structure and the maximum temperature is acquired by means of range and variance analysis, and the optimal parameters are obtained. The hot spot temperature is reduced by 34.27 K compared to the pre-optimization period, which is a guideline for the design of transformers.

干式铁心电抗器长期处于电磁、热及应力等物理场中,其温升和振动问题日益严重.为了解决上述问题,提高金属导体材料的利用率,该文提出了干式铁心电抗器多物理场耦合仿真与协同优化相结合的设计方法.首先分析铁心电抗器温升及振动机理,指出影响铁心电抗器温升及振动的主要因素.然后,搭建干式铁心电抗器系统级协同优化模型.温升方面采用包封线圈-气道单元散热效率优化方法,在振动方面采用Kriging近似模型优化方法,通过灵敏性分析将设计变量划分为敏感和不敏感2个层次.最后,采用多岛遗传算法获得最佳的设计,仿真结果验证了优化设计方法的正确性.优化结果表明,该文提出的干式铁心电抗器多物理场协同优化设计方法,在满足电感、温升和振动等参数的前提条件下,绕组和铁心的用量分别减少了17.1％和6.7％,显著提高了金属导体利用率.