This paper addresses the temperature rise problem of the ring main unit by establishing a simplified model and conducting a comparative analysis in two temperature field-solving modules.
The Ring Main Unit (RMU) is a critical device in power distribution systems used for connecting and distributing electricity. However, due to its compact internal structure and high current load, heat dissipation issues are particularly prominent. To address this problem, this study innovatively proposes a simplified RMU model, employing finite element simulation methods to accurately solve for the ohmic losses of conductors under actual operating conditions and obtain ohmic loss data for various components. This is the first in-depth investigation of the RMU’s temperature rise problem using such a comprehensive approach. Subsequently, the temperature field was solved using two different temperature field analysis modules, with a detailed comparison and analysis of the simulation results to identify similarities, differences, and trends in temperature distribution. The results indicate that the temperature field solution model, which considers convective heat transfer, is more accurate and aligns with actual operating conditions. This research provides an innovative approach and practical solutions for the design and optimization of RMUs. Future research can further explore multiphysics coupling analysis methods to address structural design and mandatory validation issues for high and ultra-high voltage RMUs and other electrical equipment, thereby providing important insights for engineering design.
The ring main unit is a group of high-voltage switchgear mounted in a steel metal cabinet or made of assembled spaced ring network power supply unit of electrical equipment. The overall structure of the load switch and conductive circuit consists of the conductive circuit, which includes a number of components comprising the main core of the ring unit. However, due to its compact internal structure, the ring main unit faces challenges in heat dissipation. This can lead to thermal deformation and aging when operating for extended periods in high-temperature environments. These issues not only affect the service life of the unit but also impact its insulating properties, posing safety risks. In particular, equipment damage and electrical accidents become more likely, posing significant safety hazards.
Within different research areas, scholars have conducted a series of studies on the temperature rise of overhead line switchgear and analyzed various factors affecting the temperature distribution1. In Polykrati et al.2, a mathematical model for the estimation of the temperature rise of components installed on the distribution network during a short-circuit fault is presented. The model was applied to the common disconnecting switches of the network, and the characteristics of the results were plotted according to the different forms of the asymmetrical part of the short-circuit current waveform and the initial value of the short-circuit DC current component. Guan et al., on the other hand, have taken into account the contact resistance and electromagnetic repulsion by building an equivalent contact bridge to simulate the contact interface and further analyzed the electromagnetic-thermal coupling field and temperature rise experiment3. In addition, the researchers investigated the temperature field and thermal stress distribution of the dynamic and static contacts inside the ring main unit by finite element simulation, which provided a basis for the study of circuit breaker life4. Finally, Mueller et al. have focused on the geometrical characteristics of heat sinks and evaluated the effects of material selection, total surface area, temperature uniformity, and maximum surface temperature on thermal performance5. These studies provide valuable insights and methods to improve switchgear performance and reliability, reduce temperature rise, and extend equipment life. Wang et al. proposed a MiNET Deep Learning Model (MDLM) in the UPIOT environment with the purpose of detecting fault diagnosis of electrical ring cabinets, which was validated to have an identification accuracy of 99.1%, which is significantly higher than that of other methods6. Lei et al. studied the thermal performance of a GIS busbar in a steady state using the magneto-fluid-thermal coupling analysis method, thereby optimizing the conductor and tank diameter based on the temperature rise simulation results7. Ouerdani et al. used the RMU temperature rise simulation model to determine the temperature rise at critical locations inside it, thereby fixing the duration of the maximum overload for the components inside the RMU accordingly8. Zheng et al. described a conventional rectangular busbar in a model of high-current switchgear by building a two-dimensional model and applying the finite element method (FEM) for electromagnetic field calculations. It enabled them to obtain the distribution of bus conductor current density and power loss. An irregular busbar was designed after considering the effects of proximity effect and skin effect. This irregular busbar design improved the performance of conventional rectangular busbar9.
As for the aspect of using the icepak simulation, Wang et al. carried out a temperature rise simulation through vortex field, airflow field, and temperature field theories and found that the temperature rise of the ring main unit was more serious under natural convection. They successfully reduced the temperature rise level by adding forced air cooling and making improvements to the internal contact structure10. Zhu et al.11 used the icepak to simulate a thermal model in order to compare the effect of the presence of thermal vias on the PCB and the presence of heat sinks on the temperature of the power devices. Finally, the theoretical analysis is compared with the simulation results to verify the correctness of the theoretical analysis. Mao et al.12 studied the temperature and internal airflow distribution under summer operating conditions by thermal simulation based on the CAE software in the icepak simulation. The problem of how to improve the cooling efficiency and control the temperature rise of multiple silver-plated contacts is given, and the temperature and internal airflow contours captured in the simulation will lay the foundation for the design of the cooling scheme for the six silver-plated contacts mounted in the sealing unit. Conversely, in the use of a steady-state thermal module, Zhang13 Modeling methods are discussed for solving the thermal network of a high-pressure bushing using an alternative transient procedure. Test and simulation results are in good agreement with the thermal steady state and transient states of the bushing. The transient results are then used to evaluate the bushing overload capacity. Vaimann et al.14 developed and analyzed an analytical thermal model of a synchronous reluctance motor for predicting the temperature of its different components and the set total parameter thermal network.
With the continuous advancement of research on electrical equipment such as ring main units, conventional temperature rise tests, and production methods are relatively inefficient. Therefore, by utilizing finite element technology combined with offline tests, not only the design cost issues are addressed, but adjustments and optimizations can be promptly made to real-world problems based on simulations. Based on the research progress mentioned above, the use of ANSYS Icepak and Steady-state thermal coupling for comparative analysis is rarely mentioned. Therefore, the protocol describes the mechanism research of finite elements, uses numerical and morphological combinations to establish a finite element temperature rise simulation model for the enclosure, and discusses the finite element temperature rise simulation model based on the results of the two analytical modules by comparing the results of the two simulation modules. Through the comparison between the two simulation modules, we will get the characteristics of the temperature rise trend of the ring main unit and find the most applicable method so as to provide the necessary basis and research ideas for a strategy to mitigate the temperature rise of the ring main unit.
1. Model
NOTE: Due to the complex structure of the ring main unit (Figure 1A), an online design software was chosen to simplify the operation of the ring main unit.
2. Eddy field solution
3. Temperature field solution
NOTE: For comparative purposes, divide the temperature field into Icepak and steady state thermal. Set up and solve each separately to achieve a comparative analysis.
Based on the data in Table 3, the following conclusions can be drawn: The overall losses for Phases A, B, and C are relatively similar. Specifically, the total losses for Phase A are 16.063 W/m³, Phase B is 16.12 W/m³, and Phase C is 19.57 W/m³. The locations with higher losses may be at the connections of various components. This is mainly because contact resistance and conductor resistance typically exist at these connection points. When current passes through these connections, significant heat is generated, leading to an increase in temperature and higher losses in those areas.
The upper and lower outgoing arms of the ring main unit bear some losses, especially when carrying the main load. The losses in the outgoing arms of the three phases are approximately the same. This is because this part of the current is relatively concentrated, and due to the regular shape, the resistance value is small. Therefore, the losses in these parts are approximately equal.
The losses in the branch busbar are relatively high, primarily due to its numerous bends and the presence of angled sections. Most of the current is concentrated in the bend area and near the corners. Apart from the vacuum circuit breaker section, the losses in the copper tube part of the busbar are also relatively high, totaling 22.32 W/m³, accounting for 40% of the overall ohmic losses of the three phases. The losses in the static contact part are relatively small compared to the overall losses.
Other components, such as the circuit breaker fixed plate, circuit breaker baffle, and the outer shell of the ring main unit, have smaller losses. Since they do not directly participate in the load, their losses are mainly generated by the internal components through conduction, resulting in smaller loss values. In post-processing calculations, the losses of these components are not particularly detailed. In summary, the main characteristics of the loss distribution have been outlined, providing valuable insights for further design optimization.
Combining the results from Figure 3 and Figure 4, along with Table 5 and Table 6, a thorough comparison of the temperature field solution results between the Icepak and Steady-state Thermal modules was conducted. In the analysis process, differences and similarities were observed between the two modules.
In the temperature range of 20-31.24 °C, as shown in Figure 2A, the higher temperature areas are concentrated in the regions where the RMU enclosure contacts the internal components. The main reason is that these contact areas typically serve as critical paths for heat conduction. During operation, the internal components generate heat, which is conducted to the enclosure through the contact surfaces with good thermal conductivity, thereby causing an increase in temperature in these regions. These areas include the contact points of the upper outgoing line arm and the portions of the lower outgoing line arm in contact with its nearby shell, with a temperature range of approximately 24-27 °C. Compared with Figure 3B, the warming range of the shells in both cases is roughly the same, and the temperature changes propagate from the hotspots to the cooler areas. Examining Figure 4A,B, the overall temperature trends in both cases are also approximately similar. The primary source of temperature rise is the heat conduction through the lower outgoing line arm, which passes through the internal conductors and dissipates from the upper outgoing line arm. The warming trend is concentrated in areas close to the lower outgoing line arm, including the branch busbars of each phase and the connected supporting busbars. Furthermore, from the observation of the temperature distribution in the internal circuits in Figure 4, whether using Icepak or the Steady-state Thermal module for solving, the overall temperature of Phase B is consistently higher than the other two phases. This mainly suggests that Phase B, during the load process, not only bears the heat generated by the current of that phase but also, due to the overly compact internal structure of the RMU, the heat produced by each phase cannot dissipate promptly. Due to the exchange of heat, the temperature of Phase B remains higher than the other two phases regardless of the solver used. The overall temperature trends also exhibit a high degree of similarity, with the main temperature rise stemming from the heat conduction through the lower outgoing line arm and the dissipation of heat from the upper outgoing line arm. This trend appears highly consistent between the two modules. Moreover, the positions of the hotspots in the temperature distribution maps of both modules are highly consistent. Particularly, in the branch busbar section of Phase C, both solvers show the same highest temperature and the differences are almost negligible. This implies that regardless of the solver used, accurate identification of the hottest temperature positions is crucial for the thermal management of the RMU.
Secondly, it can be seen from the table that the same current produces the same loss, but the temperature value of each phase component in Table 6 is generally lower than that in Table 5; for example, the temperature value of the branch bus in the hot spot area of the entire RMU is the highest temperature in Table 6 at 30.91 °C, and on the other hand, the highest temperature of the branch bus in Table 5 is 31.24 °C. The reason is the solution logic of Icepak: the RMU as a heat source will continue to exchange heat and dissipate heat, and when a fluid is set as a medium for heat transfer, the temperature in the solution domain will gradually be emitted through the medium, which results in a decrease in temperature. The Steady-state Thermal module places less emphasis on heat convection with the surrounding air and instead focuses on a heat conduction-based solution. Compared to models that account for convection, this approach results in a less comprehensive temperature field solution. Consequently, in areas where the temperature is higher, hot spots become more pronounced. In the process of the actual temperature rise test, in addition to considering the characteristics of the model itself, heat transfer at the same time also considers the influence of heat dissipation medium, such as air, etc., on the overall temperature. Combined with the practical needs and experimental operation considerations, the RMU as a heat source continues to carry out heat convection and heat dissipation; the temperature simulation of icepak is more in line with the actual needs. In the case where the ring main unit is used as a heat source with continuous heat convection and dissipation, the temperature simulation of icepak is more in line with the practical needs. On the contrary, the steady-state thermal module mainly focuses on heat conduction, which may not be able to meet the actual needs in some cases.
Figure 1: Ring main unit model. (A) Overall model of ring main unit (B) Simplified model of ring main unit. Please click here to view a larger version of this figure.
Figure 2: Polarization curves for four sets of meshes. Maxwell adaptive meshing is used for larger parts, and local mesh refinement is used for smaller parts. In design software, a simplified 3D model of the ring main cabinet is created and imported into Maxwell, and the model is meshed using its Mesh module. The figure represents the verification of the model grids. The current density of the four groups of grids is 2.357 A/cm2, 2.358 A/cm2, 2.356 A/cm2 and 2.354 A/cm2 under the voltage loading, and the relative error between the maximum current density and the minimum current density is less than 1%, and in order to take into account the efficiency and accuracy of the calculations, the final number of the grids is determined to be 1169091. Please click here to view a larger version of this figure.
Figure 3: Outer cabinet temperature field analysis model. (A) Shell temperature distribution with Icepak solution. (B) Shell temperature distribution with Steady-state thermal solution. Please click here to view a larger version of this figure.
Figure 4: Internal circuit temperature field analysis model. (A) Temperature distribution of the conducting loop with Icepak solution (B) Temperature distribution of the conducting loop with Steady-state thermal solution. Please click here to view a larger version of this figure.
Material | Air | Galvanized steel sheet | Copper | Aluminum | ||
Specific heat capacity (J/(kg·K)) | 1007 | 500 | 500 | 897 | ||
Density (kg/m³) | 1.1614 | 8030 | 8900 | 2689 | ||
Relative permeability | 1 | 0.3 | 0.9999991 | / | ||
Relative magnetic permeability | 1 | 2500 | 1 | 1 | ||
Thermal conductivity (W/(m·K)) | 0.026 | 16 | 386 | 237 | ||
Emissivity | / | 0.65 | 0.3 | 0.1 | ||
Electrical conductivity (S/m) | / | 0.8 | 5.80E+07 | / |
Table 1: Physical parameters of some materials in the ring main unit.
Components | Relative permeability | Conductivity/s | Material |
Current-carrying circuits (busbar, branch busbar, etc.) | 0 | 3,00,00,000 | Aluminium alloy |
Vacuum circuit breaker | 0.9999 | 2,00,00,000 | Copper alloys |
Body | 200 | 11,00,000 | Structural steel |
Table 2: List of materials for each component.
Ohmic loss W/m³ | A | B | C |
Out let arm | 3.78 | 3.72 | 3.73 |
Branch busbar | 2.1 | 2.09 | 2.1 |
Flexible connection | 1.3 | 1.3 | 1.3 |
Vacuum circuit breaker | 1.023 | 0.95 | 0.98 |
Static contacts | 0.36 | 0.36 | 0.36 |
feeder busbar | 1.33 | 1.35 | 1.32 |
Copper tubes for branch busbars | 6.19 | 6.35 | 9.78 |
Table 3: Ohmic loss values for phase A, B, and C components.
Number | 1 | 2 |
Materia | Aluminum6061-T6 | Cu-Pure |
Thermal conductivity (W/m·K) | 167 | 387.6 |
Density (kg/m³) | 8933 | 2700 |
Specific heat capacity/(kg·K) | / | 896 |
Surface material | Paint-AL surface | Cu-Polished-surface |
Emissivity | 0.35 | 0.052 |
Table 4: Material parameter settings.
Temperature monitoring point/temperature (°C) | A | B | C |
Upper outlet arm | 25.48 | 25.79 | 25.63 |
Main busbar | 25.93 | 26.28 | 26.13 |
Branch busbar | 29 | 29.18 | 30.01 |
Branch busbar copper tube | 31.04 | 31.18 | 31.24 |
Lower outlet arm | 26.5 | 26.98 | 26.92 |
Table 5: Temperature values of each phase of the ring main unit under the Steady-state thermal temperature field solving module.
Temperature monitoring point/temperature (°C) | A | B | C |
Upper outlet arm | 23.73 | 23.82 | 23.81 |
Main busbar | 25.15 | 25.17 | 25.35 |
Branch busbar | 27.76 | 28.04 | 29.07 |
Branch busbar copper tube | 28.42 | 29.31 | 30.91 |
Lower outlet arm | 24.95 | 24.85 | 26.33 |
Table 6: Temperature values at monitoring points of each phase of the ring cabinet under Icepak temperature field solution module
This paper is a comparative simulation analysis of the temperature rise of the ring cabinet based on engineering modeling software and finite element software, and the most suitable solution for the actual temperature rise situation is analyzed by two finite element temperature field solution modules. Thermal management is also described in Icoz23 as a critical and essential component in maintaining the high efficiency and reliability of electronic components. The significance of conducting a comparative analysis is summarized by drawing on the work in Steiner24: a comparative analysis has been carried out using COMSOL and ANSYS Mechanical. Therefore, in the process of manufacturing the actual RMU, its temperature distribution can be analyzed by finite simulation software, which can greatly save manpower and production costs.
The three-dimensional model of the RMU can be created using SolidWorks, as shown in Figure 1A. In Step 1.1, model simplification is emphasized as a crucial step in finite element analysis23. Given the numerous components of the RMU, which may impact solution accuracy and computational results, unnecessary parts are removed after considering only the conductive components. The main working parts are retained, as illustrated in Figure 1B.
In the preprocessing stage of the Eddy current field, a critical aspect involves the addition and verification of load excitation. As described in Step 2.1, it is essential to accurately add the load current to the upper and lower outgoing arms, ensuring that the entire conductive circuit forms a path for the current. This facilitates the calculation of the distribution cloud map of the eddy current field. The difficulty lies in the need to check the circuit before the solution calculation, as an incomplete current path in the circuit can lead to non-convergence during solving or situations where Maxwell cannot compute. Subsequent temperature field analysis relies entirely on the losses obtained from solving this eddy current field, making the inspection of the current path a necessary step.
In the temperature field solution, Step 3 presents two different modules for solving the model. However, ensuring identical initial conditions during the solution process poses a challenge. Since the modules have different emphases in their solutions, it is necessary to approximate or set identical environmental temperatures, convective coefficients, and other solving conditions to ensure consistency under the unique heat source provided by Maxwell. Furthermore, controlling the intervals for temperature field solution in both models to be consistent allows for a direct comparison of temperature displays for the same components in the same temperature range, highlighting differences in the solutions and facilitating intuitive conclusions.
This paper presents an innovative method for accurately measuring and analyzing the temperature distribution of electrical equipment during operation. Addressing the challenge of precisely measuring ohmic losses with traditional methods, this study utilizes the Maxwell eddy current solver for accurate calculations, which then serves as the basis for solving the temperature field. Subsequently, the temperature field-solving module is used to visually display the temperature distribution of each component, significantly enhancing the efficiency and accuracy of engineering tests. The novelty of this paper lies not only in providing an efficient method for solving the temperature field but also in demonstrating how to use these results for structural optimization and heat dissipation analysis. This offers new technical means for the design and optimization of electrical equipment. However, there were limitations in the research process, and in future work, further research will be conducted in the following areas. Firstly, model refinement and multi-field coupling. The model will be further refined to accurately reflect the thermal characteristics of the ring network cabinet during actual operation. Secondly, studying transient temperature fields. In-depth research will be carried out on the temperature field changes of the ring network cabinet under varying load conditions to provide additional support for the stable operation of the ring network cabinet in complex operating conditions.
The authors have nothing to disclose.
The authors thank Mr. Wu, MS Sun, Mr. Wang, Mr. Mu, and Mr. Li for their help. This study was supported by the China Postdoctoral Science Foundation (2022M721604) and the Wenzhou Key Science and Technology Tackling Programmer (ZG2023015).
Air | / | / | Conventional gases |
Aluminum | / | / | Alloy Materials |
Copper | / | / | Alloy Materials |
Icepak | ANSYS company | ANSYS 2021R1 | A CFD thermal simulation software |
PC hosting | / | 12th Generation Intel(R) Core(TM) i5-13500F CPU | Host computer equipment |
SolidWorks | Subsidiary of Dassault Systemes | SolidWorks2021 | An engineering software drawing tool |
Steady-state thermal | ANSYS company | ANSYS 2021R1 | A thermal simulation solution tool |