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Article

Steady-State Temperature Prediction for Cluster-Laid Tunnel Cables Based on Self-Modeling in Natural Convection

1
State Grid Shanghai Electrical Power Research Institute, Shanghai 200437, China
2
MOE Key Laboratory of Thermo-Fluid Science and Engineering, Xi’an Jiaotong University, Xi’an 710049, China
*
Author to whom correspondence should be addressed.
Energies 2024, 17(21), 5510; https://doi.org/10.3390/en17215510
Submission received: 11 September 2024 / Revised: 19 October 2024 / Accepted: 29 October 2024 / Published: 4 November 2024
(This article belongs to the Section F6: High Voltage)

Abstract

Accurate temperature prediction of the operating tunnel cable is crucial for its safe and efficient function. To achieve a rapid and accurate prediction of the steady-state temperature of the tunnel cable, the self-modeling pattern in natural convection on the cable surface in the rectangular tunnel is investigated, and the self-modeling method for the convective heat transfer coefficient calculation is proposed. A thermal circuit model for single cables is further established to predict the cable core temperature, and the model is extended to predict the cluster-laid cable core temperature based on the combined method. The results show that when the tunnel size is neglected, the maximum relative deviation of the convective heat transfer coefficient between the self-modeling method and the finite element simulation is only 1.78% in the studied cases, indicating that the natural convection on the cable surface approximately satisfies the self-modeling method. Additionally, applying the self-modeling method to the thermal circuit can accurately predict the temperature of the single cable core. Furthermore, for the three-phase four-circuit cable, the maximum deviation between the temperature prediction results and the finite element results is within 2 K in the studied cases, which verifies the predictive accuracy of the combined method for the cluster-laid tunnel cable.
Keywords: tunnel cable; steady-state cable core temperature; self-modeling in natural convection; thermal circuit model; numerical simulation tunnel cable; steady-state cable core temperature; self-modeling in natural convection; thermal circuit model; numerical simulation

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MDPI and ACS Style

Zhao, Y.; Si, W.; Fu, C.; Yang, C.; Yang, J. Steady-State Temperature Prediction for Cluster-Laid Tunnel Cables Based on Self-Modeling in Natural Convection. Energies 2024, 17, 5510. https://doi.org/10.3390/en17215510

AMA Style

Zhao Y, Si W, Fu C, Yang C, Yang J. Steady-State Temperature Prediction for Cluster-Laid Tunnel Cables Based on Self-Modeling in Natural Convection. Energies. 2024; 17(21):5510. https://doi.org/10.3390/en17215510

Chicago/Turabian Style

Zhao, Yingying, Wenrong Si, Chenzhao Fu, Chenhan Yang, and Jian Yang. 2024. "Steady-State Temperature Prediction for Cluster-Laid Tunnel Cables Based on Self-Modeling in Natural Convection" Energies 17, no. 21: 5510. https://doi.org/10.3390/en17215510

APA Style

Zhao, Y., Si, W., Fu, C., Yang, C., & Yang, J. (2024). Steady-State Temperature Prediction for Cluster-Laid Tunnel Cables Based on Self-Modeling in Natural Convection. Energies, 17(21), 5510. https://doi.org/10.3390/en17215510

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