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A Coupled, Semi-Numerical Model for Thermal Analysis of Medium Frequency Transformer

Author

Listed:
  • Haonan Tian

    (Energy Research Institute @ NTU, Nanyang Technological University, Singapore 637141, Singapore)

  • Zhongbao Wei

    (Energy Research Institute @ NTU, Nanyang Technological University, Singapore 637141, Singapore)

  • Sriram Vaisambhayana

    (Energy Research Institute @ NTU, Nanyang Technological University, Singapore 637141, Singapore)

  • Madasamy Thevar

    (Energy Research Institute @ NTU, Nanyang Technological University, Singapore 637141, Singapore)

  • Anshuman Tripathi

    (Energy Research Institute @ NTU, Nanyang Technological University, Singapore 637141, Singapore)

  • Philip Kjær

    (Vestas Wind System A/S, Hedeager 42, 8200 Aarhus N, Denmark
    Department of Energy Technology, The Faculty of Engineering and Science, Aalborg University, 9220 Aalborg, Denmark)

Abstract

Medium-frequency (MF) transformer has gained much popularity in power conversion systems. Temperature control is a paramount concern, as the unexpected high temperature declines the safety and life expectancy of transformer. The scrutiny of losses and thermal-fluid behavior are thereby critical for the design of MF transformers. This paper proposes a coupled, semi-numerical model for electromagnetic and thermal-fluid analysis of MF oil natural air natural (ONAN) transformer. An analytical model that is based on spatial distribution of flux density and AC factor is exploited to calculate the system losses, while the thermal-hydraulic behavior is modelled numerically leveraging the computational fluid dynamics (CFD) method. A close-loop iterative framework is formulated by coupling the analytical model-based electromagnetic analysis and CFD-based thermal-fluid analysis to address the temperature dependence. Experiments are performed on two transformer prototypes with different conductor types and physical geometries for validation purpose. Results suggest that the proposed model can accurately model the AC effects, losses, and the temperature rises at different system components. The proposed model is computationally more efficient than the full numerical method but it reserves accurate thermal-hydraulic characterization, thus it is promising for engineering utilization.

Suggested Citation

  • Haonan Tian & Zhongbao Wei & Sriram Vaisambhayana & Madasamy Thevar & Anshuman Tripathi & Philip Kjær, 2019. "A Coupled, Semi-Numerical Model for Thermal Analysis of Medium Frequency Transformer," Energies, MDPI, vol. 12(2), pages 1-16, January.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:2:p:328-:d:199520
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    References listed on IDEAS

    as
    1. Pei Huang & Chengxiong Mao & Dan Wang, 2017. "Electric Field Simulations and Analysis for High Voltage High Power Medium Frequency Transformer," Energies, MDPI, vol. 10(3), pages 1-11, March.
    2. Gang Liu & Zhi Zheng & Dongwei Yuan & Lin Li & Weige Wu, 2018. "Simulation of Fluid-Thermal Field in Oil-Immersed Transformer Winding Based on Dimensionless Least-Squares and Upwind Finite Element Method," Energies, MDPI, vol. 11(9), pages 1-17, September.
    3. Muhammad Hakirin Roslan & Norhafiz Azis & Mohd Zainal Abidin Ab Kadir & Jasronita Jasni & Zulkifli Ibrahim & Azalan Ahmad, 2017. "A Simplified Top-Oil Temperature Model for Transformers Based on the Pathway of Energy Transfer Concept and the Thermal-Electrical Analogy," Energies, MDPI, vol. 10(11), pages 1-15, November.
    4. Li Zhang & Wenfang Zhang & Jinxin Liu & Tong Zhao & Liang Zou & Xinghua Wang, 2017. "A New Prediction Model for Transformer Winding Hotspot Temperature Fluctuation Based on Fuzzy Information Granulation and an Optimized Wavelet Neural Network," Energies, MDPI, vol. 10(12), pages 1-13, December.
    5. Wei Chen & Jien Ma & Xiaoyan Huang & Youtong Fang, 2015. "Predicting Iron Losses in Laminated Steel with Given Non-Sinusoidal Waveforms of Flux Density," Energies, MDPI, vol. 8(12), pages 1-15, December.
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    7. Wei, Zhongbao & Zhao, Jiyun & Ji, Dongxu & Tseng, King Jet, 2017. "A multi-timescale estimator for battery state of charge and capacity dual estimation based on an online identified model," Applied Energy, Elsevier, vol. 204(C), pages 1264-1274.
    8. Ruohan Gong & Jiangjun Ruan & Jingzhou Chen & Yu Quan & Jian Wang & Shuo Jin, 2017. "A 3-D Coupled Magneto-Fluid-Thermal Analysis of a 220 kV Three-Phase Three-Limb Transformer under DC Bias," Energies, MDPI, vol. 10(4), pages 1-9, March.
    9. Ruohan Gong & Jiangjun Ruan & Jingzhou Chen & Yu Quan & Jian Wang & Cihan Duan, 2017. "Analysis and Experiment of Hot-Spot Temperature Rise of 110 kV Three-Phase Three-Limb Transformer," Energies, MDPI, vol. 10(8), pages 1-12, July.
    10. Lefeng Cheng & Tao Yu & Guoping Wang & Bo Yang & Lv Zhou, 2018. "Hot Spot Temperature and Grey Target Theory-Based Dynamic Modelling for Reliability Assessment of Transformer Oil-Paper Insulation Systems: A Practical Case Study," Energies, MDPI, vol. 11(1), pages 1-26, January.
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    Cited by:

    1. Dante Ruiz-Robles & Jorge Ortíz-Marín & Vicente Venegas-Rebollar & Edgar L. Moreno-Goytia & David Granados-Lieberman & Juan R. Rodríguez-Rodriguez, 2019. "Nanocrystalline and Silicon Steel Medium-Frequency Transformers Applied to DC-DC Converters: Analysis and Experimental Comparison," Energies, MDPI, vol. 12(11), pages 1-16, May.

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