Influence of core window height on thermal characteristics of dry-type transformers

被引:0
|
作者
Dawood, Kamran [1 ]
Kul, Seda [2 ]
机构
[1] Astor Enerji, Dept Res & Dev, Ankara, Turkiye
[2] Karamanoglu Mehmetbey Univ, Elect & Elect Engn Dept, Karaman, Turkiye
关键词
Core window; Dry-type transformer; Finite element analysis; Thermal analysis; Power transformer; TEMPERATURE; PERFORMANCE; EFFICIENCY; ONAN;
D O I
10.1016/j.csite.2025.105746
中图分类号
O414.1 [热力学];
学科分类号
摘要
Elevated temperatures in transformer windings and cores pose a significant risk of damage to power transformers. The objective of this work is to analyze the influence of core window dimensions on the thermal efficiency of power transformers. Analytical approaches are limited in their ability to consider the impact of core window dimensions on the transformer's thermal behavior. Conversely, experimental methods are both expensive and time-consuming. To overcome these constraints, this work assesses and optimizes the temperature distribution in dry-type power transformers using finite element models, specifically examining the impact of the core window. The thermal model treats core and winding losses as sources of heat generation. Four different transformers, with varying heights of the transformer core window, have been modeled to assess the impact of window height on the thermal conditions of the transformers. The simulation findings indicate that variations in core window height have a significant impact on the transformer's thermal properties. By comparing the model's predictions of short-circuit impedance with experimental data, this study demonstrates the model's capability to reliably estimate parameters influenced by core window variations, thereby validating its usefulness.
引用
收藏
页数:14
相关论文
共 50 条
  • [21] Simulation and experimental analysis of dynamic thermal rise relaxation characteristics for dry-type distribution transformer
    He, Dong-sheng
    Jia, Zhi-dong
    Yue, Yong-gang
    Wang, Ji-xiang
    Xiong, Liu-rang
    Xia, Shi
    Fu, Jian-bing
    He, Fa-wu
    INTERNATIONAL JOURNAL OF EMERGING ELECTRIC POWER SYSTEMS, 2024,
  • [22] Investigation on the Action of Eddy Current on Tank Vibration Characteristics in Dry-Type Transformer
    Zhang, Fan
    Ji, Shengchang
    Shi, Yuhang
    Zhu, Lingyu
    IEEE TRANSACTIONS ON MAGNETICS, 2019, 55 (02)
  • [23] Thermal response and failure mode evaluation of a dry-type transformer
    Blanco Alonso, Pelayo E.
    Meana-Fernandez, Andres
    Fernandez Oro, Jesus M.
    APPLIED THERMAL ENGINEERING, 2017, 120 : 763 - 771
  • [24] Temperature Protection Based on Temperature Variation Acceleration for Dry-type Transformers: Principle and Algorithm
    Feng, Jianqin
    Dong, Yu
    Song, Hailong
    Huang, Sifang
    Cui, Guangzhao
    RECENT ADVANCES IN ELECTRICAL & ELECTRONIC ENGINEERING, 2016, 9 (02) : 152 - 158
  • [25] An experimental determination of the optimum cooling model for dry-type transformers for different cooling configurations
    Ekinci, Firat
    ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS, 2020, 42 (17) : 2181 - 2197
  • [26] Thermal field and hottest spot of the ventilated dry-type transformer
    Zheng, DC
    Yang, JX
    Wen, ZH
    PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON PROPERTIES AND APPLICATIONS OF DIELECTRIC MATERIALS, VOLS 1 & 2, 2000, : 141 - 143
  • [27] Research on Fault Identification Method of Dry-type Transformers Based on Support Vector Machine
    Ji, Ling
    Li, Kunpeng
    Zhang, Pengfei
    Bao, Liwen
    Huang, Yunkai
    2019 22ND INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS 2019), 2019, : 4497 - 4502
  • [28] Effect of Barriers on Windings Temperature Rises of Dry-type Transformers: Measurements and Network Simulations
    Sun, Q.
    Wu, W.
    Cranganu-Cretu, B.
    Blaszczyk, A.
    2022 7TH INTERNATIONAL ADVANCED RESEARCH WORKSHOP ON TRANSFORMERS (ARWTR 2022), 2022, : 52 - 57
  • [29] Modeling and experimental validation of dry-type transformers with multiobjective swarm intelligence-based optimization algorithms for industrial application
    Demirdelen, Tugce
    Esenboga, Burak
    Aksu, Inayet Ozge
    Ozdogan, Alican
    Yavuzdeger, Abdurrahman
    Ekinci, Firat
    Tumay, Mehmet
    NEURAL COMPUTING & APPLICATIONS, 2022, 34 (02): : 1079 - 1098
  • [30] Thermal Network Model of High-Power Dry-Type Transformer Coupled with Electromagnetic Loss
    Chen, Yifan
    Yang, Qingxin
    Zhang, Changgeng
    Li, Yongjian
    Li, Xinghan
    IEEE TRANSACTIONS ON MAGNETICS, 2022, 58 (11)