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Heat transfer analysis of metal oxide surge arrester under power frequency applied voltage

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  • Seyyedbarzegar, Seyyed Meysam
  • Mirzaie, Mohammad

Abstract

Electro-thermal model of metal oxide surge arrester based on adaptive method has been proposed in this paper. Finite element method has been used to model surge arrester. Power loss, which is major parameter in electro-thermal analysis, has been estimated as a heat source in proposed model using artificial neural network and adaptive network based fuzzy inference system. In addition to voltage and temperature, operating history is also an important factor that must be considered in power loss estimation process. In order to formulize surge arrester performance history, degradation factor has been suggested as a new index in this paper. Therefore, voltage, temperature and degradation factor have been used as inputs in artificial models. So as to train the artificial neural network and adaptive network based fuzzy inference system, experimental results have been obtained by laboratory tests on new and utilized surge arresters varistors. In this regards, high voltage experimental setup, chamber and an oven have been prepared to acquire modeling data. Also, the results of infrared thermal camera have been used to validate the results of proposed adaptive electro-thermal model. Moreover, convection and radiation as effective factors in surface to ambient heat transfer have been studied and compared.

Suggested Citation

  • Seyyedbarzegar, Seyyed Meysam & Mirzaie, Mohammad, 2015. "Heat transfer analysis of metal oxide surge arrester under power frequency applied voltage," Energy, Elsevier, vol. 93(P1), pages 141-153.
    • Handle: RePEc:eee:energy:v:93:y:2015:i:p1:p:141-153
    DOI: 10.1016/j.energy.2015.09.031
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    References listed on IDEAS

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    1. Yuan, Fang & Chen, Qun, 2011. "Two energy conservation principles in convective heat transfer optimization," Energy, Elsevier, vol. 36(9), pages 5476-5485.
    2. Nafar, M. & Gharehpetian, G.B. & Niknam, T., 2011. "Improvement of estimation of surge arrester parameters by using Modified Particle Swarm Optimization," Energy, Elsevier, vol. 36(8), pages 4848-4854.
    3. Yazdani-Asrami, Mohammad & Mirzaie, Mohammad & Shayegani Akmal, Amir Abbas, 2013. "No-load loss calculation of distribution transformers supplied by nonsinusoidal voltage using three-dimensional finite element analysis," Energy, Elsevier, vol. 50(C), pages 205-219.
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    5. Christodoulou, C.A. & Vita, V. & Ekonomou, L. & Chatzarakis, G.E. & Stathopulos, I.A., 2010. "Application of Powell’s optimization method to surge arrester circuit models’ parameters," Energy, Elsevier, vol. 35(8), pages 3375-3380.
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    Cited by:

    1. Behnam Ranjbar & Ali Darvishi & Rahman Dashti & Hamid Reza Shaker, 2022. "A Survey of Diagnostic and Condition Monitoring of Metal Oxide Surge Arrester in the Power Distribution Network," Energies, MDPI, vol. 15(21), pages 1-18, October.
    2. Jiazheng Lu & Pengkang Xie & Zhen Fang & Jianping Hu, 2018. "Electro-Thermal Modeling of Metal-Oxide Arrester under Power Frequency Applied Voltages," Energies, MDPI, vol. 11(6), pages 1-13, June.
    3. Smitha, T.V. & Nagaraja, K.V., 2019. "An efficient automated higher-order finite element computation technique using parabolic arcs for planar and multiply-connected energy problems," Energy, Elsevier, vol. 183(C), pages 996-1011.

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