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Atomic mechanisms of long-term pyrolysis and gas production in cellulose-oil composite for transformer insulation

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  • Qu, Guanghao
  • Li, Shengtao

Abstract

Cellulose-oil composite (COC) insulating materials are widely used in the transformer owing to their excellent physical and chemical properties. However, long-term thermal instability of these materials severely threatens the stable operation of transformer and power system. To reveal the atomic-level mechanisms responsible for pyrolysis and gas production in COCs, reactive molecular dynamics (RMD) simulations are performed, and calculation results are compared with data from dissolved and evolved gas tests of thermally decomposed materials. First, force field parameters and a molecular model optimization method based on the experimental data-driven strategy are introduced. It is verified that this method and force field offer significant advantages over the classical forms in the simulation of COC pyrolysis. Then, the new parameters and model are used to investigate the long-term pyrolysis and gas production processes in the COC. By constructing the molecular pathways for characteristic gases, namely, CH4, C2H4, and C2H2, it is found that the recombination of CH3•, •CH2•, and H• radicals, which decomposed from the COC, contributes to the formation of CH4 and C2H2, whereas C2H4 can be directly produced via COC decomposition. A higher pyrolysis temperature inhibits the recombination process of radicals and reduces the volume percentages (VPs) of CH4 and C2H2 but promotes the decomposition process and improves the VP of C2H4. This study not only provides insight into the gas production of COCs in transformer but also paves a way to understand long-term pyrolysis of any other materials using MD simulations.

Suggested Citation

  • Qu, Guanghao & Li, Shengtao, 2023. "Atomic mechanisms of long-term pyrolysis and gas production in cellulose-oil composite for transformer insulation," Applied Energy, Elsevier, vol. 350(C).
    • Handle: RePEc:eee:appene:v:350:y:2023:i:c:s0306261923010590
    DOI: 10.1016/j.apenergy.2023.121695
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    References listed on IDEAS

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    1. de Faria, Haroldo & Costa, João Gabriel Spir & Olivas, Jose Luis Mejia, 2015. "A review of monitoring methods for predictive maintenance of electric power transformers based on dissolved gas analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 46(C), pages 201-209.
    2. Howlader, Abdul Motin & Sadoyama, Staci & Roose, Leon R. & Chen, Yan, 2020. "Active power control to mitigate voltage and frequency deviations for the smart grid using smart PV inverters," Applied Energy, Elsevier, vol. 258(C).
    3. Michel Duval & Thomas Heizmann, 2020. "Identification of Stray Gassing of Inhibited and Uninhibited Mineral Oils in Transformers," Energies, MDPI, vol. 13(15), pages 1-9, July.
    4. Gerber, Daniel L. & Ghatpande, Omkar A. & Nazir, Moazzam & Heredia, Willy G. Bernal & Feng, Wei & Brown, Richard E., 2022. "Energy and power quality measurement for electrical distribution in AC and DC microgrid buildings," Applied Energy, Elsevier, vol. 308(C).
    5. Chen, Cheng & Volpe, Roberto & Jiang, Xi, 2021. "A molecular investigation on lignin thermochemical conversion and carbonaceous organics deposition induced catalyst deactivation," Applied Energy, Elsevier, vol. 302(C).
    6. Nie, Xianhua & Du, Zhenyu & Zhao, Li & Deng, Shuai & Zhang, Yue, 2019. "Molecular dynamics study on transport properties of supercritical working fluids: Literature review and case study," Applied Energy, Elsevier, vol. 250(C), pages 63-80.
    7. Yiyi Zhang & Yuxuan Wang & Xianhao Fan & Wei Zhang & Ran Zhuo & Jian Hao & Zhen Shi, 2020. "An Integrated Model for Transformer Fault Diagnosis to Improve Sample Classification near Decision Boundary of Support Vector Machine," Energies, MDPI, vol. 13(24), pages 1-15, December.
    8. Akinola, Toluleke E. & Bonilla Prado, Phebe L. & Wang, Meihong, 2022. "Experimental studies, molecular simulation and process modelling\simulation of adsorption-based post-combustion carbon capture for power plants: A state-of-the-art review," Applied Energy, Elsevier, vol. 317(C).
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