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Breakdown Voltage Prediction by Utilizing the Behavior of Natural Ester for Transformer Applications

P. Samuel Pakianathan*, R. V. Maheswari

Department of Electrical and Electronics Engineering, National Engineering College, Kovilpatti, Tamilnadu, 628503, India

* Corresponding Author: P. Samuel Pakianathan. Email: email

Intelligent Automation & Soft Computing 2023, 35(3), 2717-2736. https://doi.org/10.32604/iasc.2023.029950

Abstract

This research investigates the dielectric performance of Natural Ester (NE) using the Partial Differential Equation (PDE) tool and analyzes dielectric performance using fuzzy logic. NE nowadays is found to replace Mineral Oil (MO) due to its extensive dielectric properties. Here, the heat-tolerant Natural Esters Olive oil (NE1), Sunflower oil (NE2), and Ricebran oil (NE3) are subjected to High Voltage AC (HVAC) under different electrodes configurations. The breakdown voltage and leakage current of NE1, NE2, and NE3 under Point-Point (P-P), Sphere-Sphere (S-S), Plane-Plane (PL-PL), and Rod-Rod (R-R) are measured, and survival probability is presented. The electric field distribution is analyzed using the Partial Differential Equation (PDE) tool. NE shows better HVAC with stand capacity under all the electrodes configuration, especially in the S-S shape geometry. The exponential function is developed for the oils under different electrode geometry; NE shows a higher survival probability. Likewise, the most influential dielectric properties such as breakdown voltage, kinematic viscosity, and water content are used to develop a Mamdani-based control system model that combines two variables to produce the surface model. The surface model indicates that the NE subjected for investigation is less susceptible to moisture effect and higher kinematic viscosity. Based on the surface models of PDE and fuzzy, it is concluded that NE possesses a high survival rate since its breakdown voltage does not react to changes in water content. Hence the application of NE in the transformer application is highly safe and possesses extended life.

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APA Style
Pakianathan, P.S., Maheswari, R.V. (2023). Breakdown voltage prediction by utilizing the behavior of natural ester for transformer applications. Intelligent Automation & Soft Computing, 35(3), 2717-2736. https://doi.org/10.32604/iasc.2023.029950
Vancouver Style
Pakianathan PS, Maheswari RV. Breakdown voltage prediction by utilizing the behavior of natural ester for transformer applications. Intell Automat Soft Comput . 2023;35(3):2717-2736 https://doi.org/10.32604/iasc.2023.029950
IEEE Style
P.S. Pakianathan and R.V. Maheswari, “Breakdown Voltage Prediction by Utilizing the Behavior of Natural Ester for Transformer Applications,” Intell. Automat. Soft Comput. , vol. 35, no. 3, pp. 2717-2736, 2023. https://doi.org/10.32604/iasc.2023.029950



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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