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Artificial intelligence-based surrogate model for computation of the electric field of high voltage transmission line ceramic insulator with corona ring

Shahin Alipour Bonab (Propulsion, Electrification and Superconductivity Group, James Watt School of Engineering, University of Glasgow, Glasgow, UK)
Alireza Sadeghi (Propulsion, Electrification and Superconductivity Group, James Watt School of Engineering, University of Glasgow, Glasgow, UK)
Mohammad Yazdani-Asrami (Propulsion, Electrification and Superconductivity Group, James Watt School of Engineering, University of Glasgow, Glasgow, UK)

World Journal of Engineering

ISSN: 1708-5284

Article publication date: 22 March 2024

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Abstract

Purpose

The ionization of the air surrounding the phase conductor in high-voltage transmission lines results in a phenomenon known as the Corona effect. To avoid this, Corona rings are used to dampen the electric field imposed on the insulator. The purpose of this study is to present a fast and intelligent surrogate model for determination of the electric field imposed on the surface of a 120 kV composite insulator, in presence of the Corona ring.

Design/methodology/approach

Usually, the structural design parameters of the Corona ring are selected through an optimization procedure combined with some numerical simulations such as finite element method (FEM). These methods are slow and computationally expensive and thus, extremely reducing the speed of optimization problems. In this paper, a novel surrogate model was proposed that could calculate the maximum electric field imposed on a ceramic insulator in a 120 kV line. The surrogate model was created based on the different scenarios of height, radius and inner radius of the Corona ring, as the inputs of the model, while the maximum electric field on the body of the insulator was considered as the output.

Findings

The proposed model was based on artificial intelligence techniques that have high accuracy and low computational time. Three methods were used here to develop the AI-based surrogate model, namely, Cascade forward neural network (CFNN), support vector regression and K-nearest neighbors regression. The results indicated that the CFNN has the highest accuracy among these methods with 99.81% R-squared and only 0.045468 root mean squared error while the testing time is less than 10 ms.

Originality/value

To the best of the authors’ knowledge, for the first time, a surrogate method is proposed for the prediction of the maximum electric field imposed on the high voltage insulators in the presence Corona ring which is faster than any conventional finite element method.

Keywords

Acknowledgements

For the purpose of open access, the author(s) has applied for a Creative Commons Attribution (CC BY) license to any Author Accepted Manuscript version arising from this submission.

Citation

Alipour Bonab, S., Sadeghi, A. and Yazdani-Asrami, M. (2024), "Artificial intelligence-based surrogate model for computation of the electric field of high voltage transmission line ceramic insulator with corona ring", World Journal of Engineering, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/WJE-11-2023-0478

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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