Open Access

ARTICLE

Prediction of Transformer Oil Breakdown Voltage with Barriers Using Optimization Techniques

Sherif S. M. Ghoneim^1,*, Mosleh M. Alharthi¹, Ragab A. El-Sehiemy², Abdullah M. Shaheen³

1 Department of Electrical Engineering, College of Engineering, Taif University, Taif, 21944, Saudi Arabia
2 Electrical Power and Machines Department, Faculty of Engineering, Kafr Elsheikh University, Kafr Elsheikh, Egypt
3 Electrical Engineering Department, Faculty of Engineering, Suez University, Suez, 43533, Egypt

* Corresponding Author: Sherif S. M. Ghoneim. Email:

Intelligent Automation & Soft Computing 2022, 31(3), 1593-1610. https://doi.org/10.32604/iasc.2022.020464

Received 25 May 2021; Accepted 27 July 2021; Issue published 09 October 2021

Abstract

A new procedure to optimally identifying the prediction equation of oil breakdown voltage with the barrier parameters’ effect is presented. The specified equation is built based on the results of experimental works to link the response with the barrier parameters as the inputs for hemisphere-hemisphere electrode gap configuration under AC voltage. The AC HV is applied using HV Transformer Type (PGK HB-100 kV AC) to the high voltage electrode in the presence of a barrier immersed in Diala B insulating oil. The problem is formulated as a nonlinear optimization problem to minimize the error between experimental and estimated breakdown voltages (VBD). Comprehensive comparative analyses are addressed using three recent innovative marine predators, grey wolf, and equilibrium optimization algorithms to reduce the error between the experimental and estimated breakdown voltages. In addition, the experimental results are expressed in two different models via grey and real coding. Finally, simulation results are conducted with statistical indices that show the effectiveness of the proposed models for experimental verification. The total percentage errors of the tested samples between the observed and estimated VBD are 1.207, 1.222, and 1.207 for EO, GWO, MPA, respectively. The marine predator algorithm has the best performance compared with the other two competitive algorithms for grey and actual codes.

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Citations