Electric Field Distribution on Zinc Oxide Pills in Gapless Surge Arresters Using Finite Element Method and Evolutionary Optimization Algorithms in HVAC Systems
Morteza Ghayedi and
Michal Jasinski ()
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Morteza Ghayedi: Department of Electrical Engineering, University of Birjand, Birjand 9717434765, Iran
Michal Jasinski: Department of Electrical Engineering Fundamentals, Faculty of Electrical Engineering, Wrocław University of Science and Technology, 50-370 Wrocław, Poland
Sustainability, 2023, vol. 15, issue 10, 1-13
Abstract:
This article proposes a new method for the optimal design of zinc oxide arresters based on electric field distribution on the zinc oxide column using smart algorithms and finite element analysis. This design prevents premature aging of zinc oxide tablets, especially the initial and final tablets of the column, which have a higher voltage gradient than other parts of the arrester, and subsequently increases the sustainability of the network. The spacer height, fiberglass layer thickness, and grading ring diameter and its location were taken as the problem variables. The surge arrester was designed in AC/DC mode and two-dimensional symmetry using the COMSOL Multiphysics package. For the first time, rational Bezier curves were also used for the arrester design. This paper presents an optimization approach that combines and dynamically links the electrostatic modeling process and the particle swarm optimization (PSO) and differential evolution (DE) algorithms. The proposed approach is a general method that can be used in the design of high-voltage equipment. The results showed that the lifetime and reliability were increased by reducing voltage variations in the ZnO column. Therefore, maintenance cost and implementation of a surge arrester would be reduced. Finally, the external surface of the porcelain housing was placed under the influence of uniform distribution of electric field.
Keywords: electric field; finite element method (FEM); optimization algorithm; Rational Bezier curve; ZnO arrester (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:10:p:7892-:d:1144782
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