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<p>In recent decades, high-voltage tension polymer insulators have played a significant role in enhancing the safety and stability of modern power transmission systems. However, improper electric field management and suboptimal design lead to corona discharge and surface degradation, which result in operational failure. To address these challenges, a novel Finite Element Method (FEM) based on four multi-objective nature-inspired algorithms such as Antlion Optimization (ALO), Salp Swarm Algorithm, Dragonfly Algorithm, and Grasshopper Optimization is proposed to optimize the design parameters of the grading device used in 765&#xa0;kV tension-type polymer insulator with two conductor bundles. The FEM is applied to accurately simulate and analyze the electric field distribution, thermal gradients, and mechanical stress across the insulator. The four algorithms are applied to optimize the corona and guard ring’s design parameters for minimizing the electric field in the significant region of the insulator while maintaining thermal and mechanical stability. The experimental results reveal that the Multi-Objective Salp Swarm Algorithm (MSSA) demonstrates superior performance compared to the others and offers less computational time of 85&#xa0;s and higher optimization accuracy of 98.89% compared to existing methodologies. Further, the optimized design reduces the electric field intensity to 0.533&#xa0;kV/mm, which improves thermal dissipation as well as mechanical stability and ensures operational reliability. These findings provide a robust and computationally efficient approach to improving the performance and reliability of high-voltage power transmission systems.</p>

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Advancements in power system safety: designing effective high-voltage tension polymer insulators

  • 期刊论文

  • 发表日期：

    2026年1月10日

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  • Archana Chandrasekaran,
  • Usha Kothandaraman

摘要

In recent decades, high-voltage tension polymer insulators have played a significant role in enhancing the safety and stability of modern power transmission systems. However, improper electric field management and suboptimal design lead to corona discharge and surface degradation, which result in operational failure. To address these challenges, a novel Finite Element Method (FEM) based on four multi-objective nature-inspired algorithms such as Antlion Optimization (ALO), Salp Swarm Algorithm, Dragonfly Algorithm, and Grasshopper Optimization is proposed to optimize the design parameters of the grading device used in 765 kV tension-type polymer insulator with two conductor bundles. The FEM is applied to accurately simulate and analyze the electric field distribution, thermal gradients, and mechanical stress across the insulator. The four algorithms are applied to optimize the corona and guard ring’s design parameters for minimizing the electric field in the significant region of the insulator while maintaining thermal and mechanical stability. The experimental results reveal that the Multi-Objective Salp Swarm Algorithm (MSSA) demonstrates superior performance compared to the others and offers less computational time of 85 s and higher optimization accuracy of 98.89% compared to existing methodologies. Further, the optimized design reduces the electric field intensity to 0.533 kV/mm, which improves thermal dissipation as well as mechanical stability and ensures operational reliability. These findings provide a robust and computationally efficient approach to improving the performance and reliability of high-voltage power transmission systems.