谷歌Chrome浏览器插件
订阅小程序
在清言上使用

The mechanism of EP/SiC coating modulated DC flashover characteristics of epoxy composites in SF6/N2 mixtures

Zhen Li,He Gao, Zirui Mao, Bo Zhu, Lei Sun, Xuefei Bi,Yuanwei Zhu,Yongsen Han,Daomin Min,Ji Liu,Shengtao Li

JOURNAL OF PHYSICS D-APPLIED PHYSICS(2024)

引用 0|浏览18
暂无评分
摘要
Surface flashover is an inevitable insulation issue for basin-type insulators in gas-insulated switchgears/lines, which significantly challenges the reliability of the electrical power systems. Previous studies have indicated that polymer/semiconductor-filler composite coatings effectively improve the insulation properties; however, the influence mechanism of the coating materials on flashover has not been demonstrated from a molecular perspective. In this work, epoxy/silicon-carbide (EP/SiC) composites were coated onto an EP substrate. The energy-level structure, surface trap, surface charging, and DC flashover voltage in SF6/N-2 were calculated and characterized, and the process by which the tailored molecular energy level influences surface charge transport and flashover characteristics was elucidated. The incorporating of SiC particles reduced the width of the bandgap and introduced shallow traps, which improved carrier mobility and surface conductivity. Quantitative analysis of charge transport indicated that the improved carrier mobility and reduced surface trap level accelerated the surface charge dissipation. This reduced the tangential electrical field distortion and surface charge density and further impeded gas ionization. When the SiC concentration was 15 wt%, the flashover performance improved by 20.88%. This study describes the mechanism by which the EP/SiC coating regulates the surface charge distribution to improve the surface flashover performance by establishing a relationship among the microscopic molecular energy-level structures, mesoscopic charge transport, and macroscopic discharge phenomena.
更多
查看译文
关键词
surface flashover,EP/SiC coating,surface charge dissipation,surface trap,surface conductivity
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要