Nano-Fillers Effect on Characteristics of High Voltage Silicone Rubber Insulators

Abstract

Electrical insulators are definitely important for electrical power apparatus including stations, sub-stations, distribution and transmission lines.

The use of polymeric insulators in the electric power sub-stations and distribution and transmission lines is beneficial because of its many advantages such as contamination performance, reduced construction costs, light weight, easy handling, low or no maintenance, vandalism resistance and compact design, better performance in the presence of contamination and wet conditions and its hydrophobicity under electrical and environmental stresses. Silicone polymers have inherently good electrical insulating qualities. They are nonconductive because of their chemical nature and used to produce rubber for a wide range of electrical insulating applications when compounded with the proper fillers and additives. Inorganic fillers have attracted wide interest for improving electrical properties of polymer insulator materials. In order to improve electrical performance of outdoor polymeric silicone rubber insulators used in high voltage transmission lines, micron and nano sized inorganic fillers are added to the silicone rubber matrix.

The scope of this thesis is to improve electrical, mechanical and thermal properties by adding micro and nano titanium dioxide (TiO2) and Zeolite fillers. Silicone rubber composites samples were prepared by mixing micro TiO2 or Zeolite fillers with the content of 10, 20, 30 and 40wt% and also by mixing nano TiO2 or Zeolite with the content of 1, 3, 5 and 7wt%. The dielectric strength of the composites is tested in several conditions such as dry, wet, low salty and high salty wet conditions. Tensile strength, elongation at break, themogarvimetric analysis and scanning electron microscope tests are applied to check the mechanical, thermal and morphological properties of the composites. The results obtained are tabulated, plotted and compared to each other to select most suitable filler and its concentration. The feed forward neural network technique has been used to estimate and predict the values of dielectric strength for SiR composite samples. Finally, the main points of this work have been summarized and presented, indicating the importance of this study as polymer is presently being used worldwide in highly competitive and advanced power industry.