Hybrid K Based Influential Parameter Determination and Design Optimization of 220 kV High Voltage Insulator
Insulator failure generally occurs due to improper design, and if there exists sharp edges over the insulator surface. There is a need to detect the fragile parameters in the insulator design as they can cause large electrical stress, leading to insulation failure. In this paper, machine learning based approach is used to identify the fragile design parameter and thus determine an optimized design of the insulator, which will eventually decrease the voltage stress over it. A 220 kV insulator is designed and electric field intensity and potential distribution for an assembly of live, ground and insulator is calculated for different geometries. The design parameters of the insulator are considered and varied. The electric field is calculated for the whole assembly of insulator to generate the most optimized design. The optimized design reduces the overall stress by 13.12 %.
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