Application of Grey Wolf Optimizer for Predictive Maintenance and Optimization of High Voltage Insulators

Abstract

High-voltage insulator has an important role in ensuring the reliability and longevity of electrical systems. This study investigates the optimization of corona ring design and parameters H,R,r, using the Grey Wolf Optimizer (GWO), aiming to minimize electric field concentrations and enhance insulator performance. By strategically placing corona rings, the model developed predicts optimal configurations that mitigate peak electric field levels, thereby improving durability and preventing unexpected failures. Numerical simulations, conducted via COMSOL 4.3 and Finite Element analysis, validate the effectiveness of the optimized design in significantly reducing electric field intensities near end fittings. This research underscores the transformative potential of AI-driven optimization techniques, particularly the GWO, in advancing predictive maintenance strategies for high voltage insulators. Such advancements are crucial for fostering a sustainable and resilient electrical infrastructure.