Multi-Objective Optimization of 400 kV Composite Insulator Corona Ring Design

The electric field distribution is one of the main factors governing the long-term reliability of high voltage composite insulators. However, under severe pollution conditions, electric field stresses, when exceeding thresholds and applying for long periods, could lead to degradation and deterioration of the housing materials and, therefore, to failures of the composite insulators. This paper is intended to improve the distributions of the electric field and potential by minimizing the corona ring on a 400 kV AC transmission line composite insulator. The performances of three powerful multi-objective meta-heuristic algorithms, namely Ant Lion Optimizer (MOALO), Particle Swarm Optimizer (MOPSO), and non-dominated sorting genetic algorithm (NSGA-II) are established to achieve this goal. First, variations of electrical fields on the critical parts of the string are obtained using three-dimensional finite element method (FEM) software. Then, three objective functions are developed to establish the relationships between the electric field and the guard ring parameters. Finally, the optimization parameters consist of diameter, tube diameter, and installation height of the corona ring. The obtained results confirm the effectiveness of the three algorithms; the MOLAO is the better in terms of computing time and solution quality.

Automated summary

This paper investigates the optimization of corona ring on high voltage composite insulators to improve the distribution of electric field and potential. Multiple optimization algorithms are employed to determine the optimal corona ring parameters, and the effectiveness of the algorithms is verified.