Abstract
The insulation fault is a major problem in high voltage cable lines. The major factors in the insulation faults are harmonic currents and the metal sheath voltage (MV) that occur on the metal sheath of cable. MV and harmonic distortion should be minimized to prevent insulation faults. Thus, sectional solid bonding with different grounding resistance (SSBr) method is developed as a new bonding method for minimizations of harmonic current and MV. Also, SSBr should be optimized by optimized according to minimum MV and harmonic distortion rate of high voltage cable. Inertia weighted particle swarm optimization (iPSO), particle swarm optimization (PSO), genetic algorithm (GA) and differential evolution algorithm (DEA) are used for optimization of SSBr, and three groups the prediction methods are used separately as objective function of the optimization methods to determine minimum MV and harmonic distortion. These groups are neural networks, hybrid neural networks and regression methods. Hybrid neural network with inertia weighted particle swarm optimization (H-iPSO), linear regression and feedforward backpropagation neural network are selected from their groups according to training errors. Solid bonding method is widely used for bonding of high voltage cable, and solid bonding is simulated in this study. When solid bonding is used for bonding of cable, maximum harmonic distortion rate is measured as 8.15 %, and maximum MV is measured as 1086 V. When H-iPSO is used as prediction method, and PSO is used as optimization method, maximum harmonic distortion rate is measured as 5,28 %, and maximum MV is measured as 57 V. Namely, both insulation fault and electroshock can be prevented by the optimized SSBr method.