Optimized neutral grounding system design for 3φ transformers using genetic algorithm

Abstract

Grounding systems are essential for ensuring the safety, reliability and efficiency of electrical networks. These systems act as the backbone for protecting equipment and personnel by managing fault currents, reducing over voltages and maintaining stable operating conditions in power systems. In this paper, the problem of transformer neutral grounding system design is formulated as an optimization problem. The goal is to optimally select the type of neutral grounding system and optimize its impedance value. The objective function of the problem is defined as the weighted sum of ground current, ground voltage, healthy phase voltages, voltage unbalance percentage, and total harmonic distortion percentage. Given the objective function and proposed constraints, the transformer neutral grounding system design problem is presented as a nonlinear optimization problem and solved using the genetic algorithm with two selection methods: roulette wheel and Tournament selection. Simulation results showed that under conditions where the importance of all parameters in the objective function is considered equally, the frequency-selective grounding (FSG) system is the best option for the power system under study. This neutral grounding system provides optimal performance not only for different types of loads connected to the system but also for various values of ground fault resistance. The objective function values converged to similar values in both genetic algorithm selection methods; this demonstrates that the genetic algorithm was able to find nearly identical optimal points with both selection methods.