Minimization of Grounding System Cost Using PSO, GAO, and HPSGAO Techniques

Abstract

In this paper, three metaheuristic techniques have been developed to propose a safe and economic grounding system for the future power plant of Labreg situated in Khenchela City (400 km east of Algiers). The corresponding algorithms have been elaborated using particle swarm optimization (PSO), genetic algorithm optimization (GAO) and hybrid particle swarm genetic algorithm optimization (HPSGAO). The aim is to minimize the cost of the considered grounding system basing on the optimal decision of its construction and geometrical parameters in accordance with the security restrictions required by the ANSI/IEEE Standard 80-2000. A new mathematical model has been proposed for the cost function. This later includes the number of conductors, conductor dimension, grid depth, number of rods, length of rods, total area of excavation, and revetment. The results show that the HPSGAO technique presents lower values of the cost than those obtained using GAO and PSO methods. The good accordance between HPSGAO technique safety parameters and those of the CYMGrd code confirms the efficiency of the proposed algorithms.