Nowadays, Distribution System has experienced several important changes because of the implementation of smart grid technology and incorporation of distributed and renewable energy resources. Generally, optimal incorporation of Distributed Generators and reconfiguration of the radial network have optimistic impacts on the power system. In this paper, localization, and determination of fuel cells challenges are addressed in order to connect with Distributed Generation (DG) systems. Hence, to overcome this challenge dual-phase approach is exploited. In the first phase, the Neural Network (NN) is utilized for determining the optimal position. In the second phase, the hybrid Genetic Algorithm (GA) and Grey Wolf Optimization (GWO) is exploited to determine the optimal sizing of fuel cells. In addition, the proposed technique is simulated in four IEEE bus systems, which is compared over traditional methods namely GA, Particle Swarm Optimization (PSO), and GWO. The results exhibit the performance analysis of the proposed technique and conventional techniques.
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