Optimal design of vertical silicon nanowires solar cell using hybrid optimization algorithm

An approach to enhance the ultimate efficiency of the silicon nanowires (Si NWs) solar cell is proposed based on a hybrid population-based algorithm. The suggested technique integrates the ability of exploration in a gravitational search algorithm (GSA) with the exploitation capability of particle swarm optimization (PSO) to synthesize both algorithms’ strengths. The hybrid GSA-PSO algorithm in MATLAB® code is linked to finite-difference time-domain solution technique based on Lumerical-software to simulate and optimize the Si NWs’ geometrical parameters. The suggested GSA-PSO algorithm has advantages in terms of better convergence and final fitness values than that of the PSO algorithm. Further, the Si NWs lattice with optimized diameters and heights shows a high ultimate efficiency of 42.5% with an improvement of 42.8% over the Si NWs lattice with the same diameters and heights. This enhancement is attributed to the different generated optical modes combined with multiple scattering and reduced reflection due to the different heights and different diameters, respectively.