A design of hydrogenated amorphous silicon (a-Si:H) solar cell (SC) based on one-dimensional subwavelength grating with nonuniform distribution is proposed and optimized using modified hybrid gravitational search algorithm and particle swarm optimization (GSA-PSO). The reported structure consists of nine gratings with different widths, positions, and heights that can enhance the light trapping through the SC. The nonuniform grating positions and geometrical parameters of the proposed design are optimized in terms of absorption, ultimate efficiency, and short circuit current density. The absorption inside the active layer is enhanced by 67.5% over the conventional thin-film SC. Further, the exposed area caused by forward nanotexturing surface is increased. Moreover, the nonuniform grating parameters and distribution support better light absorption than the periodic grating distribution by increasing the optical path length of the incident light through the active layer. Therefore, the suggested SC achieves a broadband absorption improvement. The enhanced absorption in the active layer is reported using three-dimensional finite-difference time-domain method. In addition, the performance of the suggested SC using different active layer materials, i.e., crystalline silicon, a-Si:H, and gallium arsenide is studied. The hydrogenated amorphous silicon-based design shows high ultimate efficiency of 38.73%, short-circuit current density (JSC) of 34.69 mA / cm2, open-circuit voltage of 1.0393 V, and power conversion efficiency of 35.4%. The modified GSA-PSO algorithm shows also high potential for the design and optimization of different types of solar cells.
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.