An optimized metal grid design to improve the solar cell performance under solar concentration using multiobjective computation

In this paper, a new multiobjective genetic algorithm (MOGA)-based approach is proposed to optimize the metal grid design in order to improve the electrical performance and the conversion efficiency behavior of the solar cells under high intensities of illumination. The proposed approach is applied to investigate the effect of two different metal grid patterns (one with 2 busbars outside the active area (linear grid) and another one with a circular busbar surrounding the active area (circular grid)) on the electrical performance of high efficiency c-Si solar cells under concentrated light (up to 150 suns). The dimensional and electrical parameters of the solar cell have been ascertained, and analytical expressions of the power losses and conversion efficiency, including high illumination effects, have been presented. The presented analytical models are used to formulate different objective functions, which are the prerequisite of the multiobjective optimization. The optimized design can also be incorporated into photovoltaic circuit simulator to study the impact of our approach on the photovoltaic circuit design.