Employing Genetic Algorithm as an Efficient Alternative to Parameter Sweep Based Multi-Layer Thickness Optimization in Solar Cells

Conventional solar cells are predominately designed similar to a stacked structure. Optimizing the layer thicknesses in this stack structure is crucial to extract the best efficiency of the solar cell. The commonplace method used in optimization simulations, such as for optimizing the optical spacer layers' thicknesses, is the parameter sweep. Our experiments show that the introduction of genetic algorithm based method results in a significantly faster and accurate search method when compared to brute-force parameter sweep method in both single and multi-layer optimization. While other sweep methods can also outperform the brute-force method, they do not consistently exhibit $100\%$ accuracy in the optimized results like our genetic algorithm. Our best case scenario was observed to utilize 57.9% less simulations than brute-force method.