Abstract
Thin-film solar cell is one of cost-effective energy technologies potentially. Optimal design of thin-film solar cell for pursuing the highest efficiency is achieved in a trial-and-error engineering way. In this work, a device simulation-based genetic algorithm (GA) is applied to optimize the dark and illuminated properties of a-Si thin-film solar cells. A set of solar cell transport equations consisting of the Poisson equation, electron-hole current continuity equations, and the photogeneration model is solved numerically. The results of device simulation are used for the optimization of the electrical characteristics via the GA method; therefore, we can deduce optimal seven parameters including the five structural parameters and two doping concentrations of explored solar cell. The iteration of evolutionary is terminated when the final convergent solution is obtained. The evolutionary technique enables us to optimize the associated electrical characteristics, such as the short-circuited current, the open-circuited voltage, and the maximum efficiency of the examined p-i-n solar cell.