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Abstract
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This study focuses on optimizing key parameters of a perovskite solar cell using three optimi-zation algorithms: PSO, Firefly, and the Enhanced-Firefly Algorithms, within the SCAPS simu-lation software. In contrast to conventional methods And also new optimization algorithms that rely on equivalent circuit models, this approach directly optimizes the actual structure of the solar cell, aiming for the ideal configuration based on internal efficiency parameters. The op-timization objectives included PCE, FF, Jsc, and Voc. The results from the single-objective op-timization revealed that varying cost functions produced different optimal doping levels and layer thicknesses. Among the algorithms tested, PSO achieved the highest PCE and FF with the fewest function evaluations. However, the Enhanced Firefly Algorithm, introduced in this study, demonstrated superior overall performance with the smallest population size. Based on these results, the Enhanced Firefly Algorithm was chosen for further multi-objective optimiza-tion. In the multi-objective optimization, adjusting the weights of the internal efficiency pa-rameters affected the convergence rates of each cost function. Ultimately, the optimized cell structure resulted in a remarkable increase in PCE, from 6.6945% to 46.0622%.
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