  An approach using a differential evolution (DE) optimization algorithm is
proposed to optimize design parameters for improving the optical absorption
efficiency of plasmonic solar cells (PSC). This approach is based on
formulating the parameters extraction as a search and optimization process in
order to maximize the optical absorption in the PSC. Determining the physical
parameters of three-dimensional (3-D) PSC is critical for designing and
estimating their performance, however, due to the complex design of the PSC,
parameters extraction is time and calculation intensive. In this paper, this
technique is demonstrated for the case of commercial thin-film hydrogenated
amorphous silicon (a-Si:H) solar photovoltaic cells enhanced through patterned
silver nano-disk plasmonic structures. The DE optimization of PSC structures
was performed to execute a real-time parameter search and optimization. The
predicted optical enhancement (OE) in optical absorption in the active layer of
the PSC for AM-1.5 solar spectrum was found to be over 19.45% higher compared
to the reference cells. The proposed technique offers higher accuracy and
automates the tuning of control parameters of PSC in a time-efficient manner.
