Optimal Design of Thin-film Plasmonic Solar Cells using Differential Evolution Optimization Algorithms
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- Ankit Vora, Satyadhar Joshi, Arun Matai, Joshua M. Pearce, Durdu Guney. Optimal Design of Thin-film Plasmonic Solar Cells using Differential Evolution Optimization Algorithms. Proceedings of the 12th INDIACom; INDIACom-2018; IEEE Conference ID: 428352018 5th International Conference on “Computing for Sustainable Global Development”, 14th - 16th March, 2018. Bharati Vidyapeeth's Institute of Computer Applications and Management (BVICAM), New Delhi (INDIA). Available: open access arxiv
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.
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