Proceedings of nanoGe Fall Meeting19 (NFM19)
Publication date: 18th July 2019
A new method for developing a realistic and accurate physical model of any type of solid state device has been previously introduced by the author. Application to model Si, GaAs, CIGS, advanced multi-junction solar cells, Thermo-photovoltaics, sensors; as well as other novel solid state devices were previously presented [1&2]. The primary goal of Tandem or Multijunction solar cell design is to maximize the output power for a given solar spectrum [3-4]. The construction of multijunction or tandem cells places the individual junction layers in series, thereby limiting the overall output current to that of the junction layer producing the lowest current. The solution to optimizing a multijunction design involves both the design of individual junction layers which produce an optimum output power and the design of a series-stacked configuration of these junction layers which yields the highest possible overall output current and voltage. This presentation demonstrates and compares the use of different optimization techniques to achieve that goal. The first approach is to use Genetic Algorithm in a two-part process to refine a given multijunction solar cell design for near-optimal output power for a desired light spectrum. Consequently, a Novel Space-Filling Experimental Design optimization technique is also utilized and comparison of the results is presented. These approaches can similarly be utilized to optimize the parameters of any Solid state device to yield any desired performance.
[1] Michael and P. Michalopoulos “A New Technique for the Development of State-of-the-Art Photovoltaic Devices using Silvaco Software," Proceedings of the 6th WSEAS International Multiconference on Circuits, Systems, Communications and Computers(CSCC 2002), Crete, Greece, July 7-14, 2002. pp. 4121-4125.
[2] S. Michael, A. Bates and M. Green, “SILVACO ATLAS as a Solar Cell Modeling Tool,” Proceedings of the 31st IEEE Photovoltaic Specialists Conference, Jan.3-7, 2005, Orlando, FL, pp.719-721.
[3] Kurtz, S., Geisz, J.F., Friedman, D.J., Olson, J.M., Duda, A., Karam, N.H., King, R.R., Ermer, J.H., and Joslin D.E., “Modeling of electron diffusion length in GaInAsN solar cells”, Conf. Record of the Twenty-Eighth IEEE Photovoltaic Specialists Conference, pp. 1210–1213, IEEE Press, NY, 2000.
[4] R.R. King, N.H. Karam, J.H. Ermer, N. Haddad, P. Colter, T. Isshiki, H. Yoon, H.L. Cotal, D.E. Joslin, D.D. Krut, R. Sudharsanan, K. Edmondson, B.T. Cavicchi, and D.R. Lillington, “Next-generation, high-efficiency III-V multijunction solar cells”, Proc. Twenty-Eighth IEEE Photovoltaic Specialists Conference, pp. 998 -1001, 2000.
[5] K.F. Man, K.S. Tang, and S. Kwong, “Genetic Algorithms: Concepts and Applica-tions”, IEEE Transactions on Industrial Electronics, Vol. 43, No. 5, pp. 519-534, 1996.
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