Flexible Nanotexture Structures for Thin Film PV Cells Using Wavelet Functions

Light trapping is an important technique in increasing the efficiency of solar cells. Inverse optimization is a systematic numerical approach that allows us to find the limits of light trapping more efficiently. It is an alternative to exhaustive search simulations or experimental measurements. In this study, we use inverse optimization to study light trapping in thin film amorphous silicon cells textured by periodic patterns of metallic surface grating. We use a finite set of Haar wavelets to describe a general form of grating structure composed of multiple rectangular nanostrips. We use a well-known global multiparameter optimization technique called simulated annealing to find the coefficients of the wavelets basis for optimal absorptivity enhancement in thin film silicon. The motivation for choosing wavelet basis (vis-a-vis other orthonormal bases such as Fourier) is the feasibility of fabricating the resulting nanostructures. The resulting improvement in the number of absorbed photons is around 130% for wavelength range of 300-700 nm, which is significantly better than the previous results using simple front surface nanostrips. In addition, we use statistical tools to evaluate the sensitivity of the characteristics of the resulting structure to numerical uncertainties.