Shima Hajimirza

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.

Inverse Optimization of Plasmonic and Antireflective Grating in Thin Film PV Cells

This work addresses inverse optimization of three dimensional front and back surface texture grating specifications, for the purpose of shaping the absorptivity spectrum of silicon thin film cells in targeted ways. Periodic plasmonic gratings with dimensions comparable or less than the incident light wavelength are known to enhance light absorption. We consider surface patterning of amorphous silicon (a-Si) thin films using front and/or back metallic nanostrips and ITO coatings, and show that wideband enhancement in unpolarized absorptivity spectrum can be achieved when back reflectors are used. The overall short circuit current enhancement using such structures is significant and can be as high as 97%. For TM-polarized wave it can be even higher as reported in previous work. In this work however, we focus on the optimization for the more realistic unpolarized radiation which is of significantly higher complexity. In addition, optimization is done with respect to two objective functions independently: spectral absorptivity and gain-bandwidth product of the absorptivity spectrum.

Broadband Absorption Enhancement in Thin Film Solar Cells Using Inverse Optimization of Light Trapping Mechanisms

In this paper, global optimization techniques are used to design broadband solar absorption enhancement in thin film amorphous silicon (a-Si) solar cells, using periodic nanostructures on the top and bottom surfaces of the cell. Considering a combination of silver rectangular gratings and indium tin oxide (ITO) coatings on both surfaces of the a-Si, numerical optimization techniques such as Simulated Annealing and a local constrained Quasi-Newton algorithm are used to optimize the surface texture patterns. Numerical results indicate that, unlike the case of metallic gratings on the front surface, a periodic silver grating structure on the back surface results in a modification of the absorption spectrum largely independent of the effect of anti-reflection ITO coatings on the front of the cell. Furthermore, additional improvement can be obtained by using a thin rear surface ITO layers. Therefore, using a combination of metallic gratings and ITO coatings on both sides, a wideband absorption spectrum enhancement is achievable. Simulations predict integrated enhancement factors as high as 2.0 (100% improvement) for the case of metallic grating on the back surface and ITO layers on the front, and as high as 2.2 (120% improvement) when a combination of grating and ITO coatings on both sides is used. Such noteworthy improvements are made possible by efficient multi-parameter optimization supplanting an intractable exhaustive search.Copyright

Rapid Optimization of External Quantum Efficiency of Thin Film Solar Cells Using Surrogate Modeling of Absorptivity

This paper uses surrogate modeling for very fast design of thin film solar cells with improved solar-to-electricity conversion efficiency. We demonstrate that the wavelength-specific optical absorptivity of a thin film multi-layered amorphous-silicon-based solar cell can be modeled accurately with Neural Networks and can be efficiently approximated as a function of cell geometry and wavelength. Consequently, the external quantum efficiency can be computed by averaging surrogate absorption and carrier recombination contributions over the entire irradiance spectrum in an efficient way. Using this framework, we optimize a multi-layer structure consisting of ITO front coating, metallic back-reflector and oxide layers for achieving maximum efficiency. Our required computation time for an entire model fitting and optimization is 5 to 20 times less than the best previous optimization results based on direct Finite Difference Time Domain (FDTD) simulations, therefore proving the value of surrogate modeling. The resulting optimization solution suggests at least 50% improvement in the external quantum efficiency compared to bare silicon, and 25% improvement compared to a random design.

A Dimensionality-Reduced First Order Method for Industrial Optimization: A Case Study in Renewable Energy Technologies

We propose and study a dimensionality-reduced first order method for solving complex optimization problems of high-dimensional search space. We demonstrate that the proposed method is very efficient in design problems where the computational bottleneck is mostly due to the time-consuming nature of the forward problem in contrast to the complexity of the function behavior in the search space or other computational overheads. Many industrial problems are of this nature including design problems based on back testing or simulation of an evolutionary equation or a dynamic system in time, frequency or other (hybrid) domains, such as Electromagnetic, Quantum equations, Navier-Stokes PDEs, etc. The premise of efficiency improvement in the proposed framework is a better modelling and utilization of the complexity distribution among the components of an inverse design problem. As a particular case study, we list some of the existing optimization problems related to energy production, distribution and utilization at the industrial level. We briefly overview the different complexity components of these problems at a high level, and make suggestions as what industrial problems can be facilitated through the proposed framework.Copyright

Design and Verification of a PECVD Fabricated Multi-Layer Nano-Scale Photovoltaic Device

This paper summarizes the results of computational and experimental studies of an enhanced thin film solar structure. The cell structure consists of a reflective aluminum layer beneath an 80nm absorbing layer of amorphous silicon, coated with a top layer of transparent and conductive indium tin oxide (ITO). The structure is mounted on a glass substrate. We first use constrained optimization techniques along with numerical solvers of the electromagnetic equations to specify the layer thicknesses of the design for maximized efficiency. Numerical analysis suggests that solar absorptivity in the thin film silicon can be enhanced by a factor of 2. The proposed design is then fabricated using Plasma Enhanced Chemical Vapor Deposition techniques, along with a control sample of bare silicon absorber for comparison. AFM imaging and spectrophotometry experiments are applied to estimate the realized thin film dimensions, deposition error, unwanted oxidation volume and the resulting reflectivity spectra. Comparisons of the measured and simulated reflectivity spectra of the fabricated cells, as well as Monte Carlo simulations based on incorporating random geometry errors in the numerical simulations suggest that the measured spectra are in accordance with the expected curves from simulations.Copyright

Wavelet Based Nano-Texture Structures for Thin Film PV Cells

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 work, 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 nano-strips. We use global simulated annealing optimization to find the coefficients of the wavelets basis for optimal absorption 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 nano-structures. The resulting improvement in the number of absorbed photons is around 130% for wavelength range of 300–700nm, which is significantly better than the previous results using simple front surface nano-strips. In addition, we use statistical analysis to evaluate the sensitivity of the characteristics of the resulting structure to numerical uncertainties.Copyright

Limits of Light Trapping in Silicon Thin Film Cells via Metallic Gratings

In this paper, we study the limits of light trapping for amorphous silicon thin film solar cells using surface metallic gratings. Adopting a method used recently by Sheng et al. [31], arbitrarily shaped periodic surface textures described by Fourier series with limited terms are considered, and global inverse optimization techniques such as Simulated Annealing are used to adjust the structural variations of the unknown texture to yield maximum light trapping. The optimization is done with respect to two objective functions: enhancement in the number of absorbed photons and, maximal spectral absorptivity enhancement. We show that compared with the rectangular structures previously studied, curved structures result in additional waveguide modes and more broadband enhancement in absorptivity of silicon. An overall improvement of over 60% is achievable in the number of absorbed photons for polarized incident sunlight using the shape functions we will describe. We compare the results with conventional Lambertian limit of light trapping [1] and with the more recent theoretical limits of Yu et al. [30] and Sheng et al. [31] for thin films. We show that at near-infrared ranges, absorptivity enhancements remarkably higher than those results can be achieved using the proposed structures and inverse optimization.© 2012 ASME

Robust Nanoscale Patterns for Thin Film Solar Cells Using Inverse Optimization of Nonuniformly Sampled Absorption Spectrum

This paper outlines several techniques for systematic and efficient optimization as well as sensitivity assessment to fabrication tolerances of surface texturing patterns in thin film amorphous silicon (a-Si) solar cells. The aim is to achieve maximum absorption enhancement. We report the joint optimization of several geometrical parameters of a three dimensional lattice of periodic square silver nanoparticles, and an absorbing thin layer of a-Si, using constraint optimization tools and numerical FDTD simulations. Global and local optimization methods, such as the Broyden–Fletcher–Goldfarb–Shanno Quasi-Newton (BFGS-QN) and Simulated Annealing (SA) are employed concurrently for solving the inverse near field radiation problem. The design of the silver patterned solar panel is optimized to yield maximum average enhancement in photon absorption over the solar spectrum. The optimization techniques are expedited and improved by using a novel nonuniform adaptive spectral sampling technique. Furthermore, the sensitivity of the optimally designed parameters of the solar structure is analyzed by postulating a probabilistic model for the errors introduced in the fabrication process. Monte Carlo (MC) simulations and Unscented Transform (UT) techniques are used for this purpose.Copyright