**6.1 Personal computer simulation software (PC1D)**

PC1D is the solar cell modeling application that is utilized the most frequently among those that are available for commercial purchase. The commercial success of this product is built upon its swiftness, user-friendliness and continuous updates to keep pace with the most recent cell models. It is used to model the performance of new devices and also helps new users build a grasp of the physics behind device operation. The University of New South Wales is now making PC1D freely accessible to the public. When the user has finished configuring the PC1D basic model, the system will create a number of nodes for them to solve. The number of nodes increases in regions of the cell when there is a change in the doping as well as in regions that are close to surfaces. It is also possible to halt the software during the simulation so that you may investigate the spatial distribution of carriers or the field throughout the device at a certain bias point. The schematic representation and doping density profile of Si-based solar is illustrated in **Figure 1**.

*Performance Evaluation of Solar Cells by Different Simulating Softwares DOI: http://dx.doi.org/10.5772/intechopen.111639*

**Figure 1.**

*Schematic representation of device architecture designed by PC1D and doping density profile generated by PC1D.*

PC1D is known as one-dimensional solar modeling software generated by computer engineer Diane Rover et al. in 1985. It was installed at IBM-compatible personal computers and written in the Pascal language as well as designed for crystalline silicon solar cell [1, 2]. The exceptional parameters like speed, interface and continuous update to the up-to-date cell model use permit it for the best utilized package. For the improvement of the basic version of this simulator the mentioned models or methods were used such as the trap-assisted tunneling model, intra-band and Newton-Gummel method. On the other hand, the updated version, (PC1D mod 6.1), incorporates several new models like Fermi-Dirac statistics. In addition, crystalline silicon solar cell efficiency simulation is included for better executions [7]. In recent times, 20.35% efficiency has been achieved and simulated for single c-Si solar cell with the help of PC1D [8]. In addition with efficiency simulations, other factors like band gap's impact and electron affinity tuning of Zinc oxide layer on crystalline solar cell enactment as well as the factor like Anti-Reflecting Coating (ARC) layer's concerns on this solar cell have simulated by using this simulator for better performance [9].

## **6.2 Advanced semiconductor analysis (ASA)**

Advanced Semiconductor Analysis (ASA) is a state-of-the-art software used for simulating thin-film hydrogenated solar cells. It is highly effective and widely regarded as the most advanced operational tool for this purpose. ASA solves onedimensional semiconductor equations using free electron concentration, hole concentration and electrostatic potential (the Poisson equation and two continuity equations for electrons and holes). It also uses advanced physical models to characterize device and material optoelectronic characteristics. The updated version of this simulating package uses an integrated optoelectronic attitude for rapid simulations of JV curves, efficiencies and fill factors for microcrystalline and thin-film silicon solar cells [10, 11].

### **6.3 Amps-1D**

AMPS-1D is another widespread simulation software for analyzing the characteristic performance of a-Si:H, polycrystalline, copper indium gallium selenide [12–14] and Copper zinc tin sulfide solar cells. AMPS explains how material properties (bandgap, affinity, doping, mobilities, gap state defect distributions in the bulk and at interfaces) and device design/structure control device physics and response to light, impressed voltage and temperature. AMPS allows users to study and compare band diagrams, current components, recombination, generation and electric field plots as a function of light intensity, voltage, temperature and location to better understand device behavior to a given circumstance (i.e., light bias, voltage bias and temperature). AMPS-1D was supported by IBM and the Electric Power Research Institute [15]. It uses the FORTRAN programming language and is based on the Newton–Raphson method. Compared to earlier software, it has better simulation features. However, data entry in AMPS can be time-consuming due to the requirement of numerous parameters and layers. **Figure 2** shows parametric information that need to be added for single layer in AMPS-1D software.
