PV Parameters Research Articles

Exploring the Optoelectronic and Photovoltaic Characteristics of Lead‐Free Cs2TiBr6 Double Perovskite Solar Cells: A DFT and SCAPS‐1D Investigations

AbstractIn recent times, the remarkable advancements achieved in the field of perovskite solar cells (PSCs) have sparked significant research efforts aimed at enhancing their overall performance because of their exceptional optoelectronic properties. Due to the toxicity of lead (Pb), the emergence of Ti‐based (Cs2TiBr6) double‐halide PSCs is regarded as a good alternative to Pb‐based PSCs. Here, density functional theory (DFT) calculations are performed to examine the prospect of Cs2TiBr6 perovskite as a layer of absorber for photovoltaic cells (SCs). These computations looked at the material's structural, optical, and electrical characteristics. The density of states (DOS) results demonstrate strong conductivity, principally provided by the 4p states of Br, whilst Ti‐3d and Cs‐5p orbital electrons offer insignificant contributions. The electronic band structure discloses a direct band gap of 1.534 eV. The covalent connections that exist between Ti and Br atoms and the robust electronic charge density around the Ti atom both demonstrate a significant buildup of electronic charge along the 100 planes. The dielectric function and the coefficient of absorption have significance irrespective of lower energies because it is extremely valuable for solar energy applications. The UV absorption peaks of Cs2TiBr6 have a maximum of ≈15.51 eV and are magnified with photon energy up to 2.46 eV, indicating that it may have potential for solar applications. This work also investigated a good combination of the hole transport layer (HTL) and electron transport layer (ETL) with the Cs2TiBr6 absorber layer. AZnO, Nb2O5, LBSO, and Zn2SnO4 are executed as the ETLs, and MoO3, CuAlO2, MEH‐PPV, ZnTe, CNTS, GaAs, MoS2, PTAA, Cu2Te, Zn3P2 are considered as the HTLs to identify the best HTL/Cs2TiBr6/ETL combinations using the SCAPS‐1D numerical simulation. Among all configurations, ITO/LBSO/Cs2TiBr6/CNTS/Au is examined as the best‐optimized structure of Ti‐based PSC, with JSC of 26.63 mA cm−2, a VOC of 1.123 V, FF of 82.94%, and a power conversion efficiency of 24.82%. To validate the findings, PV parameters like the effect of generation rate, recombination rate, J−V, and Q‐E characteristics are evaluated. The effect of series and shunt resistance and structure working temperature are explored to observe the effect of these on PSC devices. The accomplished outcomes suggest that Cs2TiBr6 can be viewed as an optimistic material for PSCs for its higher stability and environment‐friendly characteristics.

Effect of Sb2S3 sacrificial layer thickness on structural, optical and electrical properties of CuSbS2 films and investigation of diode parameters of CuSbS2/CdS heterojunctions

The ternary copper chalcogenides CuSbS2 (CAS) is found to have appealing optical and photovoltaic properties to be used as absorber layer in thin film solar cells. However, the difficulty to grow good quality CuSbS2 layer of micrometer thickness by chemical bath deposition method holds a big challenge. In this work, we reported the effect of incorporating Sb2S3 sacrificial layer of different thickness on structural, optical and electrical properties of CAS films. The X-ray diffraction results and Raman spectroscopic analysis confirm the formation of single-phase orthorhombic crystal structure for CuSbS2. The increase of Sb content in CAS films with the increase in deposition time of Sb2S3 layer has been reflected in the change in relative intensity ratio of characteristic Raman peaks as well as in diffraction peak profiles. The magnitude of defect states in terms of Urbach energy is decreased drastically by increasing Sb percentage in the films. A clear improvement in electrical properties of CAS films is observed with the decrease in Cu/Sb ratio. The carrier density is increased by one order of magnitude from 1016 to 1017 cm−3 and hole mobility increases from 1.14 to 4.87 cm2/Vs. The impact of Sb concentration on Scottky diode parameters of CAS/CdS heterojunction was studied by using thermionic emission model. Both the ideality factor and series resistance are decreased with the increase in Sb content. The J-V measurements reveal that the integration of Sb2S3 sacrificial layer improves the PV parameters such as fill factor, open circuit voltage, photocurrent and efficiency. The overall improvement in diode parameters can be ascribed to decrease in defect states, better film quality, absorber layer thickness and improved stoichiometry of CAS films.

Design and Implementation of Smell Agent Optimizer for Parameters Estimation of Single and Double Diode in PV System: A Comparative Analysis

One of the most important and desirable options for moving toward clean electric energy sources is solar energy. Therefore, a PV system's characteristics play a significant role in determining how effective it is across a range of temperature and radiation scenarios. One can consider the PV model's parameter estimation to be a nonlinear optimization situation. This work makes use of a novel application of the smell agent optimizer (SAO) created to forecast the undefined parameters of the PV model's single- and two-diode equivalent circuits. The goal of this effort is to create an accurate photovoltaic model that can accurately represent its performance under variable operating conditions. The square of the mean squared error between the actual measured curve and the current-voltage curve derived from the model defines the intended objective function. The suggested system is constructed and tested experimentally in a range of temperature and light conditions. Next, the MATLAB software is used to create the simulated PV model integrated with the SAO. The PV parameters are then predicted by comparing the experimental data with the convergence of the SAO based on the PV model. Based on the observed properties, the suggested approach for determining the parameters of an actual solar cell has been put into practice and contrasted with eight other optimization techniques. The outstanding efficacy of the method utilized compared with alternate methods is demonstrated by the statistical comparison of the ideal objective function resulting from the difference in the current-voltage curve produced from the optimized circuit model and the measurement.

Investigating the physical characteristics and photovoltaic performance of inorganic Ba3NCl3 perovskite utilizing DFT and SCAPS-1D simulations

Lead-free inorganic cubic halide perovskites exhibit outstanding physical properties in solar technology. Ba3NCl3 emerges as a promising absorber material in solar cells. Utilizing first-principles density-functional theory (FP-DFT), we thoroughly analyzed Ba3NCl3 properties. It exhibits mechanical, dynamically stability and natural ductility. Electron charge distributions indicate significant ionic bonding between Ba and Cl, and covalent bonding between N and Cl. At the Γ-point, the direct bandgap of PBE(HSE) is 0.57 eV (1.20 eV). Dielectric functions, absorption coefficients, and conductivity confirm robust absorption characteristics across the visible-ultraviolet spectrum. SCAPS-1D simulation identified optimal PV parameters for Ba3NCl3-based cells with a WS2 buffer layer, considering various layer thicknesses and doping densities. In an Al/FTO/WS2/Ba3NCl3/Au structure, under ideal conditions, impressive metrics include an open circuit voltage (VOC) of 1.036 V, photocurrent density (JSC) of 38.21 mA/cm2, fill factor (FF) of 80.75 %, and maximum power conversion efficiency (PCE) of ∼ 32 %. Ba3NCl3 shows promise as a potential absorber in hybrid perovskite photovoltaic devices, especially with WS2 electron transport layers.

Advanced extraction of PV parameters’ models based on electric field impacts on semiconductor conductivity using QIO algorithm

This article presents a novel approach for parameters estimation of photovoltaic cells/modules using a recent optimization algorithm called quadratic interpolation optimization algorithm (QIOA). The proposed formula is dependent on variable voltage resistances (VVR) implementation of the series and shunt resistances. The variable resistances reduced from the effect of the electric field on the semiconductor conductivity should be included to get more accurate representation. Minimizing the mean root square error (MRSE) between the measured (I–V) dataset and the extracted (V–I) curve from the proposed electrical model is the main goal of the current optimization problem. The unknown parameters of the proposed PV models under the considered operating conditions are identified and optimally extracted using the proposed QIOA. Two distinct PV types are employed with normal and low radiation conditions. The VVR TDM is proposed for (R.T.C. France) silicon PV operating at normal radiation, and eleven unknown parameters are optimized. Additionally, twelve unknown parameters are optimized for a Q6-1380 multi-crystalline silicon (MCS) (area 7.7 cm2) operating under low radiation. The efficacy of the QIOA is demonstrated through comparison with four established optimizers: Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), Salp Swarm Algorithm (SSA), and Sine Cosine Algorithm (SCA). The proposed QIO method achieves the lowest absolute current error values in both cases, highlighting its superiority and efficiency in extracting optimal parameters for both Single-Crystalline Silicon (SCS) and MCS cells under varying irradiance levels. Furthermore, simulation results emphasize the effectiveness of QIO compared to other algorithms in terms of convergence speed and robustness, making it a promising tool for accurate and efficient PV parameter estimation.

Materials removal mechanism for ultra-precise cutting of single-crystal silicon with natural single-crystal diamond tools by experiment and atomic simulation

The influence of tool rake angle and cutting speed on the ultra-precision cutting of single crystal silicon with natural single crystal diamond tools is studied by experiment and molecular dynamics (MD) simulations. The findings demonstrate that the 0° rake angle tool attains superior surface quality, reduced cutting force and friction coefficient in comparison to the −10° and − 20° rake angle tools. Moreover, the MD results reveal that a smaller negative rake angle tool can decrease the formation of high pressure phase atoms and other defects. In addition, the PV, RMS and Ra surface roughness parameters decrease as the machine spindle speed increases. Additionally, higher cutting speeds improve the surface morphology of the machined workpiece and produce fewer defective atoms.

Suns-Vmp method for health monitoring of 110 PV modules

One can monitor the health of the PV modules by analyzing their current-voltage (I–V) curves, which rarely are measured in commercial settings. Fortunately, nearly all PV installations measure the maximum power point current (Imp) and voltage (Vmp), along with the ambient weather conditions, which the proposed Suns-Vmp method uses to generate pseudo I–V curves. In this work, the proposed methodology was rigorously tested on 110 PV modules of various technologies installed under harsh desert conditions, for approximately 7 years and 9 months. For these modules, the fitting accuracy between the actual field measured and pseudo I–V curves, did not exceed an RMSE value of 0.35 A. The median power degradation of the mono-crystalline, poly-crystalline, and thin-film technologies were estimated to be around 0.21 %/year, 0.49 %/year, and 1.51 %/year. From the root-cause analysis using the fitted PV parameters, it was found that the dominant degradation contribution in all the modules came from series resistance, followed by shunt resistance. For mono-crystalline, poly-crystalline, and thin-film technologies, the mean yearly rate of change for series resistance was 1.47 %, 4.37 % and 13.37 %, while for shunt resistance these values were 0.68 %, 1.26 % and 3.95 % respectively. As field measured I–V curves are seldom available, techniques like the Suns-Vmp method can offer valuable insights for effective solar farm management and maintenance, without any interruption in the operation.

Analysis of Advanced TiO2/Si based Solar Cell Architecture: Improving PV Parameters and Thermal Stability

Analysis of Advanced TiO2/Si based Solar Cell Architecture: Improving PV Parameters and Thermal Stability

Tribological behavior evaluation of poly-ether-ether-ketone (PEEK) in dry journal bearing on shaft wear test

This paper investigated the tribological behavior of pure PEEK playing as a dry journal bearing, sliding against stainless steel, under real-life operating conditions in a wear test lasting 2 h. Four conditions were carried out with different magnitudes of normal load and sliding speed, while keeping a constant PV parameter. Sample topography assessments were performed with scanning electron microscopy and white light interferometry techniques. In addition, PEEK samples were also evaluated by Fourier Transformed Infrared Spectroscopy and thermal analyses by Differential Scanning Calorimetry. The coefficient of friction (COF) changed throughout the wear test and exhibited a running-in period followed by a transition, with an increase of COF, and then a tendency to reach a steady-state. Moreover, the COF behavior obtained suggests that there was an influence of the wear test parameters, mainly right after the running-in period — and the COF averages for the steady-state period were statistically equal. Stainless steel samples showed mild wear, while PEEK samples had a drastic alteration of their topography imposed by the wear test — including an increase in its degree of crystallinity. Nonetheless, the PEEK journal bearing samples did not fail from wear and their mass losses were small. Polymeric wear particles were generated and were found weakly adhered to both the body and the counter body. PEEK exhibited a lumpy transfer process — nonetheless, SEM images evaluation was useful to verify that these particles were eventually merged during sliding, and kneaded in the convex-concave contact, which provided them a film-like appearance. Furthermore, adhesive and abrasive wear mechanisms were identified, which were shown to be related to the journal bearing on shaft wear test arrangement.

Multilayers strategy with a mixed CdTe/ZnTe absorber layer for optical trapping and efficiency improvement in CdTe-based solar – SCAPS modelling

This work is a theoretical contribution to improving the performance of CdTe-based thin-film solar cells (TFSC) by optimising the collection of photons in the absorber structure. The basic data are retrieved from experimental reference work and the reference structure is as follows: CdS/CdTe/ZnTe with an efficiency of 20.16%, where ZnTe is used as a BSF to limit backward recombination. The first approach is to incorporate a ZnTe thin layer at the CdS/CdTe heterojunction, to subdivide the CdTe active layer into two (02) sub-layers and to identify the optimum structure as a function of their position in the stack. Investigating the work function of back contact materials enables to better enhance the device′s performance and stability. To take into consideration the discontinuities in the material properties, grain boundaries and performance loss factors, the impacts of charge carrier capture cross sections, bulk and interfacial defects are investigated. SCAPS software is employed for all the numerical modelling, which enables to calculate the current-voltage (J-V), power-voltage (P-V), external quantum efficiency (EQE) and other PV parameters and to draw energy band diagram to better appraise charge carrier transportation. The doping level in the CdTe active layer, the thicknesses and external temperature are also investigated to optimize our device properties. In terms of the obtained fill factor (FF) and efficiency (PCE), the performances were improved with the following structure CdS/CdTe/ZnTe/CdTe/ZnTe, FF = 81.6% and PCE = 23.45%, with 500 nm thickness of CdTe. These results are opening a promising new perspective in high efficiency CdTe TFSC.

Revolutionizing photovoltaic excellence: Unveiling a cutting-edge approach to assessing module enhancers for optimal area and cost efficiency

A photovoltaic module (PV) functions as a device for producing electricity. Increasing the number of PV units leads to higher power generation, but this also requires a larger land's area. However, limitations in available space, especially on building rooftops, coupled with consumer demands for greater power output, pose a challenge. To tackle this issue, the PV enhancer technology has been introduced. It aims to boost power generation per unit area and has been evaluated in a previous study. While this existing approach effectively compares different PV enhancers, it becomes complex when considering both the PV and enhancer's area parameters. To simplify this, a novel method is introduced for the first time which incorporates a new correlation considering the area of both the PV and its enhancer, the combined net power generated, the PV's output power without an enhancer, and the maximum PV power under standard test conditions. It also includes the cost per watt of PV power and the manufacturing cost of the PV enhancer. The impact of each parameter on this new method is thoroughly explained. The proposed technique categorizes PV enhancers based on values derived from the new method. For instance, enhancers are classified as having maximum or minimum performance based on whether the value of the new method equals the minimum value of the area and cost-effectiveness factor or unity, respectively. The effectiveness of the new method is confirmed through testing on a real-world case from a previous experimental study, demonstrating its practicality. The new method has shown applicability in real world scenarios and can aid in categorizing types of PV enhancers, offering valuable insights for researchers, designers, and manufacturers for informed decision-making.

Optimisation and numerical analysis of highly efficient CGSe-based thin film solar cell

Among the various chalcopyrites compounds used in photovoltaic devices, Copper Gallium Selenium (CGSe) turns out as an underperformer due to its limited photovoltaic performance, So far highest efficiency measured is about 11.9%. This paper investigates the possibilities for efficiency enhancement for the CuGSe layer in Cu2O/CGSe/TiO2/ZnO thin film solar cell structure using the SCAPS-1D simulation program. The short circuit current (Jsc) and power conversion efficiency (PCE) is 30.77 mA cm−2 and 27.10%, with open-circuit voltage (Voc) and fill factor (FF) of 1.03 V and 84.72% respectively. Furthermore, we evaluated some specific parameters of TiO2/CGSe heterostructure, such as the influence of layer thickness, operating temperature, the effect of defect density and acceptor density of CGSe layer, metal work function, and the effect of series and shunt resistance on cell performance. We investigated that combining TiO2 as an ETL and Cu2O as HTL with a CGSe absorber layer is novel and promising, which results in higher power conversation efficiency and improves other PV parameters. The application of CGSe/TiO2 heterojunction in a simulated model offers a viable method for the development of high-efficiency solar cell devices.

Parameter Extraction of PV Solar Cell Using Metaheuristic Methods

Due to the increasing crises in energy and environmental factors, the importance of renewable energy is increasing. However, it is gaining importance in developing photovoltaic energy systems. Therefore, great efforts are made to maximize success in accurately modeling PV parameters. Parameter estimation is a complex problem and requires advanced design tools such as optimization techniques because the current voltage (I–V) characteristics of PVs are nonlinear. This study investigates the best technique for the most accurate estimation of the parameters obtained in single-diode and double-diode cases. The Gray Wolf Optimization (GWO), Improved Gray Wolf Optimization (IGWO), Sine Cosine Algorithm (SCA), Whale Optimization Algorithm (WOA), and Multi-Verse Optimizer (MVO) are the algorithms used in this paper. Apart from the literature, this study considers that the PV parameter extraction problem is not just an offline optimization problem but also a real-time optimization issue. The performance of all methods has been compared with experimental data. The lowest error on minimum iteration and highest convergence accuracy have been achieved for offline optimization by using IGWO. The results clearly state that the IGWO is not usable in real-time applications even though IGWO is the best optimizer in offline optimization.

Dwarf Mongoose Optimizer for Optimal Modeling of Solar PV Systems and Parameter Extraction

This article presents a modified intelligent metaheuristic form of the Dwarf Mongoose Optimizer (MDMO) for optimal modeling and parameter extraction of solar photovoltaic (SPV) systems. The foraging manner of the dwarf mongoose animals (DMAs) motivated the DMO’s primary design. It makes use of distinct DMA societal groups, including the alpha category, scouts, and babysitters. The alpha female initiates foraging and chooses the foraging path, bedding places, and distance travelled for the group. The newly presented MDMO has an extra alpha-directed knowledge-gaining strategy to increase searching expertise, and its modifying approach has been led to some extent by the amended alpha. For two diverse SPV modules, Kyocera KC200GT and R.T.C. France SPV modules, the proposed MDMO is used as opposed to the DMO to efficiently estimate SPV characteristics. By employing the MDMO technique, the simulation results improve the electrical characteristics of SPV systems. The minimization of the root mean square error value (RMSE) has been used to compare the efficiency of the proposed algorithm and other reported methods. Based on that, the proposed MDMO outperforms the standard DMO. In terms of average efficiency, the MDMO outperforms the standard DMO approach for the KC200GT module by 91.7%, 84.63%, and 75.7% for the single-, double-, and triple-diode versions, respectively. The employed MDMO technique for the R.T.C France SPV system has success rates of 100%, 96.67%, and 66.67%, while the DMO’s success rates are 6.67%, 10%, and 0% for the single-, double-, and triple-diode models, respectively.

Performance enhancement of CsPbI3-xBrx perovskite solar cells via graded bandgap and affinity engineering

All inorganic cesium lead-based perovskite solar cells (PSCs) have gained attention as alternative absorbing materials owing to their exceptional thermal stability. However, these devices are suffer from transmission and thermalization losses. Therefore, a novel grading approach is used in CsPbI3-x Brx perovskite solar cell to reduce the transmission and thermalization losses by enhancing the cell’s ability to capture a broad spectrum of light wavelengths and suitably accommodate the material’s energy bandgap. In this work, the performance of CsPbI3-xBrx perovskite solar cell with graded bandgap (Eg) and affinity has been explored and analyzed using the simulation SCAPS-1D tool. Different compositions (x) are varied to adjust the bandgap of CsPbI3-xBrx with different grading profiles such as linear, parabolic and beta grading. The graded structure enhances the absorption wavelength range and carrier lifetime. However, it also leads to the redistribution of the electrical field within the device, promoting more effective charge separation and collection. By utilizing this approach, the impact of absorber thickness variations from (50 nm to 700 nm) is also studied and analyzed with respect to grading profiles. Initially, 16.75% power conversion efficiency (PCE) is obtained by calibrating the experimental CsPbI3-xBrx graded solar cell. Then, performance is further improved by adjusting the bandgap with grading profiles, optimizing ETLs/HTLs and achieving optimum PV parameters: short-circuit current density (JSC) of 20.50 mA cm−2, open-circuit voltage (VOC) of 1.35 V, fill factor (FF) of 84.15% and PCE of 23.11%. The findings of the reported study would significantly provide a path for the development of graded PSC.

An Advanced Bio-Inspired Mantis Search Algorithm for Characterization of PV Panel and Global Optimization of Its Model Parameters.

Correct modelling and estimation of solar cell characteristics are crucial for effective performance simulations of PV panels, necessitating the development of creative approaches to improve solar energy conversion. When handling this complex problem, traditional optimisation algorithms have significant disadvantages, including a predisposition to get trapped in certain local optima. This paper develops the Mantis Search Algorithm (MSA), which draws inspiration from the unique foraging behaviours and sexual cannibalism of praying mantises. The suggested MSA includes three stages of optimisation: prey pursuit, prey assault, and sexual cannibalism. It is created for the R.TC France PV cell and the Ultra 85-P PV panel related to Shell PowerMax for calculating PV parameters and examining six case studies utilising the one-diode model (1DM), two-diode model (1DM), and three-diode model (3DM). Its performance is assessed in contrast to recently developed optimisers of the neural network optimisation algorithm (NNA), dwarf mongoose optimisation (DMO), and zebra optimisation algorithm (ZOA). In light of the adopted MSA approach, simulation findings improve the electrical characteristics of solar power systems. The developed MSA methodology improves the 1DM, 2DM, and 3DM by 12.4%, 44.05%, and 48.88%, 28.96%, 43.19%, and 55.81%, 37.71%, 32.71%, and 60.13% relative to the DMO, NNA, and ZOA approaches, respectively. For the Ultra 85-P PV panel, the designed MSA technique achieves improvements for the 1DM, 2DM, and 3DM of 62.05%, 67.14%, and 84.25%, 49.05%, 53.57%, and 74.95%, 37.03%, 37.4%, and 59.57% compared to the DMO, NNA, and ZOA techniques, respectively.

An Innovative MPPT Method Based on the Estimated Model of the Photovoltaic Cell considering the Environmental Conditions

In this paper, a novel adaptive photovoltaic maximum power point tracking (MPPT) circuit is proposed, called AT2MPPT. The AT2MPPT circuit is based on a type two fuzzy logic set and utilizes a detailed two-diode model of a solar cell, as well as an innovative hybrid algorithm for designing the MPPT circuit. The effects of environmental conditions such as azimuth, wind speed, wind direction, and irradiation, as well as the uncertainty of radiation intensity, are taken into account in the solar cell model. It is demonstrated that changes in environmental conditions can cause up to a 20% change in the PV parameters. To optimize the AT2MPPT parameters and fuzzy membership functions (MFs), a hybrid lightning search algorithm and whale optimization algorithm (hLSA-WOA) are proposed. The accuracy of the hLSA-WOA is evaluated by comparing its results with those of other optimization algorithms on 10 standard benchmarks. The simulation results indicate that the hLSA-WOA has high accuracy and is nontrapping in local optima. Finally, the proposed AT2MPPT circuit is used to track the MPPT of a PV array in partial shade, and its performance is compared with that of P&O and fuzzy MPPT circuits. The results confirm the superior performance of the AT2MPPT circuit, which produces 1.1% more power than the other two circuits. Additionally, the AT2MPPT circuit has lower power ripple and tracking time compared to perturb, observation, and fuzzy MPPT circuits.

Performance Improvement of Perovskite Solar Cell Design with Double Active Layer to Achieve an Efficiency of over 31%

This research aims to optimize the efficiency of the device structures by introducing the novel double perovskite absorber layer (PAL). The perovskite solar cell (PSC) has higher efficiency with both lead perovskite (PVK), i.e., methylammonium tin iodide (MASnI3) and Caseium tin germanium iodide (CsSnGeI3). The current simulation uses Spiro-OMeTAD as the hole transport layer (HTL) and TiO2 as an electron transport layer (ETL) to sandwich the PVK layers of MASnI3 and CsSnGeI3, which have precise bandgaps of 1.3 eV and 1.5 eV. The exclusive results of the precise modeling technique for organic/inorganic PVK-based photovoltaic solar cells under the illumination of AM1.5 for distinctive device architectures are shown in the present work. Influence of defect density (DD) is also considered during simulation that revealed the best PSC parameters with JSC of 31.41 mA/cm2, VOC of 1.215 V, FF of nearly 82.62% and the highest efficiency of 31.53% at the combined DD of 1.0 × 1014 cm−3. The influence of temperature on device performance, which showed a reduction in PV parameters at elevated temperature, is also evaluated. A steeper temperature gradient with an average efficiency of −0.0265%/K for the optimized PSC is observed. The novel grading technique helps in achieving efficiency of more than 31% for the optimized device. As a result of the detailed examination of the total DD and temperature dependency of the simulated device, structures are also studied simultaneously.

Kesterite CZTS based thin film solar cell: Generation, recombination, and performance analysis

The thin film Copper Zinc Tin Sulphide (CZTS) solar cells (SC) are third-generation SC that has potential use in solar photovoltaics nowadays. The present work aims to raise the output parameter of CZTS-based SC through the generation and recombination process using Solar Cell Capacitance Simulator in one dimension (SCAPS-1D). The proposed configuration of cell ZnO/ZnS/CZTS/SnS has been evaluated by considering SnS as the back surface field (BSF). It is observed that SnS is a suitable material to be used as a BSF. In the present work, the role of variations of the different parameters such as layer thicknesses, defect densities, recombination and generation of charge carriers, and the back contact work function effect on the PV parameter have been studied. Optimized parameters from the studied cell such as power conversion efficiency (PCE) of 18.18%, current density (Jsc) as 27.7899 mA/cm2, open circuit voltage (Voc) of 0.7875 V, and fill factor (FF) of 83.07% have been recorded. This result will pave the researchers working in this field to fabricate earth-abundant, low-cost, highly efficient, and toxic-free CZTS SCs.

The Differences between Single Diode Model and Double Diode Models of a Solar Photovoltaic Cells: Systematic Review

This research paper systematically reviewed and investigated single diode model and double diode model of a solar photovoltaic systems in terms of accuracy, differences under major unknown PV parameters, different optimization and fabrication. This research paper reviewed the differences and the similarities between the single diode model and double diode model. From the review, it was clear that single diode model has less computation time and number of unknown parameters compared to double diode model. The double diode model on its own superiority is more accurate under solar shading condition effect than single diode model but single diode model performs better under high insolation levels. None of the two models is superior than the other but the solar photovoltaic modelers/installers should bear the solar irradiance of the environment before installation