PV Parameters Research Articles

A comparative numerical simulation study of CIGS solar cells with distinct back surface field layers for enhanced performance

The objective of this study is to explore the impact of various back surface field (BSF) layers including copper aluminium oxide (CuAlO2), Copper Antimony Sulphide (CuSbS2), Formamidinium tin triiodide (FASnI3), poly (3-hexylthiophene) P3HT to boost the output of conventional baseline CIGS solar cells structured. The device performance increases because of the minimized surface recombination velocity through heavily doped BSF layers, which increases the electric field at the rear contact. Among all proposed BSF layers CuAlO2 gives the best photoconversion efficiency (η) of 24.61 % followed by fill factor (FF) of 83.11 %, short circuit current density (JSC) of 35.87 mA/cm2, and open circuit voltage (VOC) of 0.82 V with quantum efficiency (QE) of ∼92 % for the whole visible range with the onset happening at ∼ 560 nm, thanks to the enhancement of carrier collection when BSF layer is incorporated. The novelty in this work is that for the first time with the CuAlO2 BSF layer, 24.61 % efficiency is reported at 1 μm CIGS layer thickness. We also examined how different BSFs affect the PV performance of the devices. The effect of temperature, the doping concentration of the BSFs, varying gallium proportion, JV & QE analysis, band diagram, and radiative recombination coefficient are varied to observe their impact on the PV parameters. This research introduces novel CIGS/CdS heterojunction configurations using various BSF layers to enhance efficiency, supporting the advancement of ultrathin, flexible, and tandem solar cell applications.

Effects of Measuring Angles on Detection of Millimeter-Scale Fractures with Fluid Flow using Full-Polarimetric GPR

Abstract The fractures with fluid flow will lead to the damage of rock cave artifacts and the detection of millimeter-scale fractures is a challenge in artifact conservation. The fluid flow in fractures and the infiltration in surrounding rocks based on hydrological modeling was simulated first. Based on the results, electric permittivity and conductivity models at different time lapse were established, and a series of models with different rotation angles were generated through coordinate rotation for full-polarimetric ground penetrating radar (FP-GPR) simulations. Subsequently, the relationships between H, α, Ps , Pd , and Pv parameters and measurement angles and infiltration time are analyzed. The results indicate that α, Ps and Pd have good variation consistency with infiltration time, while H and Pv do not show a significant relationship with the infiltration time. In addition, the analysis results of the five parameters all indicate that the measurement angle has a significant impact on the parameters at the beginning of infiltration, which is related to the frequency of the adopted electromagnetic waves. The results provide important theoretical support and technical guidance for the use of time-lapse FP-GPR to detect fractures with fluid flow in field cases.

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.

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.

Performance Optimization of MgHfS3 Chalcogenide Perovskite Solar Cells Using SCAPS-1D

In this work, magnesium hafnium sulfide MgHfS3 perovskite solar cells have been investigated using numerical modelling and simulation. Perovskite solar cells have received increasing recognition owing to their promising light-harvesting properties. The modelling and simulation of MgHfS3 was successfully carried out using the Solar cell capacitance simulator (SCAPS-1D) software. Consequently, this study developed a base model structure of FTO/TiO2/MgHfS3/Cu2O/Au and subsequently explored the effect of varying device layer properties such as absorber thickness, total and interface defect densities with a view of optimizing these parameters for better device performance. Simulating the base model gave the performance characteristics of 0.99 V, 25.21 mA/cm2, 57.59%, and 14.36% which are the open-circuit voltage (Voc), short-circuit current density (Jsc), fill factor (FF) and PCE respectively. The optimal absorber thickness was found to be 300 nm and the optimum density of defects for both TiO2/Absorber interface and Absorber/Cu2O interface are respectively 1010 cm-3 and 109 cm-3. The obtained optimized PV parameters are Voc = 1.2629 V, Jsc = 24.44 mA/cm2, FF = 89.46% and PCE = 27.61%. Also, it was established that increasing the device temperature beyond 300K enhanced the short circuit current while other performance characteristics gradually declined. The obtained results suggest that chalcogenide MgHfS3 is a potential absorber material candidate for the production of cheap and very efficient environment-friendly perovskite solar cells.

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.

New PV Metrology for performance appraisal of Poly-Silicon PV Modules in Eastern Indian climatic Zone

An appropriate number of series-connected supercapacitors (SC) forming an SC bank has been used for the first time as the load to PV generators in course of their electrical characterization. Exhaustive estimates of standard PV parameters along with figures of merits like Fill-factor(FF) and performance ratio(PR) have yielded consistent results under naturally varying levels of insolation and ambient temperature prevalent in West Bengal of India. Regression analysis of selected PV parameters has indicated values above 0.997 for poly-Si PV modules which currently constitute the only essential building blocks for PV arrays in the Indian sub-continent. Work is in progress for the adoption of this simple, user-friendly, and easily scalable I-V plotter in PV Indian industries and field trials.

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.