Solar Cell Model Research Articles

Effect of the Dynamic Resistance on the Maximum Output Power in Dynamic Modelling of Photovoltaic Solar Cells

Several studies on PV solar cells are found in the literature which use static models. Those models are mainly one-diode, two-diode or three-diode models. In the dynamic modelling, a variable parallel capacitance is incorporated. Unlike the previous studies which do not clearly establish a relationship between the capacitance and the voltage, in the present paper, the link between the capacitance and the voltage is investigated and established. In dynamic modelling investigated in this paper, the dynamic resistance is introduced in the modelling of the solar cell. It is introduced in the current-voltage characteristic. The value of the dynamic resistance is evaluated at the maximum power point and its effect on the maximum power is investigated. The study shows for the first time, that the dynamic resistance must be introduced in the current-voltage characteristic, because it has an influence on the PV cell output.

Modified Salp Swarm Optimization for Parameter Estimation of Solar PV Models

The identification of parameters in solar cell models is still a major challenge in photovoltaic (PV) system simulation and design. Because of its more basic ideas, efficiency, adaptability, swarm and evolutionary optimization algorithms, as well as simple procedural frameworks, have been generally used in industry with real-world problems. However, due to the nonlinearity and complication of the PV parameter identification, the obtained solutions from swarm and evolutionary optimizers were immature. An efficient metaheuristic approach for identifying PV model parameters based on the salp swarm algorithm (SSA) is presented in this paper. In the suggested modified salp swarm optimization (MSSA), the leaders and followers will be updated based on the new formulas. The algorithm’s exploration potential is increased by this modification while also preventing it from converge prematurely. The behavior of the suggested technique is verified using benchmark functions, and the outcomes are contrasted with those of SSA and other successful optimization approaches. The suggested MSSA detects numerous characteristics in the PV model include single diode, double diode, and PV modules, in the most efficient way possible. According to the simulation results, MSSA outperforms the competition and may produce better optimal solutions. The findings demonstrate that the best value of RMSE obtained by MSSA is up to 69 percent lower than other methods and is nearly 5.6 percent lower than that assessed by SSA.

Optoelectronic Modeling of All-Perovskite Tandem Solar Cells with Design Rules to Achieve >30% Efficiency

Optoelectronic Modeling of All-Perovskite Tandem Solar Cells with Design Rules to Achieve >30% Efficiency

Enhancing CZTS solar cell parameters using CZTSe BSF layer and non-toxic SnS2/In2S3 buffer layer

Direct bandgap, high absorption coefficient and good electronic properties are the main reasons why the quaternary semiconductor Copper Zinc Tin Sulphide (shortly named CZTS) reached a high interest in the minds of researchers. In this work, a numerical modeling of CZTS solar cells using SCAPS-1D was executed investigating two major points. One, the possibility of replacing the traditional and toxic CdS as buffer layer for CZTS cells, we suggested both Tin sulphide (SnS2) and Indium sulphide (In2S3) as they showed good conductivity, optical transparency and optimal bandgap which make them appropriate to be buffer layer materials. Two, the enhancement that could be brought in by adding a back surface field (BSF) in-between the absorber layer and the back contact of the cell, and here we suggested CZTSe for its good optoelectronic properties, nontoxicity, earth-abundant components. The substrate cell configuration Mo/CZTSe/CZTS/(SnS2 and In2S3)/ZnO/FTO is used to observe the effect of temperature, absorber, buffer, BSF layer thicknesses, absorber’s concentration of acceptors, series resistance and back contact on the cell performance and to optimize the results following a valid procedural approach. Efficiencies of 32,55% and 32,50% are reached for SnS2 and In2S3 respectively. These simulation results could be very helpful to improve our knowledge of this type of solar cells and thus control better the fabrication process.

A fully coupled opto-electro-thermal model to investigate silicon solar cells under real operating conditions

In this work, a fully coupled opto-electro-thermal model for crystalline silicon solar cells is presented. Based on a detailed set of material properties, the developed model allows us to predict and analyse the solar cell behaviour under real operating conditions in a standalone framework. The results show the potential of our model to study the influence of the cell design on its real operating performance, thus giving a new opportunity for silicon solar cell optimisation. Specifically, the doping level is found to impact both the operating temperature and the temperature coefficient, showing that two cells with the same power conversion efficiency in standard test conditions can have a very different efficiency under real operating conditions. We also demonstrate the model capability to assess in detail the influence of environmental conditions, such as the solar spectrum, which also impacts the temperature coefficient. As the latter is not required by our material-based approach but is a simulation output, this work opens the way to more reliable outdoor prediction. Moreover, the various perspectives and challenges associated with the proposed detailed multiphysics simulation of solar cells are discussed, providing important guidelines for future studies.

Micro-concentrated photovoltaics based on Cu(In,Ga)Se2microcells: an optical study

Micro-concentrated Cu(In,Ga)Se2(µCPV-CIGSe) solar cells offer the potential to greatly reduce the consumption of raw materials while maintaining high efficiencies. A theoretical model of µCPV-CIGSe solar cells, consisting of hexagonally spaced micro-CIGSe (µ-CIGSe) solar cells embedded in the low-index dielectric matrix and µ-lenses placed on top, is proposed for optical study. It is discovered that µ-lenses enable to effectively concentrate the incident light due to the inherent nanojet phenomenon, and the µ-CIGSe absorbers trap the penetrated light within absorbers arising from wave-guided modes. The two effects co-contribute to an optimized absorption for µCPV-CIGSe solar cells with a µ-CIGSe absorber diameter of 800 nm and a pitch of 1500 nm. Short-circuit current density reaches 36.5 mA/cm2and accounts for 98.8% compared to their plain counterparts without lenses, corresponding to an absorber material saving by a factor of 3/4. Notably, a large contacting area between lenses and CIGSe solar cells are recommended for an improved angular tolerance. Those findings will recommend design principles for further experiments.

Design and Simulation of Highly Efficient One-Sided Short PIN Diode Silicon Heterojunction Solar Cell

Performance of highly efficient one-sided short PIN diode heterojunction solar cell model is studied using AFORS-HET simulation software. Here, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</i> -type crystalline silicon is used as an absorber layer, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> -type amorphous silicon as emitter layer, and a thin intrinsic amorphous silicon (i-a-Si:H) layer is sandwiched in between, which acts as a passivation layer. The diode model concept has been introduced mainly to lower the reverse saturation current by appropriate selection of the cell parameters. Short diode reduces recombination phenomenon in the short quasi-neutral region (n-a-Si:H in this article), and one-sided junction allows the maximum amount of light absorption in the absorber layer (p-c-Si in this article). The one-sided junction nature has been confirmed by capacitance–voltage ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C–V</i> ) analysis. Further thickness variation of layers and role of the carrier concentration of n-a-Si layer on various parameters, such as short-circuit current density ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">J</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sc</sub> ), open-circuit voltage ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">oc</sub> ), and fill factor (FF) have also been studied. The structure has exhibited an open circuit voltage of 0.714 V, fill factor 0.80, and maximum efficiency of 24.2%. Further, experimental validation is also established by comparing the theoretical results with the fabricated NIP structure.

Optimization of MoSe2 back interface layer for highly efficient CIGS solar cells: Numerical analyses

The effect of the MoSe2 layer has been numerically investigated using SCAPS-1D solar cell modeling software. Using a combination of energy bandgap from 1 to 1.5 eV and thickness from 10 to 130 nm for MoSe2 best configuration was determined for high-efficiency CIGS solar cell. Optimized MoSe2 layer improved the efficiency to 20.4 % with Voc of 0.74 V, Jsc of 3.6 mA/cm2, and fill factor of 0.89 relative to 14.55 % for cell without MoSe2 layer. With the increase in bandgap of MoSe2, the efficiency of the cell increased gradually up to 1.35 eV and then suddenly decreased for the bandgap above 1.35 eV. The decrease in efficiency is observed mainly because of the reduction in Jsc and reduction in FF due to lower maximum voltage output. As the thickness was increased from 10 nm up to 50 nm, Jsc increased due to a reduction in recombination back contact and remains almost constant for thickness above 60 nm. Efficiency was observed to be improved with the thickness of the MoSe2 layer above 60 nm. With the increase of 8 % efficiency, the findings could be used to develop high-efficiency, cost-effective CIGS solar cells.

Cubic Silicon Carbide (3C–SiC) as a buffer layer for high efficiency and highly stable CdTe solar cell

Cubic Silicon Carbide (3C–SiC) is a potential material for use in photovoltaics for its significant advancement in growth in terms of crystal quality and domain size. Hence, 3C–SiC has been introduced here as an alternative non-toxic buffer layer for heterojunction CdTe solar cell. The solar cell is designed for the study consisted of multi-junction semiconductor layers such as p-CdTe/n-3C–SiC/n-SnO2. Device modeling of the novel CdTe solar cell including the thickness and doping concentration of the novel buffer layer 3C–SiC are investigated and optimized using SCAPS-1D software. Also, the defect density in the buffer layer is studied to see the tolerance of the proposed device structure. The working temperature and incident light intensity are also varied to deduce the effect of environmental conditions on efficient PV operation.

Theoretical and experimental evaluation on the electrical properties of multi-junction solar cells in a reflective concentration photovoltaic system

Solar photovoltaic systems represent an important technology for renewable energy utilization and have broad potential for application and development. However, the further development of solar photovoltaic systems is hindered by their higher generation costs. A high-concentration photovoltaic system (HCPVs) can use an inexpensive concentrator to replace solar cells; this, in turn, reduces the cost of electricity generation, because the solar cell requirement decreases for a given power. This study developed a mathematical model for multi-junction solar cell (MJSC) based on single-diode equivalent circuit, furthermore, an HCPVs with hyperboloid mirrors was established. The electrical properties for an MJSC module, including the short-circuit current (Isc), peak power (Pm), open-circuit voltage (Voc), fill factor (FF), and efficiency (η) were investigated at concentration ratios between 650 X and 800 X and direct solar radiation intensities between approximately 400 W/m2 and 730 W/m2. Furthermore, the experimental results and theoretical values were comparatively analyzed. The results demonstrated that Isc, Voc, and Pm of MJSC module increased as the direct solar radiation raised. In contrast, the FF and η of an MJSC module decreased as the direct solar radiation raised. As the direct solar radiation intensity was 700 W/m2 and concentration ratio increased from 650 X to 800 X, Isc, Voc, and Pm increased from 1.002 A to 1.243 A, 11.095 V to 11.158 V, and 9.466 W to 11.358 W, respectively. Conversely, the FF and η of the MJSC module decreased from 32.51 % to 31.33 % and 0.851 to 0.819, respectively. The tallied between the numerical and experimental results was evaluated, which indicated that root-mean-square error between the experimental and calculated values increased as the direct solar radiation increased.

Modeling and optimization of CZTS kesterite solar cells using TiO2 as efficient electron transport layer

In this paper, a numerical simulation study via AMPS 1D simulator is carried out to investigate the degradation mechanisms occurred in hybrid Cu2(Zn,Sn)Se4 (CZTS) solar cells that use a nonporous n-type-TiO2 material as a window. The advantageous Spike-like conformation against recombination at the TiO2/CZTS interface, which is ensured by the band-engineering offset established using TiO2 material, is discussed. The influence of the geometrical and physical parameters on the device fundamental figures of merit is assessed. Besides, the degradation effect linked to both deep and tail states situated in the gap of the materials, and the effective working temperature, are taken into account. The results reveal that the actual defect type (donor or neutral) at the Cu2ZnSnS4 layer has a harsh influence on the device performance. This is attributed to the raised Shockley–Read–Hall (SRH) recombination highlighted by investigating the variation of the carrier density along the absorber layer. A low barrier height at the back contact (ϕbl = 0.1 eV) and a suitable doping level and thickness of both the window (ND = 4 × 1017 cm−3, WTiO2 = 0.02 µm) and the absorber (NA = 6.5 × 1016 cm−3, WCZTS = 3.2 µm) layers could efficiently improve the device performance.

Elucidating the underlying physics in a two-terminal all-perovskite tandem solar cell: A guideline towards 30% power conversion efficiency

We develop an optoelectronic model for a two-terminal all-perovskite tandem solar cell comprising a top cell, a bottom cell, and a recombination junction in between that connects the two sub-cells in series electrically. In short, the model considers incoherent and coherent light propagation in the glass and thin-film layers respectively, as well as charge carrier transport, generation, and recombination. After calibrating the model to the state of the art two-terminal all-perovskite tandem solar cell with an efficiency of 24.5%, we first study the current matching behavior and S-shaped current–voltage curve of this tandem cell due to the recombination junction. Next, the light interference effect is investigated. Layer thicknesses are adjusted to increase the short circuit current. From a loss analysis, the leading order recombination channels are the surface and Shockley–Read–Hall recombinations. Moreover, we show that the power conversion efficiency of this calibrated tandem model can reach 30.5% by adjusting the layer thicknesses, increasing carrier mobility, and reducing recombination loss. Finally, after switching to bifacial operation, the model predicts a power conversion efficiency of around 35%.

Parameter Identification of Photovoltaic Cell Model Using Modified Elephant Herding Optimization-Based Algorithms

The use of metaheuristics in estimating the exact parameters of solar cell systems contributes greatly to performance improvement. The nonlinear electrical model of the solar cell has some parameters whose values are necessary to design photovoltaic (PV) systems accurately. The metaheuristic algorithms used to determine solar cell parameters have achieved remarkable success; however, most of these algorithms still produce local optimum solutions. In any case, changing to more suitable candidates through elephant herd optimization (EHO) equations is not guaranteed; in addition, instead of making parameter α adaptive throughout the evolution of the EHO, making them adaptive during the evolution of the EHO might be a preferable choice. The EHO technique is used in this work to estimate the optimum values of unknown parameters in single-, double-, and three-diode solar cell models. Models for five, seven, and ten unknown PV cell parameters are presented in these PV cell models. Applications are employed on two types of PV solar cells: the 57 mm diameter RTC Company of France commercial silicon for single- and double-diode models and multi-crystalline PV solar module CS6P-240P for the three-diode model. The total deviations between the actual and estimated result are used in this study as the objective function. The performance measures used in comparisons are the RMSE and relative error. The performance of EHO and the proposed three improved EHO algorithms are evaluated against the well-known optimization algorithms presented in the literature. The experimental results of EHO and the three improved EHO algorithms go as planned and proved to be comparable to recent metaheuristic algorithms. The three EHO-based variants outperform all competitors for the single-diode model, and in particular, the culture-based EHO (CEHO) outperforms others in the double/three-diode model. According the studied cases, the EHO variants have low levels of relative errors and therefore high accuracy compared with other optimization algorithms in the literature.

Novel perovskite solar cell with Distributed Bragg Reflector.

This paper reports numerical modeling of perovskite solar cell which has been knotted with Distributed Bragg Reflector pairs to extract high energy efficiency. The geometry of the proposed cells is simulated with three different kinds of perovskite materials including CH3NH3PbI3, CH3NH3PbBr3, and CH3NH3SnI3. The toxic perovskite material based on Lead iodide and lead bromide appears to be more efficient as compared to non-toxic perovskite material. The executed simulated photovoltaic parameters with the highest efficient structure are open circuit voltage = 1.409 (V), short circuit current density = 24.09 mA/cm2, fill factor = 86.18%, and efficiency = 24.38%. Moreover, a comparison of the current study with different kinds of structures has been made and surprisingly our novel geometry holds enhanced performance parameters that are featured with back reflector pairs (Si/SiO2). The applied numerical approach and presented designing effort of geometry are beneficial to obtain results that have the potential to address problems with less efficient thin-film solar cells.

Device modeling of non-fullerene organic solar cell by incorporating CuSCN as a hole transport layer using SCAPS

Heterojunction organic solar cells with a non-fullerene acceptor (NFA-BHJ-OSC) with inorganic hole transport layer (HTL) have drawn a lot of cognizance due to their greater efficiency compared with traditional Fullerene acceptor solar cells. The most often adopted HTL, PEDOT:PSS, degrades the device, due to the hygroscopic and acidic nature of PSS. Therefore, an alternate hole transport material is necessary to optimize the output of OSCs. A simulation on the performance of NFA-BHJ-OSC with an active layer of PBDB-T/ITIC incorporated with Copper (I) thiocyanate (CuSCN) as an HTL, is performed in the present paper using the software SCAPS 1-D. CuSCN is a p-type semiconductor having wider energy band gap in comparison to other inorganic hole transport materials. In the present simulation based work, NFA-OSC having CuSCN as the hole transport layer shows the optimized PCE of 20.36%, Fill Factor (FF) of 66.88%, JSC of 33.09 mA/cm2 and VOC of 1.0341 V by varying physical parameters such as active layer thickness, temperature, and properties of HTL and ETL. These values are promising to develop NFA-OSCs incorporating CuSCN as a HTL in the near prospect.

Optimization of accurate estimation of single diode solar photovoltaic parameters and extraction of maximum power point under different conditions

Introduction. With the snowballing requirement of renewable resources of energy, solar energy has been an area of key concern to the increasing demand for electricity. Solar photovoltaic has gotten a considerable amount of consideration from researchers in recent years. Purpose. For generating nearly realistic curves for the solar cell model it is needed to estimate unknown parameters with utmost precision. The five unknown parameters include diode-ideality factor, shunt-resistance, photon-current, diode dark saturation current, and series-resistance. Novelty. The proposed research method hybridizes flower pollination algorithm with least square method to better estimate the unknown parameters, and produce more realistic curves. Methodology. The proposed method shows many promising results that are more realistic in nature, as compared to other methods. Shunt-resistance and series-resistance are considered and diode constant is not neglected in this approach that previously has been in practice. The values of series-resistance and diode-ideality factor are found using flower pollination algorithm while shunt-resistance, diode dark saturation current and photon-current are found through least square method. Results. The combination of these techniques has achieved better results compared to other techniques. The simulation studies are carried on MATLAB/Simulink.

Parameters optimization of solar PV cell/module using genetic algorithm based on non-uniform mutation

Extracting the optimum parameters of solar photovoltaic (PV) model using the experimental data of current–voltage is very critical in simulating, controlling, and optimizing the PV systems. One of the important problems encountered in modeling and simulating is to find a model that can extract parameters from PV models quickly, accurately, and reliably. Based on this motivation, the goal of this study is to suggest an improved algorithm, namely genetic algorithm based on non-uniform mutation (GAMNU), in order to approximate efficiently the parameters of solar cells and PV modules. In GAMNU, non-uniform mutation operator is used to maintain diversity in the explored solutions and the crossover operator follows an adaptive search strategy, which consists of searching the entire space at the beginning while maintaining a focused search when the population tends to converge in a certain region of the search space. The performance of the method is comprehensively evaluated on different solar cell models, including single and double diode, and single diode PV modules, of a R.T.C France silicon solar cell, ESP-160 PPW PV, STP6-120/36 and Photowatt-PWP201 module. The results obtained from single and double diode models for R.T.C France are respectively 9.8618×10-4 and 9.8683×10-4, and for Photowatt-PWP201, STP6-120/36 and ESP-160 PPW are 2.3824×10-3 2.382420230900×10-3, 1.6735×10-21.6735786505085×10-2 and 8.2942×10-2 8.2942×10-2. The statistical obtained results show that the proposed method has very competitive performance in terms of accuracy and reliability when compared to other advanced algorithms. Therefore, the proposed algorithm is highly useful to extract the parameters of solar PV models.

Simulation and Numerical Modelling of CIGSSe-Based Solar Cells by AFORS-HET

A general equation to determine properties of penternary solar cell based on Cu (In, Ga) (Se, S) 2 (CIGSSe) with a double buffer layer ZnS/Zn0.8Mg0.2O(ZMO) were derived. Numerical analysis of a (CIGSSe) solar cell with a double buffer layer ZnS/ZMO, CdS free absorber layer, were investigated using the AFORS-HET software simulation. Taking into consideration the effect of thickness and doping concentration for the CIGSSe absorption layer, ZnS buffer layer and ZnO:B(BZO) window layer on the electron transport, short circuit current density (Jsc) and open circuit voltage (Voc); numerical simulation demonstrated that the changes in band structure characteristics occurred. The solar energy conversion efficiency is 28.34%, the filling factor is 85.59%, the open circuit voltage is 782.3 mV, the short circuit current is 42.32 mA. then we take the range of the gradient between the ratio of x and y for the absorption layer, and the best result of Voc, Jsc, FF, Eff equal (838.7 mV, 40.94 mA/cm2, 86.23%, 29.61%) respectively at x= 0, y= 0.26.

Performance Predictions Accuracy of a Smart Sun Tracking System for Photovoltaic Applications

Despite technological innovations, solar energy efficiency is still low nowadays. It thus needs to be optimized. To improve solar photovoltaic (PV) modules efficiency, several methods have been designed and implemented. Such methods are the Maximum Power Point Tracking (MPPT) and Solar Tracking (ST). In this decade, the solar tracking method is facing a great challenge: the minimization of the electrical energy consumption of electromechanical systems used to track the sun’s position. Manufacturers must be able to predict the net electrical power output obtained from a tracking PV panel to save energy and time. The purpose of the present work is to simulate the performance of a smart solar tracker and assess the accuracy of predictions. To achieve this objective, the one diode model of solar PV cell has been used. In an innovative approach, the one diode model has been simulated using experimental data of temperature and global solar irradiance which are easily available on the internet. The accuracy of predicted values was analysed using reliable statistical indicators such as the Mean Absolute Error (MAE), the Root Mean Square Error (RMSE), the Coefficient of determination (R-square) and the Pearson Coefficient of Correlation (PCC). Simulation results of the power output of the tracking PV panel is better than the one of the fixed panel with 0.25, 0.32, 0.66, and 0.81 respectively for the MAE, the RMSE, the R-square and the PCC. These results show that predictions are in good agreement with experimental measures.

Parameter extraction of solarPVcell models using novel metaheuristic chaotic tunicate swarm algorithm

The photovoltaic(PV) system's efficiency can be improved with the aid of effective solar PV cell modeling. However, flawed solar cell parameters affect PV cell modeling incorrectly. The manufacturers are usually not providing all the necessary data for the exact modeling of PV cells. It is therefore necessary to efficiently predict the parameters of the PV cell. The literature discusses various optimization algorithms, but the suboptimal outcomes are obtained by most of the algorithms due to their convergence toward local minima. This paper introduces a new stochastic optimization algorithm for the estimation of solar PV cell parameters. Therefore, for the evaluation of the solar cell, a new novel chaotic algorithm is introduced in this paper called the chaotic tunicate swarm algorithm (CTSA). The proposed algorithm has a new function called an outstanding mathematical model of adaptive weights to stimulate negative and positive inputs from the spreading wave in order to find the best way to connect food with an excellent exploitation tendency and exploratory ability. For the double-diode model, the computation time of the chaotic variants (CTSA1-1.1885, CTSA2-1.2502, CTSA3-1.2962, CTSA4-1.1204, and CTSA5-1.2214) is better than the rest of the compared algorithms (particle swarm optimization [PSO]-17.4532, tunicate swarm algorithm (TSA)-2.5278, Harris hawks optimization [HHO]-10.8942, ant lion optimizer [ALO]-15.0214, and atom search optimization [ASO]-9.5214). For the triple-diode model, the computation time of the chaotic variants (CTSA1-1.2658, CTSA2-1.3520, CTSA3-1.3056, CTSA4-1.2290, and CTSA5-1.3859) is better than the rest of the compared algorithms (PSO-18.5421, TSA-3.2568, HHO-9.8754, ALO-13.5841, and ASO-11.8412). The superiority of proposed algorithm is established using ranking test, statistical error analysis, and sensitivity temperature variation.