scholarly journals Development of an Improved Bonobo Optimizer and Its Application for Solar Cell Parameter Estimation

2021 ◽  
Vol 13 (7) ◽  
pp. 3863
Author(s):  
Reem Y. Abdelghany ◽  
Salah Kamel ◽  
Hamdy M. Sultan ◽  
Ahmed Khorasy ◽  
Salah K. Elsayed ◽  
...  
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
Power Plants ◽  
New Technologies ◽  
Cell Model ◽  
Search Space ◽  
Cosine Function ◽  
Unknown Parameters ◽  
Lévy Flights ◽  
Levy Flights

Recently, photovoltaic (PV) energy has been considered one of the most exciting new technologies in the energy sector. PV power plants receive considerable attention because of their wide applications. Consequently, it is important to study the parameters of the solar cell model to control and determine the characteristics of the PV systems. In this study, an improved bonobo optimizer (IBO) was proposed to improve the performance of the conventional bonobo optimizer (BO). Both the IBO and the BO were utilized to obtain the accurate values of the unknown parameters of different mathematical models of solar cells. The proposed IBO improved the performance of the conventional BO by enhancing the exploitation (local search) and exploration (global search) phases to find the best optimal solution, where the search space was reduced using Levy flights and the sine–cosine function. Levy flights enhance the explorative phase, whereas the sine–cosine function improves the exploitation phase. Both the proposed IBO and the conventional BO were applied on single, double, and triple diode models of solar cells. To check the effectiveness of the proposed algorithm, statistical analysis based on the results of 20 runs of the optimization program was performed. The results obtained by the proposed IBO were compared with other algorithms, and all results of the proposed algorithm showed their durability and exceeded other algorithms.

scholarly journals Transmission of Sound via a Perovskite Solar Cell

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
Cell Model ◽  
Perovskite Solar Cells ◽  
Perovskite Solar Cell ◽  
Lead Free ◽  
Metal Contact ◽  
Simple Process ◽  
Short Span ◽  
System Prototype

T Perovskite solar cells are becoming a dominant alternative for the traditional solar cells reaching an efficiency of 25.2% in a short span of twelve years (2008-2020). Here, we are going to describe a simple process to 'put a voice on a laser beam' and transmit it over a distance via a perovskite solar cell. This process considered as a fascinating example of amplitude modulation of light using sound vibrations. Therefore, the design and simulation of the perovskite solar cell will be described in details in this work. This design is concerned about the lead-free based perovskite solar cell model with the total proposed structure “Metal contact /PEDOT:PSS/ CH3NH3SnI3/ ZnO/ SnO2:F/ Metal contact”. To study the efficiency and the performances of a solar cell, the use of well-known software so-called SCAPS-1D is undertaken to perform the system simulation. The obtained results show also the influence of the doping level of the HTM layer and absorber layer thickness on the performance of the device. So far, only the simulation part has been validated. Despite the costeffect of the system prototype, however, it could be implemented here in the laboratory as perspective work.

Enhancement of solar cell using two nanoparticles (Ag–Au)

2019 ◽  
Vol 33 (24) ◽  
pp. 1950289 ◽  
Author(s):  
Khoulud Kh. AbuShaar ◽  
Mohammed M. Shabat ◽  
Dena M. El-Amassi ◽  
Daniel M. Schaadt
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
Cell Model ◽  
Cell Structure ◽  
Incident Light ◽  
Physical Parameters ◽  
Structure Model ◽  
Metallic Nanoparticle ◽  
Solar Cell Structure ◽  
The Matrix

In this paper, photovoltaics (PV)- or solar cells based on two types of nanoparticles have been investigated. The suggested four-layer solar cell model consists of metallic nanoparticle (Ag–Au) layers that are Si-based and covered by SiN. The transmission and reflection of the incident light on the structure model have been computed for different physical parameters of the structure. Higher transmission and lower reflections have been obtained leading to higher efficiency of the solar cells. The matrix model is used, and the numerical results obtained by MAPLE Software Program. The obtained results confirm that the nanoparticle solar cell structure can effectively enhance the efficiency of such structure model.

scholarly journals TCAD 2D numerical simulations for increasing efficiency of AlGaAs – GaAs Solar Cells

2018 ◽  
Vol 14 (2) ◽  
pp. 96-107
Author(s):  
César Palacios A. ◽  
Noemi Guerra ◽  
Marco Guevara ◽  
María José López
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
Numerical Simulations ◽  
Initial Conditions ◽  
Cell Model ◽  
Tandem Solar Cell ◽  
Group Iii ◽  
Group Iii V Compounds ◽  
Simulation Parameters ◽  
Lower Contact

The performance of solar cells has improved quickly in recent years, the latest research focuses on thin cells, multijunction cells, solar cells of the group III-V compounds, Tandem cells, etc. In the present work, numerical simulations are developed, using SENTAURUS TCAD as a tool, in order to obtain a solar cell model based on Galium Arsenide (GaAs). This solar cell corresponds to the so-called "Thin Films" due to the fact that can make layers thinner than we would have if we work with conventional semiconductors, such as; Silicon or Germanium; thus opening the possibility of placing the cell as a top layer within a tandem solar cell configuration with compounds of group III-V. That is why two types of simulations are performed with respect to the contact of the rear contact; one corresponds to the cell with a lower contact equal to the length of the cell and the other with a small contact of 5 μm. In addition, the cell undergoes an optimization process by modifying the geometry and doping of the layers that comprise it, in order to improve its performance. To achieve this objective, the initial conditions and the appropriate simulation parameters must be determined, which have been selected and corroborated with the literature, allowing us to arrive at coherent results and optimal models of solar cell design through numerical simulations.

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

2021 ◽  
Vol 11 (24) ◽  
pp. 11929
Author(s):  
Amer Malki ◽  
Abdallah A. Mohamed ◽  
Yasser I. Rashwan ◽  
Ragab A. El-Sehiemy ◽  
Mostafa A. Elhosseini
Keyword(s):  
Solar Cell ◽  
Cell Model ◽  
Optimization Algorithms ◽  
Metaheuristic Algorithms ◽  
Local Optimum ◽  
Cell Models ◽  
Unknown Parameters ◽  
Solar Module ◽  
Cell Parameters ◽  
Pv Cell

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.

Improving Cuckoo Search Algorithm With Mittag-Leffler Distribution

2019 ◽  
Author(s):  
Jiamin Wei ◽  
YangQuan Chen ◽  
Yongguang Yu ◽  
Yuquan Chen
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Search Space ◽  
Cuckoo Search Algorithm ◽  
Lévy Flights ◽  
Lévy Distribution ◽  
Levy Flights ◽  
Levy Distribution ◽  
Heavy Tailed ◽  
The Impact

Abstract Cuckoo search (CS), as one of the recent nature-inspired metaheuristic algorithms, has proved to be an efficient approach due to the combination of Lévy flights, local search capabilities and guaranteed global convergence. CS uses Lévy flights in global random walk to explore the search space. The Lévy step is taken from the Lévy distribution which is a heavy-tailed probability distribution. In this case, a fraction of large steps are generated, which plays an important role in enhancing search capability of CS. Besides, although many foragers and wandering animals have been shown to follow a Lévy distribution of steps, investigation into the impact of other different heavy-tailed probability distributions on CS is still insufficient up to now. Based on the above considerations, we are motivated to apply the well-known Mittag-Leffler distribution to the standard CS algorithm, and proposed an improved cuckoo search algorithm (CSML) in this paper, where a more efficient search is supposed to take place in the search space thanks to the long jumps. In order to verify the performance of CSML, experiments are carried out on a test suite of 20 benchmark functions. In terms of the observations and results analysis, CSML can be regarded as a new potentially promising algorithm for solving optimization problems.

scholarly journals Diagnostics of Solar Cells

2019 ◽  
Vol 302 ◽  
pp. 01013
Author(s):  
Valeriy Martynyuk ◽  
Juliy Boiko ◽  
Marcin Łukasiewicz ◽  
Ewa Kuliś ◽  
Janusz Musiał
Keyword(s):  
Mathematical Model ◽  
Solar Cells ◽  
Solar Cell ◽  
Series Resistance ◽  
Cell Model ◽  
Methodological Approach ◽  
Technical Condition ◽  
Impedance Model ◽  
Voltage Ratio ◽  
The Mathematical Model

The paper represents the mathematical model for diagnostics of solar cell. The research objectives are the problem of determining a solar cell technical condition during its operation. The solar cell diagnostics is based on the mathematical model of solar cells. The single-diode solar cell model is characterized by a slight deviation of the theoretically calculated characteristics from the characteristics of the real solar cell, one of the reasons being the complexity of the accurate measurement of the series resistance. The single-diode solar cell model uses the current and voltage ratio in the form of an implicit function and it cannot be solved directly. For its solution it is necessary to use numerical methods. This is main disadvantage of the single-diode solar cell model. The methodological approach to increasing the reliability of the solar cell diagnostic has been proposed, in terms of multi-parameter the solar cell diagnostic by applying the solar cell impedance model.

A two subcell equivalent solar cell model for III–V triple junction solar cells under spectrum and temperature variations

Solar Energy ◽  
2013 ◽  
Vol 92 ◽  
pp. 221-229 ◽  
Author(s):  
Eduardo F. Fernández ◽  
Gerald Siefer ◽  
F. Almonacid ◽  
A.J. García Loureiro ◽  
P. Pérez-Higueras
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
Triple Junction ◽  
Cell Model ◽  
Temperature Variations

scholarly journals Probabilistic screening and behavior of solar cells under Gaussian parametric uncertainty using polynomial chaos representation model

2021 ◽  
Author(s):  
Akshit Samadhiya ◽  
Kumari Namrata
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
Polynomial Chaos ◽  
Cell Model ◽  
Probabilistic Approach ◽  
Parametric Uncertainty ◽  
Polynomial Chaos Expansion ◽  
Chaos Expansion ◽  
Model Response ◽  
Probabilistic Response

AbstractThe paper presents a hierarchical polynomial chaos expansion-based probabilistic approach to analyze the single diode solar cell model under Gaussian parametric uncertainty. It is important to analyze single diode solar cell model response under random events or factors due to uncertainty propagation. The optimal values of five electrical parameters associated with the single diode model are estimated using six deterministic optimization techniques through the root-mean-square minimization approach. Values corresponding to the best objective function response are further utilized to describe the probabilistic design space of each random electrical parameter under uncertainty. Adequate samples of each parameter corresponding Gaussian uncertain distribution are generated using Latin hypercube sampling. Furthermore, a multistage probabilistic approach is adopted to evaluate the model response using low-cost polynomial chaos series expansion and perform global sensitivity analysis under specified Gaussian distribution. Coefficients of polynomial basis functions are calculated using least square and least angle regression techniques. Unlike the highly non-linear and complex single diode representation of solar cells, the polynomial chaos expansion model provides a low computational burden and reduced complexity. To ensure reproducibility, probabilistic output response computed using proposed polynomial chaos expansion model is compared with the true model response. Finally, a multidimensional sensitivity analysis is performed through Sobol decomposition of polynomial chaos series representation to quantify the contribution of each parameter to the variance of the probabilistic response. The validation and assessment result shows that the output probabilistic response of the solar cell under Gaussian parametric uncertainty correlates to a Rayleigh probability distribution function. Output response is characterized by a mean value of 0.0060 and 0.0760 for RTC France and Solarex MSX83 solar cells, respectively. The standard deviation of $$ \pm $$ ± 0.0034 and $$ \pm $$ ± 0.0052 was observed in the probabilistic response for RTC France and Solarex MSX83 solar cells, respectively.

Design of Thin Film Solar Cell Material Structures for Reliability and Performance Robustness

2013 ◽  
Author(s):  
Nita Yodo ◽  
Pingfeng Wang
Keyword(s):  
Thin Film ◽  
Solar Cells ◽  
Solar Cell ◽  
Cell Model ◽  
Low Cost ◽  
Operating Conditions ◽  
Robust Design Optimization ◽  
And Performance ◽  
Solar Powered ◽  
Performance Robustness

An exponential growth of photovoltaic (PV) technologies in the past decade has paved a path to a sustainable solar-powered world. The development of alternative PV technologies with low-cost and high-stability materials has attracted a growing amount of attention. One of these alternatives is the use of second generation thin film PV technologies. However, even in the presence of their bandgap properties, a major issue faced by most thin film solar cells is the low output efficiency due to manufacturing variability and uncertain operating conditions. Thus, to ensure the reliability and performance robustness of the thin film PV technologies, the design of the solar cell is studied. To represent the thin film PV technologies, a copper gallium (di)selenide (CIGS) solar cell model is developed and optimized with Reliability-based Robust Design Optimization (RBRDO) method. This model takes into account the variability of the structure and the material properties of the CIGS solar cells, and assumes an ideal-weather operating condition. This study presents a general methodology to optimize the design of the CIGS PV technologies and could be used to facilitate the development and assessment of new PV technologies with more robust performance in efficiency and stability.

scholarly journals The Design and Optimization of GaAs Single Solar Cells Using the Genetic Algorithm and Silvaco ATLAS

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Kamal Attari ◽  
Lahcen Amhaimar ◽  
Ali El yaakoubi ◽  
Adel Asselman ◽  
Mounir Bassou
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
Quantum Efficiency ◽  
Conversion Efficiency ◽  
Cell Model ◽  
Search Algorithm ◽  
Internal Quantum Efficiency ◽  
The Other ◽  
Genetic Search ◽  
Single Junction

Single-junction solar cells are the most available in the market and the most simple in terms of the realization and fabrication comparing to the other solar devices. However, these single-junction solar cells need more development and optimization for higher conversion efficiency. In addition to the doping densities and compromises between different layers and their best thickness value, the choice of the materials is also an important factor on improving the efficiency. In this paper, an efficient single-junction solar cell model of GaAs is presented and optimized. In the first step, an initial model was simulated and then the results were processed by an algorithm code. In this work, the proposed optimization method is a genetic search algorithm implemented in Matlab receiving ATLAS data to generate an optimum output power solar cell. Other performance parameters such as photogeneration rates, external quantum efficiency (EQE), and internal quantum efficiency (EQI) are also obtained. The simulation shows that the proposed method provides significant conversion efficiency improvement of 29.7% under AM1.5G illumination. The other results were Jsc = 34.79 mA/cm2, Voc = 1 V, and fill factor (FF) = 85%.

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