scholarly journals An Improved Artificial Jellyfish Search Optimizer for Parameter Identification of Photovoltaic Models

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1867
Author(s):  
Mohamed Abdel-Basset ◽  
Reda Mohamed ◽  
Ripon K. Chakrabortty ◽  
Michael J. Ryan ◽  
Attia El-Fergany
Keyword(s):  
Thin Film ◽  
Solar Cells ◽  
Convergence Rate ◽  
Numerical Simulations ◽  
Solar Pv ◽  
Unknown Parameters ◽  
Pv Systems ◽  
Operation Conditions ◽  
Pv Modules ◽  
Parameter Values

The optimization of photovoltaic (PV) systems relies on the development of an accurate model of the parameter values for the solar/PV generating units. This work proposes a modified artificial jellyfish search optimizer (MJSO) with a novel premature convergence strategy (PCS) to define effectively the unknown parameters of PV systems. The PCS works on preserving the diversity among the members of the population while accelerating the convergence toward the best solution based on two motions: (i) moving the current solution between two particles selected randomly from the population, and (ii) searching for better solutions between the best-so-far one and a random one from the population. To confirm its efficacy, the proposed method is validated on three different PV technologies and is being compared with some of the latest competitive computational frameworks. The numerical simulations and results confirm the dominance of the proposed algorithm in terms of the accuracy of the final results and convergence rate. In addition, to assess the performance of the proposed approach under different operation conditions for the solar cells, two additional PV modules (multi-crystalline and thin-film) are investigated, and the demonstrated scenarios highlight the utility of the proposed MJSO-based methodology.

scholarly journals Phototransistor Behavior in CIGS Solar Cells and the Effect of the Back Contact Barrier

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4753
Author(s):  
Ricardo Vidal Lorbada ◽  
Thomas Walter ◽  
David Fuertes Marrón ◽  
Dennis Muecke ◽  
Tetiana Lavrenko ◽  
...  
Keyword(s):  
Thin Film ◽  
Solar Cells ◽  
Numerical Simulations ◽  
Forward Bias ◽  
Thin Film Solar Cells ◽  
Normal Operation ◽  
Back Contact ◽  
Operation Conditions ◽  
Contact Barrier ◽  
The Impact

In this paper, the impact of the back contact barrier on the performance of Cu (In, Ga) Se2 solar cells is addressed. This effect is clearly visible at lower temperatures, but it also influences the fundamental parameters of a solar cell, such as open-circuit voltage, fill factor and the efficiency at normal operation conditions. A phototransistor model was proposed in previous works and could satisfactorily explain specific effects associated with the back contact barrier, such as the dependence of the saturated current in the forward bias on the illumination level. The effect of this contribution is also studied in this research in the context of metastable parameter drift, typical for Cu (In, Ga) Se2 thin-film solar cells, as a consequence of different bias or light soaking treatments under high-temperature conditions. The impact of the back contact barrier on Cu (In, Ga) Se2 thin-film solar cells is analyzed based on experimental measurements as well as numerical simulations with Technology Computer-Aided Design (TCAD). A barrier-lowering model for the molybdenum/Cu (In, Ga) Se2 Schottky interface was proposed to reach a better agreement between the simulations and the experimental results. Thus, in this work, the phototransistor behavior is discussed further in the context of metastabilities supported by numerical simulations.

scholarly journals A Simple Mismatch Mitigating Partial Power Processing Converter for Solar PV Modules

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2308
Author(s):  
Kamran Ali Khan Niazi ◽  
Yongheng Yang ◽  
Tamas Kerekes ◽  
Dezso Sera
Keyword(s):  
Experimental Tests ◽  
Energy Yield ◽  
Power Electronic ◽  
Solar Pv ◽  
Partial Shading ◽  
Loss Analysis ◽  
Pv Systems ◽  
Pv Module ◽  
Pv Modules ◽  
In Series

Partial shading affects the energy harvested from photovoltaic (PV) modules, leading to a mismatch in PV systems and causing energy losses. For this purpose, differential power processing (DPP) converters are the emerging power electronic-based topologies used to address the mismatch issues. Normally, PV modules are connected in series and DPP converters are used to extract the power from these PV modules by only processing the fraction of power called mismatched power. In this work, a switched-capacitor-inductor (SCL)-based DPP converter is presented, which mitigates the non-ideal conditions in solar PV systems. A proposed SCL-based DPP technique utilizes a simple control strategy to extract the maximum power from the partially shaded PV modules by only processing a fraction of the power. Furthermore, an operational principle and loss analysis for the proposed converter is presented. The proposed topology is examined and compared with the traditional bypass diode technique through simulations and experimental tests. The efficiency of the proposed DPP is validated by the experiment and simulation. The results demonstrate the performance in terms of higher energy yield without bypassing the low-producing PV module by using a simple control. The results indicate that achieved efficiency is higher than 98% under severe mismatch (higher than 50%).

A Six Parameter Single Diode Model for Photovoltaic Modules

2020 ◽  
Vol 143 (1) ◽  
Author(s):  
Mete Nacar ◽  
Emre Özer ◽  
Aysel Ersoy Yılmaz
Keyword(s):  
Environmental Conditions ◽  
Optimization Problem ◽  
Equivalent Circuit Model ◽  
Electrical Circuit ◽  
Current Data ◽  
Metaheuristic Algorithms ◽  
Unknown Parameters ◽  
Pv Systems ◽  
Proposed Model ◽  
Pv Modules

Abstract The modeling of photovoltaic (PV) systems is substantial for the estimation of energy production and efficiency analysis in the PV systems under the changing environmental conditions. A PV model mathematically expresses the electrical characteristic of the PV modules according to temperature and irradiance. The most popular electrical circuit models are the single-diode model (SDM) and the double-diode model (DDM). Considering accuracy and complexity, SDM was used in this paper. In the equivalent circuit model used to estimate the electrical behavior of the PV modules, the parameter estimating has become an optimization problem. In recent studies, it is seen that metaheuristic algorithms are often employed in solving this optimization problem. In this paper, a new six-parameter PV model is proposed to improve the accuracy of the five-parameter SDM, taking into account the temperature dependence of the series resistance. Particle swarm optimization (PSO) and a couple of metaheuristic algorithms have been executed to estimate six unknown parameters of the proposed model under standard test conditions (STC: 25 °C, 1000 W/m2, AM1.5) using current–voltage (I–V) data of PV module. In order to evaluate the performance of the proposed method under the changing environmental conditions, it was compared with the three methods commonly used in the literature. Accuracy of the proposed model has been indicated by the root mean square error (RMSE) within the range of current data and the model current values. Simulation results demonstrate that the proposed model can predict the I–V curve for the PV modules with high accuracy.

Passive Thermal Management of Photovoltaic Modules—Mathematical Modeling and Simulation of Photovoltaic Modules

2017 ◽  
Vol 139 (6) ◽  
Author(s):  
Abdelhakim Hassabou ◽  
Ahmed Abotaleb ◽  
Amir Abdallah
Keyword(s):  
Mathematical Modeling ◽  
Thermal Management ◽  
Phase Change Materials ◽  
Thick Layer ◽  
Vapor Condensation ◽  
Solar Pv ◽  
Photovoltaic Modules ◽  
Pv Systems ◽  
Pv Modules ◽  
Testing Condition

Operation of solar photovoltaic (PV) systems under high temperatures and high humidity represents one of the major challenges to guarantee higher system’s performance and reliability. The PV conversion efficiency degrades considerably at higher temperatures, while dust accumulation on PV module together with atmospheric water vapor condensation may cause a thick layer of mud that is difficult to be removed. Therefore, thermal management in hot climates is crucial for reliable application of PV systems to prevent the efficiency to drop due to temperature rise. This research focuses on the utilization of phase-change materials (PCM) for passive thermal management of solar systems. The main focus is to explore the effect of utilization of PCM-based cooling elements on the thermal behavior of solar PV modules. This paper presents the mathematical modeling and validation of PV modules. Both simulation and experimental data showed that the significant increase in PV peak temperature in summer affects the module’s efficiency, and consequently produced power, by 3% compared to standard testing condition (STC) as an average over the entire day, while it goes up to 8% and 10% during peak noon hours in winter and summer, respectively.

scholarly journals Study of a New Hybrid Optimization-Based Method for Obtaining Parameter Values of Solar Cells

2020 ◽  
Author(s):  
Selma Tchoketch_Kebir
Keyword(s):  
Solar Cells ◽  
Hybrid Method ◽  
Traditional Method ◽  
Hybrid Methods ◽  
Optimization Method ◽  
Parameter Determination ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Unknown Parameters ◽  
Parameter Values

This chapter presents a comprehensive study of a new hybrid method developed for obtaining the electrical unknown parameters of solar cells. The combination of a traditional method and a recent smart swarm-based optimization method is done, with a big focus on the application of the topic of artificial intelligence algorithms into solar photovoltaic production. The combined approach was done between the traditional method, which is the noniterative Levenberg-Marquardt technic and between the recent meta-heuristic optimization technic, called Grey Wolf optimizer algorithm. For comparison purposes, some other classical solar cell parameter determination optimization-based methods are carried out, such as the numerical (iterative, noniterative) methods, the meta-heuristics (evolution, human, physic, and swarm) methods, and other hybrid methods. The final obtained results show that the used hybrid method outperforms the above-mentioned classical methods, under this study.

scholarly journals Design and Fabrication of Low Cost Automatic Cleaning Module for Solar PV Systems

2019 ◽  
Vol 9 (2S2) ◽  
pp. 1112-1114
Keyword(s):  
Automatic System ◽  
Low Cost ◽  
The Sun ◽  
Solar Pv ◽  
Servo Motor ◽  
Pv Systems ◽  
Pv Module ◽  
Cleaning System ◽  
Pv Modules ◽  
Long Time

The Solar PV modules are usually engaged in dusty environments which are the condition in many tropical countries like India. The dirt gets hoarded on the superficial of the PV module and chunks the photons from the sun. It decreases the generation ability of the PV module. The power output decreases the efficiency, if the PV module is not cleaned for a long time. In order to habitually clean the dust, an automatic cleaning system has been proposed, which senses the light energy from the sun on the solar panel and also cleans the PV module automatically. This system is realized with PIC16F877A microcontroller which controls the geared servo motor. This system consists of a sensor (LDR) to make it dusk to dawn. While for cleaning the PV modules, a mechanism consists of a sliding wipers has been developed. In earlier machinery, cleaning of PV panels was done manually. But here the PV panels has been cleaned by automatic system i.e. wiping mechanism with water flow for effective cleaning

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