Diode Saturation Current Research Articles

Solar Power Prediction Modeling Based on Artificial Neural Networks under Partial Shading

Photovoltaic systems are emerging as an important device to address the environmental pollution generated from conventional energy production. The objectives of this study are to accurately predict the power of photovoltaic systems under partial shading conditions and to model high-efficiency photovoltaic systems. First, the power loss under partial shading conditions was addressed using a bypass diode. In previous studies, for the power prediction, one or two parameters were trained through artificial neural networks. In this study, we employ five main parameters to improve the accuracy: the photo-current (Iph), diode saturation current (I0 ), diode idealization factor (n), series resistance (Rs), and shunt resistance (Rsh). Compared to the results of previous studies, the proposed model yielded consistent results. As a result, more accurate power predictions are possible with variations in temperature and irradiation.

Innovative approaches to extract double-diode model physical parameters of a PV module serving outdoors under real-world conditions

This paper presents innovative techniques for modeling and simulating photovoltaic (PV) solar modules. The major objective is to determine the seven parameters of Double-Diode Model (DDM) for PV modules serving indoors under standard test conditions (STC), non-STC conditions, or outdoors under real-world conditions. The first method employs a precise iterative technique utilizing numerical variation of two diode ideality factors on a newly derived transcendental equation relating series resistance to ideality factors and PV measurements to find values of series resistance, parallel conductance, photocurrent and two diode saturation currents at STC. The second method utilizes a system of non-linear equations corresponding to key-points of current–voltage (I-V) curve and numerical values of seven parameters at STC to determine time dependent values of DDM physical parameters throughout an arbitrary day under real-world conditions. The third is a predictive approach based on analytical formulas portraying effects of solar irradiance and temperature on DDM physical parameters for PV modules installed at any location and serving during an arbitrary day. The proposed techniques are validated with actual data of four PV modules of polycrystalline silicon (poly-Si) and monocrystalline silicon (mono-Si) technologies from National Renewable Energy Laboratory (NREL) database. Absolute Error (AE) values for DDM parameter extraction method at STC do not exceed 5 μA. Normalized Root Mean Square Error (NRMSE) ceiling value is equal to 3 % for both numerical approach of extraction and analytical approach of prediction under real-word conditions. The results demonstrate the reliability of extracted DDM physical parameters and their compatibility with experimental I-V data, lending credibility to these methods for analyzing and optimizing PV systems.

Thermal effect on curved photovoltaic panels: Model validation and application in the Tabuk region.

This paper aimed to investigate the temperature effect on photovoltaic (PV) cell parameters. The PV cell parameters such as series and parallel resistances, diode ideality factor, and diode saturation current, are not considered in the reported stepwise modeling. The present work aims to improve available models used in the modeling and simulation of PV modules to support the researcher and power project developer. All the required temperature-dependent parameters are determined to model the simulated PV module with high accuracy using Simulink/MATLAB software. To validate the method, a 36-cell-50W solar panel with different radii of curvature is set up to assess solar power outputs under varying irradiance and temperature conditions. For the present application, the Tabuk region (Saudi Arabia) is chosen based on its location and climatic conditions. The method provided conformity to the measured power outputs for varying Global Horizontal Irradiance (GHI) and temperature conditions. The maximum power output of the PV module increases from 14.4 W to 25.8 W when the received solar power density varies from 307 W/m2 to 526 W/m2 depending on the level of curvature starting from a semi-cylindrical shape to a vaulted shape to a flat shape. The curved PV module shows slightly higher power variation with temperature as compared to the flat one. Above 25°C, the power output is about 20% less at a maximum temperature of 65°C. When the temperature drops below 25°C, the power outputs increase about 6% and 11.5% for corresponding temperatures of 15°C and 5°C, respectively.

A Critical Review on the Estimation Techniques of the Solar PV Cell’s Unknown Parameters

To meet the exponentially growing demand for clean and green energy, the solar photovoltaic (PV) system’s importance is increasing day by day, for which PV modeling is considered to be one of the most important work in the current state-of-the-art methods. To effectively model a PV system, accurate PV parameter estimation is of the utmost importance. In line with this, although the values of some of the parameters are provided in the manufacturer’s datasheet, the values of unknown parameters, such as shunt resistance, series resistance, the diode ideality factor, photo-generated current and diode saturation current, are not provided. To estimate these values a lot of algorithms are already reported in the literature. After careful observation of all the reported algorithms, a few best-reported algorithms are identified and their performances are compared with respect to accuracy, convergence issues, computational complexity and thermal stability. All kind of algorithms, such as numerical, analytical and evolutionary algorithms, are considered in this study, and only the best reported algorithms are considered for the comparison.

An accurate parameter estimation approach to modeling of solar photovoltaic module using hybrid grey wolf optimization

AbstractThis paper proposes a hybrid method for an accurate parameter estimation of the solar photovoltaic (PV) module. The proposed method combines the features of analytical as well as the optimization technique to ensure the speed and accuracy in computation. Two‐diode model consist of seven unknown parameters namely the photocurrent (), reverse saturation current of diode and ( and ), series resistance (), shunt resistance (), diode ideality factor for diode and ( and ). First five parameters are analytically determined with the help of area under the curve, while the remaining two are optimally calculated by using the Grey Wolf Optimization technique. The results obtained by simulation are verified with the experimental data of different PV module and the error is calculated. The superiority of the proposed estimation approach is compared with the recent literature and the results are presented. The proposed model is very useful for the solar PV module designers and simulators to realize its physical characteristics.

A simple method for accurate modeling of diode parameters

Reverse saturation current of diodes is a very small value which cannot be measured with normal measurement devices. In this paper, a simple method to measure the reverse saturation current of diodes is proposed. Then the emission coefficient is calculated with the aid of forward biased region of I-V characteristics. The model extracted with the aid of proposed method shows good agreement with the I-V characteristics of device under test in laboratory experiments.

Estimation of the parameters of the mathematical model of an equivalent diode of a photovoltaic panel using a continuous genetic algorithm

This document presents the implementation of a con- tinuous population genetic optimization algorithm (CGA) as a solution method to the parameter estimation problem of a diode model (SDM) of a photovoltaic panel (PV) from experimental data of voltage versus current (V-I). The parameters to be estimated by means of the CGA are: the photoinduced current, the diode saturation current, the ideality factor, the series resistance and the parallel resistance. The estimation of the SDM parameters is carried out in order to obtain the real values that represent the power profile of the panel and thus carry out an analysis of its physical state. For which, the mean square error of the PV current estimated by the solution method from the selected parameters is used as the objective function, with the real curve of the PV panel used as the test scenario. All of the above subject to the set of restrictions that limits the problem under analysis. To validate the effectiveness and robustness of the proposed method, in this document two comparison methods have been used: the particle swarm optimization method (PSO) and a traditional genetic algorithm (GAT). In addition, four different panel types were used to generate the test scenarios: the MSX60, the SOLAR SJ65, the KYOCERA KC200GT, and the STP245S. All simulations were obtained using MATLAB 2019b. The results obtained in this document show that the proposed method presents the best relationship between the estimation of parameters and the computation time required to solve the SDM problem.

Estimation for Model Parameters and Maximum Power Points of Photovoltaic Modules Using Stochastic Fractal Search Algorithms

The performance of a photovoltaic (PV) power generation system could be improved through the optimal control and operation of a PV module which is one of the fundamental components of this system. Thus, an appropriate PV module model along with precise knowledge of its parameters is necessary. This paper proposes a novel technique to estimate the source current, the saturation current of diodes, the shunt resistance, the series resistance, the ideality coefficient of diodes and the maximum power points (MPPs) of PV modules at the same time. This estimation problem can be described by the minimization of the root mean squared error (RMSE) of the powers obtained from the PV module through estimation and experiment. The improved stochastic fractal search (ISFS) algorithm is proposed to solve this minimization with two modifications. The first replaces the logarithmic function with the exponential function in the standard deviation of the diffusion technique to improve the exploration ability efficiently in the search space. The second utilizes the sine map instead of the uniform distribution in both the diffusion and update techniques for improving the performance of the ISFS algorithm. Numerical results demonstrate the remarkable ability of the ISFS algorithm in obtaining both the model parameters and MPPs of the PV module with high accuracy. The comparison shows that the ISFS algorithm outperforms other meta-heuristic algorithms such as a stochastic fractal search (SFS) algorithm, a particle swarm optimization (PSO) algorithm, and an improved particle swarm optimization (IPSO) algorithm in the proposed parameter estimation application.

Improving the efficiency of industrial samples of silicon solar elements

Possibilities of increasing the efficiency by more than 20 % for silicon photoelectric converters made in China have been investigated. It has been established by the method of computer simulation that the life-times of nonequilibrium charge carriers, which are 520 μs, realized in such photoelectric converters, do not limit the possibility of increasing their efficiency by more than 20 %. It is shown that an increase in the photocurrent density to 43.1 mA/cm2 leads to an increase in efficiency to 20.1 %, and a decrease in the diode saturation current density to 3.1∙10-14 A/cm2 leads to an increase in efficiency to 20.4 %. Simultaneous change of these diode characteristics leads to an increase in efficiency to 23.1 %. The paper proposes physical and technological approaches to increase the photocurrent density and reduce the diode saturation current density in ready-made photovoltaic converters. The study of the influence of operating temperature on the efficiency of crystalline silicon photoelectric converters is carried out in the article. It is shown that with increasing operating temperature the relative decrease in the efficiency of single-crystal devices is –0.7 relative %/C, which is significantly higher than in the instrument structures of European production and due to non-traditional decrease in short-circuit current density. Mathematical modeling of the influence of light-emitting diode characteristics on the efficiency of crystalline silicon solar cells showed that the decrease in the efficiency of instrument structures with increasing operating temperature is due not only to an increase in diode saturation current density from 10-13 A to 3·10-13 A, which is 300 %, but also by reducing the shunt resistance from 2.5 kOhm to 1.5 kOhm. A study of the effect of operating temperature on the diode saturation current showed that the height of the potential barrier in the studied silicon photovoltaic converters is 0.87 eV, due to the insufficient level of doping of the base material. The limited height of the potential barrier leads to an unconventional decrease in the shunt resistance with increasing operating temperature.

The Effects of Optical Power of Semiconductor Laser on the Characteristics of Si-diode in an Exposed Device

In this paper, we experimentally studied the effects of optical power of semiconductor laser on the electrical properties of silicon diode of an exposed device. The experimental results showed that the laser diode light of different optical powers (2, 3, and 4 mW) had effects on the silicon diode that are somewhat similar to those of thermal treatment. A shift in the current-voltage curve to the left side was also noticed, which led to a non-linear decrease of the barrier voltage of the diode by the effect of laser light. We also reveal a decrease by 344.8 nA/mW in the reverse saturation current of the silicon diode as a result of exposure to laser light. The forward resistance of the silicon diode decreased with increased incident optical power. The value of the maximum current of diode increased by 0.5 A/W with increasing the optical power incident on the diode.

Accurate modeling and simulation of solar photovoltaic panels with simulink-MATLAB

A unique procedure to model and simulate a 36-cell-50 W solar panel using analytical methods has been developed. The generalized expression of solar cell equivalent circuit was validated and implemented, making no influential assumptions, under Simulink/MATLAB R2020a environment. The approach is based on extracting all the needed parameters by exploiting the available parameters from the data sheets of commercial PV panels and by estimating the slopes at both short-circuit and open-circuit conditions of the current–voltage characteristic, usually provided by most solar panels manufacturers under standard test conditions (STC). The effects of solar irradiance and temperature were both considered in the modeling. A system of coupled nonlinear simultaneous equations for diode saturation current, diode ideality factor, and series and shunt resistances has been solved. To accurately model the PV module used in our simulation and analysis, the needed temperature- dependent parameters have been extracted for the first time. At STC irradiance of 1000 W/m2, the modeled I-V curve was found identical to the experimental one which is provided by the solar panel manufacturer. The maximum power output of the PV module increases from 8.75 W to 50 W when irradiance varies from 200 W/m2 to 1000 W/m2 at STC temperature. At temperatures higher than STC and for the same solar irradiance, the power output of the PV module came down about 14.5% only when the operating temperature reached a value of 65 °C. However, as temperature is below STC, the power output went up of about 7.4% beyond the maximum power of the rated PV panel. The calculated power temperature coefficient was about −0.39%/ oC which is quite close to the one provided by the solar panel manufacturer.

An Improved Mathematical Model Derivation Based on Circuitry Approach for Crystalline Silicon Photovoltaic Module

This paper revises the five-parameter model, an approach that contributes the fundamental knowledge on performing accurate mathematical modelling for most of the commercially-available photovoltaic cells. However, such model can be further improved in order to increase the modelling accuracy while reducing the required modelling parameters at the same time. Improvement is made through formula derivation for photo-generated current and diode saturation current, while the remaining parameters (series resistance, shunt resistance, and diode ideality factor) remained un-managed for the parameterisation procedure. The derivations presented in this paper are direct, yet such procedures are frequently overlooked by others. The comparison between conventional and proposed modelling methods is presented. The methodology of this work is presented through MATLAB script demonstrated on the measured field data for 70W mono and poly-crystalline silicon photovoltaic modules. The performed methodology justifies that formula derivation can be applied for photo-generated and diode saturation current parameters that originated from five-parameter model. Such approach simplifies the works of parameterising the theoretical model matches with the experimental I-V curve. Generally, the work of this paper contributes to the mathematical modelling of photovoltaic module, simulation of experimental I-V curve result, and interactive education tool.

Voltage dependence of equivalent circuit parameters of bilayer organic photovoltaics

Despite the very different underlying physics of organic photovoltaics (OPVs), inorganic p-n junction’s Shockley’s diode equation is often applied to describe current density–voltage (JV) curves of OPVs. The model parameters, including the diode saturation current, diode ideality factor, series, and parallel resistances, are usually extracted and treated as constants in JV curve analyses. In this work, we develop a drift-diffusion bilayer interface (DD-BI) model for bilayer OPVs, which treats the donor–acceptor (D–A) heterojunction using the detailed balance between densities of polaron pairs, free electrons, and free holes. From the DD-BI model, we derive a diode equation, which is of Shockley’s equation form, but each parameter is explicitly written in terms of the D–A interface properties. We call this model the self-consistent diode (SCD) model as it is consistent with the DD-BI results provided that the key parameters are from the simulation data. By studying the effects of light intensity and carrier mobility, we find that the Shockley SCD parameters are voltage dependent because of space charge accumulation around the D–A heterojunction. Our models are successful in explaining the common discrepancies in OPV JV curve analyses, such as the validity of fitting for series resistance, deviation of ideality factor from the theoretical values, and different resistance values under light and dark conditions. The results provide a better understanding of OPVs with a D–A heterojunction and how we can capture its physics using the SCD equation.

Devising a technique to improve the efficiency of CdS/CdTe/Cu/Au solar cells intended for use as a backup power source for the systems of safety and control of objects

This paper reports a study into the impact of cadmium telluride layer thickness on the effectiveness of the CdS/CdTe/Cu/Au film solar cells. The physical mechanisms have been investigated of charge transfer in the CdS/CdTe/Cu/Au solar cells, which are intended for use as a backup power source for the systems of safety and control of objects. This is important because, despite the growing popularity of solar cell application, the effectiveness of laboratory samples differs greatly from the theoretical maximum. Thus, it has been established that the optimum thickness of the base layer of film CdS/CdTe/Cu/Au SCs is 4 µm. When the thickness of the cadmium telluride layer is reduced, the effectiveness of such an assembly decreases. The decrease in efficiency occurs as a result of reducing the shunting electric resistance, increasing the density of a diode saturation current, as well as consistent electric resistance. With the increase in the thickness of the telluride layer exceeding 4 µm, there is also a decrease in the efficiency of a solar cell due to the reduced shunting resistance and the increased serial electric resistance. The deterioration of the specified light diode characteristics of CdS/CdTe/Cu/Au SCs, which occurs when the thickness of the base layer is reduced by more than 4 µm, is due to the diffusion of copper from the contact to the area of the separating barrier. The deterioration of light diode characteristics when increasing the thickness of the base layer of cadmium telluride is associated with a decrease in the positive effects of chloride treatment. The examined physical charge transfer mechanisms in the CdS/CdTe/Cu/Au solar cells have made it possible to establish the height of the rear potential barrier. In the samples studied, the height of the rear potential barrier is 0.3 eV. The existence of such a barrier gives rise to the thermal-emission mechanism of charge transfer in such solar cells when applying a direct offset exceeding 1 V

REQUIREMENTS ANALYSIS AND DEVELOPMENT OF THE FLEXIBLE SOLAR CELLS OPTIMAL SOLUTION FOR USE IN COMBINED PV/T SYSTEMS

The article defines the requirements for photovoltaic converters designed to work as integrated power sources for combined PV/T systems: efficiently generate electricity at a temperature of 55 °С; provide the coefficient of absorption of solar energy at the level of not less than 90 % and to have the coefficient of reflection in the infrared part of the spectrum not more than 10 %; together with the cooling system cooling system, the design of the converter must provide a difference between the temperature of the converter and the temperature of the coolant not more than 5 °C. A study of the temperature dependence of efficiency for film photoelectric converters based on CdTe and CuInSe2 compounds, amorphous silicon and crystalline GaAs, showed that structures based on cadmium telluride base layers have the smallest decrease in efficiency with increasing operating temperature. When the temperature changes by 50 °С, the efficiency of such devices decreases by only 1 %, and the relative rate of decrease is –0.14 rel. %/C, which is significantly less than the same parameter for other types of converters: GaAs –0.16 rel. %/C, amorphous silicon –0.21 rel. %/C, CuInSe2 –0.36 rel. %/C. Analytical processing and analysis of the influence of light characteristics on the efficiency of cadmium-based transducers showed that the temperature stability of their efficiency is ensured by the density of the diode saturation current. With increasing temperature from 20 °С to 50 °С, the density of the diode saturation current increases by 50 % from 1.9·10-9 A to 2.7·10-9 A, which is less than for silicon devices, for which the diode saturation current increases by 300 %. Studies have shown that the absorption coefficient of solar energy of a flexible element based on cadmium telluride in the visible range is 94–96 %, and the reflection coefficient in the infrared region of the spectrum does not exceed 7–8 %, which allows the design of the collector to abandon the use of selective coating, since its function will be performed by a film photoelectric converter. A constructive-technological solution of a photovoltaic system with flexible photovoltaic converters based on cadmium telluride is proposed.

A Fast and Accurate Analytical Method for Parameter Determination of a Photovoltaic System Based on Manufacturer’s Data

Modeling and simulation of a photovoltaic solar system play a significant role in understanding its behavior in various environmental conditions. Utilization of the datasheet information in modeling and simulation of the PV system correlates the experimental data and the theory that instigate the mathematical predictions of an actual system. A single-diode model gives a simple, fast, and straightforward way of depicting the PV system performance. We have developed a new approach of determining the five unknown parameters of a single-diode model using manufacturer’s data at three main points: the open circuit point (OCP), short circuit point (SCP), and the maximum power point (MPP) of the IV and PV curves. The ideality factor (A) and the diode saturation current (Io) are the key unknown parameters that greatly affect the reduplication of the three main points. The purpose of this study is to evaluate the ideality factor using simple calculation procedure starting from its optimal value (Ao) and other values within the proximity of Ao. The optimal value is obtained by assumptions of negligible series resistance (Rs) and very large shunt resistance (Rsh). Therefore, the choice of the other ideality factors in the neighborhood of its optimal value gives rise to different values of Rs, Rsh, and Iph that are more realistic in an experimental setup. Positive values of Rsh and Rs have been iteratively obtained by utilizing data at maximum power point combined with open and short circuit data. The five unknown parameters have been determined in the proximity of Ao and have been used to plot the PV curve with accuracy and precision of less than 0.5% error of maximum power and less than 0.1% error of Voc of manufacturer’s data. The proposed method has been implemented using fast, simple, and accurate procedures using GNU Octave programming software to calculate Ao, Io, Rs, Rsh, and Iph and to execute both Rs-Rsh and PV characteristic equations of BP3235T, KC200GT, BP-SX 150, and MSX60 PV modules. The reduced steps employed in the algorithm improve execution speed, thereby reducing the computation time.

Reliability of the MPPT Control on the Energy Parameters of a Photovoltaic Generator

This article describes a technique that allows a photovoltaic (PV) production unit to obtain the maximum power at all times. Here, we use the MPPT control via fuzzy logic on a DC/DC boost-type converter. In order to achieve our goals, we first proceeded to model a PV panel. The resulting model offers the possibility to better account for the influence of different physical quantities such as temperature, irradiation, series resistance, shunt resistance and diode saturation current. Thus, the maximum power to be provided by the PV system is acquired by fuzzification and defuzzification of the input and output variables of the converter. Subsequently, a virtual model of an 800 Watt PV prototype is implemented in the Matlab environment. The simulation results obtained and presented, show the feasibility and efficiency of the proposed technology. Indeed, for a disturbance caused by a variation in brightness, our system guarantees the maximum stable power after 1.4 s. While for a load variation, the maximum power is continuous.

A Simplified Simulation Procedure and Analysis of a Photovoltaic Solar System Using a Single Diode Model

A single diode model for a photovoltaic solar module is the most ideal and quick way of analyzing the module characteristics before implementing them in a solar plant. Solar modules manufacturers provide information for three critical points that are essential in I-V, P-V or P-I curves. In this study, we propose four separate simulation procedures to estimate the five-model parameters of an analogous single diode equivalent circuit by utilizing three cardinal points of the photovoltaic module I-V curve, described from experimental data using a solar simulator and manufacturer’s datasheet. The main objective is to extract and use the five unknown parameters of a single diode model to describe the photovoltaic system using I-V ad P-V plots under different environmental conditions. The most influential parameters that greatly alter the cardinal points defined at short circuit point (SCP), the maximum power point (MPP) and the open circuit point(OCP) are the ideality factor (n) and the diode saturation current (Io). For a quick and fast convergence, we have determined the optimal ideality factor (no) and optimal saturation current (Ioopt) as the primary parameters by first assuming the optimal values of Rsh, Rs and Iph at standard test conditions (STC). Further, we evaluated the effects of Iph, Rs and Rsh on I-V and P-V curves by considering the values of n below no. We have evaluated different iterative procedures of determining Rsh and Rs at open-circuit, short-circuit point and the maximum-power points. These procedures have been classified into four approaches that guarantees positive shunt and series resistance for n ≤ no. These approaches have been categorized by deriving the saturation current as a dependent variable at each cardinal point with or without Rs and Rsh pair. The values obtained for the five parameters have been used to simulate the photovoltaic solar module characteristic curves with great precision at different air temperatures and irradiances, considering the effect of Nominal Operating Cell Temperature (NOCT).

Investigation of performance of P3HT:PCBM organic photovoltaic module under real operating conditions

In this work the behavior of an organic solar module operating under real solar radiation conditions is presented. This allows to understand which parameters limit the efficiency of an organic device and their underlying mechanisms. The characterization of a module, produced by CSEM Brasil, with active layer P3HT:PCBM, is based on instantaneous voltage and current curves, dark current curves and analysis of the module operating continuously with fixed voltage. This allows to extract the parameters of the equivalent circuit of the module, such as diode saturation current (I0), series resistance (RS) and shunt resistance (RSH) as well as to understand the influence of different levels of radiation and temperature on such parameters. The work presented was performed by using a commercial organic solar module in extensive outdoor experiments. The results are based on continuous use and for several levels of radiation and temperature under real operating conditions in comparison with a theoretical model for the first time. With the continuous tests it was possible to demonstrate the average daily generation of the module in Wh/m2, and also to verify experimentally, that the module presents better efficiency for diffuse radiation.

ESTIMATION OF PV MODULE PARAMETERS USING GENERALIZED HOPFIELD NEURAL NETWORK

The estimation of solar photovoltaic (PV) system with help of electrical model parameters, suchas photon generated current, the diode saturation current, series resistance, shunt resistance, anddiode ideality factor, are desirable to predict the real performance characteristics of solar PVunder varying environmental conditions. Finally, performance indices, such as PV characteristicscurve are estimated for the various solar PV panels using GHNN optimization technique.