Module Datasheet Research Articles

Matlab-Simulink of photovoltaic system based on a two-diode model simulator with shaded solar cells

This paper proposes a photovoltaic system modeling and characterization software based on Matlab-Simulink in order to estimate the parameters and the characteristic and electrical behavior of a cell/module with respect to changes in environmental parameter regarding irradiance, temperature, and surface conditions (partial shading). The first objective is to find the parameters of the nonlinear I–V equation by adjusting the curve regarding three particular points: open circuit, maximum power, and short circuit. Given these three points, which are provided by all commercial module datasheets, the method finds the best I–V equation for the two-diode photovoltaic (PV) model, with the best series and parallel resistances estimates. The accurateness of the simulator is verified by applying the model to different manufacturer’s modules. Thanks to an interactive graphic interface, this software offers a great flexibility to PV professional and to researchers.

Simpson’s rule based accurate mathematical modelling of photovoltaic cell using multi-objective genetic algorithm for hardware verification

The behaviour and effective performance of solar cell is represented by Triple Diode Solar Cell Module (TDSCM) circuit with five parameters for different environmental conditions. The equations described the solar modules behaviour are usually implicit in nature and the parameter extraction was very complexity. From the Photovoltaic (PV) module data sheet, one can identify the four equations applying to single, double, and triple diode parameters. For getting fifth equation researchers have gone with several approximations, which concludes the computation complexity, convergence problem, and low accuracy issues. In the proposed work the fifth equation are framed under the area characteristics curve (V-I & P-V) concept using Simpson’s approximation. To find which PV module is less accuracy and non-linearity consideration for the performance level. Therefore, to overcome these issues the multi-objective Genetic Algorithm (GA) optimization method are prescribed to frame the fifth equation of the Simpson’s rules. This works improved non-linearity performance and gives the high accuracy modelling compare to other single, double diode methods.

Detailed Power Loss Analysis of T-Type Neutral Point Clamped Converter for Reactive Power Compensation

The paper presents an analysis of power losses in a three-phase T-type neutral point clamped converter with insulated gate bipolar transistors. The paper’s main aim is to perform a detailed analysis of power losses in the converter operating as an active power filter. The study is based on the use of characteristics of semiconductor devices provided by the manufacturer in the module datasheet. Thanks to the analysis, it is possible to recognise the value of power losses, which facilitates the design of the converter cooling system. Identifying how power losses are distributed between the module switching devices is also possible. Power losses are shown as functions of the output current and module temperature. The analysis results were successfully verified by measuring power losses using a laboratory model of the converter with rated currents of 10 and 20 A. The obtained results indicate relatively low power losses and a relatively even distribution of power losses between the semiconductor devices. This is a superior feature of the three-level T-type neutral point clamped converter topology.

Modeling of the operating characteristics of photovoltaic modules based on particle swarm optimization

AbstractThis work evaluates the use of particle swarm optimization to extract the parameters that represent a photovoltaic cell in the model of one diode and five parameters (1D5P) to obtain current versus voltage characteristic curves (I × V) of a photovoltaic module operating under a wide range of temperature and irradiation scenarios. In all the modeling and simulation processes, only information of the module's data sheet provided by the manufacturers was used, without depending on results from other simulations or external data collections. To validate the study, the simulation of the current versus voltage (I × V) curves of a commercial photovoltaic module was made, and this was compared with data provided by the manufacturer and also compared with Chenni's method, which is consolidated by the literature. Errors of less than 0.3% were obtained for the simulations performed under the standard test conditions and in temperature and irradiation situations commonly found in practice, as is the case, of G = 700 W/m2 and Tc = 40°C, the 1D5P method showed an average error of approximately 1%, slightly surpassing the Chenni's method where the error was approximately 1.4%.Statement of Industrial RelevanceIn developing countries, such as Brazil, a significant increase in the portion referring to solar energy in the Brazilian energy grid is noted. As in 2016, this portion was only 0.02%, though in 2020, according to the Brazilian Solar Energy Association (ABSOLAR),1 this portion had an increase of 75 times and reached the value of 1.5%. In addition, ABSOLAR's forecast for 2030 is that solar energy will reach 10% of the Brazilian energy grid. One of the reasons for this is that industrial consumer units are increasingly looking for alternative energy sources due to high energy inflation. Photovoltaic generators are an excellent option for industries because they are clean and sustainable energy.2 It is silent and brings a financial return for the investor. Although, even with all the benefits, the photovoltaic generator has a high acquisition cost, especially for consumer units that demand much energy, as is the case of industries. Thus, correct and precise dimensioning for the photovoltaic generator is necessary. One way to increase the accuracy of dimensioning is to use simulation of the photovoltaic modules, which is the objective of this article.Novelty or SignificanceThe developed method uses the particle swarm optimization with constriction factor to simulate I × V curves of a photovoltaic module for any temperature and irradiation values, using only the module's datasheet information. This study demonstrates that the proposed method presents more accurate results than consolidated methods in the literature, as is the case with the Chenni's method.3

A single-diode model for photovoltaic panels in variable environmental conditions: Investigating dust impacts with experimental evaluation

The current study utilized a single-diode equivalent electrical circuit with a non-iterative parameter extraction approach and innovative modifications to predict the photovoltaic modules' electrical behavior in variable environmental conditions. The model's outputs were validated using both the presented data in the module's datasheet and experimental investigations under more than 500 different real conditions. For the first time, besides irradiation and temperature, dust accumulation effects on the single-diode model's main parameters have been investigated to predict the module's electrical behavior under real environmental conditions. Comparing and simulating more than 13,200 different cases, it was shown that by considering dust effects, respectively, the series resistance, parallel resistance, ideality factor, reverse saturation current, and photocurrent source could be defined with up to 25%, 40%, 9%, 35%, and 40% more accuracy. The trend and dependencies of the prediction improvements for each parameter were also investigated thoroughly. Finally, compared with experimental results in more than 500 different cases showed that, on average, the proposed model improved the prediction of the module's output electrical behavior by 25% to 35%. The proposed model could be easily adjusted and applied to predict photovoltaic modules' output behavior under diverse environmental conditions.

An Improved Method for Extracting Photovoltaic Module I–V Characteristic Curve Using Hybrid Learning Machine System

Abstract This paper provides an improved method for predicting the I–V curve of the photovoltaic module using a hybrid machine learning system. The proposed method is based on a random forest algorithm and a cascade forward neural network. A random forest algorithm is used to predict a specific factor that is subsequently used as an input for the cascade neural network to remove the correlation between voltage and current. Then, the actual current is predicted using the cascade neural network. This procedure assures the ability of the proposed model to extract the I–V curve of any photovoltaic module regardless of its rating or type. A dataset that contains values for air temperature, solar radiation, voltage, and current of two polycrystalline photovoltaic modules is used in the training process of the proposed algorithm. The hybrid model has general inputs such as ambient temperature, solar radiation, and data from the photovoltaic module datasheet (Voc and Isc). The proposed model is trained, tested, and validated by 86% of the data. Meanwhile, 14% of the data are used for testing. Thus, the proposed model is tested using unknown data so as to avoid overfitting. Results show that the proposed model is very accurate in predicting I–V curves based on three types of errors which are mean absolute percentage error (0.68%), mean bias error (0.0191 A), and root-mean-squared error (0.04458 A). This hybrid model can be used to obtain the I–V curves for several types of photovoltaic modules.

Empirical Models Applied to Distributed Energy Resources—An Analysis in the Light of Regulatory Aspects

According to the International Electrotechnical Commission (IEC) 61853 standard, the power rating of photovoltaic (PV) modules must be done on a measurement matrix that broadly covers the ranges of operating conditions encountered in the field. These results are becoming more frequent in recent module datasheets. This paper investigates the effectiveness of applying existing empirical PV performance models while using a matrix with 18 operational records, similar to the 22 that were recommended by IEC 61853, as an alternative to the thousands of records that are conventionally used to determine their coefficients. A review of fifteen empirical models is presented and the procedures for determining their coefficients are discussed. In order to validate them, they were applied to data from fourteen PV modules, which remained installed outdoors for about one year, in three locations with distinct climate types. Although the uncertainties that were obtained with the proposed approach, as compared to the conventional one, are about 1% higher for xSi and CdTe modules, and somewhat higher for mSi and CIGS modules, the total uncertainties were only around 5%, a value that is quite adequate for evaluating module performance. Moreover, these uncertainties were from two to five times smaller than those that were obtained by the method that was recommended by IEC 61853 for this purpose.

Expert System-Based EMI Modeling Method for IGBT in Electric Drive System of EV

In the working process of the electric drive system, the transient, high-amplitude, high-frequency voltage and current generated by the turn-on and turn-off of the IGBT (Insulated Gate Bipolar Transistor) are the most important sources of electromagnetic interference in EVs (electric vehicles). To this end, this paper proposes an EMI (Electromagnetic interference) modeling method for IGBT power modules of electric drive systems, which can realize accurate simulation of EMI source characteristics. First, an expert system based on IGBT model library is proposed. Then the expert system is used to simulate the characteristic curves provided in the IGBT module datasheet and extract the key parameters. Based on the expert system, an IGBT behavioral model is established, and a double-pulse simulation circuit is built to evaluate the simulation waveforms of the collector-emitter voltage, gate-emitter voltage and collector current during the two pulse switching periods. At the same time, measure the collector-emitter voltage, gate-emitter voltage and collector current test waveforms collected in the above simulation test on the built double-pulse test circuit, and compare the turn-on and turn-off processes of the simulation and test respectively to evaluate the accuracy of the EMI source model. Finally, to further test the universality of the model, the IGBT behavior model and the double pulse simulation circuit are established on the Simulink platform, and the accuracy of the model is evaluated by comparing with the test waveform. The comparative analysis results show that the proposed EMI source modeling method for IGBT power module has good versatility and accuracy.

Development of a Comprehensive Matlab/Simulink Based Model for High-Efficiency 2nd Generation Photovoltaic (PV) Modules

Background:The accurate energy yield prediction of a PV system under various environmental conditions is important for designing a high-performance PV system.Objective:The robust and cost-effective digital simulation studies on PV systems have the advantage in comparison to studies based on measurements because they provide the opportunity for sensitivity analysis on various design parameters of the PV system.Methods:Herein, we present the development and implementation of a generalized photovoltaic computational model using Matlab/Simulink software package. The model is based on the equivalent diode circuit approach. It is designed to simulate two ubiquitous and high performing 2nd generation photovoltaic (PV) modules constructed with Cadmium Telluride (CdTe) and Copper Indium Gallium di-Selenide (CIGS) photoactive thin films, respectively. The values of key input parameters to the simulator, i.e., parallel resistor (Rp) and series resistor (Rs) have been computed by an efficient Newton-Raphson iteration method.Results:The output current-voltage (I-V) and power-voltage (P-V) characteristic curves of the aforementioned PV modules have been simulated by taking two input variables (ambient irradiance and temperature) into consideration. The electrical performance of both PV modules under various environmental conditions have been mathematically investigated by the solution of classical non-linear equations.Conclusion:The developed PV model has been validated with the experimental results obtained from standard PV module datasheets provided by manufacturers. The relative error between the simulated and experimental values of various photovoltaic parameters for CdTe and CIGS PV modules at Standard Test Conditions (STC) has been observed to be below 3%.

Accurate Expressions for Single-Diode-Model Solar Cell Parameterization

The performance of a photovoltaic (PV) module is represented by a single-diode-model circuit with the five parameters for a given environmental condition. However, the model characteristic equation which is implicit in nature makes the parameters’ extraction computationally complex. In addition, for finding the five parameters from the specifications of the PV module datasheet, one can formulate only four equations. To complete the solution, the formulation of the fifth equation is really tricky. Therefore, the researchers have attempted several approximations to complete the problem formulation, but the obtained results have low accuracy in many cases. This paper specifically focuses on the formulation of the fifth equation without any approximation, which considers an exact area under the current–voltage ( I – V ) curve of a PV cell/module. The method is employed for different cells as case study-I and for the experimental data of a silicon cell and a module as case study-II commonly available in the literature. The numerical results are highly accurate with respect to the existing methods.

Mathematical Modeling of Photovoltaic Module with Simulink

Solar Energy is a good choice for electric power generation, since the solar energy is directly converted into electrical energy by solar photovoltaic modules Solar cells generates most of their electricity from direct sunlight. However, they also generate electricity on cloudy days and some systems can even generate very small amounts of electricity on bright moonlit nights. Individual solar cells typically only generate tiny amounts of electrical energy. To make useful amounts of electricity, these cells are connected together to make a solar module, otherwise known as a solar panel or, to be more precise, a photovoltaic module.The PV model plays an important role in the accuracy of the time simulation of the PV cell model. Modeling of PV cell involves the estimation of the I–V and P–V characteristics curves to emulate the real cell under various environmental conditions Photovoltaic (PV) model is used in a simulation study to validate the system design of a PV system. This paper presents modeling of Photo- voltaic (PV) module using MATLAB/SIMULINK. The model is developed on the basis of mathematical model of the PV module. The PV module of SN72-CELL-POLY CRYSTALLINE PV MODULE SN325P is selected for the experimental and technical data to analyze the developed model. The output current and power characteristic curves highly depend on some climatic factors such as solar radiation and temperature, are obtained by simulation for the selected module with the output power of 325 W .The objective of this paper is to develop a model to simulate the behavior of a photovoltaic cell. The achieved Voc voltage and current values from I-V and P-V characteristics are compared with module data sheet both models are implemented in MATLAB /SIMULINK. The “five-parameter model” is a performance model for photovoltaic solar cells that predicts the voltage and current output by representing the cells as an equivalent electrical circuit with radiation and temperature-dependent components. An important feature of the five-parameter model is that its parameters can be determined using data commonly provided by module manufacturers on their published datasheets.

New analytical approach for modelling effects of temperature and irradiance on physical parameters of photovoltaic solar module

In this paper, a new exact method has been presented to extract physical parameters of single diode equivalent circuit modelling a photovoltaic solar module operating at standard test conditions. The method uses four equations, three are linking output current to output voltage in short-circuit, maximum power and open-circuit points, the fourth equation is the first derivative of output power with regard to output voltage in maximal power point. According to this method, we used ideality factor η as variation parameter and solved the system of four nonlinear equations to get values of photocurrent Iph, saturation current Is, series resistance Rs and shunt conductance Gp. We then varied ideality factor to minimize root mean square error and maximize the coefficient of determination. We assumed series resistance and shunt conductance constant, and derived analytical expressions describing effects of module temperature and incident solar irradiance on photocurrent, on ideality factor and also on saturation current using both temperature coefficients available as well as irradiance coefficients extracted from module datasheet. We considered standard test conditions numerical values of physical parameters as initial conditions and determined numerical models for Iph(T,G), η(T,G) and Is(T,G). We also derived new mathematical expressions of maximum power point voltage and module efficiency. We tested these numerical models as well as mathematical expressions derived on Kyocera KC200GT and Shell SQ80 photovoltaic solar modules under different conditions of module temperature and incident solar irradiance and found good agreement between experimental and forecasted characteristics.

Experimental Investigation of Temperature Effect on PV Monocrystalline Module

The importance of the module’s temperature has been severally discussed in previous reviews. What is of concern to us is the percentage of the power loss with each increase in unit temperature. The experiment illustrated in this research has allowed the monitoring of the variants in the power produced during the two months of August and December. The parameters of module temperature and solar irradiation have been monitored, and the maximum output voltage and the power produced were recorded. The drop in power was usually a result of increase in temperature but on a different scale, which draws attention to other parameters that may affect the percentage of drop in power. The system was simulated using the tool of MATLAB using the module data sheet, and the difference in power produced was noted. The objective of this research is to improve the simulation tools in order to be more accurate in increasing the number of parameters that may contribute to the power produced from the cells.

An efficient parameters extraction technique of photovoltaic models for performance assessment

The accurate and efficient photovoltaic (PV) model is very crucial for performance assessment of solar PV (SPV) systems in embedded power system applications and maximum power point tracking. A five parameter single-diode and seven parameter double-diode models of SPV system for ensuring the reliable and accurate performance assessment are presented. Since these parameters are unknown, it is important to extract these parameters for accurate modeling of the SPV systems. The accurate parameter extraction using numerical method needs suitable initial values, for which an approximate analytical solution is provided which serves as an initial value. A hybrid approach of numerical and analytical solutions are utilized which require minimal information from the module datasheet. Moreover, the reciprocal of slope of I-V curve at short circuit and open circuit conditions is calculated, which further used in analytical and numerical algebraic equations of double-diode model to enhance the parameters extraction accuracy. This makes it a cheaper and efficient parameter extraction technique. The outcomes of both PV models are compared with the manufacturer, indoor and outdoor experimental results for validation. Further, the performance of both models has been assessed at different temperature and solar insolation for determining the best-suited model for characterizing the SPV system under given environmental conditions. Double-diode model has been found more accurate than single-diode model, particularly at low-level solar insolation.

Fault detection in PV systems

A practical fault detection approach for PV systems intended for online implementation is developed. The fault detection model here is built using artificial neural network. initially the photovoltaic system is simulated using MATLAB software and output power is collected for various combinations of irradiance and temperature. Data is first collected for normal operating condition and then four types of faults are simulated and data are collected for faulty conditions. Four faults are considered here and they are: Line to Line faults with a small voltage difference, Line to line faults with a large voltage difference, degradation fault and open-circuit fault. This data is then used to train the neural network and to develop the fault detection model. The fault detection model takes irradiance, temperature and power as the input and accurately gives the type of fault in the PV system as the output. This system is a generalized one as any PV module datasheet can be used to simulate the Photovoltaic system and also this fault detection system can be implemented online with the use of data acquisition system.

A simple approach to extract the unknown parameters of PV modules

A simple and accurate technique to compute essential parameters needed for electrical characterization of photovoltaic (PV) modules is proposed. A single-diode model of PV modules, including those with series and shunt resistances, is considered accurate and simple. However, PV module datasheets provided by manufacturers provide current-voltage ($I$-$V)$ characteristics as well as the values of selected parameters at standard test conditions (STC), i.e. solar radiation of 1000 W/m$^{2}$, air temperature of 25 $^{\circ}$C, and air mass AM = 1.5. Consequently, important parameters such as series resistance ($R_{s})$, shunt resistance ($R_{sh})$, photocurrent ($I_{ph})$, and diode reverse-saturation current ($I_{o})$ are not provided by most manufacturers. Since these parameters are crucial for PV module characterization, our study presents an exact, closed-form expression for $R_{s}$ that is solvable numerically while increasing the value of the ideality factor ($a)$ in small increments, so that four equations are formulated to compute the unknown parameters. To validate the proposed approach, a set of $I-V$ curves were computed for different values of $a$, and these results were compared alongside corresponding reference data for the BP SX150 and MSX60 PV modules. Average RMS errors of 0.035 for BP SX150 and 0.014 for MSX60 between the reference data and the computed data suggest that proposed approach could be used as an alternative method to quantify important missing parameters required for characterization of PV modules.

Determination of Unknown Parameters of Photovoltaic Module Using Genetic Algorithm

<p> In this paper, the unknown parameters of the photovoltaic (PV) module are determined using Genetic Algorithm (GA) method. This algorithm based on minimizing the absolute difference between the maximum power obtained from module datasheet and the maximum power obtained from the mathematical model of the PV module, at different operating conditions. This method does not need to initial values, so these parameters of the PV module are easily obtained with high accuracy. To validate the proposed method, the results obtained from it are compared with the experimental results obtained from the PV module datasheet for different operating conditions. The results obtained from the proposed model are found to be very close compared to the results given in the datasheet of the PV module.</p>

Modeling and performance analysis of PV module with Maximum Power Point Tracking in Matlab/Simulink

This paper presents a detailed approach to develop and characterize generalized photovoltaic (PV) module in Matlab/Simulink environment, which can be a standard for designing PV module. Performance of PV module with different irradiance, temperature and load conditions is briefly analyzed here. Simulation result of the proposed model is verified and compared with an existing PV module datasheet which shows a close similarity with the simulated model. To operate the total system at maximum power point, Maximum Power Point Tracking (MPPT) following incremental conductance method is employed with proposed PV module. Undesired output power variation with varying load is eliminated with this tracking technique. Maximum power is delivered to the load via a DC/DC boost converter. A circuit based simulation model is essential for a PV module for delivering the output power to the load interfaced with the converter. Our proposed system shows that output voltage, current and power level exactly matches with the maximum power point of a well designed PV module which is compatible with various PV modules.

Distributed Photovoltaic Architecture for HVDC-bus Feeding with a Simple Evaluation of Optimal Tracking

This contribution describes, compares, and analyses two structures and their operating modes dedicated to renewable energy production from photovoltaic (PV) sources. Between the two different technical approaches, photovoltaic sources placed in a distributed architecture supplying a high DC voltage HVDC bus points large advantages. Thus, after preliminary comparison of both solutions and concluding phases, this efficient solution finally constitutes the main original analysis presented in this contribution. The distributed PV structure is investigated, implemented and simulated in an original way under the OrCAD/Pspice software environment. The adaptation stage for maximum power transfer is modelled in detail. A method to calculate the optimal duty cycle for optimal use of PV panels power is proposed, tested and validated by the use of a marketed PV module datasheet.

Parameter estimation for five- and seven-parameter photovoltaic electrical models using evolutionary algorithms

Equivalent electric circuit modeling of PV devices is widely used to predict PV electrical performance. The first task in using the model to calculate the electrical characteristics of a PV device is to find the model parameters which represent the PV device. In the present work, parameter estimation for the model parameter using various evolutionary algorithms is presented and compared. The constraint set on the estimation process is that only the data directly available in module datasheets can be used for estimating the parameters. The electrical model accuracy using the estimated parameters is then compared to several electrical models reported in literature for various PV cell technologies.