Extraction of Efficient Electrical Parameters

of Single Diode and Double Diode Model

by Analytical-Numerical Technique

Manjunath1

Research Scholar

Department of E&E Engineering Malnad College of Engineering

Hassan – 573 202, India. [email protected]

Avinash K. M4

UG Student

Department of E&E Engineering Malnad College of Engineering

Hassan – 573 202, India. [email protected]

H. N. Suresh2 Professor

Department of E&E Engineering Malnad College of Engineering

Hassan – 573 202, India.

[email protected]

Ajith S5

UG Student

Department of E&E Engineering Malnad College of Engineering

Hassan – 573 202, India. [email protected]

S. Rajanna3Associate Professor

Department of E&E Engineering Malnad College of Engineering

Hassan – 573 202, India.

[email protected]

Karthik Praveen6

UG Student

Department of E&E Engineering Malnad College of Engineering

Hassan – 573 202, India. [email protected]

Abstract—This paper examines the investigation of parameter extraction strategies which are basically dependent on the maker’s datasheets. An investigation is done for different advances of Solar Photovoltaic (SPV) modules, utilizing the five parameters from Single Diode Model (SDM) and seven parameters from Double Diode Model (DDM) methods. Determining the exact and accurate parameters from the PV model by analytical as well as numerical techniques is still a challenging task for researchers. In this examination, extraction of accurate parameters is done by Levenberg-Marquardt (LM) numerical iterative technique for both (SDM ; DDM) methods. Examination of different SPV module simulation (MATLAB SIMULINK) results (I-V) is plotted and compared for both methods. The proposed work is to evaluate the accuracy of the two methods for different PV modules corresponding to the various temperature conditions.

Keywords—Solar Photo-Voltaic (SPV), Parameters Extraction, Single Diode Model, Double Diode Model, Analytical ; Numerical Techniques.

Introduction

The maximum generation of electrical energy mainly depends on the conventional energy sources of which in terms pollutes the environment. To reduce such environmental issues or impacts, a suitable alternative source is required for lessening the dependency of conventional energy sources is non-conventional energy sources or renewable energy sourcesADDIN CSL_CITATION { “citationItems” : { “id” : “ITEM-1”, “itemData” : { “DOI” : “10.1109/SGRE.2015.7208722”, “ISBN” : “9781467367653”, “author” : { “dropping-particle” : “”, “family” : “Azab”, “given” : “Mohamed”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “2015 1st Workshop on Smart Grid and Renewable Energy, SGRE 2015”, “id” : “ITEM-1”, “issued” : { “date-parts” : “2015” }, “title” : “Identification of one-diode model parameters of PV devices from nameplate information using particle swarm and least square methods”, “type” : “article-journal” }, “uris” : “http://www.mendeley.com/documents/?uuid=b22baed6-0170-4e6f-93a8-2e1c4bf5eca6” }, { “id” : “ITEM-2”, “itemData” : { “DOI” : “10.1109/RTEICT.2016.7808032”, “ISBN” : “978-1-5090-0774-5”, “author” : { “dropping-particle” : “”, “family” : “Sawant”, “given” : “Pallavi T”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Lbhattar”, “given” : “P Ctejasvi”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Bhattar”, “given” : “C L”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)”, “id” : “ITEM-2”, “issue” : “1”, “issued” : { “date-parts” : “2016” }, “page” : “1251-1255”, “title” : “Enhancement of PV system based on artificial bee colony algorithm under dynamic conditions”, “type” : “article-journal” }, “uris” : “http://www.mendeley.com/documents/?uuid=1f97734e-48da-4d07-b116-9fdc74c59dfa” }, { “id” : “ITEM-3”, “itemData” : { “DOI” : “10.1016/j.solener.2016.01.061”, “ISSN” : “0038092X”, “abstract” : “The performance of a photovoltaic (PV) system depends on several factors, such as the solar radiation availability and its spectral distribution, the PV module temperature, soiling, cable losses, PV power degradation over time and so forth. An important factor that also affects the PV array power is the mismatch loss due to the differences between single modules, since is inherent to the manufacturing process certain variability in the I-V curve parameters. The manufacturing technology of PV modules has improved considerably, resulting in higher efficiencies and better quality control process, which enabled a lower maximum power tolerance range of PV modules available in the market. The actual shape of the statistical distribution of the main electrical parameters is necessary to evaluate the mismatch losses using simulation software, and also to verify if a new selection of PV modules besides the one performed by the manufacturer is relevant. In order to analyze these topics, a statistical study was carried out based on data obtained from I-V curve measurements of 105 multicrystalline PV modules with the same nominal characteristics. The measurements were performed in a pulsed solar simulator in standard test conditions. The descriptive statistics were obtained for each main electrical parameter and the best probability density function that describes the parameters dispersion was determined. The results show that the maximum power, the maximum power voltage and the open circuit voltage are preferably represented by a Burr probability density function, however a normal distribution is adequate as well. The short circuit current, the maximum power current and the fill factor are actually described by a two parameter Weibull distribution. In order to analyze the effects of the mismatch losses in arrays, several I-V curves of strings with 10 PV modules randomly selected from the sample were synthesized and compared to strings of modules sorted by the maximum power current value. The advantage of performing a new selection of PV modules with better current match was not relevant in comparison to random strings. The selection performed at the factory for a PV module with the same nominal power is sufficient to prevent considerably mismatch losses considering that the PV modules were sorted using standard procedures.”, “author” : { “dropping-particle” : “”, “family” : “Gasparin”, “given” : “Fabiano Perin”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Bu00fchler”, “given” : “Alexandre Josu00e9”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Rampinelli”, “given” : “Giuliano Arns”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Krenzinger”, “given” : “Arno”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Solar Energy”, “id” : “ITEM-3”, “issued” : { “date-parts” : “2016” }, “page” : “30-38”, “title” : “Statistical analysis of I-V curve parameters from photovoltaic modules”, “type” : “article-journal”, “volume” : “131” }, “uris” : “http://www.mendeley.com/documents/?uuid=bf94f162-0f9f-4708-8fbb-0e7f27e2640e” } , “mendeley” : { “formattedCitation” : “1u20133”, “plainTextFormattedCitation” : “1u20133”, “previouslyFormattedCitation” : “1u20133” }, “properties” : { }, “schema” : “https://github.com/citation-style-language/schema/raw/master/csl-citation.json” }1–3. In renewable energy sources, solar energy is the most abundant and freely available source in the atmosphere. There are many ways of utilizing the solar energy in that, Solar Photo-Voltaic (SPV) is the most reliable, low running cost and it is free from the environmental issuesADDIN CSL_CITATION { “citationItems” : { “id” : “ITEM-1”, “itemData” : { “DOI” : “10.1016/j.enconman.2015.08.023”, “ISBN” : “9781467395724”, “ISSN” : “01968904”, “PMID” : “109176610”, “abstract” : “Accurate modeling of photovoltaic (PV) modules is helpful in designing and assessing the energy production of PV systems. A new version of the differential evolution (DE) algorithm, called differential evolution with integrated mutation per iteration (DEIM), is proposed in this study to extract the seven parameters of a double-diode PV module model. This algorithm applies the attraction-repulsion concept of an electromagnetism-like algorithm to boost the mutation operation of the conventional DE algorithm. Moreover, a new adaptive strategy is proposed to tune mutation scaling and crossover rate for each generation. The proposed model is validated through experimental data and other models, which have been proposed in literature using various statistical errors. Results show that DEIM exhibits high accuracy and fast convergence speed compared with other methods. The average root mean square error, mean bias error, and absolute error at maximum power point of the proposed model are 1.713%, 0.149%, and 4.515%, respectively.”, “author” : { “dropping-particle” : “”, “family” : “Muhsen”, “given” : “Dhiaa Halboot”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Ghazali”, “given” : “Abu Bakar”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Khatib”, “given” : “Tamer”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Abed”, “given” : “Issa Ahmed”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Energy Conversion and Management”, “id” : “ITEM-1”, “issued” : { “date-parts” : “2015” }, “page” : “552-561”, “publisher” : “Elsevier Ltd”, “title” : “Parameters extraction of double diode photovoltaic module’s model based on hybrid evolutionary algorithm”, “type” : “article-journal”, “volume” : “105” }, “uris” : “http://www.mendeley.com/documents/?uuid=db840207-2dcb-4c38-b314-5c2672b1b206” }, { “id” : “ITEM-2”, “itemData” : { “DOI” : “10.1016/j.solmat.2013.11.011”, “ISBN” : “0927-0248”, “ISSN” : “09270248”, “abstract” : “This paper deals with the extraction of the parameters of the single-diode solar cell model from experimental I-V characteristics of Si and Multi-junction solar cells. The extraction is carried out by three different optimization methods in an attempt to judge which method surpasses the others in terms of data-to-model fitting. The first and the second methods are a variation of the Newton-Raphson method and the Levenberg-Marquardt algorithm, respectively. Both methods are based on the gradient descent approach. The third method is a global-search method based on a Genetic-Algorithm. The extraction of the parameters was done in two stages. On the first stage, empirical I-V characteristics of solar cells that contained measurement errors were used, whereas on the second stage the parameters were re-extracted using a smooth synthetic I-V data. In the absence of true measured parameter values of the cells, it was left to rate the performance of the three optimization methods by the extraction error alone. Although no definitive conclusions could be drawn from the results of the noisy data, results of the smooth data are far more pronounced in terms of the extraction error, and tend to favor the Newton-Raphson method. u00a9 2013 Published by Elsevier B.V. All rights reserved.”, “author” : { “dropping-particle” : “”, “family” : “Appelbaum”, “given” : “J.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Peled”, “given” : “A.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Solar Energy Materials and Solar Cells”, “id” : “ITEM-2”, “issued” : { “date-parts” : “2014” }, “page” : “164-173”, “publisher” : “Elsevier”, “title” : “Parameters extraction of solar cells – A comparative examination of three methods”, “type” : “article-journal”, “volume” : “122” }, “uris” : “http://www.mendeley.com/documents/?uuid=602b74eb-eb75-4582-9d30-fb8540cc2933” }, { “id” : “ITEM-3”, “itemData” : { “DOI” : “10.1016/j.swevo.2017.02.005”, “ISSN” : “22106502”, “abstract” : “In order to carry out precise performance investigations and control studies on photovoltaic (PV) systems, an accurate model is always desired. In this work, a new and powerful metaheuristic optimization technique known as Evaporation Rate based Water Cycle Algorithm (ER-WCA) has been explored for effective parameters estimation of PV cell/module. Single and double diode based models of PV cell and single diode based model of PV module have been successfully identified from their respective single I-V non-linear characteristics and the modeling performance of ER-WCA, assessed in terms of root mean square error, mean absolute error and mean relative error, between computed and experimental data, is found to be superior to the several recent prominent published works particularly the modeling of a single diode based PV module. Furthermore, the PV module modeling capability of ER-WCA under varying temperature and irradiation conditions is also analysed and it is found to be effective, proving its practical applications. Based on the presented detailed investigation, it is concluded that ER-WCA is a promising optimization technique for PV cell/module identification.”, “author” : { “dropping-particle” : “”, “family” : “Kler”, “given” : “Dhruv”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Sharma”, “given” : “Pallavi”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Banerjee”, “given” : “Ashish”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Rana”, “given” : “K. P.S.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Kumar”, “given” : “Vineet”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Swarm and Evolutionary Computation”, “id” : “ITEM-3”, “issued” : { “date-parts” : “2017” }, “page” : “93-110”, “publisher” : “Elsevier”, “title” : “PV cell and module efficient parameters estimation using Evaporation Rate based Water Cycle Algorithm”, “type” : “article-journal”, “volume” : “35” }, “uris” : “http://www.mendeley.com/documents/?uuid=56004696-1742-4532-9f53-589612f2ebbd” }, { “id” : “ITEM-4”, “itemData” : { “DOI” : “10.1016/j.enconman.2017.06.064”, “ISSN” : “01968904”, “abstract” : “In the photovoltaic (PV) panels modeling field, this paper presents a comparative study of two parameter estimation methods: the iterative method called Gauss Seidel, applied on the single diode model, and the analytical method used on the double diode model. These parameter estimation methods are based on the manufacturer’s datasheets. They are also tested on three PV modules of different technologies: multicrystalline (kyocera KC200GT), monocrystalline (Shell SQ80), and thin film (Shell ST40). For the iterative method, five existing mathematical models classified from 1 to 5 are used to estimate the parameters of these PV modules under varying environmental conditions. Only two models of them are used for the analytical method. Each model is based on the combination of the photocurrent and the reverse saturation current’s expressions in terms of temperature and irradiance. In addition, the results of the modelsu2019 simulation are compared with the experimental data obtained from the PV modulesu2019 datasheets, in order to evaluate the accuracy of the models. The simulation shows that the I-V characteristics obtained are matching to the experimental data. In order to validate the reliability of the two methods, both the Absolute Error (AE) and the Root Mean Square Error (RMSE) were calculated. The results suggest that the analytical method can be very useful for monocrystalline and multicrystalline modules, but for the thin film module, the iterative method is the most suitable.”, “author” : { “dropping-particle” : “”, “family” : “Et-torabi”, “given” : “K.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Nassar-eddine”, “given” : “I.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Obbadi”, “given” : “A.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Errami”, “given” : “Y.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Rmaily”, “given” : “R.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Sahnoun”, “given” : “S.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “fajri”, “given” : “A.”, “non-dropping-particle” : “El”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Agunaou”, “given” : “M.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Energy Conversion and Management”, “id” : “ITEM-4”, “issued” : { “date-parts” : “2017” }, “page” : “1041-1054”, “publisher” : “Elsevier Ltd”, “title” : “Parameters estimation of the single and double diode photovoltaic models using a Gaussu2013Seidel algorithm and analytical method: A comparative study”, “type” : “article-journal”, “volume” : “148” }, “uris” : “http://www.mendeley.com/documents/?uuid=1f16776d-125a-4036-a6c4-f38b85161ffa” } , “mendeley” : { “formattedCitation” : “4u20137”, “plainTextFormattedCitation” : “4u20137”, “previouslyFormattedCitation” : “4u20137” }, “properties” : { }, “schema” : “https://github.com/citation-style-language/schema/raw/master/csl-citation.json” }4–7. A Solar Photo-Voltaic cell is a semiconductor device which directly converts the sunlight into electrical energy without polluting the environment. Such solar cells are connected together to form a module later these modules are connected in series or parallel to become an array depending on the applicationsADDIN CSL_CITATION { “citationItems” : { “id” : “ITEM-1”, “itemData” : { “DOI” : “10.1016/j.energy.2018.05.131”, “ISSN” : “03605442”, “abstract” : “Partial Shading plays a vital role in the power generation from PV arrays. It can drastically reduce the power output from PV arrays resulting in multiple maximum peak points in power-voltage characteristics. The power reduction in PV arrays less depends on area of shading but significantly depends on the pattern of shading. In this paper, a static shade dispersion positioning (SDP) technique for modules of PV array to the reduce power loss caused by partial shading has been proposed. The technique aims to reduce the power loss by distributing the effect of partial shading into whole array without changing the electrical configuration of the system. The performance of the proposed technique has been compared with the existing hitherto known conventional topologies i.e. Series-Parallel, Bridge-Linked and Total Cross Tied under various non-uniform and uniform shading conditions. The comparison is done for a 3 u00d7 3 PV array using MATLAB and a prototype field experiment. Also, the proposed SDP technique has been compared with Su Do Ku arrangement and EAR strategy. It is found that the proposed SDP technique excels in performance by maximizing the power generation of PV arrays under various shading conditions and can be easily implemented in field conditions without any complexity.”, “author” : { “dropping-particle” : “”, “family” : “Satpathy”, “given” : “Priya Ranjan”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Sharma”, “given” : “Renu”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Energy”, “id” : “ITEM-1”, “issued” : { “date-parts” : “2018” }, “page” : “569-585”, “publisher” : “Elsevier Ltd”, “title” : “Power loss reduction in partially shaded PV arrays by a static SDP technique”, “type” : “article-journal”, “volume” : “156” }, “uris” : “http://www.mendeley.com/documents/?uuid=3e57fcc9-c3c1-4daf-a088-427bcbe5cea3” } , “mendeley” : { “formattedCitation” : “8”, “plainTextFormattedCitation” : “8”, “previouslyFormattedCitation” : “10” }, “properties” : { }, “schema” : “https://github.com/citation-style-language/schema/raw/master/csl-citation.json” }8. The increasing demands of the SPV rising rapidly day by day which in terms creates to design a suitable SPV system because efficiency of the SPV cell is very low and it is not economicalADDIN CSL_CITATION { “citationItems” : { “id” : “ITEM-1”, “itemData” : { “DOI” : “10.1016/j.enconman.2017.06.064”, “ISSN” : “01968904”, “abstract” : “In the photovoltaic (PV) panels modeling field, this paper presents a comparative study of two parameter estimation methods: the iterative method called Gauss Seidel, applied on the single diode model, and the analytical method used on the double diode model. These parameter estimation methods are based on the manufacturer’s datasheets. They are also tested on three PV modules of different technologies: multicrystalline (kyocera KC200GT), monocrystalline (Shell SQ80), and thin film (Shell ST40). For the iterative method, five existing mathematical models classified from 1 to 5 are used to estimate the parameters of these PV modules under varying environmental conditions. Only two models of them are used for the analytical method. Each model is based on the combination of the photocurrent and the reverse saturation current’s expressions in terms of temperature and irradiance. In addition, the results of the modelsu2019 simulation are compared with the experimental data obtained from the PV modulesu2019 datasheets, in order to evaluate the accuracy of the models. The simulation shows that the I-V characteristics obtained are matching to the experimental data. In order to validate the reliability of the two methods, both the Absolute Error (AE) and the Root Mean Square Error (RMSE) were calculated. The results suggest that the analytical method can be very useful for monocrystalline and multicrystalline modules, but for the thin film module, the iterative method is the most suitable.”, “author” : { “dropping-particle” : “”, “family” : “Et-torabi”, “given” : “K.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Nassar-eddine”, “given” : “I.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Obbadi”, “given” : “A.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Errami”, “given” : “Y.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Rmaily”, “given” : “R.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Sahnoun”, “given” : “S.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “fajri”, “given” : “A.”, “non-dropping-particle” : “El”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Agunaou”, “given” : “M.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Energy Conversion and Management”, “id” : “ITEM-1”, “issued” : { “date-parts” : “2017” }, “page” : “1041-1054”, “publisher” : “Elsevier Ltd”, “title” : “Parameters estimation of the single and double diode photovoltaic models using a Gaussu2013Seidel algorithm and analytical method: A comparative study”, “type” : “article-journal”, “volume” : “148” }, “uris” : “http://www.mendeley.com/documents/?uuid=1f16776d-125a-4036-a6c4-f38b85161ffa” }, { “id” : “ITEM-2”, “itemData” : { “DOI” : “10.1109/ICPDEN.2015.7084502”, “ISBN” : “9781479964598”, “abstract” : “Solar Energy is a clean and boundless energy source and the worldwide solar market demand is increasing for industrial and domestic purposes. The purpose of this paper is to show the comparison of Stochastic Method(Genetic Algorithm) over derivative methods. A mathematical development 3 is provided for the extraction of Solar Panel equivalent circuit parameters from datasheet values. The analytical approach is selected for the mathematical development as the initial-point vital for proper evaluation of the Parameters of the double diode Model of PV cells. And thus using Evolutionary technique to extract the values of the parameters, a valid comparison has been presented between the numerical approaches and the Evolutionary Algorithms.”, “author” : { “dropping-particle” : “”, “family” : “Saha”, “given” : “Paramjit”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Kumar”, “given” : “Saurabh”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Nayak”, “given” : “Sisir Kr”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Sahu”, “given” : “Himanshu Sekhar”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “2015 1st Conference on Power, Dielectric and Energy Management at NERIST, ICPDEN 2015”, “id” : “ITEM-2”, “issued” : { “date-parts” : “2015” }, “page” : “3-6”, “title” : “Parameter estimation of double diode photo-voltaic module”, “type” : “article-journal” }, “uris” : “http://www.mendeley.com/documents/?uuid=def04111-b67e-4f95-a6c2-7374455425be” }, { “id” : “ITEM-3”, “itemData” : { “DOI” : “10.1109/ICIT.2015.7125507”, “ISBN” : “978-1-4799-7800-7”, “abstract” : “u2014The paper presents a technique for parameter estimation of photovoltaic (PV) modules from datasheet information. The manufacturer normally provides open-circuit voltage, short-circuit current, maximum power, and voltage at maximum power under the standard test conditions (STC). The four datasheet values represent the targeted performance of the module. Parameter estimation is formulated as an optimization problem solved by traditional nonlinear programming techniques as well as global search algorithms. The objective is to search a set of parameters that minimizes the error between targeted and computed performance. The methodology is successfully applied to single-and double-diode equivalent circuits of PV modules. Evidently, the need to perform prototype lab testing, for the purpose of parameter estimation, is eliminated. Results show that genetic algorithms (GA) outperform other optimization techniques in obtaining the equivalent circuit parameters of a commercially available PV module.”, “author” : { “dropping-particle” : “”, “family” : “Awadallah”, “given” : “Mohamed A.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Venkatesh”, “given” : “Bala”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Proceedings of the IEEE International Conference on Industrial Technology”, “id” : “ITEM-3”, “issue” : “June”, “issued” : { “date-parts” : “2015” }, “page” : “2777-2782”, “title” : “Estimation of PV module parameters from datasheet information using optimization techniques”, “type” : “article-journal”, “volume” : “2015-June” }, “uris” : “http://www.mendeley.com/documents/?uuid=6e4a43fb-9cc2-4bb6-b2f9-9cd0bca24626” }, { “id” : “ITEM-4”, “itemData” : { “DOI” : “10.1109/CSNDSP.2014.6923947”, “ISBN” : “9781479925810”, “abstract” : “In this paper, a parameter extraction technique of a single- and a two-diode photovoltaic (PV) solar cell models using MATLAB/Simulink are presented. To reduce the computational time, the proposed method uses an accurate iterational technique and limits the inputs to four parameters, which are normally provided by the manufacturers’ datasheets. Derived models are validated by plotting their I-V characteristics and compared to a photovoltaic (PV) cell under variable conditions of solar irradiance and temperature. The main contribution of this work is to validate the utilization of the two-diode model as a better representative model of a PV cell. This is important particularly at low levels of solar irradiance and temperature.”, “author” : { “dropping-particle” : “”, “family” : “Abdulal”, “given” : “Fayad”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Anani”, “given” : “Nader”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Bowring”, “given” : “Nick”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “2014 9th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2014”, “id” : “ITEM-4”, “issue” : “1”, “issued” : { “date-parts” : “2014” }, “page” : “856-860”, “title” : “Comparative modelling and parameter extraction of a single- and two-diode model of a solar cell”, “type” : “article-journal” }, “uris” : “http://www.mendeley.com/documents/?uuid=1fb63cde-fae2-4444-899b-10c921bd59e8” }, { “id” : “ITEM-5”, “itemData” : { “DOI” : “10.1016/j.solener.2013.01.010”, “ISBN” : “0038-092X”, “ISSN” : “0038092X”, “abstract” : “Maximum power point of solar cells can be extracted by knowing the values of the electrical parameters. The validity of the obtained result depends on the accuracy of the model parameters. Hence, it is important to use a superior optimization technique to identify the optimal values of the parameters. Recently, a metaheuristic optimization algorithm, bird mating optimizer (BMO), has been devised which tries to metaphorically imitate the mating strategies of bird species. BMO employs several searching patterns to explore the region under consideration. This ability helps the algorithm to maintain the diversity and avoid premature convergence, and therefore, get close to the global solution. In this paper, the electrical parameters of a 57. mm diameter commercial (RTC France) silicon solar cell are identified using BMO. The optimal parameters are then used to extract the maximum power point of the system. The accuracy of the proposed parameter identification approach is compared with the results found by the other optimization techniques. Simulation results accentuate the superior potential of BMO algorithm. u00a9 2013 Elsevier Ltd.”, “author” : { “dropping-particle” : “”, “family” : “Askarzadeh”, “given” : “Alireza”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Rezazadeh”, “given” : “Alireza”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Solar Energy”, “id” : “ITEM-5”, “issued” : { “date-parts” : “2013” }, “page” : “123-133”, “title” : “Extraction of maximum power point in solar cells using bird mating optimizer-based parameters identification approach”, “type” : “article-journal”, “volume” : “90” }, “uris” : “http://www.mendeley.com/documents/?uuid=87405ac5-aae8-48d3-ad64-2bd3dd2086f6” }, { “id” : “ITEM-6”, “itemData” : { “DOI” : “10.1016/j.renene.2016.10.010”, “ISSN” : “18790682”, “abstract” : “Photo-voltaic (PV) is a static medium to convert solar energy directly into electricity. In order to predict the performance of a PV system before being installed, a reliable and accurate model design of PV systems is essential. To validate the design of a PV system like maximum power point (MPP) and micro-grid system through simulation, an accurate solar PV model is required. However, information provided by manufacturers in data sheets is not sufficient for simulating the characteristic of a PV module under normal as well as under diverse environmental conditions. In this paper, a particle swarm optimization (PSO) technique with binary constraints has been presented to identify the unknown parameters of a single diode model of solar PV module. Multi-crystalline and mono-crystalline technologies based PV modules are considered under the present study. Based on the results obtained, it has been found that PSO algorithm yields a high value of accuracy irrespective of temperature variations.”, “author” : { “dropping-particle” : “”, “family” : “Bana”, “given” : “Sangram”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Saini”, “given” : “R. P.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Renewable Energy”, “id” : “ITEM-6”, “issued” : { “date-parts” : “2017” }, “page” : “1299-1310”, “publisher” : “Elsevier Ltd”, “title” : “Identification of unknown parameters of a single diode photovoltaic model using particle swarm optimization with binary constraints”, “type” : “article-journal”, “volume” : “101” }, “uris” : “http://www.mendeley.com/documents/?uuid=6c83a9c0-3642-4dce-b01e-c0efe56d76cc” } , “mendeley” : { “formattedCitation” : “7, 9u201313”, “manualFormatting” : “11u201315”, “plainTextFormattedCitation” : “7, 9u201313”, “previouslyFormattedCitation” : “7, 11u201315” }, “properties” : { }, “schema” : “https://github.com/citation-style-language/schema/raw/master/csl-citation.json” }11–15. To design an efficient SPV system is mainly depends on the DC parameters which are generally not given in the any manufactures datasheets. It is essential to extract those unknown DC parameters accurately from the known parameters using the manufactures datasheets by this above mentioned drawbacks of SPV are reducedADDIN CSL_CITATION { “citationItems” : { “id” : “ITEM-1”, “itemData” : { “DOI” : “10.1016/j.asoc.2017.06.044”, “ISSN” : “15684946”, “abstract” : “The grey wolf optimizer (GWO) is a new efficient population-based optimizer. The GWO algorithm can reveal an efficient performance compared to other well-established optimizers. However, because of the insufficient diversity of wolves in some cases, a problem of concern is that the GWO can still be prone to stagnation at local optima. In this article, an improved modified GWO algorithm is proposed for solving either global or real-world optimization problems. In order to boost the efficacy of GWO, Lu00e9vy flight (LF) and greedy selection strategies are integrated with the modified hunting phases. LF is a class of scale-free walks with randomly-oriented steps according to the Lu00e9vy distribution. In order to investigate the effectiveness of the modified Lu00e9vy-embedded GWO (LGWO), it was compared with several state-of-the-art optimizers on 29 unconstrained test beds. Furthermore, 30 artificial and 14 real-world problems from CEC2014 and CEC2011 were employed to evaluate the LGWO algorithm. Also, statistical tests were employed to investigate the significance of the results. Experimental results and statistical tests demonstrate that the performance of LGWO is significantly better than GWO and other analyzed optimizers.”, “author” : { “dropping-particle” : “”, “family” : “Heidari”, “given” : “Ali Asghar”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Pahlavani”, “given” : “Parham”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Applied Soft Computing Journal”, “id” : “ITEM-1”, “issued” : { “date-parts” : “2017” }, “page” : “115-134”, “publisher” : “Elsevier B.V.”, “title” : “An efficient modified grey wolf optimizer with Lu00e9vy flight for optimization tasks”, “type” : “article-journal”, “volume” : “60” }, “uris” : “http://www.mendeley.com/documents/?uuid=19dc4393-887e-4059-a48d-e533598ce196” }, { “id” : “ITEM-2”, “itemData” : { “DOI” : “10.1016/j.swevo.2017.02.005”, “ISSN” : “22106502”, “abstract” : “In order to carry out precise performance investigations and control studies on photovoltaic (PV) systems, an accurate model is always desired. In this work, a new and powerful metaheuristic optimization technique known as Evaporation Rate based Water Cycle Algorithm (ER-WCA) has been explored for effective parameters estimation of PV cell/module. Single and double diode based models of PV cell and single diode based model of PV module have been successfully identified from their respective single I-V non-linear characteristics and the modeling performance of ER-WCA, assessed in terms of root mean square error, mean absolute error and mean relative error, between computed and experimental data, is found to be superior to the several recent prominent published works particularly the modeling of a single diode based PV module. Furthermore, the PV module modeling capability of ER-WCA under varying temperature and irradiation conditions is also analysed and it is found to be effective, proving its practical applications. Based on the presented detailed investigation, it is concluded that ER-WCA is a promising optimization technique for PV cell/module identification.”, “author” : { “dropping-particle” : “”, “family” : “Kler”, “given” : “Dhruv”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Sharma”, “given” : “Pallavi”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Banerjee”, “given” : “Ashish”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Rana”, “given” : “K. P.S.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Kumar”, “given” : “Vineet”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Swarm and Evolutionary Computation”, “id” : “ITEM-2”, “issued” : { “date-parts” : “2017” }, “page” : “93-110”, “publisher” : “Elsevier”, “title” : “PV cell and module efficient parameters estimation using Evaporation Rate based Water Cycle Algorithm”, “type” : “article-journal”, “volume” : “35” }, “uris” : “http://www.mendeley.com/documents/?uuid=56004696-1742-4532-9f53-589612f2ebbd” }, { “id” : “ITEM-3”, “itemData” : { “DOI” : “10.1016/j.solener.2017.10.063”, “ISSN” : “0038092X”, “abstract” : “Today, photovoltaic (PV) systems are generating a significant share of electric power. Parameter estimation of photovoltaic cells and modules is a hot research topic and plays an important role in modelling PV systems. This problem is commonly converted into an optimisation problem and is solved by metaheuristic optimisation algorithms. Among metaheuristic optimisation algorithms, particle swarm optimisation (PSO) is a popular leader-based stochastic optimisation algorithm. However, premature convergence is the main drawback of PSO which does not let it to provide high-quality solutions in multimodal problems such as PV cells/modules parameter estimation. In PSO, all particles are pulled toward the leader, so the leader can significantly affect collective performance of the particles. A high-quality leader may pull all particles toward good regions of search space and vice versa. Therefore, in this research, an improved PSO variant, with enhanced leader, named as enhanced leader PSO (ELPSO) is used. In ELPSO, by enhancing the leader through a five-staged successive mutation strategy, the premature convergence problem is mitigated in a way that more accurate circuit model parameters are achieved in the PV cell/module parameter estimation problem. RTC France silicon solar cell, STM6-40/36 module with monocrystalline cells and PVM 752 GaAs thin film cell have been used as the case studies of this research. Parameter estimation results for various PV cells and modules of different technologies confirm that in most of the cases, ELPSO outperforms conventional PSO and a couple of other state of the art optimisation algorithms.”, “author” : { “dropping-particle” : “”, “family” : “Rezaee Jordehi”, “given” : “A.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Solar Energy”, “id” : “ITEM-3”, “issue” : “March 2017”, “issued” : { “date-parts” : “2018” }, “page” : “78-87”, “publisher” : “Elsevier”, “title” : “Enhanced leader particle swarm optimisation (ELPSO): An efficient algorithm for parameter estimation of photovoltaic (PV) cells and modules”, “type” : “article-journal”, “volume” : “159” }, “uris” : “http://www.mendeley.com/documents/?uuid=c46b4955-6dbb-4d0c-8afd-c4674ac94e04” }, { “id” : “ITEM-4”, “itemData” : { “ISBN” : “9781509045303”, “abstract” : “Energy extraction from the solar irradiance by the use of solar cell Module is very important in the field of renewable energy. The Electrical properties derived from the non-linear Current-voltage (I-V) curve of the solar cell module play a vital role in the exploration of device performance and overall efficiency. In this paper, two recently developed heuristic algorithm Cuckoo search optimization and Firefly algorithm has been applied for the extraction of parameters of double diode lumped electrical circuit model of a solar cell. The study carried out using data set generated from a MATLAB/SIMULINK model of a PV module. Results suggest that Cuckoo Search and Firefly algorithm outperform other popular evolutionary computing techniques like DE and PSO in terms of convergence speed and excellent final solution. The curves obtained from the extracted values using FA and CS are identical with those of the experimental one at different environmental conditions validates the purpose of this study which is novel also in the solar energy domain.”, “author” : { “dropping-particle” : “”, “family” : “Chakrabarti”, “given” : “Tapas”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Sharma”, “given” : “Udit”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Chakrabarti”, “given” : “Tyajodeep”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Sarkar”, “given” : “Subir Kumar”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “id” : “ITEM-4”, “issued” : { “date-parts” : “2016” }, “title” : “Extraction of Efficient Electrical Parameters of Solar Cell using Firefly and Cuckoo Search Algorithm”, “type” : “article-journal” }, “uris” : “http://www.mendeley.com/documents/?uuid=7dec636e-2a4c-4923-a84d-4e6b019ea99e” }, { “id” : “ITEM-5”, “itemData” : { “DOI” : “10.1016/j.solener.2017.09.046”, “ISSN” : “0038092X”, “abstract” : “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.”, “author” : { “dropping-particle” : “”, “family” : “Kumar”, “given” : “Manish”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Kumar”, “given” : “Arun”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Solar Energy”, “id” : “ITEM-5”, “issue” : “June”, “issued” : { “date-parts” : “2017” }, “page” : “192-206”, “publisher” : “Elsevier”, “title” : “An efficient parameters extraction technique of photovoltaic models for performance assessment”, “type” : “article-journal”, “volume” : “158” }, “uris” : “http://www.mendeley.com/documents/?uuid=1eaf53b9-8a7c-46d4-9735-94b1d63a4227” }, { “id” : “ITEM-6”, “itemData” : { “DOI” : “10.1016/j.enconman.2017.04.042”, “ISSN” : “01968904”, “abstract” : “Building highly accurate model for solar cells and photovoltaic (PV) modules based on experimental data is vital for the simulation, evaluation, control, and optimization of PV systems. Powerful optimization algorithms are necessary to accomplish this task. In this study, a new optimization algorithm is proposed for efficiently and accurately estimating the parameters of solar cells and PV modules. The proposed algorithm is developed based on the flower pollination algorithm by incorporating it with the Nelder-Mead simplex method and the generalized opposition-based learning mechanism. The proposed algorithm has a simple structure thus is easy to implement. The experimental results tested on three different solar cell models including the single diode model, the double diode model, and a PV module clearly demonstrate the effectiveness of this algorithm. The comparisons with some other published methods demonstrate that the proposed algorithm is superior than most reported algorithms in terms of the accuracy of final solutions, convergence speed, and stability. Furthermore, the tests on three PV modules of different types (Multi-crystalline, Thin-film, and Mono-crystalline) suggest that the proposed algorithm can give superior results at different irradiance and temperature. The proposed algorithm can serve as a new alternative for parameter estimation of solar cells/PV modules.”, “author” : { “dropping-particle” : “”, “family” : “Xu”, “given” : “Shuhui”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Wang”, “given” : “Yong”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Energy Conversion and Management”, “id” : “ITEM-6”, “issued” : { “date-parts” : “2017” }, “page” : “53-68”, “publisher” : “Elsevier Ltd”, “title” : “Parameter estimation of photovoltaic modules using a hybrid flower pollination algorithm”, “type” : “article-journal”, “volume” : “144” }, “uris” : “http://www.mendeley.com/documents/?uuid=6c987e31-857e-4b90-8915-d0ff1a889f1b” } , “mendeley” : { “formattedCitation” : “6, 14u201318”, “manualFormatting” : “16u201319”, “plainTextFormattedCitation” : “6, 14u201318”, “previouslyFormattedCitation” : “6, 9, 16u201319” }, “properties” : { }, “schema” : “https://github.com/citation-style-language/schema/raw/master/csl-citation.json” }16–19.

In this paper, an investigation is done for the parameters extraction of the five and seven unknown parameters for both methods (SDM ;DDM) at STC of three sorts of SPV modules which utilize different strategies, namely polycrystalline, monocrystalline and thin-film. Extraction of accurate parameters is done by Levenberg-Marquardt numerical iterative technique for both (SDM ; DDM) methods. Examination of different SPV module simulation (MATLAB SIMULINK) results (I-V) is plotted and compared for both methods under different techniques. The proposed work is to evaluate the accuracy of the two methods under various techniques for different SPV modules corresponding to the various temperature conditions.

Section II and section III portrays the methodology and analysis of SDM ; DDM of an SPV for the investigation. Examination of different SPV module simulation results (I-V) are plotted and compared for both methods under different techniques are discussed. The outcomes and discussions are presented in Section IV. Section V records the conclusions from the examination.

Methodology

An SPV cell is a semiconductor device that directly converts sunlight into electrical energy without using any mechanical rotating devices and it is free from environmental impacts. In this investigation extraction of parameters is done by two methods SDM and DDM respectively. In SDM, SPV cells are modeled as a current source in parallel with a nonlinear single diode to extract five unknown parameters from manufactures datasheetsADDIN CSL_CITATION { “citationItems” : { “id” : “ITEM-1”, “itemData” : { “DOI” : “10.1016/j.matcom.2015.10.008”, “ISSN” : “03784754”, “abstract” : “In this paper the identification of the single-diode model of photovoltaic (PV) generators operating in outdoor conditions has been carried out. The non-linear equation system, describing the PV source in five operating points, is re-written as an optimization problem and it is solved by using a genetic algorithm. The parameters of the single-diode model are evaluated for different combinations of irradiance and temperature conditions. Contrary to several approaches proposed in literature such analysis shows that all the parameters need to be adjusted with respect to the environmental conditions to reduce the errors in the current, power and energy predictions.”, “author” : { “dropping-particle” : “”, “family” : “Bastidas-Rodriguez”, “given” : “J. D.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Petrone”, “given” : “G.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Ramos-Paja”, “given” : “C. A.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Spagnuolo”, “given” : “G.”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Mathematics and Computers in Simulation”, “id” : “ITEM-1”, “issued” : { “date-parts” : “2017” }, “page” : “38-54”, “publisher” : “Elsevier Ltd”, “title” : “A genetic algorithm for identifying the single diode model parameters of a photovoltaic panel”, “type” : “article-journal”, “volume” : “131” }, “uris” : “http://www.mendeley.com/documents/?uuid=1dcf2441-35f3-415b-8b26-10c109f48c7d” }, { “id” : “ITEM-2”, “itemData” : { “DOI” : “10.1016/j.rser.2013.10.015”, “ISBN” : “1364-0321”, “ISSN” : “13640321”, “abstract” : “The paper offers a novel approach to parameter estimation of a single-diode solar cell/panel equivalent circuit, based on analysis of either technical characteristics supplied by the manufacturer or user-obtained experimental I-V curve. The derived model allows predicting the solar cell/panel output for arbitrary environmental conditions. The method combines a solution of an algebraic equations system with an optimization algorithm. The main advantage of the proposed method is that in order to obtain the required parameters of the model, minimal set of experimental data is required. In order to validate the feasibility of the proposed approach, several solar panels of different types from several manufacturers were analyzed. The results demonstrate 0.1-0.5% estimation precision when the Standard Operation Conditions data from the manufacturers’ datasheets are employed. u00a9 2013 Elsevier Ltd.”, “author” : { “dropping-particle” : “”, “family” : “Lineykin”, “given” : “Simon”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Averbukh”, “given” : “Moshe”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Kuperman”, “given” : “Alon”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Renewable and Sustainable Energy Reviews”, “id” : “ITEM-2”, “issued” : { “date-parts” : “2014” }, “page” : “282-289”, “publisher” : “Elsevier”, “title” : “An improved approach to extract the single-diode equivalent circuit parameters of a photovoltaic cell/panel”, “type” : “article-journal”, “volume” : “30” }, “uris” : “http://www.mendeley.com/documents/?uuid=e669b37d-4a47-4371-9e79-cbdc07196b56” }, { “id” : “ITEM-3”, “itemData” : { “DOI” : “10.1109/IRSEC.2014.7059778”, “ISBN” : “9781479973361”, “abstract” : “Recently solar power has increasingly been used to generate electricity worldwide through photovoltaic (PV) systems. The electrical performance of each PV module plays major role in maximum power transfer. In order to absorb the maximum power from such systems, optimal output voltage and current should be obtained from the I-V characteristics of previously developed models. It is fact that, this is a relatively uneasy task because manufacturer’s data sheet is confined to limited number of measured values. In this study, the hybrid genetic algorithms method is employed to extract basic parameters of the ideality factor and the parasitic resistances in the single diode model to transfer maximum power from a PV module to a resistive electrical load. Optimal parameters in the circuital model are found using the I-V characteristic of a silicon diode expressed by the Lambert W function. The results are meaningful and encouraging for maximum power transfer under certain conditions.”, “author” : { “dropping-particle” : “”, “family” : “Tutkun”, “given” : “Nedim”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Elibol”, “given” : “Erdem”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Maden”, “given” : “Dinu00e7er”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Proceedings of 2014 International Renewable and Sustainable Energy Conference, IRSEC 2014”, “id” : “ITEM-3”, “issued” : { “date-parts” : “2014” }, “page” : “554-558”, “title” : “Basic parameter extraction from an organic solar cell through the single diode model and a metaheuristic technique with the lambert W function”, “type” : “article-journal” }, “uris” : “http://www.mendeley.com/documents/?uuid=ac32056c-d75f-40f8-9f6f-07c1908b8be7” }, { “id” : “ITEM-4”, “itemData” : { “DOI” : “10.1016/j.solener.2017.12.054”, “ISSN” : “0038092X”, “abstract” : “A novel model-based technique is presented for maximum power point tracking (MPPT) of photovoltaic (PV) systems. In this paper, an exact single-diode circuit model without any simplification or approximation is considered. Using datasheet information, an adaptive identification technique is utilized to find the electrical parameters uniquely and precisely. After this offline identification scheme, an estimation of solar irradiation is achieved from real-time measurements of PV voltage and current. In the next step, the gradient function of power with respect to voltage is represented from strongly concave mapping between power and voltage. Since the nonlinear gradient consists the complex Lambert W-function, a mathematical formulation is derived to approximate it with conventional logarithmic functions. Finally, a gradient update law is derived to find the unknown optimal voltage value, which results in maximum power generation for any environmental condition. 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In DDM, SPV cells is modeled as a current source in parallel with two nonlinear diodes to extract seven unknown parameters from manufactures datasheetsADDIN CSL_CITATION { “citationItems” : { “id” : “ITEM-1”, “itemData” : { “DOI” : “10.1109/ICPDEN.2015.7084502”, “ISBN” : “9781479964598”, “abstract” : “Solar Energy is a clean and boundless energy source and the worldwide solar market demand is increasing for industrial and domestic purposes. The purpose of this paper is to show the comparison of Stochastic Method(Genetic Algorithm) over derivative methods. A mathematical development 3 is provided for the extraction of Solar Panel equivalent circuit parameters from datasheet values. The analytical approach is selected for the mathematical development as the initial-point vital for proper evaluation of the Parameters of the double diode Model of PV cells. 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Unlike previous methods, it does not rely on assumptions that cause the accuracy to be compromised. The key to this improvement is the implementation of a hybrid solution, i.e. by incorporating the analytical method with the differential evolution (DE) optimization technique. Three parameters, i.e. IPV, Io1, and Rpare computed analytically, while the remaining, a1, a2, Io2and Rsare optimized using the DE. To validate its accuracy, the proposed method is tested on three PV modules of different technologies: mono-crystalline, poly-crystalline and thin film. Furthermore, its performance is evaluated against two popular computational methods for the two-diode model. The proposed method is found to exhibit superior accuracy for the variation in irradiance and temperature for all module types. In particular, the improvement in accuracy is evident at low irradiance conditions; the root-mean-square error is one order of magnitude lower than that of the other methods. 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Single Diode Model (SDM)

In SDM, SPV cell is represented by current source connected in anti-parallel with a single nonlinear diode (D). The loss across the ohmic contact and the metal is represented by series resistance (Rs) and leakage current across the junction is represented by parallel resistance (Rp) are connected in parallel. The SDM is solved by outstanding single exponential Shockley diode equation and considering diffusion mechanism is represented by ideality factor (a) as shown in the figure (1).

The current-voltage (I-V) correlation is obtained by applying Kirchhoff’s current law (KCL) to the SDM and the output current is given by equation (1),

I=Iph-ID-Ip (1)

Fig. 1. Schematic diagram of a Solar Photo-voltaic cell by Single Diode Model (SDM).

Where ID is the current moving through the diode which initiates the nonlinear qualities of the solar PV cell and expressed by Shockley diode equation. The leakage current moving through the parallel resistor is given by Ip, Iph is the photo-voltaic current generated by the current source and total output current is ‘I’. Consequently, the output current expression can be composed in equation (2):

I=Iph-I0expqv+IRsaNskt-1-v+IRsRp (2)

From equation (2),

‘a’ is the ideality or quality factor,

‘k’ is the Boltzmann constant (1.38 * 10?23 J/ºK),

‘q’ is the electron charge (1.6 * 10?19 C),

‘Ns’ is the number of cells connected series in a SPV module,

‘Io’ is the reverse saturation current and ‘t’ is the cell temperature in Kelvin.

Due to the absence of the recombination losses in the depletion region, this makes the SDM cannot be modeled effectively in low irradiation conditions. To reduce such problem DDM is the best suitable method for low irradiation conditions by considering recombination losses.

Double Diode Model (DDM)

At lower irradiation conditions SDM method cannot be modeled effectively due to the absence of recombination losses, to overcome such drawback DDM method is considered. In DDM, SPV cell is represented by the current source connected in anti-parallel with two nonlinear diodes (D1 & D2). The DDM is solved by an outstanding double exponential Shockley diode equation. The ideality factors (a1) & (a2) represents the diffusion current and recombination space charge current respectively as shown in the figure (2).

Fig. 2. Schematic diagram of a Solar Photo-voltaic cell by Double Diode Model (DDM).

The current-voltage (I-V) correlation is obtained by applying Kirchhoff’s current law (KCL) to the DDM and the output current is given by equation (3),

I=Iph-ID1-ID2-Ip (3)

Where ID1 ; ID2 is the current moving through the diode D1 ; D2 which initiates the nonlinear qualities of the SPV cell and expressed by Shockley diode equation. Consequently, output current expression can be composed in equation (4);

I=Iph-I01expqv+IRsa1Nskt-1-I02expqv+IRsa2Nskt-1-v+IRsRp (4) From equation (2), ‘a1’ ; ‘a2’ are the ideality or quality factor for diode1 and diode2; ‘I01’ ; ‘I02’ are the reverse saturation current of the diffusion mechanism and recombination in space charge region diode1 and diode2. The obtained equations are considered for the following three operational conditions of the I-V curve, Open circuit condition where V=Voc ; I=0, Short circuit condition where V=0 ; I=ISC and Maximum Power Point (MPP) condition where V=Vm ; I=Im at STC.

Solution Techniques

Designing of an efficient SPV system is mainly depends on the DC parameters which are generally not given in the any manufactures datasheets. It is essential to extract those unknown parameters accurately from the known parameters using the manufactures datasheets, because of these unknown DC parameters are directly proportional to the efficiency of the SPV cell. It is necessary to extract accurate parameters using appropriate analytical or numerical techniques. In this paper, parameter extraction is done by analytical as well as numerical iterative methods and compared the same for different advanced SPV module. In numerical iterative techniques, Levenberg–Marquardt is adapted to extracting the DC unknown parameters accurately.

Analytical Technique For Parameters Extraction.

In this type of technique parameters extraction is done by analytically. The numerical iterative technique needs initial assumptions to extract accurate parameters, extracted parameters from the analytical are given input to the numerical iterative method.

Analytical Technique for SDM: The extraction of five unknown parameters from the SDM (I0, Iph, a, Rs ; Rp) is calculated by solving five equations (8-12). The following equations are obtained by considering three operational conditions of the I-V curve, Open circuit condition where V=Voc ; I=0, Short circuit condition where V=0 ; I=ISC and Maximum Power Point (MPP) condition where V=Vm ; I=Im at STC.

The following (5-7) are the assumptions are made for the simplicity of solving equations,

Xmoc(1,2)= expqVoca(1,2)Nskt (5)

Xm(1,2)= expqVm+ImRsa(1,2)Nskt (6)

Xmsc(1,2)= expqVoc+IscRsa(1,2)Nskt (7)

I0=VocIsc-Im-VmIscVocXm-VmXmoc (8)

Iph=VocIm+Is(VocXm-VmXmoc)Voc-Vm (9)

Parallel resistance (Rp) and series resistance (Rs) is obtained from equation (1) at MPP conditions,

Rp=Vm+ImRsIph-Im-I0(Xm-1) (10)

Rs=VmIm-1qI0aNsktXm+1Rp (11)

a=NsAktq (12)

From above equations (8,9,10,11;12), five unknown (I0,Iph,Rp,Rs ; a ) parameters are calculated by analytically for SDM method.

Analytical Technique for DDM: The extraction of seven unknown parameters from the DDM method (I01,I02,Iph,a1,a2,Rs;Rp) is calculated by solving seven equations (13-19) by considering three operational conditions.

I01=VocIsc-Im-VmIscVocXm1-KXm2-VmXmoc1-KXmoc2 (13)

I02=t253.77I01 (14)

Iph=VocIm+I01(Voc(Xm1+KXm2)-Vm(Xmoc1-Xmoc2)Voc-Vm (15)

Parallel resistance (Rp) and series resistance (Rs) is obtained from equation (3) at MPP conditions,

Rp=Vm+ImRsIph-Im-I01Xm-1-I02(Xm2-1) (16)

Rs=VmIm-1qI01a1NsktXm1+qI02a2NsktXm2+1Rp (17)

a1=NsA1ktq (18)a2=NsA2ktq (19)From above equations (13-19), seven unknown (I01,I02,Iph,Rs,Rp,a1;a2) parameters are calculated by analytically for DDM method.

Extracted five and seven unknown parameters for both methods (SDM ; DDM) from the analytical technique is given input to the numerical iterative technique. The numerical iterative technique requires suitable input assumptions to extract accurate parameters for both SDM and DDM methods.

Numerical Iterative Technique for Parameters Extraction.

In this type of technique parameters extraction is done by numerically. The numerical iterative technique needs suitable initial assumptions to extract accurate parameters, extracted parameters from the analytical output are made suitable input assumptions to the numerical iterative method.

Numerical Iterative Technique for SDM: The extraction of five unknown parameters from the SDM method (I0, Iph, a, Rs ; Rp) is calculated by solving five non-linear equations.These five non-linear equations consist of five unknown parameters solved by MATLAB with fsolve tool which is embedded with “Levenberg-Marquardt” algorithm. The following equations (20, 22 ; 23) is obtained by considering three operational conditions of the I-V curve, Open circuit condition where V=Voc ; I=0, Short circuit condition where V=0 ; I=ISC and Maximum Power Point (MPP) condition where V=Vm ; I=Im at STC.

Iph=I0expVocNsaVt-1+VocRp (20)

Where,

Vt= ktq (21)

Isc=I0expVocNsaVt-expIscRsNsaVt+Voc-IscRsRp (22)

Im1+RsRp=I0expVocNsaVt-expVm+ImRsNsaVt+Voc-VmRp (23)

The following equation (24) is obtained by differentiating equation (2) with respect to the voltage,

dIdV=-I0NsaVt1+RsdIdVexpV+IRsNsaVt-1Rp1+RsdIdV (24)

Equation (25) is obtained by substituting the equation (26) into equation (25).

ImVm=I0NsaVt1-RsImVm expVm+ImRsNsaVt+1Rp1-RsImVm (25)

Where,

dIdV=-ImVm (26)

1Rp-Rs=1Rp+I0NsaVtexpIscRsNsaVt (27)

Equation (51), derivative of current respect voltage to the equation (48) during the short circuit condition. The five nonlinear equations (20, 22-24 ; 27) with five unknown parameters (I0,Iph,Rp,Rs ; a ) is solved by MATLAB with fsolve tool which is embedded “Levenberg-Marquardt” algorithm.

Numerical Iterative Technique for DDM: The extraction of seven unknown parameters from the DDM method (I01,I02,Iph,Rs,Rp,a1;a2) is calculated by solving six non-linear equations. These six non-linear equations consists of seven unknown parameters solved by MATLAB with fsolve tool which is embedded with “Levenberg-Marquardt” algorithm. The following equations (28, 29 ; 30) is obtained by considering three operational conditions of the I-V curve, Open circuit condition where V=Voc ; I=0, Short circuit condition where V=0 ; I=ISC and Maximum Power Point (MPP) condition were V=Vm ; I=Im at STC.

Iph=I01expVocNsa1Vt-1+I02expVocNsa2Vt-1+VocRp (28)

Isc=I01expVocNsa1Vt-expIscRsNsa2Vt+I02expVocNsa2Vt-expIscRsNsa2Vt+Voc-IscRsRp (29)

Im1+RsRp=I01expVocNsa1Vt-expVm+ImRsNsa1Vt+I02expVocNsa2Vt-expVm+ImRsNsa2Vt+Voc-VmRp (30)

The following equation (55) is obtained by differentiating equation (4) with respect to the voltage,

dIdV=-I01Nsa1Vt1+RsdIdVexpV+IRsNsa1Vt-I02Nsa2Vt1+RsdIdVexpV+IRsNsa2Vt-1Rp1+RsdIdV (31)

Equation (32) is obtained by substituting the equation (26) into equation (26).

ImVm=I01Nsa1Vt1-RsImVm expVm+ImRsNsa1Vt+I02Nsa2Vt1-RsImVm expqVm+ImRsNsa2Vt+1Rp1-RsImVm (32)

1Rp-Rs=1Rp+I01Nsa1VtexpIscRsNsa1Vt+I02Nsa2VtexpIscRsNsa2Vt 33

Equation (57), derivative of current respect voltage to the equation (55) during the short circuit condition.

a1+a2=3 (34)

The seven nonlinear equations (28-34) with seven unknown parameters (I01,I02,Iph,Rs,Rp,a1;a2) is solved by MATLAB with fsolve tool which is embedded with “Levenberg-Marquardt” algorithm. These seven nonlinear equations is solved by suitable input assumption from the analytical technique.

Different types of spv module technical specifications under stc conditions.

Parameters ST40 (Thin Film) SM55 (Mono-Crystalline) S75 (Poly-Crystalline)

Isc (A) 2.68 3.45 4.7

Voc (V) 23.3 21.7 21.6

Im (A) 2.41 3.15 4.26

Vm (V) 16.6 17.4 17.6

Pmax(W) 40 55 75

KV (mV/ 0C) 100 -76 -76

KI (mA/ 0C) 0.35 1.4 2

Ns 36 36 36

Fig. 3. Current-Voltage (I-V) characteristics of Single Diode Model (SDM) and Double Diode Model (DDM) for S75 Poly-Crystalline SPV module by Varying irradiation with fixed temperature (250C).

Extracted single diode model (sdm) parameters of the projected and available modules for different SPV modules.

Model Parameters S75 (Poly-Crystalline) SM55 (Mono-Crystalline) ST40 (Thin Film)

Projected Sakaros27 (2013) Yong Wang18 (2017) Projected Sakaros (2013) Yong Wang (2017) Projected Sakaros (2013) Yong Wang (2017)

Iph (A) 4.7 4.715 4.69 3.45 3.453 3.403 2.68 2.7 2.7

I0(A) 1.76E-06 9.19E-08 2.42E-07 1.06E-06 9.72E-08 1.22E-07 1.41E-07 3.46E-07 8.25E-07

a 1.58 1.31 1.22 1.56 1.338 1.08 1.28 1.36 1.25

Rs(?) 0.05 0.2 0.25 0.19 0.3 0.47 1.42 1.3 1.29

Rp(?) 198.45 179 373.18 408.81 350 455.66 952.87 250 223.41

RMSE 0.0184 ? 0.0253 0.0091 ? 0.0146 0.0127 ? 0.0188

Extracted double diode model (ddm) parameters of the projected and available modules for different SPV modules.

Model Parameters S75 (Poly-Crystalline) SM55 (Mono-Crystalline) ST40 (Thin Film)

Projected TaheriADDIN CSL_CITATION { “citationItems” : { “id” : “ITEM-1”, “itemData” : { “DOI” : “10.1016/j.solmat.2010.09.023”, “ISBN” : “0927-0248”, “ISSN” : “09270248”, “abstract” : “This paper proposes an improved modeling approach for the two-diode model of photovoltaic (PV) module. The main contribution of this work is the simplification of the current equation, in which only four parameters are required, compared to six or more in the previously developed two-diode models. Furthermore the values of the series and parallel resistances are computed using a simple and fast iterative method. To validate the accuracy of the proposed model, six PV modules of different types (multi-crystalline, mono-crystalline and thin-film) from various manufacturers are tested. The performance of the model is evaluated against the popular single diode models. It is found that the proposed model is superior when subjected to irradiance and temperature variations. In particular the model matches very accurately for all important points of the IV curves, i.e. the peak power, short-circuit current and open circuit voltage. The modeling method is useful for PV power converter designers and circuit simulator developers who require simple, fast yet accurate model for the PV module. u00a9 2010 Elsevier B.V. All rights reserved.”, “author” : { “dropping-particle” : “”, “family” : “Ishaque”, “given” : “Kashif”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Salam”, “given” : “Zainal”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Taheri”, “given” : “Hamed”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “container-title” : “Solar Energy Materials and Solar Cells”, “id” : “ITEM-1”, “issue” : “2”, “issued” : { “date-parts” : “2011” }, “page” : “586-594”, “publisher” : “Elsevier”, “title” : “Simple, fast and accurate two-diode model for photovoltaic modules”, “type” : “article-journal”, “volume” : “95” }, “uris” : “http://www.mendeley.com/documents/?uuid=ed87b01a-01c4-4298-8bd6-45726e4ced12” } , “mendeley” : { “formattedCitation” : “28”, “plainTextFormattedCitation” : “28”, “previouslyFormattedCitation” : “29” }, “properties” : { }, “schema” : “https://github.com/citation-style-language/schema/raw/master/csl-citation.json” }28 (2011) GurjarADDIN CSL_CITATION { “citationItems” : { “id” : “ITEM-1”, “itemData” : { “author” : { “dropping-particle” : “”, “family” : “Babu”, “given” : “B Chitti”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” }, { “dropping-particle” : “”, “family” : “Gurjar”, “given” : “Suresh”, “non-dropping-particle” : “”, “parse-names” : false, “suffix” : “” } , “id” : “ITEM-1”, “issue” : “4”, “issued” : { “date-parts” : “2014” }, “page” : “1156-1161”, “title” : “A Novel Simplified Two-Diode Model of Photovoltaic ( PV ) Module”, “type” : “article-journal”, “volume” : “4” }, “uris” : “http://www.mendeley.com/documents/?uuid=14b2c5d5-a578-4df1-a8d4-14618e8ce8f8” } , “mendeley” : { “formattedCitation” : “29”, “plainTextFormattedCitation” : “29”, “previouslyFormattedCitation” : “30” }, “properties” : { }, “schema” : “https://github.com/citation-style-language/schema/raw/master/csl-citation.json” }29 (2014) Projected Taheri (2011) Gurjar (2014) Projected Taheri (2011) Gurjar (2014)

Iph (A) 4.69 4.7 4.7 3.44 3.45 3.45 2.63 2.68 2.68

I01 (A) 3.01E-10 3.39E-10 1.23E-05 2.01E-10 2.23E-10 1.43E-05 2.60E-11 3.07E-11 1.18E-03

I02 (A) 1.70E-09 3.39E-10 3.18E-05 2.59E-09 2.23E-10 3.70E-05 4.63E-10 3.07E-11 3.07E-03

a1 1.25 1 1.82 1.011 1 1.89 1.14 1 3.26

a2 2.293 1.3 3.36 2.174 1.3 3.65 2.028 1.3 22.44

Rs(?) 0.0306 0.27 0 0.0475 0.48 0 0 1.71 0

Rp(?) 49.99 84.38 ? 80.3 146.43 ? 68.68 198.94 ?

RMSE 0.0325 0.0774 0.1434 0.043 0.045 0.1333 0.0580 0.0778 0.1334

Results and discussion

Extraction of DC parameters is done for both (SDM ;DDM) methods at Standard Test Conditions (STC) of three sorts of SPV modules which utilize different strategies, namely Poly-Crystalline (S75), Monocrystalline (SM55) and Thin-film (ST40). The technical specifications of the above mentioned different types of standard type of SPV modules is given in the Table I. Examination of different SPV module simulation (MATLAB SIMULINK) results (I-V) are plotted and compared for both methods under different techniques.

The extracted five unknown parameters from SDM using projected technique is compared with the two existing techniques (Sakaros(2013) ; Yong Wang(2017)) as shown in the figures (4, 5 ; 6). Table II represents the extracted accurate five parameters from the projected technique. The extracted seven unknown parameters from DDM using projected technique is compared with the two existing techniques (Taheri (2011) ; Gurjar (2014)) as shown in the figures (7, 8 ; 9). Table III represents the extracted accurate seven parameters from the projected technique.

The Comparison of the projected and existing techniques are done for two cases. In the 1st case, Current-Voltage (I-V) characteristic is plotted for four different (250, 500, 750 ; 1000 W/m2) irradiation conditions keeping temperature (250C) constant because of the short circuit current(Isc) directly depends on the irradiation level shown in the figure (4(a), 5(a) ; 6(a)). In the 2nd case, Current-Voltage characteristic is plotted for four different temperature (25, 35, 45 ; 55)0C conditions keeping irradiation (1000 W/m2) constant because the output from the SPV decreases when the cell temperature increased beyond the certain conditions as shown in the figure (4(b), 5(b) ; 6(b)). In both case, there is a difference between the open circuit voltage for projected and two existing techniques in all irradiation condition. The projected technique is leading in all the three different types of SPV modules as compared to the existing techniques this is because of the accurate DC parameters. This is due to the Rp ; Rs, the value of Rp is generally high in terms of K? and Rs is almost near to 0?. The parallel resistance (Rp) which effects slope of the curve between short circuit current point and MPP. The series resistance (Rs) which effects slope of the curve between open circuit voltage point and MPP. In the projected technique for both model, the value of the Rp and Rs is obtained much lower than the two existing techniques. During the low and high irradiation conditions DDM works more efficient than the SDM. This makes projected technique is more accurate and reliable for both methods as compared to the two existing techniques.

Conclusion

The investigation is done for different advances of Solar Photovoltaic (SPV) modules, utilizing the five parameters from Single Diode Model (SDM) and seven parameters from Double Diode Model (DDM) methods. In this examination, extraction of accurate parameters is done by Levenberg-Marquardt (LM) numerical iterative techniques for both (SDM ; DDM) methods at Standard Test Conditions (STC) of three sorts of SPV modules which utilize different strategies, namely polycrystalline, monocrystalline and thin-film. From the above investigation, it shows that the DDM method works much more superior than the SDM in all irradiation specifically

(a) (b)

Fig. 4. Current-Voltage (I-V) characteristics of Single Diode Model (SDM) for ST40 Thin-film PV module, (a) Varying irradiation with fixed temperature (250C) and (b) Varying temperature with fixed irradiation (1000 Wm2).

(a) (b)

Fig. 5. Current-Voltage (I-V) characteristics of Single Diode Model (SDM) for SM55 Mono-Crystalline PV module, (a) Varying irradiation with fixed temperature (250C) and (b) Varying temperature with fixed irradiation (1000 Wm2).

(a) (b)

Fig. 6. Current-Voltage (I-V) characteristics of Single Diode Model (SDM) for S75 Poly-Crystalline PV module, (a) Varying irradiation with fixed temperature (250C) and (b) Varying temperature with fixed irradiation (1000 Wm2).

(a) (b)

Fig. 7. Current-Voltage (I-V) characteristics of Double Diode Model (DDM) for ST40 Thin-film PV module, (a) Varying irradiation with fixed temperature (250C) and (b) Varying temperature with fixed irradiation (1000 Wm2).

(a) (b)

Fig. 8. Current-Voltage (I-V) characteristics of Double Diode Model (DDM) for SM55 Mono-Crystalline PV module, (a) Varying irradiation with fixed temperature (250C) and (b) Varying temperature with fixed irradiation (1000 Wm2).

(a) (b)

Fig. 9. Current-Voltage (I-V) characteristics of Double Diode Model (DDM) for S75 Poly-Crystalline PV module, (a) Varying irradiation with fixed temperature (250C) and (b) Varying temperature with fixed irradiation (1000 Wm2).

during low irradiation conditions. The projected technique is more reliable, accurate and least execution time. Examination of different SPV module simulation (MATLAB SIMULINK) results (I-V) are plotted and compared for both methods under different techniques.

Acknowledgement

This work is carried out at the Research Centre, Dept. of Electrical ; Electronics Engineering, Malnad College of Engineering, Hassan, India, affiliated to VTU, Belagavi, Karnataka.

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