Researches On Measuring Model Of Solar Cell’s Performance Parameters

Solar energy is a green energy of sustainable use. With the increasing shortage of energytoday, photovoltaic power generation system, one of the main forms to develop and utilize solarenergy,has been valued by national academics, business and governments for its safety,pollutionlessness, without geographical restrictions, and many other advantages. Photovoltaicindustry is developing at a high speed.Solar cell is the basic unit to converse light energy which is collected by photovoltaic powergeneration system into electric energy. In the research of production and application of solar cell, itis necessary to carry on a large number of optical, electrical and other tests for solar cell’sperformance and reliability. The five-parameter exponential model is the macro-features of solarcell’s current-voltage (I-V) characteristics, it has specific meaning which contains abundantinformation of solar cells performance . it has become an important tool for testing and analysis ofsolar cell’s performance and it is widely used in solar cell materials, structure, manufacturingprocess and the design and analysis of application system.The five-parameter model is a typical nonlinear transcendental equation. Direct method toextract the five model’s parameters is lacked. it is required to extract the accurate parameters fromthe I-V characteristics curves measured under some fixed conditions of temperature andillumination. Many extraction methods have been presented by the researchers, such as exponentialmodel analysis algorithm, Quasi-Monte-Carlo algorithm, Adaptative Quasi-Monte-Carlo algorithm,etc. As the solar cell’s I-V characteristics shows a high degree of non-linear with irradiance,temperature and other environmental parameters change, these methods have the shortage ofcomputational complexity and low accuracy, sensitivity to noise, poor robustness .Based on thefive-parameter model, aiming at the problems of quickly extracting performance parameters forsolar cell’s test and sorting system , this paper studies on the numerical analysis of the solar cell’sI-V characteristics curves and measuring model of solar cell’s performance parameters. Therelated research work and main context are presented as follows:⑴the numerical analysis of solar cell’s I-V characteristics curvesThe method of numerical analysis for solar cell’s model parameters extraction is a method bysolving nonlinear equation group obtained through bringing testing I、V data points into the modelequation, the objective is to get the approximate solutions of the model parameters by iterativemethod. This paper presents an extraction algorithm for solar cell’s model parameters based on the modified Gauss-Newton method. The algorithm is introduced Lambert W function to transformthe implicit transcendental equation into an explicit expression form of current and voltage,reducing the difficulty of solving model parameters and the complexity of calculation by usingLambert W function’s computational performance.⑵extraction for solar cell’s model parameters based upon hybrid genetic algorithmThe numerical analysis method used in the extraction of the parameters of solar cell’s modeldepends on the gradient info, thus there exists some shortcomings, for instance, it tends to seek thepartial optimal solutions. Besides, it exerts a very demanding requirement for the initial values ofthese parameters and the computational steps. A hybrid genetic algorithm(GA) method based ondouble population is presented to solve the problem of the sensitivity to the minor changes in thetesting data. In the process of searching optimal solutions, two populations are generated. One isgenerated by using the improved self-adaptive genetic algorithm which emphasizes global search.The self-adaptively adjusted cross and variation probabilities, which are based on the populationvariety evaluation functions, can guarantee the population variability at the most. The other one isformed by the modified Gauss-Newton algorithm, which puts emphasis on partial search. Eachpopulation has different controlling parameters and initial values, the population of the newgeneration is generated according to the evaluation of adaptability function. Typical testingfunctions are chosen to test and verify the hybrid genetic algorithm, the results show that thehybrid genetic algorithm effectively uses the characteristics of local search and global search,which numerical analysis algorithms and genetic algorithms are good at respectively, thusimproving the computational performance of the genetic algorithm.The algorithm presented here is based upon a hybrid genetic algorithm, and is applied in theparameters extraction of solar cell’s model. It uses the characteristics of the voltage-current plotsof the solar cell and the empirical data relevant to their parameters to determine the search scopesof these parameters, and extract these parameters employing the hybrid genetic algorithm. Also,the testing data for I-V characteristics of single solar cell and modules and the parameter-extractionalgorithms involved reported in early literatures are analyzed and compared experimentally. Theresults indicate that the presented algorithm, which is based on a hybrid genetic algorithm, hasadvantages over these parameter-extraction algorithms reported earlier. Or rather, the specificationsobtained through the statistical analysis of curve-fitting I-V curves of the parameters obtained usingthe presented algorithm are better than those given by earlier algorithms.⑶testing data correction and modeling for solar cell’s I-V characteristicsDuring solar cell’s test, as the limit of uncertain factors such as the measurement error of I-Vcharacteristics testing equipment , the control accuracy of environmental conditions as irradiance,temperature, etc. and the temporal stability, the measured I, V data’s small changes is hard to avoid. In order to reduce the influence of uncertain factors on solar cell’s model parameters extraction, thepaper extract the Standard Testing Condition’s (STC) model parameters using solar cell’s modelparameters extraction algorithm based on hybrid genetic algorithm on the basis of discussing andanalyzing the change relations between sun cell’s model parameters with the change of irradianceand temperature.The paper presents a set of testing data correction models for solar cell’s I-V characteristicsbased on the morphological characteristics of I-V characteristics curves and a set of semi-empiricalformula. It can correct the testing data and deliver them to the STC ’s data according to solar cell’smonitoring data for test condition of solar cell’s I-V characteristics testing system using thecorrection model. A series of testing data for solar cell’s I-V characteristics curves and themonitoring data in the test are used for the modeling, It can identify the correction modelparameters using the hybrid genetic algorithm. Verification test results of the correction modelshow that: the correction model can correct testing data to the STC ’s data under different testingconditions for the same kind of material and the same process of solar cells, meanwhile, achieve ahigher accuracy.⑷solar cell’s performance parameters detection algorithm and verification testThe paper presents a solar cell’s performance parameters detection algorithm which is suitablefor the solar cell sorting system based on testing data correction model for solar cell’s I-Vcharacteristics, It uses data correction model to correct the testing data and deliver them to the STC’s, then, calculates the cell’s model parameters with the solar cell’s model parameter parsingalgorithm directly.Solar cell’s model parameters parsing algorithm, which uses solar cell model’s explicitexpression form of current and voltage , the mathematical characteristics of special point(maximum power point, point of open circuit voltage, short circuit current point) on I-V curves andconstitutes the five simultaneous equations, calculates solar cell’s model parameters directlythrough solving these equations. This paper uses manufacturers’data to test and verify solar cellmodel parameters parsing algorithm.For solar cell testing and sorting system, this paper verifies the solar cell’s performanceparameters detection algorithm using the data for solar cell I-V characteristic curve and monitoringdata of testing conditions.