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14 th European …, 1997
The performance of different search/fitting algorithms and error criteria for recovering the parameters needed for the solar cell double exponential model are considered. Synthesised measurement data have been used to test the algorithms. Standard approaches, namely the Simplex and Marquardt-Levenberg algorithms, were compared with a hybrid algorithm for the most commonly applied error criteria: those of least squares and the area matching. The accuracy of the Marquardt-Levenberg algorithm employing a least squares criterion and of the hybrid algorithm (which was implemented with both error criteria) were found to be equally good. The Simplex routine performed better, but only if the initial parameter values chosen had to be in very close proximity to the real values, otherwise it significantly under-performs. In the presence of measurement error, the Simplex algorithm performs well compared with the other algorithms, but is still very sensitive to minor variations in the starting values. Overall, the method of choice is either the Marquardt-Levenberg algorithm in combination with a least squares criterion or the hybrid algorithm.
Shockley's Equation Fit Analyses for Solar Cell Parameters from I-V Curves
Some of the technical problems that appear are obtaining solar cell parameters from I-V curve measurement data. One simple method is using linear graphical fit at zero current or voltage conditions. Although the accuracy of the obtained values is acceptable, other problems may arise regarding the number of parameters which could be obtained. We report a comparison between manual or graphical fit and fit using Shockley's equation. The single I-V curve under the lighting was inferred to obtain the intrinsic parameters of the solar cells' performance. The fittings were performed using the nonlinear equation of Shockley by determining some initial values of fittings such as R s , R sh , n, I 0 , I ph , and T. In the case of the Shockley equation fit, the iteration was performed several times to obtain the least possible inferred parameters. We have successfully obtained a better result of nonlinear Shockley fitting compared to the manual linear fit.
Non-empirical prediction of solar cell degradation in space
Semiconductor Science and Technology, 2005
We describe a way to obtain the degradation, induced by proton and electron irradiations, of solar cell parameters (short-circuit current, open-circuit voltage and maximum power) versus fluence, directly from the calculation of the characteristics of the cell and of the irradiation-induced recombination centres. The calculation can be performed for any energy of the irradiating particle and for any specific thicknesses and doping levels of the base and emitters. The validity of this approach is illustrated in the case of GaAs cells of different origins and extended to GaInP cells. It will allow us to deduce the degradation of multijunction cells.
Model physical parameters effects on real solar cell characteristics and power curve
Global Journal of Physical Chemistry, 2011
The climate change crisis and the running out of fossil resources are motivating the use of renewable energies. Solar energy is the main source of the renewable energies and photovoltaics is one of the main ways of photon conversion. This alternative energy is safe, clean and abundant. The purpose of this paper is the use of Maple software in: Determining, without any approximation, the model physical parameters of real photovoltaic solar cell as a basic element of photovoltaic conversion.
A Numerical Fitting-Based Compact Model: An Effective Way to Extract Solar Cell Parameters
Journal of Electronic Materials, 2020
We have developed an electrical circuit-based compact numerical fitting model to determine industry-related physical parameters of solar cells utilizing only 3-8 current-voltage coordinate points without any specific selection of an experimental coordinate axis. The proposed compact numerical fitting model was effectively tested to determine the peak power point, fill factor and efficiencies for organic and inorganic solar cells, as well as for solar panels. This research facilitates cost-effective energy management of solar modules and farms.
Parameterization of solar cells
The aggregation (sorting) of the individual solar cells into an array is commonly based on a single operating point on the I-V characteristic curve, An alternative approach for cell performance prediction and cell screening is provided by modeling the cell using an equivalent electrical circuit, in which the parameters involved are related to the physical phenomena in the device. These analytical models may be represented by a double exponential I-V characteristic with seven parameters_ by a double exponential model with five parameters, or by a single exponential equation with four or five parameters. In this article we address issues concerning methodologies for the determination of solar cell parameters based on measured data points of the I-V characteristic, and introduce a procedure for screening of solar cells for arrays. We show that common curve fitting techniques, e.g., least squares, may produce many combinations of parameter values while maintaining a good fit between the fitted and measured I-V characteristics of the cell. Therefore, techniques relying on curve fitting criteria alone cannot be directly used for cell parameterization. We propose a consistent procedure which takes into account the entire set of parameter values for a batch of cells. This procedure is based on a definition of a mean cell representing the batch, and takes into account the relative contribution of each parameter to the overall goodness of fit. The procedure is demonstrated on a batch of 50 silicon cells for Space Station Freedom. aspect of this collection of information, including suggestions/or reducing this burden, to Washington Headquarters Services, Di_tectorate for infoemation Operations and Repods,
Comparative study of the three equivalent models’ response of solar cell
ITM Web of Conferences
The photovoltaic cell is the main part of the solar energy conversion. The analysis of the response of the solar cell becomes a necessity. In the literature the solar cell is generally modeled by three equivalent electrical circuits. There are single diode, double diode and triple diodes model. the aim of this paper is to study the accuracy of each model. Therefore, by comparing the generated errors between each model and those obtained by measured data from RTC France solar cell, it was proven that the triple diodes model is the most precise among the three models. errors functions like RMSE and IAE were used to demonstrate this outcome.
A Review: extraction of solar cell modelling parameters
Energy from the sun is the best option for electricity generation as it is abundantly available everywhere and sustainable source. Advance of Photovoltaic (PV) technology in recent years has made solar energy one of the practical alternative energy sources available in the energy market. In order to make the PV energy more affordable and cost effective, major focus of the research community and industry is improvement on power efficiency of PV systems. Parameter extraction of solar cell plays a crucial role in the simulation and design calculation of PV system. The circuit model of a solar cell is non-linear and transcendental. Different methods under the categories of analytic, iterative, and evolutionary computational have been proposed to extract the parameters of solar cell in recent years. This paper presents a survey on parameter extraction of solar cell model and its recent advances.
Extraction of equivalent circuit parameters of solar cell: influence of temperature
The European Physical Journal Applied Physics, 2011
A new method to evaluate the five parameters of illuminated solar cells is described. The method is based on nonlinear least squares approach. On calculating the lsqcurvefit-function with constraints, between the experimental current-voltage I(V) characteristic and a theoretical arbitrary characteristic based on Lambert W-function. The used model is implemented as a MATLAB r script which yields the I(V) characteristics of the LILT under test. The model has been validated against by applying it to experimental I(V) characteristics. Some parameters of the model have been measured directly whereas others have been evaluated by means of direct computation on the data sheet or by means of best-fit on the measured data. The results have been compared and an analysis of the errors is presented.