Parameters extraction from commercial solar cells I–V characteristics and shunt analysis

Chen, Yifeng; Wang, Xuemeng; Li, Da; Hong, Rui; Shen, Hui

doi:10.1016/j.apenergy.2010.12.048

Cited by 105 publications

(36 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Fitting to integrated data offers the advantage of suppressing the effects of random measurement error. In contrast, [27] estimates parameters by fitting the derivative dI dV to measured data.…”

Section: Review Of Parameter Estimation Methodsmentioning

confidence: 99%

“…Error in the measurements of current and/or voltage may be amplified by numerical differentiation; consequently, the method in [27] fits polynomials to the IV data before differentiation to smooth the effects of measurement error, a step which is not necessary with integral methods. We first implemented and tested the method in [25].…”

Section: Review Of Parameter Estimation Methodsmentioning

confidence: 99%

“…(1 When formulating the system of equations it is common to adopt the approximation (e.g., [19], [23] [26], [27]) that consider the full range of each IV curve and make no simplifying approximations.…”

Section: Review Of Parameter Estimation Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Estimation of parameters for single diode models using measured IV curves

Hansen

2013

2013 IEEE 39th Photovoltaic Specialists Conference (PVSC)

View full text Add to dashboard Cite

-Many popular models for photovoltaic system performance (e.g., [1], [2]) employ a single diode model (e.g., [3]) to compute the IV curve for a module or string of modules for given irradiance and temperature conditions. Most commonly (e.g., [4]), parameters are determined using only current and voltage at short circuit, open circuit and maximum power from a single IV curve at standard test conditions, along with reported temperature coefficients. In contrast, module testing frequently records IV curves at a wide range of irradiance and temperature conditions, such as those specified in IEC 61853-1 [5], which, when available, should also be used to parameterize the performance model. We propose a parameter estimation method that makes use of the full range of available IV curves, and demonstrate the accuracy of the resulting performance model. Index Terms -semiconductor device modeling, photovoltaic systems, parameter estimation.

show abstract

Section: Review Of Parameter Estimation Methodsmentioning

confidence: 99%

Section: Review Of Parameter Estimation Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Estimation of parameters for single diode models using measured IV curves

Hansen

2013

2013 IEEE 39th Photovoltaic Specialists Conference (PVSC)

View full text Add to dashboard Cite

show abstract

“…Outliers usually have a great impact on the LSM fitting performance because the effect of these extreme data points is magnified by squaring the residuals. (2) two types of analytical solution methods [9][10][11][12][13][14][15][16]: one type is approximate analytical methods [9][10][11] which are commonly expressed in terms of elementary functions, the other type is exact analytical methods [12][13][14][15][16] based on the Lambert W-function which cannot be expressed in terms of elementary functions. However, the accuracy of analytical solution methods is at the cost of computation speed.…”

Section: Introductionmentioning

confidence: 99%

Parameter extraction of solar cell models using chaotic asexual reproduction optimization

Yuan

Liu³

2014

Neural Comput & Applic

View full text Add to dashboard Cite

To simulate solar cell systems or to optimize photovoltaic (PV) system performance, the estimation of solar cell model parameters is extremely crucial. In this paper, the parameter extraction of solar cell models is formalized as a multi-dimensional optimization problem, and an objective function is established minimizing the errors between the estimated and measured data. A novel chaotic asexual reproduction optimization (CARO) using chaotic sequence for global search is applied to this parameter extraction problem. All the seven or five parameters of solar cell models are extracted simultaneously using measured input-output data. The CARO has been tested with different solar cell models, i.e., double diode, single diode, and PV module. Comparison simulation results with other parameter extraction techniques show that the CARO signifies its potential as another optional method.

show abstract

“…At this time, a variety of methods are available for parameter estimation of these two electrical models. Some attempts in this field are focused on using classical analytical and numerical methods for parameter estimation based on minimization of a suitably chosen cost function [1,[5][6][7][8][9][10]. The main drawback of such classical methods is the high probability of falling in local optimums, besides the complexity of calculations.…”

Section: Introductionmentioning

confidence: 99%

Very accurate parameter estimation of single- and double-diode solar cell models using a modified artificial bee colony algorithm

Jamadi

Merrikh-Bayat

Bigdeli

2015

Int J Energy Environ Eng

104

View full text Add to dashboard Cite

This paper proposes an effective method for very accurate parameter estimation of single-and doublediode solar cell models. For this purpose, unknown parameters of model are estimated by minimization of an objective function using a new highly effective modified version of artificial bee colony (ABC) algorithm. The proposed algorithm is used for parameter estimation of single-and double-diode models and the results are compared, from different aspects, with recently developed related works (including those applied GA, CPSO, PS, SA, IGHS, ABSO, ABC, GGHS, and IADE for this purpose). The proposed algorithm is also compared with other modified explanations of ABC algorithm. The results show that the proposed strategy is considerably faster and more accurate compared to all the previous studies.

show abstract

Parameters extraction from commercial solar cells I–V characteristics and shunt analysis

Cited by 105 publications

References 26 publications

Estimation of parameters for single diode models using measured IV curves

Estimation of parameters for single diode models using measured IV curves

Parameter extraction of solar cell models using chaotic asexual reproduction optimization

Very accurate parameter estimation of single- and double-diode solar cell models using a modified artificial bee colony algorithm

Contact Info

Product

Resources

About