Parameter extraction of solar cell models using repaired adaptive differential evolution

Gong, Wenyin; Cai, Zhihua

doi:10.1016/j.solener.2013.05.007

Cited by 322 publications

(135 citation statements)

References 40 publications

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“…Then, the PV parameters have been calculated from these experimental data using a least square method in the PV parameters extraction algorithm. The results confirm that the diode reverse saturation current effectively depends on the temperature and the mathematical expression obtained in the literature has been validated [6][7][8][9]. The diode ideality factor, , changes less with the weather conditions.…”

Section: Introductionsupporting

confidence: 73%

“…(ii) A one diode model (ODM) which is simple and represents precisely the operation of a monocrystalline solar cell [5][6][7][8][9][10][11][12][13]. This model which is used in this work is presented in Figure 1 with , a diode which represents the -junction; and are the series and shunt resistances.…”

Section: Modeling Of a Photovoltaicmentioning

confidence: 99%

“…Due to the fact that is higher than ( ≫ ) and its influence on the performance of the PV cell is insignificant [5][6][7][8][9][10][11][12][13], (1) becomes Equation (2) is a nonlinear expression of pv because it expresses pv in function of pv and pv . In order to obtain a linear expression of pv , the Lambert function can be used.…”

Section: Modeling Of a Photovoltaicmentioning

confidence: 99%

“…But the other parameters have not been in the center of a particular study for a mathematical model. Nevertheless, these parameters and the diode reverse saturation current have been determined by some authors [3][4][5][6][7][8]. These authors measured the -characteristic of a PV module using a solar simulator instead of the normal operating conditions.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Simulations Based on Experimental Data of the Behaviour of a Monocrystalline Silicon Photovoltaic Module

Dandoussou

Kampel

Bouchet

et al. 2015

Journal of Solar Energy

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The performance of monocrystalline silicon cells depends widely on the parameters like the series and shunt resistances, the diode reverse saturation current, and the ideality factor. Many authors consider these parameters as constant while others determine their values based on the -characteristic when the module is under illumination or in the dark. This paper presents a new method for extracting the series resistance, the diode reverse saturation current, and the ideality factor. The proposed extraction method using the least square method is based on the fitting of experimental data recorded in 2014 in Ngaoundere, Cameroon. The results show that the ideality factor can be considered as constant and equal to 1.2 for the monocrystalline silicon module. The diode reverse saturation current depends only on the temperature. And the series resistance decreases when the irradiance increases. The extracted values of these parameters contribute to the best modeling of a photovoltaic module which can help in the accurate extraction of the maximum power.

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Section: Introductionsupporting

confidence: 73%

Section: Modeling Of a Photovoltaicmentioning

confidence: 99%

Section: Modeling Of a Photovoltaicmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Simulations Based on Experimental Data of the Behaviour of a Monocrystalline Silicon Photovoltaic Module

Dandoussou

Kampel

Bouchet

et al. 2015

Journal of Solar Energy

View full text Add to dashboard Cite

show abstract

“…For example, application of genetic algorithm (GA) [11][12][13], particle swarm optimization (PSO) [14][15][16], simulated annealing (SA) [17], differential evolution (DE) [18][19][20][21][22], pattern search (PS) [23], harmony search (HS) [24], artificial bee swarm optimization (ABSO) [25], bird mating optimizer (BMO) [26], bacterial foraging optimization (BFO) [27], artificial bee colony (ABC) [28], biogeography-based optimization algorithm with mutation strategies (BBO-M) [29] and teaching-learning based optimization (TLBO) [30] for this purpose can be found in the literature.…”

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

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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.

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Review on parameter estimation techniques of solar photovoltaic systems

Venkateswari

Rajasekar

2021

Int Trans Electr Energ Syst

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Beyond meeting power demand, switching to solar energy especially solar photovoltaic (PV) offers many advantages like modularity, minimal maintenance, pollution free, and zero noise. Yet, its cell modeling is critical in design, simulation analysis, evaluation, and control of solar PV system; most importantly to tap its maximum potential. However, precise PV cell modeling is complicated by PV nonlinearity, presence of large unknown model parameter, and absence of a unique method. Since number of model parameters involved is directly related to model accuracy, and efficiency; determination of its values assume high priority. Besides, application of meta-heuristic algorithms via numerical extraction is popular as it suits for any PV cell/module types and operating conditions. However, existence of many algorithms have drawn attention toward assessment of each method based on its merits, demerits, suitability/ability to parameter estimation problem, and complexity involved. Hence, few authors reviewed the subject of PV model parameter estimation.But existing reviews focused on comparative analysis of analytical and metaheuristic approaches, analysis of models, and application of meta-heuristic methods for model parameter extraction. Thus, lack a comprehensive analysis on methods based on different objective function, assessment on

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Parameter extraction of solar cell models using repaired adaptive differential evolution

Cited by 322 publications

References 40 publications

Simulations Based on Experimental Data of the Behaviour of a Monocrystalline Silicon Photovoltaic Module

Simulations Based on Experimental Data of the Behaviour of a Monocrystalline Silicon Photovoltaic Module

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

Review on parameter estimation techniques of solar photovoltaic systems

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