Solar cell parameters estimation from illuminated <i>I</i>-<i>V</i> characteristic using linear slope equations and Newton-Raphson technique

Raj, Shubham; Sinha, Ankit; Panchal, Ashish K.

doi:10.1063/1.4803748

Cited by 35 publications

(16 citation statements)

References 9 publications

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“…This model is known as single diode model and is widely used to represent the solar cell behavior. [1][2][3][4][5][6][7][8][9][10][11] The output current, I a , is given as…”

Section: A Single-diode Modelmentioning

confidence: 99%

“…A few models have been proposed to describe the current-voltage relationship (I-V) in solar cells. [1][2][3][4][5][6][7][8][9][10][11] The I-V curve of a solar cell exhibits non-linear characteristics determined by the solar cell parameters that describe its model. To gain better understanding of the solar cell physics, a lumped parameter single diode equivalent circuit model is commonly used to simulate its behaviour under different operating conditions.…”

Section: Introductionmentioning

confidence: 99%

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Solar cell parameters identification using hybrid Nelder-Mead and modified particle swarm optimization

Hamid

Rahim

Selvaraj

2016

Journal of Renewable and Sustainable Energy

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Solar cell modelling primarily involves the formulation of the non-linear current versus voltage (I-V) curve. Determination of parameters plays an important role in solar cell accurate modelling. This paper presents an application of the hybrid Nelder-Mead simplex search method and modified Particle Swarm Optimization technique for identifying the parameters of solar cell and photovoltaic module models. The proposed technique is used to identify the unknown model parameters, namely, the generated photocurrent, saturation current, series resistance, shunt resistance, and ideality factor that govern the current-voltage relationship of a solar cell. A measurement data of 57 mm diameter commercial (R.T.C. France) silicon solar cell and a module consisting of 36 polycrystalline silicon cells (Photowatt-PWP 201) are used to test and verify the consistency of accurately estimating various parameters. Comparative study among different parameter estimation techniques is presented to demonstrate the effectiveness of the proposed approach. Furthermore, to verify the accurateness of the proposed technique, an experimental test bench unit is built using 72 mono-crystalline silicon cells (HIP-210NKHB5-2 module) on different environment conditions.

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“…This model is known as single diode model and is widely used to represent the solar cell behavior. [1][2][3][4][5][6][7][8][9][10][11] The output current, I a , is given as…”

Section: A Single-diode Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Solar cell parameters identification using hybrid Nelder-Mead and modified particle swarm optimization

Hamid

Rahim

Selvaraj

2016

Journal of Renewable and Sustainable Energy

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show abstract

“…e former, including Newton method [7], Newton-Raphson method [8], iterative curve fitting [9], and Levenberg-Marquardt algorithm [10], are considerably dependent on the gradient information and subjected to initial conditions. erefore, they easily plunge into local minima leading to inaccurate and unreliable solutions especially for complicated multimodal problems such as the parameter extraction problem of PV models.…”

Section: Introductionmentioning

confidence: 99%

Application of Supply‐Demand‐Based Optimization for Parameter Extraction of Solar Photovoltaic Models

et al. 2019

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Modeling solar photovoltaic (PV) systems accurately is based on optimal values of unknown model parameters of PV cells and modules. In recent years, the use of metaheuristics for parameter extraction of PV models gains more and more attentions thanks to their efficacy in solving highly nonlinear multimodal optimization problems. This work addresses a novel application of supply-demand-based optimization (SDO) to extract accurate and reliable parameters for PV models. SDO is a very young and efficient metaheuristic inspired by the supply and demand mechanism in economics. Its exploration and exploitation are balanced well by incorporating different dynamic modes of the cobweb model organically. To validate the feasibility and effectiveness of SDO, four PV models with diverse characteristics including RTC France silicon solar cell, PVM 752 GaAs thin film cell, STM6-40/36 monocrystalline module, and STP6-120/36 polycrystalline module are employed. The experimental results comparing with ten state-of-the-art algorithms demonstrate that SDO performs better or highly competitively in terms of accuracy, robustness, and convergence. In addition, the sensitivity of SDO to variation of population size is empirically investigated. The results indicate that SDO with a relatively small population size can extract accurate and reliable parameters for PV models.

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“…Extensive studies on the determination of the PV modules' and solar cells' electrical parameters were performed in the last decades. Studies were focused on calculating both the DC and AC [6][7][8][9][10][11][12][13][14][15][16] electrical parameters.…”

Section: Introductionmentioning

confidence: 99%

Solar Cell Capacitance Determination Based on an RLC Resonant Circuit

Cotfas

Borza

et al. 2018

Energies

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The capacitance is one of the key dynamic parameters of solar cells, which can provide essential information regarding the quality and health state of the cell. However, the measurement of this parameter is not a trivial task, as it typically requires high accuracy instruments using, e.g., electrical impedance spectroscopy (IS). This paper introduces a simple and effective method to determine the electric capacitance of the solar cells. An RLC (Resistor Inductance Capacitor) circuit is formed by using an inductor as a load for the solar cell. The capacitance of the solar cell is found by measuring the frequency of the damped oscillation that occurs at the moment of connecting the inductor to the solar cell. The study is performed through simulation based on National Instruments (NI) Multisim application as SPICE simulation software and through experimental capacitance measurements of a monocrystalline silicon commercial solar cell and a photovoltaic panel using the proposed method. The results were validated using impedance spectroscopy. The differences between the capacitance values obtained by the two methods are of 1% for the solar cells and of 9.6% for the PV panel. The irradiance level effect upon the solar cell capacitance was studied obtaining an increase in the capacitance in function of the irradiance. By connecting different inductors to the solar cell, the frequency effect upon the solar cell capacitance was studied noticing a very small decrease in the capacitance with the frequency. Additionally, the temperature effect over the solar cell capacitance was studied achieving an increase in capacitance with temperature.Energies 2018, 11, 672 2 of 13 be determined by using the fitting method (like the series and parallel resistance and the capacitance in the case of solar cells). The IS method has the advantage of offering the information about three important dynamic parameters and can be implemented with dedicated instruments or LCR meters. The disadvantage of this method is the need for an external signal injection into the DUT which can increase the price of the used instruments, especially if the tests are conducted under light conditions. These conditions involve DC power electronics in the instruments in order to bias the PV.Other methods are based on the time response of the PV modules. These methods are based on the transient effect of the Resistor Capacitor (RC) circuit (discharging effect of the PV capacitance [19,20] or time constant of the PV circuit [21]). The reported time response-based methods require external signal injection into the DUT and are used only in dark conditions.The dynamic parameters can be used as tools to characterize and diagnose the quality and the degradation status of the PV modules. One of the key dynamic parameters is the electrical capacitance of the PV modules. Oprea et al. [22] found that the PV panel capacitance and parallel resistance are affected by the PV panel degradation state when the potential-induced degradation was studied. Bhat et al. [23] found that t...

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Solar cell parameters estimation from illuminated I-V characteristic using linear slope equations and Newton-Raphson technique

Cited by 35 publications

References 9 publications

Solar cell parameters identification using hybrid Nelder-Mead and modified particle swarm optimization

Solar cell parameters identification using hybrid Nelder-Mead and modified particle swarm optimization

Application of Supply‐Demand‐Based Optimization for Parameter Extraction of Solar Photovoltaic Models

Solar Cell Capacitance Determination Based on an RLC Resonant Circuit

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