A simple but accurate procedure for solving the five-parameter model

Mares, Oana; Paulescu, Marius; Badescu, Viorel

doi:10.1016/j.enconman.2015.07.046

Cited by 75 publications

(40 citation statements)

References 23 publications

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“…For running the numerical algorithm, the slopes of the I-V curve at short circuit and open circuit are estimated from the I-V characteristic at STC presented by datasheet; Ref. [2] using a procedure for extracting the parameters only on basis of the notable points. Ref.…”

Section: Resultsmentioning

confidence: 99%

Parameters extraction for the one-diode model of a solar cell

Sabadus

Mihailetchi

Paulescu

2017

AIP Conference Proceedings

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Section: Resultsmentioning

confidence: 99%

Parameters extraction for the one-diode model of a solar cell

Sabadus

Mihailetchi

Paulescu

2017

AIP Conference Proceedings

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“…The parameter N − p in (8) has been settled to 216, so that 90% of experimental points have been taken into account for the feasibility condition. Thus, 10% of points are excluded, regardless of their position in the I-V curve, but the short-circuit current I sc and the open circuit voltage V oc have been always included in the 90%, so that the feasibility condition for this example has been formalized as in (9):…”

Section: Relaxation Of the Inclusion Property: Second Approachmentioning

confidence: 99%

“…These parameters are in turn dependent on other ones related to the cell material and the environmental conditions-the irradiance and the temperature; see [7,8]. The double diode model (DDM) allows one to model the dark current losses and the effect of pair generation-recombination in the space charge region [9], but at the cost of an increase in the number of parameters, increasing from five for the SDM, to seven. A more complicated model can be used in a case where the PV cells' behavior at negative voltage values has to be accounted for.…”

Section: Introductionmentioning

confidence: 99%

An Interval-Arithmetic-Based Approach to the Parametric Identification of the Single-Diode Model of Photovoltaic Generators

Orozco-Gutierrez

2020

Energies

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Parametric identification of the single diode model of a photovoltaic generator is a key element in simulation and diagnosis. Parameters’ values are often determined by using experimental data the modules manufacturers provide in the data sheets. In outdoor applications, the parametric identification is instead performed by starting from the current vs. voltage curve acquired in non-standard operating conditions. This paper refers to this latter case and introduces an approach based on the use of interval arithmetic. Photovoltaic generators based on crystalline silicon cells are considered: they are modeled by using the single diode model, and a divide-and-conquer algorithm is used to contract the initial search space up to a small hyper-rectangle including the identified set of parameters. The proposed approach is validated by using experimental data measured in outdoor conditions. The information provided by the approach, in terms of parametric sensitivity and of correlation between current variations and drifts of the parameters values, is discussed. The results are analyzed in view of the on-site application of the proposed approach for diagnostic purposes.

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“…The major challenge in photovoltaics system is posed by the instability, nonlinearity and complexity of the current-voltage and power-voltage characteristics equation. The relation between photovoltaic current and voltage is both implicit and nonlinear [3][4][5][6] and it depends on several factors such as module temperature, solar radiation and its distribution, spectrum, cable losses, dust accumulation, shading and soiling [7,8]. Therefore, it is vital to produce a more accurate mathematical model that can better reveal the actual behavior and represent the relationship between current and voltage.…”

Section: Introductionmentioning

confidence: 99%

“…They can be classified globally into two categories: implicit and explicit models [12,13]. The former [5,[14][15][16] need iterative numerical methods to solve the nonlinear current-voltage equation. On the other hand, the latter models are based on simple analytical expressions [4,[17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Metaheuristic Algorithm for Photovoltaic Parameters: Comparative Study and Prediction with a Firefly Algorithm

et al. 2018

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In this paper, a Firefly algorithm is proposed for identification and comparative study of five, seven and eight parameters of a single and double diode solar cell and photovoltaic module under different solar irradiation and temperature. Further, a metaheuristic algorithm is proposed in order to predict the electrical parameters of three different solar cell technologies. The first is a commercial RTC mono-crystalline silicon solar cell with single and double diodes at 33 • C and 1000 W/m 2. The second, is a flexible hydrogenated amorphous silicon a-Si:H solar cell single diode. The third is a commercial photovoltaic module (Photowatt-PWP 201) in which 36 polycrystalline silicon cells are connected in series, single diode, at 25 • C and 1000 W/m 2 from experimental current-voltage. The proposed constrained objective function is adapted to minimize the absolute errors between experimental and predicted values of voltage and current in two zones. Finally, for performance validation, the parameters obtained through the Firefly algorithm are compared with recent research papers reporting metaheuristic optimization algorithms and analytical methods. The presented results confirm the validity and reliability of the Firefly algorithm in extracting the optimal parameters of the photovoltaic solar cell.

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A simple but accurate procedure for solving the five-parameter model

Cited by 75 publications

References 23 publications

Parameters extraction for the one-diode model of a solar cell

Parameters extraction for the one-diode model of a solar cell

An Interval-Arithmetic-Based Approach to the Parametric Identification of the Single-Diode Model of Photovoltaic Generators

Metaheuristic Algorithm for Photovoltaic Parameters: Comparative Study and Prediction with a Firefly Algorithm

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