An Efficient Iterative Method for Extracting Parameters of Photovoltaic Panels with Single Diode Model

Benahmida, Abdelaaziz; Maouhoub, Noureddine; Sahsah, H.

doi:10.1109/redec49234.2020.9163858

Cited by 10 publications

(8 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The three other parameters are determined by using three analytical expressions based on preliminary selective data of the I-V curve; the open-circuit voltage (V oc ), the short circuit current (I sc ), and maximum power point MPP (V mp , I mp ). Given that the values of the key-points available on the datasheet can be different from their real-values corresponding to the measured I-V characteristics, the accuracy of predicting using this technique can be strongly affected by their precision (Benahmida et al, 2020). Angulo Cardenas et al (Angulo Cardenas et al, 2017) proposed another reduced search space approach for the five parameter's estimation from I-V characteristics; this method reduces the number of complexities and does not rely on any additional data from I-V curves.…”

Section: Background and Limitationsmentioning

confidence: 99%

A New Reduced Form for Real-Time Identification of PV Panels Operating Under Arbitrary Conditions

Tifidat

Maouhoub

Benahmida

2022

International Journal of Energy Optimization and Engineering

Self Cite

View full text Add to dashboard Cite

In this work, an efficient solution based on the reducing forms approach is presented to extract the five parameters of the single-diode model of PV generators from their I-V curves. Thus, by reducing the number of the five unknown parameters to two unknowns, the analytical expression of the current based on the LambertW function will then depend only on the ideality factor and the series resistance, as the two unknowns to predict numerically using the non-linear least square technique. The three other parameters are calculated as functions of the two predicted parameters using a linear system of three equations. Two sets of experiments are used for the validation of the proposed approach, which first showed its rapidity and high accuracy compared to the best approaches from the literature. Then, the method was applied for the real-time identification of four PV modules operating outdoors during one reference day at Cocoa (Florida).

show abstract

Section: Background and Limitationsmentioning

confidence: 99%

A New Reduced Form for Real-Time Identification of PV Panels Operating Under Arbitrary Conditions

Tifidat

Maouhoub

Benahmida

2022

International Journal of Energy Optimization and Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

“…To check the accuracy and certainty of the presented model, the normalized error (NE) given by Equation (11) and normalized mean square error (NRMSE) given by Equation (12), are selected 4,27,28 :…”

Section: Accuracy Assessment Of Proposed Modelmentioning

confidence: 99%

“…However, the maximum power prediction based on the SDM requires firstly extraction of five parameters at reference conditions from an implicit equation that relies on current and voltage and then determine the model parameters under various temperature and irradiance conditions using set transformation equations. [6][7][8][9][10][11][12] Recently, many methods have been presented based on artificial neural networks (ANNs) to predict the maximum power of PV modules. [13][14][15] However, these technics have some computational problems such as higher computational complexity and cost.…”

mentioning

confidence: 99%

An accurate analytical model for predicting the maximum power of photovoltaic module operating outdoor under varying conditions

Benahmida

Maouhoub

Tifidat

et al. 2022

Intl J of Energy Research

Self Cite

View full text Add to dashboard Cite

Summary One of the crucial study areas for renewable energy is the output power prediction of photovoltaic (PV) generators under various operating situations. Accurate prediction of maximum power is important for the control and design of grid‐connected PV systems. In this study, a new analytical model of voltage and current at maximum power point in relation to temperature and solar irradiation has been proposed to predict the maximum power of PV modules operating from dawn to dusk under real outdoor environmental conditions. Real‐time monitoring values of PV module temperature and solar irradiation have been used to optimize the analytical model parameters during one reference day and then to forecast the maximum power of the PV module for all other days. To validate our proposed analytical model, experimental data recorded by National Renewable Energy Laboratory for three PV modules from single‐crystalline silicon, multi‐crystalline silicon, and amorphous silicon/crystalline silicon heterojunction with intrinsic thin‐layer technologies have been used. Real‐time experimental and optimized characteristic using the proposed model of voltage at maximum power has been compared to three other analytical models in one reference day. The results have shown a good agreement and the normalized error has not exceeded 1%. Furthermore, the comparison of experimental and predicted curves of peak power point in two other arbitrary days has shown a good agreement and the NRMSE values have not exceeded 0.92%.

show abstract

“…Up until now, several authors have proposed various methods to determine different parameters in the single diode model. These methods can be divided into two categories [5,6]. One category is non-iterative analysis procedures [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22], which are reviewed in [23].…”

Section: Introductionmentioning

confidence: 99%

An Effective Method to Accurately Extract the Parameters of Single Diode Model of Solar Cells

et al. 2021

View full text Add to dashboard Cite

A non-iterative method is presented to accurately extract the five parameters of single diode model of solar cells in this paper. This method overcomes the problems of complexity and accuracy by simplifying the calculation process. Key parts of the equation are to be adjusted dynamically so that the desired five parameters can be obtained from the I–V curve. Then, the I-V and P-V characteristic curves of solar cells are used to compare the effectiveness of this method with other methods. Furthermore, the root mean square error analysis shows that this method is more applicable than other methods. Finally, the I-V and P-V characteristics simulated by using the extracted parameters in this method are compared and discussed with the experimental data of solar cells under different conditions. In fact, this extraction process can be regarded as an effective and accurate method to estimate solar cells’ single diode model parameters.

show abstract

An Efficient Iterative Method for Extracting Parameters of Photovoltaic Panels with Single Diode Model

Cited by 10 publications

References 40 publications

A New Reduced Form for Real-Time Identification of PV Panels Operating Under Arbitrary Conditions

A New Reduced Form for Real-Time Identification of PV Panels Operating Under Arbitrary Conditions

An accurate analytical model for predicting the maximum power of photovoltaic module operating outdoor under varying conditions

An Effective Method to Accurately Extract the Parameters of Single Diode Model of Solar Cells

Contact Info

Product

Resources

About