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Approximation of photovoltaic characteristics curves using Bézier Curve

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  • Louzazni, Mohamed
  • Al-Dahidi, Sameer

Abstract

Accuracy of solar cell model parameters is now a requirement for the manufacturing of appropriate photovoltaic models. Consequently, the methodologies of the parameters had already attracted immense interest among researchers over the years. This paper deals about the approximation of the characteristics curves of a solar cell using the Bézier curve method. This technique is selected to overcome the problems of the non-linearity, complexity, multivariate and multimodal of the characteristic's curves. The Bézier curves method is a parametric curve used throughout computer graphics and related disciplines. It is a robust methodology for constructing free-form curves, surfaces, shape design, and geometric representation of various products. Six different cases are carried out to test the validity of the proposed method, they are: (i) organic flexible dual junction amorphous silicon solar cell, (ii) silicon solar cell, (iii) Schutten Solar STP6-120/36 polycrystalline photovoltaic module, (iv) Schutten Solar STM6-40/36 monocrystalline photovoltaic module, (v) Photowatt-PWP 201 polycrystalline photovoltaic module and (vi) 230-W multi-silicon photovoltaic module under partial shading conditions. The technique is implemented and adapted by the mean of the De Casteljo algorithm to optimize the control points and minimize the distance between the experimental and calculated points. It is based on subdividing the curve into various segments and controlled by control points using the De Casteljo algorithm to minimize the distance between the experimental and theoretical points. The performance of the approximated characteristics curves is compared with experimental data as well as recent algorithms and techniques from the literature. For more validity, statistical error metrics from literature are computed and compared to ensure the accuracy of the approximated results and the performance of the proposed method. For instance, the comparison is carried out by resorting to the Individual Absolute Error (IAE) and the Relative Error (RE). Further, the Bias metrics and accuracy are calculated using the Autocorrelation Function (ACF), Tracking Signal (TS), and Normalized Forecast Metric (NFM). The proposed method provides a low error for the six case studies and better than that obtained by the other algorithms.

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  • Louzazni, Mohamed & Al-Dahidi, Sameer, 2021. "Approximation of photovoltaic characteristics curves using Bézier Curve," Renewable Energy, Elsevier, vol. 174(C), pages 715-732.
    • Handle: RePEc:eee:renene:v:174:y:2021:i:c:p:715-732
    DOI: 10.1016/j.renene.2021.04.103
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    1. Pindado, Santiago & Cubas, Javier, 2017. "Simple mathematical approach to solar cell/panel behavior based on datasheet information," Renewable Energy, Elsevier, vol. 103(C), pages 729-738.
    2. Tong, Nhan Thanh & Pora, Wanchalerm, 2016. "A parameter extraction technique exploiting intrinsic properties of solar cells," Applied Energy, Elsevier, vol. 176(C), pages 104-115.
    3. Tong Kang & Jiangang Yao & Min Jin & Shengjie Yang & ThanhLong Duong, 2018. "A Novel Improved Cuckoo Search Algorithm for Parameter Estimation of Photovoltaic (PV) Models," Energies, MDPI, vol. 11(5), pages 1-31, April.
    4. Toledo, F.J. & Blanes, José M., 2016. "Analytical and quasi-explicit four arbitrary point method for extraction of solar cell single-diode model parameters," Renewable Energy, Elsevier, vol. 92(C), pages 346-356.
    5. Javier Cubas & Santiago Pindado & Carlos De Manuel, 2014. "Explicit Expressions for Solar Panel Equivalent Circuit Parameters Based on Analytical Formulation and the Lambert W-Function," Energies, MDPI, vol. 7(7), pages 1-18, June.
    6. Mayer, Martin János & Gróf, Gyula, 2021. "Extensive comparison of physical models for photovoltaic power forecasting," Applied Energy, Elsevier, vol. 283(C).
    7. Diego Oliva & Ahmed A. Ewees & Mohamed Abd El Aziz & Aboul Ella Hassanien & Marco Peréz-Cisneros, 2017. "A Chaotic Improved Artificial Bee Colony for Parameter Estimation of Photovoltaic Cells," Energies, MDPI, vol. 10(7), pages 1-19, June.
    8. Efstratios Batzelis, 2019. "Non-Iterative Methods for the Extraction of the Single-Diode Model Parameters of Photovoltaic Modules: A Review and Comparative Assessment," Energies, MDPI, vol. 12(3), pages 1-26, January.
    9. Askarzadeh, Alireza & Rezazadeh, Alireza, 2013. "Artificial bee swarm optimization algorithm for parameters identification of solar cell models," Applied Energy, Elsevier, vol. 102(C), pages 943-949.
    10. AlHajri, M.F. & El-Naggar, K.M. & AlRashidi, M.R. & Al-Othman, A.K., 2012. "Optimal extraction of solar cell parameters using pattern search," Renewable Energy, Elsevier, vol. 44(C), pages 238-245.
    11. Wang, Shinong & Luo, Huan & Ge, Yuan & Liu, Shilin, 2021. "A new approach for modeling photovoltaic modules based on difference equation," Renewable Energy, Elsevier, vol. 168(C), pages 85-96.
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