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Identification of electrical parameters for three-diode photovoltaic model using analytical and sunflower optimization algorithm

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  • Qais, Mohammed H.
  • Hasanien, Hany M.
  • Alghuwainem, Saad

Abstract

This article proposes an accurate and straightforward method for modeling and simulation of photovoltaic (PV) modules. The main target is to find the nine-parameter of a three-diode (TD) model based on the datasheet parameters, which are given by all commercial PV modules. The objective function is formulated based on short circuit, open circuit, power derivative, and maximum power equations. Two parameters (parallel resistance and photo-generated current) are calculated analytically and rest parameters are optimally designed using the sunflower optimization (SFO) algorithm. The presented method is applied to model three types of commercial PV modules (multicrystal KC200GT, poly-crystalline MSX-60, and mono-crystalline CS6K-280M). The optimal nine-parameters obtained in this paper are paralleled with that attained by other approaches. In order to assess the efficiency of the offered approach, I-V and P-V characteristics are validated with measured data under various temperatures and solar irradiations. The error among these results records a value less than 0.5%. Therefore, the simulation results indicate an excellent agreement with the measured data. This proposed approach can be utilized to model any marketable PV module based on given datasheet parameters only.

Suggested Citation

  • Qais, Mohammed H. & Hasanien, Hany M. & Alghuwainem, Saad, 2019. "Identification of electrical parameters for three-diode photovoltaic model using analytical and sunflower optimization algorithm," Applied Energy, Elsevier, vol. 250(C), pages 109-117.
    • Handle: RePEc:eee:appene:v:250:y:2019:i:c:p:109-117
    DOI: 10.1016/j.apenergy.2019.05.013
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    14. Samuel R. Fahim & Hany M. Hasanien & Rania A. Turky & Shady H. E. Abdel Aleem & Martin Ćalasan, 2022. "A Comprehensive Review of Photovoltaic Modules Models and Algorithms Used in Parameter Extraction," Energies, MDPI, vol. 15(23), pages 1-56, November.
    15. Li, Guorong & Zhang, Yunpeng & Zhou, Hai & Wu, Ji & Sun, Shumin & You, Daning & Zhang, Yuanpeng, 2024. "Novel reference condition independent method for estimating performance for PV modules based on double-diode model," Renewable Energy, Elsevier, vol. 226(C).
    16. Jingwei Zhang & Zenan Yang & Kun Ding & Li Feng & Frank Hamelmann & Xihui Chen & Yongjie Liu & Ling Chen, 2022. "Modeling of Photovoltaic Array Based on Multi-Agent Deep Reinforcement Learning Using Residuals of I–V Characteristics," Energies, MDPI, vol. 15(18), pages 1-17, September.
    17. Rizk-Allah, Rizk M. & El-Fergany, Attia A., 2021. "Emended heap-based optimizer for characterizing performance of industrial solar generating units using triple-diode model," Energy, Elsevier, vol. 237(C).
    18. Long, Wen & Jiao, Jianjun & Liang, Ximing & Xu, Ming & Tang, Mingzhu & Cai, Shaohong, 2022. "Parameters estimation of photovoltaic models using a novel hybrid seagull optimization algorithm," Energy, Elsevier, vol. 249(C).
    19. Ren, Xiaojun & Wu, Yongtang & Hao, Dongmin & Liu, Guoxu & Zafetti, Nicholas, 2021. "Analysis of the performance of the multi-objective hybrid hydropower-photovoltaic-wind system to reduce variance and maximum power generation by developed owl search algorithm," Energy, Elsevier, vol. 231(C).
    20. Ridha, Hussein Mohammed & Hizam, Hashim & Mirjalili, Seyedali & Othman, Mohammad Lutfi & Ya'acob, Mohammad Effendy & Ahmadipour, Masoud, 2022. "Parameter extraction of single, double, and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphson methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    21. Jialan Sun & Jinwei Fan, 2024. "Experimental Assessment of a Novel Irradiance Sensorless Intelligent Control Scheme for a Standalone Photovoltaic System under Real Climatic Conditions," Energies, MDPI, vol. 17(18), pages 1-31, September.
    22. Long, Wen & Wu, Tiebin & Xu, Ming & Tang, Mingzhu & Cai, Shaohong, 2021. "Parameters identification of photovoltaic models by using an enhanced adaptive butterfly optimization algorithm," Energy, Elsevier, vol. 229(C).
    23. Mostafa Elshahed & Ali M. El-Rifaie & Mohamed A. Tolba & Ahmed Ginidi & Abdullah Shaheen & Shazly A. Mohamed, 2022. "An Innovative Hunter-Prey-Based Optimization for Electrically Based Single-, Double-, and Triple-Diode Models of Solar Photovoltaic Systems," Mathematics, MDPI, vol. 10(23), pages 1-22, December.

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