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Emended heap-based optimizer for characterizing performance of industrial solar generating units using triple-diode model

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  • Rizk-Allah, Rizk M.
  • El-Fergany, Attia A.

Abstract

This paper presents an emended Heap-based optimizer (EHBO) for characterizing the accurate-performance of three-diode-based model (3DbM) of solar generating units (SGUs). The accurate extraction of the 3DbM parameters is an important issue to meet the actual characteristics of SGUs. Therefore, a better-quality version of HBO, named EHBO, is proposed to attain the same. As the complicated natures accompanied with the 3DbM such as multi-variable, multi-modal as well as its sensitivity to tiny changes, an EHBO is introduced through two improvements viz Hill-Climbing strategy (HCS), and informed searching-based learning strategy (ISLS). The HCS assists the algorithm to attain the promising areas of the search space and then enriches the diversity as well as the exploration capability while the ISLS aims to bolster the quality of the best individual and thus, can enable the exploitation ability. Therefore, EHBO is faster and more accurate than the classical HBO in achieving the global optimum as well as balancing exploration and exploitation abilities. The proposed EHBO is investigated on three commercial SGUs, namely, PWP-201, Kyocera polycrystalline KC200GT, and Ultra 85-P with maximum cropped errors of 2.0507 mA, 0.2211 mA, and 2.417 mA for these modules; respectively. Comprehensive experiments with comparisons are conducted to show the effectiveness and efficacy of the EHBO based model versus other competing optimizers. Based on the conducted investigations, it can be confirmed that the EHBO is a promising optimization method to deal with uncertain parameters of SGUs with different technologies.

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  • 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).
    • Handle: RePEc:eee:energy:v:237:y:2021:i:c:s0360544221018090
    DOI: 10.1016/j.energy.2021.121561
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    1. Mohamed Abdel-Basset & Reda Mohamed & Ripon K. Chakrabortty & Michael J. Ryan & Attia El-Fergany, 2021. "An Improved Artificial Jellyfish Search Optimizer for Parameter Identification of Photovoltaic Models," Energies, MDPI, vol. 14(7), pages 1-33, March.
    2. Bana, Sangram & Saini, R.P., 2017. "Identification of unknown parameters of a single diode photovoltaic model using particle swarm optimization with binary constraints," Renewable Energy, Elsevier, vol. 101(C), pages 1299-1310.
    3. Rongjie Wang & Yiju Zhan & Haifeng Zhou, 2015. "Application of Artificial Bee Colony in Model Parameter Identification of Solar Cells," Energies, MDPI, vol. 8(8), pages 1-19, July.
    4. Zhang, Yiying & Ma, Maode & Jin, Zhigang, 2020. "Comprehensive learning Jaya algorithm for parameter extraction of photovoltaic models," Energy, Elsevier, vol. 211(C).
    5. Omnia S. Elazab & Hany M. Hasanien & Ibrahim Alsaidan & Almoataz Y. Abdelaziz & S. M. Muyeen, 2020. "Parameter Estimation of Three Diode Photovoltaic Model Using Grasshopper Optimization Algorithm," Energies, MDPI, vol. 13(2), pages 1-15, January.
    6. 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.
    7. Qais, Mohammed H. & Hasanien, Hany M. & Alghuwainem, Saad, 2020. "Parameters extraction of three-diode photovoltaic model using computation and Harris Hawks optimization," Energy, Elsevier, vol. 195(C).
    8. Huawen Sheng & Chunquan Li & Hanming Wang & Zeyuan Yan & Yin Xiong & Zhenting Cao & Qianying Kuang, 2019. "Parameters Extraction of Photovoltaic Models Using an Improved Moth-Flame Optimization," Energies, MDPI, vol. 12(18), pages 1-23, September.
    9. Fathy, Ahmed & Rezk, Hegazy, 2017. "Parameter estimation of photovoltaic system using imperialist competitive algorithm," Renewable Energy, Elsevier, vol. 111(C), pages 307-320.
    10. Yu, Kunjie & Qu, Boyang & Yue, Caitong & Ge, Shilei & Chen, Xu & Liang, Jing, 2019. "A performance-guided JAYA algorithm for parameters identification of photovoltaic cell and module," Applied Energy, Elsevier, vol. 237(C), pages 241-257.
    11. Mohamed Abdel-Basset & Reda Mohamed & Attia El-Fergany & Mohamed Abouhawwash & S. S. Askar, 2021. "Parameters Identification of PV Triple-Diode Model Using Improved Generalized Normal Distribution Algorithm," Mathematics, MDPI, vol. 9(9), pages 1-23, April.
    12. Khanna, Vandana & Das, B.K. & Bisht, Dinesh & Vandana, & Singh, P.K., 2015. "A three diode model for industrial solar cells and estimation of solar cell parameters using PSO algorithm," Renewable Energy, Elsevier, vol. 78(C), pages 105-113.
    13. Ishaque, Kashif & Salam, Zainal & Mekhilef, Saad & Shamsudin, Amir, 2012. "Parameter extraction of solar photovoltaic modules using penalty-based differential evolution," Applied Energy, Elsevier, vol. 99(C), pages 297-308.
    14. Qais, Mohammed H. & Hasanien, Hany M. & Alghuwainem, Saad & Nouh, Adnan S., 2019. "Coyote optimization algorithm for parameters extraction of three-diode photovoltaic models of photovoltaic modules," Energy, Elsevier, vol. 187(C).
    15. 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.
    16. Qiao, Weibiao & Yang, Zhe, 2020. "Forecast the electricity price of U.S. using a wavelet transform-based hybrid model," Energy, Elsevier, vol. 193(C).
    17. Abbassi, Abdelkader & Abbassi, Rabeh & Heidari, Ali Asghar & Oliva, Diego & Chen, Huiling & Habib, Arslan & Jemli, Mohamed & Wang, Mingjing, 2020. "Parameters identification of photovoltaic cell models using enhanced exploratory salp chains-based approach," Energy, Elsevier, vol. 198(C).
    18. Oliva, Diego & Abd El Aziz, Mohamed & Ella Hassanien, Aboul, 2017. "Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm," Applied Energy, Elsevier, vol. 200(C), pages 141-154.
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    1. Shaheen, Abdullah M. & Ginidi, Ahmed R. & El-Sehiemy, Ragab A. & El-Fergany, Attia & Elsayed, Abdallah M., 2023. "Optimal parameters extraction of photovoltaic triple diode model using an enhanced artificial gorilla troops optimizer," Energy, Elsevier, vol. 283(C).

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