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Lambert W function-based technique for tracking the maximum power point of PV modules connected in various configurations

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  • Fathabadi, Hassan

Abstract

In this study, a novel exact technique is proposed for tracking the maximum power point (MPP) of photovoltaic (PV) modules connected in various configurations. The Lambert W function is used to perform the equations which express current–voltage (I–V), power–voltage (P–V) and power–current (P–I) characteristics of various configured PV modules. Then, the Lambert W function-based equations are converted into discrete equations. The maximum output powers of each configuration under nominal and shaded conditions are determined by numerically solving the discrete equations. It is shown that the maximum output power of a PV array strictly depends on the configuration of its PV modules. Two comparisons between various configurations are presented under nominal and shaded conditions which explicitly show higher performance of the parallel homogenous configuration. Simulation results not only verify that the proposed Lambert W function-based technique is a high accuracy technique but also show a good agreement between the calculated parameters and the experimental data obtained from the datasheet. The contribution of this work is to present a novel exact technique for determining the maximum output powers of various configured PV modules. The results of this research can be effectively used to determine the MPP of PV arrays/panels.

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  • Fathabadi, Hassan, 2015. "Lambert W function-based technique for tracking the maximum power point of PV modules connected in various configurations," Renewable Energy, Elsevier, vol. 74(C), pages 214-226.
    • Handle: RePEc:eee:renene:v:74:y:2015:i:c:p:214-226
    DOI: 10.1016/j.renene.2014.07.059
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    References listed on IDEAS

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    Cited by:

    1. Fathabadi, Hassan, 2019. "Two novel methods for converting the waste heat of PV modules caused by temperature rise into electric power," Renewable Energy, Elsevier, vol. 142(C), pages 543-551.
    2. Fathabadi, Hassan, 2017. "Novel grid-connected solar/wind powered electric vehicle charging station with vehicle-to-grid technology," Energy, Elsevier, vol. 132(C), pages 1-11.
    3. Ramli, Makbul A.M. & Twaha, Ssennoga & Ishaque, Kashif & Al-Turki, Yusuf A., 2017. "A review on maximum power point tracking for photovoltaic systems with and without shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 144-159.
    4. Mahmoudinezhad, S. & Rezania, A. & Cotfas, D.T. & Cotfas, P.A. & Rosendahl, L.A., 2018. "Experimental and numerical investigation of hybrid concentrated photovoltaic – Thermoelectric module under low solar concentration," Energy, Elsevier, vol. 159(C), pages 1123-1131.
    5. Chen, Jinxin & Pan, Guobing & Ouyang, Jing & Ma, Jin & Fu, Lei & Zhang, Libin, 2020. "Study on impacts of dust accumulation and rainfall on PV power reduction in East China," Energy, Elsevier, vol. 194(C).
    6. Belhachat, Faiza & Larbes, Cherif, 2017. "Global maximum power point tracking based on ANFIS approach for PV array configurations under partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 875-889.
    7. Wu, Jing & Zhang, Ling & Liu, Zhongbing & Wu, Zhenghong, 2021. "Coupled optical-electrical-thermal analysis of a semi-transparent photovoltaic glazing façade under building shadow," Applied Energy, Elsevier, vol. 292(C).
    8. Fathabadi, Hassan, 2016. "Novel fast dynamic MPPT (maximum power point tracking) technique with the capability of very high accurate power tracking," Energy, Elsevier, vol. 94(C), pages 466-475.
    9. Fathabadi, Hassan, 2016. "Novel high accurate sensorless dual-axis solar tracking system controlled by maximum power point tracking unit of photovoltaic systems," Applied Energy, Elsevier, vol. 173(C), pages 448-459.
    10. Fathabadi, Hassan, 2016. "Novel highly accurate universal maximum power point tracker for maximum power extraction from hybrid fuel cell/photovoltaic/wind power generation systems," Energy, Elsevier, vol. 116(P1), pages 402-416.
    11. Gulin, Marko & Pavlović, Tomislav & Vašak, Mario, 2016. "Photovoltaic panel and array static models for power production prediction: Integration of manufacturers’ and on-line data," Renewable Energy, Elsevier, vol. 97(C), pages 399-413.
    12. Xiong, Wei & Liu, Zhongbing & Wu, Zhenghong & Wu, Jing & Su, Fanghan & Zhang, Ling, 2022. "Investigation of the effect of Inter-Building Effect on the performance of semi-transparent PV glazing system," Energy, Elsevier, vol. 245(C).
    13. Wu, Jing & Zhang, Ling & Liu, Zhongbing & Luo, Yongqiang & Wu, Zhenghong & Wang, Pengcheng, 2020. "Experimental and theoretical study on the performance of semi-transparent photovoltaic glazing façade under shaded conditions," Energy, Elsevier, vol. 207(C).
    14. Tian, Xinyi & Wang, Jun & Wang, Chuyao & Ji, Jie, 2023. "Comparison analysis of the glazed and unglazed curved water-based PV/T roofs in the non-heating season," Renewable Energy, Elsevier, vol. 205(C), pages 899-917.
    15. Fathabadi, Hassan, 2017. "Novel fast and high accuracy maximum power point tracking method for hybrid photovoltaic/fuel cell energy conversion systems," Renewable Energy, Elsevier, vol. 106(C), pages 232-242.
    16. Fathabadi, Hassan, 2016. "Novel high efficient offline sensorless dual-axis solar tracker for using in photovoltaic systems and solar concentrators," Renewable Energy, Elsevier, vol. 95(C), pages 485-494.

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