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Novel fast dynamic MPPT (maximum power point tracking) technique with the capability of very high accurate power tracking

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  • Fathabadi, Hassan
Abstract
In this paper, a novel maximum power point tracking (MPPT) technique is proposed to track the maximum power point (MPP) of photovoltaic (PV) systems. The proposed MPPT scheme concurrently uses PV voltage and current deviations to find the MPP of a PV module/array/panel under every condition. A PV system has been built to implement the proposed MPPT technique as a MPPT controller, and experimental results obtained under standard test condition (STC), uniform and non-uniform shading conditions, and partial shading conditions are presented that explicitly validate theoretical results. A comparative study together with real experimental results obtained under STC verify that the proposed MPPT technique has a dynamic response with the shortest convergence time of 12 ms and the highest MPPT efficiency more than 99.6% compared to other MPPT techniques. Static-dynamic response obtained experimentally under uniform and non-uniform shading conditions again verifies that the method has a very fast high accurate dynamic response with the MPPT efficiency more than 99.6%. It is also experimentally shown that the proposed technique high accurately tracks the global maximum power point (GMPP) under partial shading conditions, so that, the MPPT efficiency is again more than 99.6%, and the convergence time is less than 140 ms.

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  • 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.
    • Handle: RePEc:eee:energy:v:94:y:2016:i:c:p:466-475
    DOI: 10.1016/j.energy.2015.10.133
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    References listed on IDEAS

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    1. Daraban, Stefan & Petreus, Dorin & Morel, Cristina, 2014. "A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading," Energy, Elsevier, vol. 74(C), pages 374-388.
    2. Mellit, Adel & Kalogirou, Soteris A., 2014. "MPPT-based artificial intelligence techniques for photovoltaic systems and its implementation into field programmable gate array chips: Review of current status and future perspectives," Energy, Elsevier, vol. 70(C), pages 1-21.
    3. Jiang, Joe-Air & Su, Yu-Li & Shieh, Jyh-Cherng & Kuo, Kun-Chang & Lin, Tzu-Shiang & Lin, Ta-Te & Fang, Wei & Chou, Jui-Jen & Wang, Jen-Cheng, 2014. "On application of a new hybrid maximum power point tracking (MPPT) based photovoltaic system to the closed plant factory," Applied Energy, Elsevier, vol. 124(C), pages 309-324.
    4. Rizzo, Santi Agatino & Scelba, Giacomo, 2015. "ANN based MPPT method for rapidly variable shading conditions," Applied Energy, Elsevier, vol. 145(C), pages 124-132.
    5. Ahmed, Jubaer & Salam, Zainal, 2015. "An improved perturb and observe (P&O) maximum power point tracking (MPPT) algorithm for higher efficiency," Applied Energy, Elsevier, vol. 150(C), pages 97-108.
    6. Parlak, Koray Sener, 2014. "FPGA based new MPPT (maximum power point tracking) method for PV (photovoltaic) array system operating partially shaded conditions," Energy, Elsevier, vol. 68(C), pages 399-410.
    7. 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.
    8. Mellit, A. & Sağlam, S. & Kalogirou, S.A., 2013. "Artificial neural network-based model for estimating the produced power of a photovoltaic module," Renewable Energy, Elsevier, vol. 60(C), pages 71-78.
    9. Shen, Chih-Lung & Ko, Yong-Xian, 2014. "Hybrid-input power supply with PFC (power factor corrector) and MPPT (maximum power point tracking) features for battery charging and HB-LED driving," Energy, Elsevier, vol. 72(C), pages 501-509.
    10. Hong, Chih-Ming & Ou, Ting-Chia & Lu, Kai-Hung, 2013. "Development of intelligent MPPT (maximum power point tracking) control for a grid-connected hybrid power generation system," Energy, Elsevier, vol. 50(C), pages 270-279.
    11. Bouilouta, A. & Mellit, A. & Kalogirou, S.A., 2013. "New MPPT method for stand-alone photovoltaic systems operating under partially shaded conditions," Energy, Elsevier, vol. 55(C), pages 1172-1185.
    12. Ahmed, Jubaer & Salam, Zainal, 2014. "A Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search with partial shading capability," Applied Energy, Elsevier, vol. 119(C), pages 118-130.
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    Citations

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    Cited by:

    1. Ali M. Eltamaly & M. S. Al-Saud & A. G. Abo-Khalil, 2020. "Performance Improvement of PV Systems’ Maximum Power Point Tracker Based on a Scanning PSO Particle Strategy," Sustainability, MDPI, vol. 12(3), pages 1-20, February.
    2. Rajesh, R. & Mabel, M. Carolin, 2016. "Design and real time implementation of a novel rule compressed fuzzy logic method for the determination operating point in a photo voltaic system," Energy, Elsevier, vol. 116(P1), pages 140-153.
    3. Novie Ayub Windarko & Muhammad Nizar Habibi & Bambang Sumantri & Eka Prasetyono & Moh. Zaenal Efendi & Taufik, 2021. "A New MPPT Algorithm for Photovoltaic Power Generation under Uniform and Partial Shading Conditions," Energies, MDPI, vol. 14(2), pages 1-22, January.
    4. Fathabadi, Hassan, 2017. "Novel standalone hybrid solar/wind/fuel cell/battery power generation system," Energy, Elsevier, vol. 140(P1), pages 454-465.
    5. Yinxiao Zhu & Moon Keun Kim & Huiqing Wen, 2018. "Simulation and Analysis of Perturbation and Observation-Based Self-Adaptable Step Size Maximum Power Point Tracking Strategy with Low Power Loss for Photovoltaics," Energies, MDPI, vol. 12(1), pages 1-20, December.
    6. 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.
    7. 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.
    8. Hou, Guolian & Ke, Yin & Huang, Congzhi, 2021. "A flexible constant power generation scheme for photovoltaic system by error-based active disturbance rejection control and perturb & observe," Energy, Elsevier, vol. 237(C).
    9. Fathabadi, Hassan, 2020. "Novel solar-powered photovoltaic/thermoelectric hybrid power source," Renewable Energy, Elsevier, vol. 146(C), pages 426-434.
    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. Fathabadi, Hassan, 2016. "Novel high-efficient unified maximum power point tracking controller for hybrid fuel cell/wind systems," Applied Energy, Elsevier, vol. 183(C), pages 1498-1510.
    12. 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.
    13. Fathabadi, Hassan, 2020. "Novel stand-alone, completely autonomous and renewable energy based charging station for charging plug-in hybrid electric vehicles (PHEVs)," Applied Energy, Elsevier, vol. 260(C).
    14. Osmani, Khaled & Haddad, Ahmad & Lemenand, Thierry & Castanier, Bruno & Ramadan, Mohamad, 2021. "An investigation on maximum power extraction algorithms from PV systems with corresponding DC-DC converters," Energy, Elsevier, vol. 224(C).
    15. 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.
    16. Gang Zhang & Zhongbei Tian & Huiqing Du & Zhigang Liu, 2018. "A Novel Hybrid DC Traction Power Supply System Integrating PV and Reversible Converters," Energies, MDPI, vol. 11(7), pages 1-24, June.
    17. 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.
    18. Boukenoui, R. & Ghanes, M. & Barbot, J.-P. & Bradai, R. & Mellit, A. & Salhi, H., 2017. "Experimental assessment of Maximum Power Point Tracking methods for photovoltaic systems," Energy, Elsevier, vol. 132(C), pages 324-340.
    19. Fathabadi, Hassan, 2019. "Solar energy harvesting in buildings using a proposed novel electrochemical device as an alternative to PV modules," Renewable Energy, Elsevier, vol. 133(C), pages 118-125.
    20. 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.
    21. Mao, Mingxuan & Zhang, Li & Duan, Pan & Duan, Qichang & Yang, Ming, 2018. "Grid-connected modular PV-Converter system with shuffled frog leaping algorithm based DMPPT controller," Energy, Elsevier, vol. 143(C), pages 181-190.
    22. He, Fulin & Fathabadi, Hassan, 2020. "Novel standalone plug-in hybrid electric vehicle charging station fed by solar energy in presence of a fuel cell system used as supporting power source," Renewable Energy, Elsevier, vol. 156(C), pages 964-974.

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