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FPGA-based real time implementation of MPPT-controller for photovoltaic systems

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  • Mellit, A.
  • Rezzouk, H.
  • Messai, A.
  • Medjahed, B.

Abstract

In this paper an FPGA-based implementation of a real time perturb and observe (P&O) algorithm for tracking the Maximum Power Point (MPP) of a photovoltaic (PV) generator is presented. The P&O algorithm has been designed using the very high-speed description language (VHDL) and implemented on Xilinx Virtex-II-Pro(xc2v1000-4fg456) - Field Programmable Gate Array (FPGA). The algorithm and the hardware have been simulated and tested by conditioning the power produced by the PV-modules installed on the rooftop of the “Hall of Technology Laboratory” at Jijel University. The main advantages of the developed MPPT are low cost, good velocity, acceptable reliability, and easy implementation. However, its main disadvantage is related to the fact that for fast changes in irradiance it may fail to track the maximum power point. The efficiency of the implemented P&O controller is about 96%.

Suggested Citation

  • Mellit, A. & Rezzouk, H. & Messai, A. & Medjahed, B., 2011. "FPGA-based real time implementation of MPPT-controller for photovoltaic systems," Renewable Energy, Elsevier, vol. 36(5), pages 1652-1661.
    • Handle: RePEc:eee:renene:v:36:y:2011:i:5:p:1652-1661
    DOI: 10.1016/j.renene.2010.11.019
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    References listed on IDEAS

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    1. Houssamo, Issam & Locment, Fabrice & Sechilariu, Manuela, 2010. "Maximum power tracking for photovoltaic power system: Development and experimental comparison of two algorithms," Renewable Energy, Elsevier, vol. 35(10), pages 2381-2387.
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    1. Belaout, A. & Krim, F. & Mellit, A. & Talbi, B. & Arabi, A., 2018. "Multiclass adaptive neuro-fuzzy classifier and feature selection techniques for photovoltaic array fault detection and classification," Renewable Energy, Elsevier, vol. 127(C), pages 548-558.
    2. Periasamy, Packiam & Jain, N.K. & Singh, I.P., 2015. "A review on development of photovoltaic water pumping system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 918-925.
    3. 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.
    4. Salah Beni Hamed & Mouna Ben Hamed & Lassaad Sbita, 2022. "Robust Voltage Control of a Buck DC-DC Converter: A Sliding Mode Approach," Energies, MDPI, vol. 15(17), pages 1-21, August.
    5. Shahrooz Hajighorbani & Mohd Amran Mohd Radzi & Mohd Zainal Abidin Ab Kadir & Suhaidi Shafie, 2015. "Dual Search Maximum Power Point (DSMPP) Algorithm Based on Mathematical Analysis under Shaded Conditions," Energies, MDPI, vol. 8(10), pages 1-31, October.
    6. Saravanan, S. & Ramesh Babu, N., 2016. "Maximum power point tracking algorithms for photovoltaic system – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 192-204.
    7. 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.
    8. 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.
    9. Qi, Jun & Zhang, Youbing & Chen, Yi, 2014. "Modeling and maximum power point tracking (MPPT) method for PV array under partial shade conditions," Renewable Energy, Elsevier, vol. 66(C), pages 337-345.
    10. Neeraj Priyadarshi & Vigna K. Ramachandaramurthy & Sanjeevikumar Padmanaban & Farooque Azam, 2019. "An Ant Colony Optimized MPPT for Standalone Hybrid PV-Wind Power System with Single Cuk Converter," Energies, MDPI, vol. 12(1), pages 1-23, January.
    11. Ankit, & Sahoo, Sarat Kumar & Sukchai, Sukruedee & Yanine, Franco Fernando, 2018. "Review and comparative study of single-stage inverters for a PV system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 962-986.
    12. Dileep, G. & Singh, S.N., 2015. "Maximum power point tracking of solar photovoltaic system using modified perturbation and observation method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 109-129.
    13. Lalili, D. & Mellit, A. & Lourci, N. & Medjahed, B. & Berkouk, E.M., 2011. "Input output feedback linearization control and variable step size MPPT algorithm of a grid-connected photovoltaic inverter," Renewable Energy, Elsevier, vol. 36(12), pages 3282-3291.
    14. Carlos Robles Algarín & John Taborda Giraldo & Omar Rodríguez Álvarez, 2017. "Fuzzy Logic Based MPPT Controller for a PV System," Energies, MDPI, vol. 10(12), pages 1-18, December.
    15. Rajesh, R. & Carolin Mabel, M., 2015. "A comprehensive review of photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 231-248.

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