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Modified Maximum Power Point Tracking Algorithm under Time-Varying Solar Irradiation

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  • Mehmet Ali Yildirim

    (Department of Energy, Cracow University of Technology, 31-864 Kraków, Poland)

  • Marzena Nowak-Ocłoń

    (Department of Energy, Cracow University of Technology, 31-864 Kraków, Poland)

Abstract

Solar photovoltaic (PV) energy is one of the most viable renewable energy sources, considered less polluting than fossil energy. However, the average power conversion efficiency of PV systems is between 15% and 20%, and they must operate with high efficiency. Photovoltaic cells have non-linear voltage–current characteristics that are dependent on environmental factors such as solar irradiation and temperature, and have low efficiency. Therefore, it becomes crucial to harvest the maximum power from PV panels. This paper aims to study and analyze the most common and well-known maximum power point tracking (MPPT) algorithms, perturb and observe (P&O) and incremental conductance (IncCond). These algorithms were found to be easy to implement, low-cost techniques suitable for large- and medium-sized photovoltaic applications. The algorithms were tested and compared dynamically using MATLAB/Simulink software. In order to overcome the low performance of the P&O and IncCond methods under time-varying and fast-changing solar irradiation, several modifications are proposed. Results show an improvement in the tracking and overall system efficiencies and a shortened response time compared with original techniques. In addition, the proposed algorithms minimize the oscillations around the maximum power point (MPP), and the power converges faster.

Suggested Citation

  • Mehmet Ali Yildirim & Marzena Nowak-Ocłoń, 2020. "Modified Maximum Power Point Tracking Algorithm under Time-Varying Solar Irradiation," Energies, MDPI, vol. 13(24), pages 1-15, December.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:24:p:6722-:d:465297
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    References listed on IDEAS

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    1. John Macaulay & Zhongfu Zhou, 2018. "A Fuzzy Logical-Based Variable Step Size P&O MPPT Algorithm for Photovoltaic System," Energies, MDPI, vol. 11(6), pages 1-15, May.
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    4. Islam, Md Tasbirul & Huda, Nazmul & Abdullah, A.B. & Saidur, R., 2018. "A comprehensive review of state-of-the-art concentrating solar power (CSP) technologies: Current status and research trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 987-1018.
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    Citations

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    Cited by:

    1. Dominika Siwiec & Andrzej Pacana, 2021. "Model of Choice Photovoltaic Panels Considering Customers’ Expectations," Energies, MDPI, vol. 14(18), pages 1-32, September.
    2. Alfredo Gil-Velasco & Carlos Aguilar-Castillo, 2021. "A Modification of the Perturb and Observe Method to Improve the Energy Harvesting of PV Systems under Partial Shading Conditions," Energies, MDPI, vol. 14(9), pages 1-12, April.
    3. Sheikholeslami, M. & Ghasemian, Mehran & Dehghan, Maziar, 2024. "Numerical simulation and Enviro-economic examination of Photovoltaic system in presence of complex shape of tube equipped with turbulator," Renewable Energy, Elsevier, vol. 231(C).
    4. Mohamed Derbeli & Cristian Napole & Oscar Barambones, 2023. "A Fuzzy Logic Control for Maximum Power Point Tracking Algorithm Validated in a Commercial PV System," Energies, MDPI, vol. 16(2), pages 1-14, January.
    5. Eneko Artetxe & Jokin Uralde & Oscar Barambones & Isidro Calvo & Imanol Martin, 2023. "Maximum Power Point Tracker Controller for Solar Photovoltaic Based on Reinforcement Learning Agent with a Digital Twin," Mathematics, MDPI, vol. 11(9), pages 1-21, May.
    6. Mohamed Derbeli & Cristian Napole & Oscar Barambones & Jesus Sanchez & Isidro Calvo & Pablo Fernández-Bustamante, 2021. "Maximum Power Point Tracking Techniques for Photovoltaic Panel: A Review and Experimental Applications," Energies, MDPI, vol. 14(22), pages 1-31, November.
    7. Yousaf, Muhammad Zain & Koondhar, Mohsin Ali & Zaki, Zaki A. & Ahmed, Emad M. & Alaas, Zuhair Muhammed & Mahariq, Ibrahim & Guerrero, Josep M., 2025. "Improved MPPT of solar PV Systems under different Environmental conditions utilizes a Novel Hybrid PSO," Renewable Energy, Elsevier, vol. 244(C).
    8. Grzegorz Ostasz & Dominika Siwiec & Andrzej Pacana, 2022. "Model to Determine the Best Modifications of Products with Consideration Customers’ Expectations," Energies, MDPI, vol. 15(21), pages 1-21, October.
    9. Yildirim, Mehmet Ali & Cebula, Artur & Sułowicz, Maciej, 2022. "A cooling design for photovoltaic panels – Water-based PV/T system," Energy, Elsevier, vol. 256(C).

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