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Arithmetic optimization based MPPT for photovoltaic systems operating under nonuniform situations

Author

Listed:
  • Maheshwari Adaikkappan
  • Nageswari Sathiyamoorthy
  • Durga Devi Ravichandran
  • Karthikeyan Balasubramani
  • Sundararaju Karuppannan
  • Ramasamy Palanisamy
  • Zakaria M S Elbarbary
  • Saad F Al-Gahtani
  • Ahmed I Omar

Abstract

Photovoltaic (PV) modules may encounter nonuniform situations that reduce their useable power volume, causing ineffective maximum power point tracking (MPPT). Moreover, due to the incorporation of bypass diodes, power-voltage (P-V) graph has multi-peaks when each component of the module receives different solar irradiation. This paper proposes a solution to this problem using an arithmetic optimization algorithm (AOA) for MPPT in PV systems operating in nonuniform situations. The non-operational regions associated with the voltage are excluded using a single-ended primary inductance converter (SEPIC) with voltage step-up and step-down capability. The AOA-MPPT algorithm gets current and voltage as inputs from the PV modules. It computes the converter’s duty cycle and regulates the operational point to keep MPP under all working conditions. The proposed AOA-MPPT’s efficacy under different insolation patterns has been validated using three nonuniform conditions in terms of convergence, tracking speed, steady state oscillations, and tracking efficiency. In simulations, the proposed AOA-MPPT method and SEPIC converter demonstrated quick response and excellent steady-state performance. The tracking efficiency of the AOA-MPPT is above 99% and settling time is 200 to 300ms for all three non-uniform conditions.

Suggested Citation

  • Maheshwari Adaikkappan & Nageswari Sathiyamoorthy & Durga Devi Ravichandran & Karthikeyan Balasubramani & Sundararaju Karuppannan & Ramasamy Palanisamy & Zakaria M S Elbarbary & Saad F Al-Gahtani & Ah, 2024. "Arithmetic optimization based MPPT for photovoltaic systems operating under nonuniform situations," PLOS ONE, Public Library of Science, vol. 19(12), pages 1-26, December.
    • Handle: RePEc:plo:pone00:0311177
    DOI: 10.1371/journal.pone.0311177
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    References listed on IDEAS

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    1. Reshma Gopi, R. & Sreejith, S., 2018. "Converter topologies in photovoltaic applications – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 1-14.
    2. Ahmed Hussain Elmetwaly & Ramy Adel Younis & Abdelazeem Abdallah Abdelsalam & Ahmed Ibrahim Omar & Mohamed Metwally Mahmoud & Faisal Alsaif & Adel El-Shahat & Mohamed Attya Saad, 2023. "Modeling, Simulation, and Experimental Validation of a Novel MPPT for Hybrid Renewable Sources Integrated with UPQC: An Application of Jellyfish Search Optimizer," Sustainability, MDPI, vol. 15(6), pages 1-30, March.
    3. Izhar Ul Haq & Qudrat Khan & Safeer Ullah & Shahid Ahmed Khan & Rini Akmeliawati & Mehmood Ashraf Khan & Jamshed Iqbal, 2022. "Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-29, January.
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