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Modeling and Simulation of Modified MPPT Techniques under Varying Operating Climatic Conditions

Author

Listed:
  • Doaa Khodair

    (Faculty of Engineering and Technology, Future University in Egypt, Cairo 11835, Egypt)

  • Saad Motahhir

    (Engineering, Systems and Applications Laboratory, ENSA, SMBA University, Fez 30000, Morocco)

  • Hazem H. Mostafa

    (Energy and Renewable Energy Department, Faculty of Engineering, Egyptian Chinese University, Cairo 11724, Egypt)

  • Ahmed Shaker

    (Engineering Physics and Mathematics Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt)

  • Hossam Abd El Munim

    (Computer and Systems Engineering Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt)

  • Mohamed Abouelatta

    (Electronics and Electrical Communications Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt)

  • Ahmed Saeed

    (Electrical Engineering Department, Future University in Egypt, Cairo 11835, Egypt)

Abstract

Enhancing the performance of photovoltaic (PV) systems has recently become a key concern because of the market demand for green energy. To obtain the most possible power from the solar module, it is imperative to allow the PV system to operate at its maximum power point (MPP) regardless of the climatic conditions. In this study, a comparison of distinctive Maximum Power-Point Tracking (MPPT) techniques is provided, which are Perturb and Observe (P&O) and Modified Variable Step-Size P&O, as well as Incremental Conductance (INC) and Modified Variable Step-Size INC, using a boost converter for two types of solar panels. Using MATLAB software, simulations have been performed to assess the efficiency of the solar module under several environmental conditions, standard test conditions (STCs), and sudden and ramp variations in both solar irradiance and temperature. The output power efficiency, time response, and steady-state power oscillations have all been taken into account in this study. The simulation results of the improved algorithms demonstrate an enhancement in the PV module performance over conventional algorithms in many factors including steady-state conditions, tracking time, and converter efficiency. Furthermore, a boost in the dynamic response in monitoring the MPP is observed in a variety of climatical circumstances. Moreover, the proposed P&O MPPT algorithm is implemented in a hardware system and the experimental results verified the effectiveness, regarding both fast-tracking speed and lower oscillations, of the proposed Variable Step-Size P&O algorithm and its superiority over the conventional P&O technique.

Suggested Citation

  • Doaa Khodair & Saad Motahhir & Hazem H. Mostafa & Ahmed Shaker & Hossam Abd El Munim & Mohamed Abouelatta & Ahmed Saeed, 2023. "Modeling and Simulation of Modified MPPT Techniques under Varying Operating Climatic Conditions," Energies, MDPI, vol. 16(1), pages 1-20, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:1:p:549-:d:1023876
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    References listed on IDEAS

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    1. Muhammad Annas Hafeez & Ahmer Naeem & Muhammad Akram & Muhammad Yaqoob Javed & Aamer Bilal Asghar & Yong Wang, 2022. "A Novel Hybrid MPPT Technique Based on Harris Hawk Optimization (HHO) and Perturb and Observer (P&O) under Partial and Complex Partial Shading Conditions," Energies, MDPI, vol. 15(15), pages 1-18, July.
    2. Ishaque, Kashif & Salam, Zainal & Lauss, George, 2014. "The performance of perturb and observe and incremental conductance maximum power point tracking method under dynamic weather conditions," Applied Energy, Elsevier, vol. 119(C), pages 228-236.
    3. Nouman Akram & Laiq Khan & Shahrukh Agha & Kamran Hafeez, 2022. "Global Maximum Power Point Tracking of Partially Shaded PV System Using Advanced Optimization Techniques," Energies, MDPI, vol. 15(11), pages 1-29, May.
    4. Victor Arturo Martinez Lopez & Ugnė Žindžiūtė & Hesan Ziar & Miro Zeman & Olindo Isabella, 2022. "Study on the Effect of Irradiance Variability on the Efficiency of the Perturb-and-Observe Maximum Power Point Tracking Algorithm," Energies, MDPI, vol. 15(20), pages 1-12, October.
    5. Belkaid, A. & Colak, I. & Isik, O., 2016. "Photovoltaic maximum power point tracking under fast varying of solar radiation," Applied Energy, Elsevier, vol. 179(C), pages 523-530.
    6. Imran Pervez & Charalampos Antoniadis & Yehia Massoud, 2022. "Advanced Limited Search Strategy for Enhancing the Performance of MPPT Algorithms," Energies, MDPI, vol. 15(15), pages 1-19, August.
    7. Verma, Deepak & Nema, Savita & Shandilya, A.M. & Dash, Soubhagya K., 2016. "Maximum power point tracking (MPPT) techniques: Recapitulation in solar photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1018-1034.
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    Cited by:

    1. Musong L. Katche & Augustine B. Makokha & Siagi O. Zachary & Muyiwa S. Adaramola, 2023. "A Comprehensive Review of Maximum Power Point Tracking (MPPT) Techniques Used in Solar PV Systems," Energies, MDPI, vol. 16(5), pages 1-23, February.
    2. Matías Garbarino & Jaime Rohten & Rodrigo Morales & José Espinoza & Javier Muñoz & José Silva & David Dewar, 2023. "Extended Operating Region Algorithm for PV Array Connected to Microgrids for Wide Frequency and Amplitude Variations," Energies, MDPI, vol. 16(7), pages 1-22, March.
    3. Anderson Aparecido Dionizio & Leonardo Poltronieri Sampaio & Sérgio Augusto Oliveira da Silva & Sebastián de Jesús Manrique Machado, 2023. "Grid-Tied Single-Phase Integrated Zeta Inverter for Photovoltaic Applications," Energies, MDPI, vol. 16(9), pages 1-19, April.
    4. Franciéli Lima de Sá & Domingo Ruiz-Caballero & Cleiton Dal’Agnol & William Rafhael da Silva & Samir Ahmad Mussa, 2023. "High Static Gain DC–DC Double Boost Quadratic Converter," Energies, MDPI, vol. 16(17), pages 1-24, September.

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