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Multifunctional Distributed MPPT Controller for 3P4W Grid-Connected PV Systems in Distribution Network with Unbalanced Loads

Author

Listed:
  • Emad M. Ahmed

    (Department of Electrical Engineering, Faculty of Engineering, Jouf University, Sakaka 2014, Saudi Arabia
    Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt)

  • Mokhtar Aly

    (Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt
    Solar Energy Research Center (SERC-Chile), Uni. Técnica Federico Santa María, Valparaiso 2390123, Chile)

  • Ahmed Elmelegi

    (Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt)

  • Abdullah G. Alharbi

    (Department of Electrical Engineering, Faculty of Engineering, Jouf University, Sakaka 2014, Saudi Arabia)

  • Ziad M. Ali

    (Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt
    Department of Electrical Engineering, College of Engineering at Wadi Addawasir, Prince Sattam Bin Abdulaziz University, Wadi Addawasir 11991, Saudi Arabia)

Abstract

The integration of photovoltaic (PV) systems with three-phase four-wire (3P4W) distribution networks has imposed several challenges related to existing unbalanced loads, reactive power generation and harmonics content. In this paper, a multifunctional distributed maximum power point (MPPT) controller for grid integration of PV systems is proposed. The proposed distributed MPPT controller is developed based on employing a four-leg three-level T-type multilevel inverter. The proposed inverter performs multifunctionalities, including distributed MPPT, neutral current compensation for the unbalanced loads, supplying reactive power into the grid and the grid integration. Moreover, the proposed inverter overcomes the stochastic behavior of both the PV generation with partial shading problems and its operation with unbalanced loads as well. Furthermore, the new proposed controller injects sinusoidal output currents with decreased levels of total harmonic distortion (THD) into the grid. The tested case study is investigated for the various operating scenarios of PV generation and load demands. The results and tabulated performance comparisons have proven the superior performance of the proposed multifunctional PV generation system. The results show the ability of the proposed controller to efficiently extract distributed MPPT for all PV modules at all the tested scenarios. Additional improvement of the energy efficiency is achieved through the elimination of the neutral current due to existing unbalanced loads.

Suggested Citation

  • Emad M. Ahmed & Mokhtar Aly & Ahmed Elmelegi & Abdullah G. Alharbi & Ziad M. Ali, 2019. "Multifunctional Distributed MPPT Controller for 3P4W Grid-Connected PV Systems in Distribution Network with Unbalanced Loads," Energies, MDPI, vol. 12(24), pages 1-19, December.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:24:p:4799-:d:298637
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    References listed on IDEAS

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    1. Monfared, Houman Jamshidi & Ghasemi, Ahmad & Loni, Abdolah & Marzband, Mousa, 2019. "A hybrid price-based demand response program for the residential micro-grid," Energy, Elsevier, vol. 185(C), pages 274-285.
    2. Marzband, Mousa & Azarinejadian, Fatemeh & Savaghebi, Mehdi & Pouresmaeil, Edris & Guerrero, Josep M. & Lightbody, Gordon, 2018. "Smart transactive energy framework in grid-connected multiple home microgrids under independent and coalition operations," Renewable Energy, Elsevier, vol. 126(C), pages 95-106.
    3. Kofinas, P. & Doltsinis, S. & Dounis, A.I. & Vouros, G.A., 2017. "A reinforcement learning approach for MPPT control method of photovoltaic sources," Renewable Energy, Elsevier, vol. 108(C), pages 461-473.
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    Cited by:

    1. Mohammad Alathamneh & Haneen Ghanayem & Xingyu Yang & R. M. Nelms, 2022. "Three-Phase Grid-Connected Inverter Power Control under Unbalanced Grid Conditions Using a Time-Domain Symmetrical Components Extraction Method," Energies, MDPI, vol. 15(19), pages 1-16, September.
    2. Mohammad Alathamneh & Haneen Ghanayem & Xingyu Yang & R. M. Nelms, 2022. "Three-Phase Grid-Connected Inverter Power Control under Unbalanced Grid Conditions Using a Proportional-Resonant Control Method," Energies, MDPI, vol. 15(19), pages 1-17, September.
    3. Mohammad Alathamneh & Haneen Ghanayem & R. M. Nelms, 2022. "Bidirectional Power Control for a Three-Phase Grid-Connected Inverter under Unbalanced Grid Conditions Using a Proportional-Resonant and a Modified Time-Domain Symmetrical Components Extraction Method," Energies, MDPI, vol. 15(24), pages 1-23, December.
    4. Guoli Feng & Zhihao Ye & Yihui Xia & Heng Nian & Liming Huang & Zerun Wang, 2022. "High Frequency Resonance Suppression Strategy of Three-Phase Four-Wire Split Capacitor Inverter Connected to Parallel Compensation Grid," Energies, MDPI, vol. 15(4), pages 1-20, February.
    5. Karar Mahmoud & Mohamed Abdel-Nasser & Eman Mustafa & Ziad M. Ali, 2020. "Improved Salp–Swarm Optimizer and Accurate Forecasting Model for Dynamic Economic Dispatch in Sustainable Power Systems," Sustainability, MDPI, vol. 12(2), pages 1-21, January.
    6. Emad M. Ahmed & Mokhtar Aly & Manar Mostafa & Hegazy Rezk & Hammad Alnuman & Waleed Alhosaini, 2022. "An Accurate Model for Bifacial Photovoltaic Panels," Sustainability, MDPI, vol. 15(1), pages 1-27, December.
    7. Mokhtar Aly & Emad A. Mohamed & Hegazy Rezk & Ahmed M. Nassef & Mostafa A. Elhosseini & Ahmed Shawky, 2023. "An Improved Optimally Designed Fuzzy Logic-Based MPPT Method for Maximizing Energy Extraction of PEMFC in Green Buildings," Energies, MDPI, vol. 16(3), pages 1-23, January.
    8. Rezk, Hegazy & Aly, Mokhtar & Fathy, Ahmed, 2021. "A novel strategy based on recent equilibrium optimizer to enhance the performance of PEM fuel cell system through optimized fuzzy logic MPPT," Energy, Elsevier, vol. 234(C).

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