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Grid-Connected PV System with Reactive Power Management and an Optimized SRF-PLL Using Genetic Algorithm

Author

Listed:
  • Bashar Aldbaiat

    (School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, UK)

  • Mutasim Nour

    (School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, UK)

  • Eyad Radwan

    (Department of Electrical Engineering, Faculty of Engineering Technology, Applied Science Private University, P.O. Box 166, Amman 11931, Jordan)

  • Emad Awada

    (Department of Electrical Engineering, College of Engineering Technology, Al-Balqa Applied University, P.O. Box 166, Amman 11931, Jordan)

Abstract

This paper presents a two-stage grid-connected PV system with reactive power management capability. The proposed model can send phase-shifted current to the grid during a low-voltage ride through (LVRT) to recover the voltage levels of the grid’s feeders. The novelty of the proposed algorithm, unlike the common methods, is that it does not need to disable the maximum power point tracking (MPPT) state while managing active and reactive power injection simultaneously. Moreover, the new method promotes a safety factor by offering overcurrent protection to the PV inverter. The phase-locked loop based on the synchronous reference frame (SRF-PLL) is optimized using a genetic algorithm (GA). The settling time of SRF-PLL’s step response is minimized, and the frequency dynamics are improved to enhance synchronization during LVRT. The system’s performance is tested and verified using MATLAB/Simulink simulations. The obtained results prove the effectiveness of the proposed control algorithm in managing reactive power interventions. The optimized phase-locked loop shows robust performance and is compared to the conventional low-gain PLL to spot the enhancement.

Suggested Citation

  • Bashar Aldbaiat & Mutasim Nour & Eyad Radwan & Emad Awada, 2022. "Grid-Connected PV System with Reactive Power Management and an Optimized SRF-PLL Using Genetic Algorithm," Energies, MDPI, vol. 15(6), pages 1-21, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:6:p:2177-:d:772716
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    References listed on IDEAS

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    1. Naderi, Yahya & Hosseini, Seyed Hossein & Ghassem Zadeh, Saeid & Mohammadi-Ivatloo, Behnam & Vasquez, Juan C. & Guerrero, Josep M., 2018. "An overview of power quality enhancement techniques applied to distributed generation in electrical distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 201-214.
    2. Talha, Muhammad & Raihan, S.R.S. & Rahim, N Abd, 2020. "PV inverter with decoupled active and reactive power control to mitigate grid faults," Renewable Energy, Elsevier, vol. 162(C), pages 877-892.
    3. Aravind Chellachi Kathiresan & Jeyaraj PandiaRajan & Asokan Sivaprakash & Thanikanti Sudhakar Babu & Md. Rabiul Islam, 2020. "An Adaptive Feed-Forward Phase Locked Loop for Grid Synchronization of Renewable Energy Systems under Wide Frequency Deviations," Sustainability, MDPI, vol. 12(17), pages 1-15, August.
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    Cited by:

    1. Gilberto A. Herrejón-Pintor & Enrique Melgoza-Vázquez & José Luis Monroy-Morales, 2023. "A Three-Phase Synchronization Algorithm Based on a Modified DSOGI with Adjustable Re-Filtering," Energies, MDPI, vol. 16(18), pages 1-18, September.
    2. Afzal, Asif & Buradi, Abdulrajak & Jilte, Ravindra & Shaik, Saboor & Kaladgi, Abdul Razak & Arıcı, Muslum & Lee, Chew Tin & Nižetić, Sandro, 2023. "Optimizing the thermal performance of solar energy devices using meta-heuristic algorithms: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
    3. Gilberto A. Herrejón-Pintor & Enrique Melgoza-Vázquez & Jose de Jesús Chávez, 2022. "A Modified SOGI-PLL with Adjustable Refiltering for Improved Stability and Reduced Response Time," Energies, MDPI, vol. 15(12), pages 1-20, June.
    4. Naamane Debdouche & Brahim Deffaf & Habib Benbouhenni & Zarour Laid & Mohamed I. Mosaad, 2023. "Direct Power Control for Three-Level Multifunctional Voltage Source Inverter of PV Systems Using a Simplified Super-Twisting Algorithm," Energies, MDPI, vol. 16(10), pages 1-32, May.
    5. Zhen Huang & Xuechun Xiao & Yuan Gao & Yonghong Xia & Tomislav Dragičević & Pat Wheeler, 2023. "Emerging Information Technologies for the Energy Management of Onboard Microgrids in Transportation Applications," Energies, MDPI, vol. 16(17), pages 1-26, August.

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