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African Vulture Optimization-Based Optimal Control Strategy for Voltage Control of Islanded DC Microgrids

Author

Listed:
  • Basma Salah

    (Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt
    Power Electronics and Energy Conversion Department, Electronics Research Institute, Cairo 12622, Egypt)

  • Hany M. Hasanien

    (Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt)

  • Fadia M. A. Ghali

    (Power Electronics and Energy Conversion Department, Electronics Research Institute, Cairo 12622, Egypt)

  • Yasser M. Alsayed

    (Power Electronics and Energy Conversion Department, Electronics Research Institute, Cairo 12622, Egypt)

  • Shady H. E. Abdel Aleem

    (Department of Electrical Engineering, Valley High Institute of Engineering and Technology, Science Valley Academy, Qalyubia 44971, Egypt)

  • Adel El-Shahat

    (Energy Technology Program, School of Engineering Technology, Purdue University, West Lafayette, IN 47907, USA)

Abstract

DC microgrids have gained a lot of interest recently due to increasing dc loads such as electric vehicles and the penetration of renewable energy sources (RESs). However, DC microgrids face challenges concerning bus voltage fluctuations, which severely impact the system stability when subjected to uncertainties of load and RESs. This paper focuses on maintaining the stability of a DC-bus through voltage control for a dc islanded microgrid using the concept of cascade double-loop control. The rule in cascade double-loop control is based on a proportional-integral (PI) controller tuned through a new nature-inspired African vulture optimization algorithm (AVOA). The paper presents a comparison of the performance of the African vulture optimization algorithm against particle swarm optimization (PSO) under several operating conditions. The simulation considers actual data for the solar irradiance and temperature and sudden load changes. The system is implemented on MATLAB/Simulink. The results demonstrate that the AVOA-based PI controller performs better in voltage regulation than the PSO-based PI controller.

Suggested Citation

  • Basma Salah & Hany M. Hasanien & Fadia M. A. Ghali & Yasser M. Alsayed & Shady H. E. Abdel Aleem & Adel El-Shahat, 2022. "African Vulture Optimization-Based Optimal Control Strategy for Voltage Control of Islanded DC Microgrids," Sustainability, MDPI, vol. 14(19), pages 1-26, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:11800-:d:919486
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    References listed on IDEAS

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    1. Aml Sayed & Mohamed Ebeed & Ziad M. Ali & Adel Bedair Abdel-Rahman & Mahrous Ahmed & Shady H. E. Abdel Aleem & Adel El-Shahat & Mahmoud Rihan, 2021. "A Hybrid Optimization Algorithm for Solving of the Unit Commitment Problem Considering Uncertainty of the Load Demand," Energies, MDPI, vol. 14(23), pages 1-21, November.
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    4. Mahmoud Elsisi & Minh-Quang Tran & Hany M. Hasanien & Rania A. Turky & Fahad Albalawi & Sherif S. M. Ghoneim, 2021. "Robust Model Predictive Control Paradigm for Automatic Voltage Regulators against Uncertainty Based on Optimization Algorithms," Mathematics, MDPI, vol. 9(22), pages 1-19, November.
    5. Igyso Zafeiratou & Ionela Prodan & Laurent Lefévre, 2021. "A Hierarchical Control Approach for Power Loss Minimization and Optimal Power Flow within a Meshed DC Microgrid," Energies, MDPI, vol. 14(16), pages 1-27, August.
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    Cited by:

    1. Arindita Saha & Puja Dash & Naladi Ram Babu & Tirumalasetty Chiranjeevi & Mudadla Dhananjaya & Łukasz Knypiński, 2022. "Dynamic Stability Evaluation of an Integrated Biodiesel-Geothermal Power Plant-Based Power System with Spotted Hyena Optimized Cascade Controller," Sustainability, MDPI, vol. 14(22), pages 1-26, November.
    2. Amr Saleh & Hany M. Hasanien & Rania A. Turky & Balgynbek Turdybek & Mohammed Alharbi & Francisco Jurado & Walid A. Omran, 2023. "Optimal Model Predictive Control for Virtual Inertia Control of Autonomous Microgrids," Sustainability, MDPI, vol. 15(6), pages 1-25, March.

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