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Droop Control Optimization for Improved Power Sharing in AC Islanded Microgrids Based on Centripetal Force Gravity Search Algorithm

Author

Listed:
  • Mohammed Qasim Taha

    (Department of Electrical & Computer Engineering, Graduate School of Science and Engineering, Altinbas University, Istanbul 34200, Turkey
    College of Applied Sciences-Hit, University of Anbar, Anbar 31001, Iraq)

  • Sefer Kurnaz

    (Department of Electrical & Computer Engineering, Graduate School of Science and Engineering, Altinbas University, Istanbul 34200, Turkey)

Abstract

The urgent demand for clean and renewable energy sources has led to the emergence of the microgrid (MG) concept. MGs are small grids connecting various micro-sources, such as diesel, photovoltaic wind, and fuel cells. They operate flexibly, connected to the grid, standalone, and in clusters. In AC MG control, a hierarchical system consists of three levels: primary, secondary, and tertiary. It monitors and ensures MG stability, power quality, and power sharing based on the specifications of governing protocols. Various challenging transient disturbances exist, such as generator tripping, secondary control failure due to communication delay, and drastic load changes. Although several optimal power sharing methods have been invented, they pose complex control requirements and provide limited improvement. Therefore, in this paper, a novel optimized droop control is proposed using a metaheuristic multi-objective evolutionary algorithm called the Centripetal Force-Gravity Search Algorithm (CF-GSA) to improve the droop performance of power sharing, voltage and frequency stability, and power quality. CF-GSA is an improved algorithm designed to address the issue of local solutions commonly encountered in optimization algorithms. The effectiveness and superiority of the proposed method are validated through a series of simulations. The results of these simulations show that the proposed multi-objective optimization droop control method works well to fix problems caused by power sharing errors in isolated AC microgrids that have to deal with high inductive loads and changes in line impedance.

Suggested Citation

  • Mohammed Qasim Taha & Sefer Kurnaz, 2023. "Droop Control Optimization for Improved Power Sharing in AC Islanded Microgrids Based on Centripetal Force Gravity Search Algorithm," Energies, MDPI, vol. 16(24), pages 1-20, December.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:24:p:7953-:d:1296019
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    References listed on IDEAS

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    1. Hegazy Rezk & A. G. Olabi & Enas Taha Sayed & Tabbi Wilberforce, 2023. "Role of Metaheuristics in Optimizing Microgrids Operating and Management Issues: A Comprehensive Review," Sustainability, MDPI, vol. 15(6), pages 1-27, March.
    2. Ahmed M. Nassef & Mohammad Ali Abdelkareem & Hussein M. Maghrabie & Ahmad Baroutaji, 2023. "Review of Metaheuristic Optimization Algorithms for Power Systems Problems," Sustainability, MDPI, vol. 15(12), pages 1-27, June.
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