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A Modified Particle Swarm Optimization Algorithm for Power Sharing and Transient Response Improvement of a Grid-Tied Solar PV Based A.C. Microgrid

Author

Listed:
  • Ghulam Abbas

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Aqeel Ahmed Bhutto

    (Department of Mechanical Engineering, Mehran University of Engineering and Technology, SZAB Campus, Khairpur Mirs 66020, Pakistan)

  • Touqeer Ahmed Jumani

    (Department of Electrical Engineering, Mehran University of Engineering and Technology, SZAB Campus, Khairpur Mirs 66020, Pakistan)

  • Sohrab Mirsaeidi

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Mohsin Ali Tunio

    (Department of Electrical Engineering, Mehran University of Engineering and Technology, SZAB Campus, Khairpur Mirs 66020, Pakistan)

  • Hammad Alnuman

    (Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka 72388, Saudi Arabia)

  • Ahmed Alshahir

    (Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka 72388, Saudi Arabia)

Abstract

The increasing penetration of Distributed Generators (D.G.) into the existing power system has brought some real challenges regarding the transient response of electrical systems. The injection of D.G.s and abrupt load changes may cause massive power, current, and voltage overshoots/undershoots, which consequently affects the equilibrium of the existing power system and deteriorate the performance of the connected electrical appliances. A robust and intelligent control strategy is of utmost importance to cope with these issues and enhance the penetration level of D.G.s into the existing power system. This paper presents a Modified Particle Swarm Optimization (MPSO) algorithm-based intelligent controller for attaining a desired power-sharing ratio between the M.G. and the main grid with an optimal transient response in a grid-tied Microgrid (M.G.) system. The proposed MPSO algorithm includes an additional parameter named best neighbor particles (rbest) in the velocity updating equation to convey additional information to every individual particle about all its neighbor particles, consequently leading to the increased exploration capability of the algorithm. The MPSO algorithm optimizes P.I. parameters for transient and steady-state response improvement of the studied M.G. system. The main dynamic response evaluation parameters are the overshoot and settling time for active and reactive power during the D.G. connection and load change. Furthermore, the performance of the proposed controller is compared with the PI-PSO-based MG controller, which validates the effectiveness of the proposed M.G. control scheme in maintaining the required active and reactive power under different operating conditions with minimum possible overshoot and settling time.

Suggested Citation

  • Ghulam Abbas & Aqeel Ahmed Bhutto & Touqeer Ahmed Jumani & Sohrab Mirsaeidi & Mohsin Ali Tunio & Hammad Alnuman & Ahmed Alshahir, 2022. "A Modified Particle Swarm Optimization Algorithm for Power Sharing and Transient Response Improvement of a Grid-Tied Solar PV Based A.C. Microgrid," Energies, MDPI, vol. 16(1), pages 1-14, December.
    • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:348-:d:1018014
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    References listed on IDEAS

    as
    1. Touqeer Ahmed Jumani & Mohd Wazir Mustafa & Nawaf N. Hamadneh & Samer H. Atawneh & Madihah Md. Rasid & Nayyar Hussain Mirjat & Muhammad Akram Bhayo & Ilyas Khan, 2020. "Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids," Energies, MDPI, vol. 13(16), pages 1-22, August.
    2. Touqeer Ahmed Jumani & Mohd Wazir Mustafa & Madihah Md Rasid & Nayyar Hussain Mirjat & Zohaib Hussain Leghari & M. Salman Saeed, 2018. "Optimal Voltage and Frequency Control of an Islanded Microgrid Using Grasshopper Optimization Algorithm," Energies, MDPI, vol. 11(11), pages 1-20, November.
    3. Zhi Wu & Yuxuan Zhuang & Suyang Zhou & Shuning Xu & Peng Yu & Jinqiao Du & Xiner Luo & Ghulam Abbas, 2020. "Bi-Level Planning of Multi-Functional Vehicle Charging Stations Considering Land Use Types," Energies, MDPI, vol. 13(5), pages 1-17, March.
    4. Salman Habib & Ghulam Abbas & Touqeer A. Jumani & Aqeel Ahmed Bhutto & Sohrab Mirsaeidi & Emad M. Ahmed, 2022. "Improved Whale Optimization Algorithm for Transient Response, Robustness, and Stability Enhancement of an Automatic Voltage Regulator System," Energies, MDPI, vol. 15(14), pages 1-18, July.
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