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Enhanced Salp Swarm Algorithm for Multimodal Optimization and Fuzzy Based Grid Frequency Controller Design

Author

Listed:
  • Smrutiranjan Nayak

    (Department of Electrical Engineering, ITER, Siksha ‘o’ Anusandhan (Deemed to Be University), Bhubaneswar 751030, India)

  • Sanjeeb Kumar Kar

    (Department of Electrical Engineering, ITER, Siksha ‘o’ Anusandhan (Deemed to Be University), Bhubaneswar 751030, India)

  • Subhransu Sekhar Dash

    (Department of Electrical Engineering, Government College of Engineering, Keonjhar 758002, India)

  • Pradeep Vishnuram

    (Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology, Chennai 603203, India)

  • Sudhakar Babu Thanikanti

    (Department of Electrical and Electronics Engineering, Chaitanya Bharathi Institute of Technology, Hyderabad 500075, India)

  • Benedetto Nastasi

    (Department of Planning, Design, and Technology of Architecture, Sapienza University of Rome, Via Flaminia 72, 00196 Rome, Italy)

Abstract

In the present study, an Enhanced SSA (ESSA) has been proposed where the parameter of the SSA technique, which balances the exploration and exploitation phases, has been modified. Additionally, the variable scaling factor is engaged to regulate the salp’s position during the search procedure to minimize the random movement of salps. To demonstrate the effectiveness of the enhanced SSA (ESSA), a set of multimodal test functions are engaged. The statistical outcomes demonstrate that ESSA profits from local optima evasion and quick convergence speed, which aids the proposed ESSA algorithm to outclass the standard SSA and other recent algorithms. The fair analysis displays that ESSA delivers very promising results and outclass current methods. Next, frequency control of power systems is executed by designing a Combined Fuzzy PID (CFPID) controller with the projected ESSA method. Next, a Partially Distributed CFPID (PD-CFPID) controller is designed for a distributed power system (DPS). It is shown that the ESSA method outclasses the SSA method in engineering problems. It is also noted that the ESSA-based PD-CFPID scheme has become more operative in monitoring the frequency than similar structured centralized fuzzy PID (CFPID) as well as PID controller. Finally, the outcomes of the PD-CFPID controller are equated with CFPID and PID for various uncertain situations to validate the benefit of the proposed control approach.

Suggested Citation

  • Smrutiranjan Nayak & Sanjeeb Kumar Kar & Subhransu Sekhar Dash & Pradeep Vishnuram & Sudhakar Babu Thanikanti & Benedetto Nastasi, 2022. "Enhanced Salp Swarm Algorithm for Multimodal Optimization and Fuzzy Based Grid Frequency Controller Design," Energies, MDPI, vol. 15(9), pages 1-22, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3210-:d:803935
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    References listed on IDEAS

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    1. Francesco Mancini & Benedetto Nastasi, 2020. "Solar Energy Data Analytics: PV Deployment and Land Use," Energies, MDPI, vol. 13(2), pages 1-18, January.
    2. Savino, Matteo M. & Manzini, Riccardo & Della Selva, Vincenzo & Accorsi, Riccardo, 2017. "A new model for environmental and economic evaluation of renewable energy systems: The case of wind turbines," Applied Energy, Elsevier, vol. 189(C), pages 739-752.
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    Cited by:

    1. Ziwei Lin & Andrea Matta & Sichang Du & Evren Sahin, 2022. "A Partition-Based Random Search Method for Multimodal Optimization," Mathematics, MDPI, vol. 11(1), pages 1-30, December.

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