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A Novel Sooty Terns Algorithm for Deregulated MPC-LFC Installed in Multi-Interconnected System with Renewable Energy Plants

Author

Listed:
  • Hossam Hassan Ali

    (Electrical Department, Faculty of Technology and Education, Sohag University, Sohag 82524, Egypt)

  • Ahmed Fathy

    (Electrical Power & Machine Department, Faculty of Engineering, Zagazig University, Zagazig 44519, Egypt)

  • Abdullah M. Al-Shaalan

    (Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia)

  • Ahmed M. Kassem

    (Electrical Engineering Department, Faculty of Engineering, Sohag University, Sohag 82524, Egypt)

  • Hassan M. H. Farh

    (Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia)

  • Abdullrahman A. Al-Shamma’a

    (Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia)

  • Hossam A. Gabbar

    (Faculty of Energy Systems and Nuclear Science, Ontario Tech University (UOIT), 2000 Simcoe St N, Oshawa, ON L1G 0C5, Canada)

Abstract

This paper introduces a novel metaheuristic approach of sooty terns optimization algorithm (STOA) to determine the optimum parameters of model predictive control (MPC)-based deregulated load frequency control (LFC). The system structure consists of three interconnected plants with nonlinear multisources comprising wind turbine, photovoltaic model with maximum power point tracker, and superconducting magnetic energy storage under deregulated environment. The proposed objective function is the integral time absolute error (ITAE) of the deviations in frequencies and powers in tie-lines. The analysis aims at determining the optimum parameters of MPC via STOA such that ITAE is minimized. Moreover, the proposed STOA-MPC is examined under variation of the system parameters and random load disturbance. The time responses and performance specifications of the proposed STOA-MPC are compared to those obtained with MPC optimized via differential evolution, intelligent water drops algorithm, stain bower braid algorithm, and firefly algorithm. Furthermore, a practical case study of interconnected system comprising the Kuraymat solar thermal power station is analyzed based on actual recorded solar radiation. The obtained results via the proposed STOA-MPC-based deregulated LFC confirmed the competence and robustness of the designed controller compared to the other algorithms.

Suggested Citation

  • Hossam Hassan Ali & Ahmed Fathy & Abdullah M. Al-Shaalan & Ahmed M. Kassem & Hassan M. H. Farh & Abdullrahman A. Al-Shamma’a & Hossam A. Gabbar, 2021. "A Novel Sooty Terns Algorithm for Deregulated MPC-LFC Installed in Multi-Interconnected System with Renewable Energy Plants," Energies, MDPI, vol. 14(17), pages 1-27, August.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:17:p:5393-:d:625586
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    References listed on IDEAS

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    1. Hassan Haes Alhelou & Mohamad-Esmail Hamedani-Golshan & Reza Zamani & Ehsan Heydarian-Forushani & Pierluigi Siano, 2018. "Challenges and Opportunities of Load Frequency Control in Conventional, Modern and Future Smart Power Systems: A Comprehensive Review," Energies, MDPI, vol. 11(10), pages 1-35, September.
    2. Ghasemi-Marzbali, Ali, 2020. "Multi-area multi-source automatic generation control in deregulated power system," Energy, Elsevier, vol. 201(C).
    3. Dhundhara, Sandeep & Verma, Yajvender Pal, 2018. "Capacitive energy storage with optimized controller for frequency regulation in realistic multisource deregulated power system," Energy, Elsevier, vol. 147(C), pages 1108-1128.
    4. Pappachen, Abhijith & Peer Fathima, A., 2017. "Critical research areas on load frequency control issues in a deregulated power system: A state-of-the-art-of-review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 163-177.
    5. Selvaraju, Ramesh Kumar & Somaskandan, Ganapathy, 2016. "Impact of energy storage units on load frequency control of deregulated power systems," Energy, Elsevier, vol. 97(C), pages 214-228.
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