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Hybrid Gravitational–Firefly Algorithm-Based Load Frequency Control for Hydrothermal Two-Area System

Author

Listed:
  • Deepak Kumar Gupta

    (School of Electrical Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar 751024, India)

  • Ankit Kumar Soni

    (School of Electrical Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar 751024, India)

  • Amitkumar V. Jha

    (School of Electronics Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar 751024, India)

  • Sunil Kumar Mishra

    (School of Electronics Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar 751024, India)

  • Bhargav Appasani

    (School of Electronics Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar 751024, India)

  • Avireni Srinivasulu

    (Department of Electronics Engineering, JECRC University, Jaipur 303905, India)

  • Nicu Bizon

    (Faculty of Electronics, Communication and Computers, University of Pitesti, 110040 Pitesti, Romania
    ICSI Energy, National Research and Development Institute for Cryogenic and Isotopic Technologies, 240050 Ramnicu Valcea, Romania
    Doctoral School, Polytehnic University of Bucharest, 313 Splaiul Independentei, 060042 Bucharest, Romania)

  • Phatiphat Thounthong

    (Renewable Energy Research Centre (RERC), Department of Teacher Training in Electrical Engineering, Faculty of Technical Education, King Mongkut’s University of Technology North Bangkok, 1518, Pracharat 1 Road, Bangsue, Bangkok 10800, Thailand
    Groupe de Recherche en Energie Electrique de Nancy (GREEN), Université de Lorraine, F-54000 Nancy, France)

Abstract

The load frequency control (LFC) and tie-line power are the key deciding factors to evaluate the performance of a multiarea power system. In this paper, the performance analysis of a two-area power system is presented. This analysis is based on two performance metrics: LFC and tie-line power. The power system consists of a thermal plant generation system and a hydro plant generation system. The performance is evaluated by designing a proportional plus integral (PI) controller. The hybrid gravitational search with firefly algorithm (hGFA) has been devised to achieve proper tuning of the controller parameter. The designed algorithm involves integral time absolute error (ITAE) as an objective function. For two-area hydrothermal power systems, the load frequency and tie-line power are correlated with the system generation capacity and the load. Any deviation in the generation and in the load capacity causes variations in the load frequencies, as well as in the tie-line power. Variations from the nominal value may hamper the operation of the power system with adverse consequences. Hence, performance of the hydrothermal power system is analyzed using the simulations based on the step load change. To elucidate the efficacy of the hGFA, the performance is compared with some of the well-known optimization techniques, namely, particle swarm optimization (PSO), genetic algorithm (GA), gravitational search algorithm (GSA) and the firefly algorithm (FA).

Suggested Citation

  • Deepak Kumar Gupta & Ankit Kumar Soni & Amitkumar V. Jha & Sunil Kumar Mishra & Bhargav Appasani & Avireni Srinivasulu & Nicu Bizon & Phatiphat Thounthong, 2021. "Hybrid Gravitational–Firefly Algorithm-Based Load Frequency Control for Hydrothermal Two-Area System," Mathematics, MDPI, vol. 9(7), pages 1-15, March.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:7:p:712-:d:524064
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    References listed on IDEAS

    as
    1. Sunil Kumar Mishra & Bhargav Appasani & Amitkumar Vidyakant Jha & Izaskun Garrido & Aitor J. Garrido, 2020. "Centralized Airflow Control to Reduce Output Power Variation in a Complex OWC Ocean Energy Network," Complexity, Hindawi, vol. 2020, pages 1-16, August.
    2. Deepak Kumar Gupta & Amitkumar V. Jha & Bhargav Appasani & Avireni Srinivasulu & Nicu Bizon & Phatiphat Thounthong, 2021. "Load Frequency Control Using Hybrid Intelligent Optimization Technique for Multi-Source Power Systems," Energies, MDPI, vol. 14(6), pages 1-16, March.
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    Cited by:

    1. Wadi, Mohammed & Shobole, Abdulfetah & Elmasry, Wisam & Kucuk, Ismail, 2024. "Load frequency control in smart grids: A review of recent developments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    2. Bhargav Appasani & Amitkumar V. Jha & Deepak Kumar Gupta & Nicu Bizon & Phatiphat Thounthong, 2023. "PSO α : A Fragmented Swarm Optimisation for Improved Load Frequency Control of a Hybrid Power System Using FOPID," Energies, MDPI, vol. 16(5), pages 1-17, February.

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