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An Eagle Strategy Arithmetic Optimization Algorithm for Frequency Stability Enhancement Considering High Renewable Power Penetration and Time-Varying Load

Author

Listed:
  • Ahmed. H. A. Elkasem

    (Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt)

  • Salah Kamel

    (Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt)

  • Mohamed H. Hassan

    (Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt)

  • Mohamed Khamies

    (Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt)

  • Emad M. Ahmed

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

Abstract

This study proposes a new optimization technique, known as the eagle strategy arithmetic optimization algorithm (ESAOA), to address the limitations of the original algorithm called arithmetic optimization algorithm (AOA). ESAOA is suggested to enhance the implementation of the original AOA. It includes an eagle strategy to avoid premature convergence and increase the populations’ efficacy to reach the optimum solution. The improved algorithm is utilized to fine-tune the parameters of the fractional-order proportional-integral-derivative (FOPID) and the PID controllers for supporting the frequency stability of a hybrid two-area multi-sources power system. Here, each area composites a combination of conventional power plants (i.e., thermal-hydro-gas) and renewable energy sources (i.e., wind farm and solar farm). Furthermore, the superiority of the proposed algorithm has been validated based on 23 benchmark functions. Then, the superiority of the proposed FOPID-based ESAOA algorithm is verified through a comparison of its performance with other controller performances (i.e., PID-based AOA, PID-based ESAOA, and PID-based teaching learning-based optimization TLBO) under different operating conditions. Furthermore, the system nonlinearities, system uncertainties, high renewable power penetration, and control time delay has been considered to ensure the effectiveness of the proposed FOPID based on the ES-AOA algorithm. All simulation results elucidate that the domination in favor of the proposed FOPID-based ES-AOA algorithm in enhancing the frequency stability effectually will guarantee a reliable performance.

Suggested Citation

  • Ahmed. H. A. Elkasem & Salah Kamel & Mohamed H. Hassan & Mohamed Khamies & Emad M. Ahmed, 2022. "An Eagle Strategy Arithmetic Optimization Algorithm for Frequency Stability Enhancement Considering High Renewable Power Penetration and Time-Varying Load," Mathematics, MDPI, vol. 10(6), pages 1-38, March.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:6:p:854-:d:766561
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    References listed on IDEAS

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    1. Abdelhady Ramadan & Salah Kamel & Mohamed H. Hassan & Marcos Tostado-Véliz & Ali M. Eltamaly, 2021. "Parameter Estimation of Static/Dynamic Photovoltaic Models Using a Developed Version of Eagle Strategy Gradient-Based Optimizer," Sustainability, MDPI, vol. 13(23), pages 1-29, November.
    2. Hamza Yapıcı & Nurettin Çetinkaya, 2017. "An Improved Particle Swarm Optimization Algorithm Using Eagle Strategy for Power Loss Minimization," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-11, March.
    3. Jeffrey O Agushaka & Absalom E Ezugwu, 2021. "Advanced arithmetic optimization algorithm for solving mechanical engineering design problems," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-29, August.
    4. Ahmed H. A. Elkasem & Mohamed Khamies & Gaber Magdy & Ibrahim B. M. Taha & Salah Kamel, 2021. "Frequency Stability of AC/DC Interconnected Power Systems with Wind Energy Using Arithmetic Optimization Algorithm-Based Fuzzy-PID Controller," Sustainability, MDPI, vol. 13(21), pages 1-29, November.
    5. Chen, Zhicong & Wu, Lijun & Lin, Peijie & Wu, Yue & Cheng, Shuying, 2016. "Parameters identification of photovoltaic models using hybrid adaptive Nelder-Mead simplex algorithm based on eagle strategy," Applied Energy, Elsevier, vol. 182(C), pages 47-57.
    6. Shankar, Ravi & Pradhan, S.R. & Chatterjee, Kalyan & Mandal, Rajasi, 2017. "A comprehensive state of the art literature survey on LFC mechanism for power system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1185-1207.
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    Cited by:

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    2. Emad M. Ahmed & Ali Selim & Hammad Alnuman & Waleed Alhosaini & Mokhtar Aly & Emad A. Mohamed, 2022. "Modified Frequency Regulator Based on TI λ -TD μ FF Controller for Interconnected Microgrids with Incorporating Hybrid Renewable Energy Sources," Mathematics, MDPI, vol. 11(1), pages 1-39, December.
    3. Emad A. Mohamed & Mokhtar Aly & Masayuki Watanabe, 2022. "New Tilt Fractional-Order Integral Derivative with Fractional Filter (TFOIDFF) Controller with Artificial Hummingbird Optimizer for LFC in Renewable Energy Power Grids," Mathematics, MDPI, vol. 10(16), pages 1-33, August.
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