IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i17p5393-d625586.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/17/5393/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/17/5393/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Ghasemi-Marzbali, Ali, 2020. "Multi-area multi-source automatic generation control in deregulated power system," Energy, Elsevier, vol. 201(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kaleem Ullah & Abdul Basit & Zahid Ullah & Sheraz Aslam & Herodotos Herodotou, 2021. "Automatic Generation Control Strategies in Conventional and Modern Power Systems: A Comprehensive Overview," Energies, MDPI, vol. 14(9), pages 1-43, April.
    2. Dillip Kumar Mishra & Daria Złotecka & Li Li, 2022. "Significance of SMES Devices for Power System Frequency Regulation Scheme considering Distributed Energy Resources in a Deregulated Environment," Energies, MDPI, vol. 15(5), pages 1-32, February.
    3. Rafiq Asghar & Francesco Riganti Fulginei & Hamid Wadood & Sarmad Saeed, 2023. "A Review of Load Frequency Control Schemes Deployed for Wind-Integrated Power Systems," Sustainability, MDPI, vol. 15(10), pages 1-29, May.
    4. Eleftherios Vlahakis & Leonidas Dritsas & George Halikias, 2019. "Distributed LQR Design for a Class of Large-Scale Multi-Area Power Systems," Energies, MDPI, vol. 12(14), pages 1-28, July.
    5. Chaudhary, Aniket Karan & Roy, Satyabrata & Guha, Dipayan & Negi, Richa & Banerjee, Subrata, 2024. "Adaptive cyber-tolerant finite-time frequency control framework for renewable-integrated power system under deception and periodic denial-of-service attacks," Energy, Elsevier, vol. 302(C).
    6. Arya, Yogendra, 2019. "AGC of PV-thermal and hydro-thermal power systems using CES and a new multi-stage FPIDF-(1+PI) controller," Renewable Energy, Elsevier, vol. 134(C), pages 796-806.
    7. Sadeq D. Al-Majidi & Hisham Dawood Salman Altai & Mohammed H. Lazim & Mohammed Kh. Al-Nussairi & Maysam F. Abbod & Hamed S. Al-Raweshidy, 2023. "Bacterial Foraging Algorithm for a Neural Network Learning Improvement in an Automatic Generation Controller," Energies, MDPI, vol. 16(6), pages 1-19, March.
    8. Sadeq D. Al-Majidi & Mohammed Kh. AL-Nussairi & Ali Jasim Mohammed & Adel Manaa Dakhil & Maysam F. Abbod & Hamed S. Al-Raweshidy, 2022. "Design of a Load Frequency Controller Based on an Optimal Neural Network," Energies, MDPI, vol. 15(17), pages 1-28, August.
    9. Ajay Kumar & Deepak Kumar Gupta & Sriparna Roy Ghatak & Bhargav Appasani & Nicu Bizon & Phatiphat Thounthong, 2022. "A Novel Improved GSA-BPSO Driven PID Controller for Load Frequency Control of Multi-Source Deregulated Power System," Mathematics, MDPI, vol. 10(18), pages 1-41, September.
    10. 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).
    11. 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.
    12. Balvender Singh & Adam Slowik & Shree Krishan Bishnoi, 2023. "Review on Soft Computing-Based Controllers for Frequency Regulation of Diverse Traditional, Hybrid, and Future Power Systems," Energies, MDPI, vol. 16(4), pages 1-30, February.
    13. 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.
    14. Latif, Abdul & Hussain, S.M. Suhail & Das, Dulal Chandra & Ustun, Taha Selim, 2020. "State-of-the-art of controllers and soft computing techniques for regulated load frequency management of single/multi-area traditional and renewable energy based power systems," Applied Energy, Elsevier, vol. 266(C).
    15. Yin, Linfei & Zhang, Bin, 2021. "Time series generative adversarial network controller for long-term smart generation control of microgrids," Applied Energy, Elsevier, vol. 281(C).
    16. Amil Daraz & Suheel Abdullah Malik & Ihsan Ul Haq & Khan Bahadar Khan & Ghulam Fareed Laghari & Farhan Zafar, 2020. "Modified PID controller for automatic generation control of multi-source interconnected power system using fitness dependent optimizer algorithm," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-31, November.
    17. Xu, Ying & Ren, Li & Zhang, Zhongping & Tang, Yuejin & Shi, Jing & Xu, Chen & Li, Jingdong & Pu, Dongsheng & Wang, Zhuang & Liu, Huajun & Chen, Lei, 2018. "Analysis of the loss and thermal characteristics of a SMES (Superconducting Magnetic Energy Storage) magnet with three practical operating conditions," Energy, Elsevier, vol. 143(C), pages 372-384.
    18. Narendra Kumar Jena & Subhadra Sahoo & Binod Kumar Sahu & Amiya Kumar Naik & Mohit Bajaj & Stanislav Misak & Vojtech Blazek & Lukas Prokop, 2023. "Impact of a Redox Flow Battery on the Frequency Stability of a Five-Area System Integrated with Renewable Sources," Energies, MDPI, vol. 16(14), pages 1-29, July.
    19. Daraz, Amil, 2023. "Optimized cascaded controller for frequency stabilization of marine microgrid system," Applied Energy, Elsevier, vol. 350(C).
    20. Shreya Shree Das & Arup Das & Subhojit Dawn & Sadhan Gope & Taha Selim Ustun, 2022. "A Joint Scheduling Strategy for Wind and Solar Photovoltaic Systems to Grasp Imbalance Cost in Competitive Market," Sustainability, MDPI, vol. 14(9), pages 1-22, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:17:p:5393-:d:625586. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.