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Load Frequency Control and Automatic Voltage Regulation in a Multi-Area Interconnected Power System Using Nature-Inspired Computation-Based Control Methodology

Author

Listed:
  • Tayyab Ali

    (Department of Electrical Engineering, FET, International Islamic University, Islamabad 44000, Pakistan)

  • Suheel Abdullah Malik

    (Department of Electrical Engineering, FET, International Islamic University, Islamabad 44000, Pakistan)

  • Ibrahim A. Hameed

    (Department of ICT and Natural Sciences, Norwegian University of Science and Technology, Larsgårdsve-gen, 2, 6009 Ålesund, Norway)

  • Amil Daraz

    (School of Information Science and Engineering, Ningbotech University, Ningbo 315100, China)

  • Hana Mujlid

    (Department of Computer Engineering, Taif University, Taif 21944, Saudi Arabia)

  • Ahmad Taher Azar

    (College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia
    Automated Systems and Soft Computing Lab (ASSCL), Prince Sultan University, Riyadh 12435, Saudi Arabia
    Faculty of Computers and Artificial Intelligence, Benha University, Benha 13518, Egypt)

Abstract

The stability control of nominal frequency and terminal voltage in an interconnected power system (IPS) is always a challenging task for researchers. The load variation or any disturbance affects the active and reactive power demands, which badly influence the normal working of IPS. In order to maintain frequency and terminal voltage at rated values, controllers are installed at generating stations to keep these parameters within the prescribed limits by varying the active and reactive power demands. This is accomplished by load frequency control (LFC) and automatic voltage regulator (AVR) loops, which are coupled to each other. Due to the complexity of the combined AVR-LFC model, the simultaneous control of frequency and terminal voltage in an IPS requires an intelligent control strategy. The performance of IPS solely depends upon the working of the controllers. This work presents the exploration of control methodology based on a proportional integral–proportional derivative (PI-PD) controller with combined LFC-AVR in a multi-area IPS. The PI-PD controller was tuned with recently developed nature-inspired computation algorithms including the Archimedes optimization algorithm (AOA), learner performance-based behavior optimization (LPBO), and modified particle swarm optimization (MPSO). In the earlier part of this work, the proposed methodology was applied to a two-area IPS, and the output responses of LPBO-PI-PD, AOA-PI-PD, and MPSO-PI-PD control schemes were compared with an existing nonlinear threshold-accepting algorithm-based PID (NLTA-PID) controller. After achieving satisfactory results in the two-area IPS, the proposed scheme was examined in a three-area IPS with combined AVR and LFC. Finally, the reliability and efficacy of the proposed methodology was investigated on a three-area IPS with LFC-AVR with variations in the system parameters over a range of  ± 50%. The simulation results and a comprehensive comparison between the controllers clearly demonstrates that the proposed control schemes including LPBO-PI-PD, AOA-PI-PD, and MPSO-PI-PD are very reliable, and they can effectively stabilize the frequency and terminal voltage in a multi-area IPS with combined LFC and AVR.

Suggested Citation

  • Tayyab Ali & Suheel Abdullah Malik & Ibrahim A. Hameed & Amil Daraz & Hana Mujlid & Ahmad Taher Azar, 2022. "Load Frequency Control and Automatic Voltage Regulation in a Multi-Area Interconnected Power System Using Nature-Inspired Computation-Based Control Methodology," Sustainability, MDPI, vol. 14(19), pages 1-30, September.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12162-:d:925310
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    References listed on IDEAS

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    1. Ch. Naga Sai Kalyan & B. Srikanth Goud & Ch. Rami Reddy & Haitham S. Ramadan & Mohit Bajaj & Ziad M. Ali, 2021. "Water Cycle Algorithm Optimized Type II Fuzzy Controller for Load Frequency Control of a Multi-Area, Multi-Fuel System with Communication Time Delays," Energies, MDPI, vol. 14(17), pages 1-19, August.
    2. Hady H. Fayek & Eugen Rusu, 2022. "Novel Combined Load Frequency Control and Automatic Voltage Regulation of a 100% Sustainable Energy Interconnected Microgrids," Sustainability, MDPI, vol. 14(15), pages 1-16, August.
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    Cited by:

    1. Daraz, Amil, 2023. "Optimized cascaded controller for frequency stabilization of marine microgrid system," Applied Energy, Elsevier, vol. 350(C).
    2. Tayyab Ali & Suheel Abdullah Malik & Amil Daraz & Muhammad Adeel & Sheraz Aslam & Herodotos Herodotou, 2023. "Load Frequency Control and Automatic Voltage Regulation in Four-Area Interconnected Power Systems Using a Gradient-Based Optimizer," Energies, MDPI, vol. 16(5), pages 1-27, February.
    3. Md. Shafiul Alam & Tanzi Ahmed Chowdhury & Abhishak Dhar & Fahad Saleh Al-Ismail & M. S. H. Choudhury & Md Shafiullah & Md. Ismail Hossain & Md. Alamgir Hossain & Aasim Ullah & Syed Masiur Rahman, 2023. "Solar and Wind Energy Integrated System Frequency Control: A Critical Review on Recent Developments," Energies, MDPI, vol. 16(2), pages 1-31, January.
    4. 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).
    5. Mehmood, Khizer & Chaudhary, Naveed Ishtiaq & Khan, Zeshan Aslam & Cheema, Khalid Mehmood & Raja, Muhammad Asif Zahoor & Shu, Chi-Min, 2023. "Novel knacks of chaotic maps with Archimedes optimization paradigm for nonlinear ARX model identification with key term separation," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    6. Alaa M. Abdel-hamed & Almoataz Y. Abdelaziz & Adel El-Shahat, 2023. "Design of a 2DOF-PID Control Scheme for Frequency/Power Regulation in a Two-Area Power System Using Dragonfly Algorithm with Integral-Based Weighted Goal Objective," Energies, MDPI, vol. 16(1), pages 1-34, January.

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