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Automatic Generation Control of Multi-Source Interconnected Power System Using FOI-TD Controller

Author

Listed:
  • Amil Daraz

    (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)

  • Athar Waseem

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

  • Ahmad Taher Azar

    (College of Computer & Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia
    Faculty of Computers and Artificial Intelligence, Benha University, Benha 13518, Egypt)

  • Ihsan Ul Haq

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

  • Zahid Ullah

    (Department of Electrical Engineering, UMT Lahore, Sialkot Campus, Sialkot 51310, Pakistan)

  • Sheraz Aslam

    (Department of Electrical Engineering, Computer Engineering, and Informatics, Cyprus University of Technology, Limassol 3036, Cyprus)

Abstract

Automatic Generation Control (AGC) delivers a high quality electrical energy to energy consumers using efficient and intelligent control systems ensuring nominal operating frequency and organized tie-line power deviation. Subsequently, for the AGC analysis of a two-area interconnected hydro-gas-thermal-wind generating unit, a novel Fractional Order Integral-Tilt Derivative (FOI-TD) controller is proposed that is fine-tuned by a powerful meta-heuristic optimization technique referred as Improved-Fitness Dependent Optimizer (I-FDO) algorithm. For more realistic analysis, various constraints, such as Boiler Dynamics (BD), Time Delay (TD), Generation Rate Constraint (GRC), and Governor Dead Zone (GDZ) having non-linear features are incorporated in the specified system model. Moreover, a comparative analysis of I-FDO algorithm is performed with state-of-the-art approaches, such as FDO, teaching learning based optimization, and particle swarm optimization algorithms. Further, the proposed I-FDO tuned controller is compared with Fractional Order Tilt Integral Derivative (FOTID), PID, and Integral-Tilt Derivative (I-TD) controllers. The performance analysis demonstrates that proposed FOI-TD controller provides better performance and show strong robustness by changing system parameters and load condition in the range of  ± 50%, compared to other controllers.

Suggested Citation

  • Amil Daraz & Suheel Abdullah Malik & Athar Waseem & Ahmad Taher Azar & Ihsan Ul Haq & Zahid Ullah & Sheraz Aslam, 2021. "Automatic Generation Control of Multi-Source Interconnected Power System Using FOI-TD Controller," Energies, MDPI, vol. 14(18), pages 1-18, September.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5867-:d:636835
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    References listed on IDEAS

    as
    1. 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.
    2. Anil Kumar Yedluri & Eswar Reddy Araveeti & Hee-Je Kim, 2019. "Facilely Synthesized NiCo 2 O 4 /NiCo 2 O 4 Nanofile Arrays Supported on Nickel Foam by a Hydrothermal Method and Their Excellent Performance for High-Rate Supercapacitance," Energies, MDPI, vol. 12(7), pages 1-11, April.
    3. 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.
    4. 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.
    5. Yedluri Anil Kumar & Hee-Je Kim, 2018. "Effect of Time on a Hierarchical Corn Skeleton-Like Composite of CoO@ZnO as Capacitive Electrode Material for High Specific Performance Supercapacitors," Energies, MDPI, vol. 11(12), pages 1-16, November.
    6. Arya, Yogendra, 2019. "Impact of hydrogen aqua electrolyzer-fuel cell units on automatic generation control of power systems with a new optimal fuzzy TIDF-II controller," Renewable Energy, Elsevier, vol. 139(C), pages 468-482.
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    Cited by:

    1. Kaleem Ullah & Abdul Basit & Zahid Ullah & Rafiq Asghar & Sheraz Aslam & Ayman Yafoz, 2022. "Line Overload Alleviations in Wind Energy Integrated Power Systems Using Automatic Generation Control," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    2. Tayyab Ali & Suheel Abdullah Malik & Amil Daraz & Sheraz Aslam & Tamim Alkhalifah, 2022. "Dandelion Optimizer-Based Combined Automatic Voltage Regulation and Load Frequency Control in a Multi-Area, Multi-Source Interconnected Power System with Nonlinearities," Energies, MDPI, vol. 15(22), pages 1-34, November.
    3. Sabrina Mohand Saidi & Rabah Mellah & Arezki Fekik & Ahmad Taher Azar, 2022. "Real-Time Fuzzy-PID for Mobile Robot Control and Vision-Based Obstacle Avoidance," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 13(1), pages 1-32, January.
    4. 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.
    5. Preeti Ranjan Sahu & Kumaraswamy Simhadri & Banaja Mohanty & Prakash Kumar Hota & Almoataz Y. Abdelaziz & Fahad Albalawi & Sherif S. M. Ghoneim & Mahmoud Elsisi, 2023. "Effective Load Frequency Control of Power System with Two-Degree Freedom Tilt-Integral-Derivative Based on Whale Optimization Algorithm," Sustainability, MDPI, vol. 15(2), pages 1-20, January.

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