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Three-Pond Model with Fuzzy Inference System-Based Water Level Regulation Scheme for Run-of-River Hydropower Plant

Author

Listed:
  • Ahmad Saeed

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

  • Ebrahim Shahzad

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

  • Adnan Umar Khan

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

  • Athar Waseem

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

  • Muhammad Iqbal

    (Department of Electrical Engineering, International Islamic University, Islamabad 44000, Pakistan
    Department of Automation and Mechanical Engineering, Tampere University, 33100 Tampere, Finland)

  • Kaleem Ullah

    (US-Pakistan Center for Advanced Studies in Energy, University of Engineering and Technology Peshawar, Peshawar 25000, Pakistan)

  • Sheraz Aslam

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

Abstract

Power generation from river hydropower plants depends mainly on river flow. Water fluctuations in the river make the yield process unpredictable. To reduce these fluctuations, building a small reservoir at the river flow of the hydropower plant is recommended. Conventionally, classic single-pond models are commonly used to design run-of-river hydropower plants. However, such models are associated with fluctuations, sagging, and irregular power fluctuations that lead to irregular water fluctuations. This research proposes a novel idea to replace the single-pond model with a three-pond model to increase the plant’s overall efficiency. The three-pond model is developed as a three-tank nonlinear hydraulic system that contains the same amount of water as a conventional single pond. It also has the advantage of minimizing the run-of-river power plant’s dependence on river flow and increasing efficiency by trapping swell and turbulence in the water. To further increase the efficiency, the developed model was tested for smooth and effective level control using fuzzy control.

Suggested Citation

  • Ahmad Saeed & Ebrahim Shahzad & Adnan Umar Khan & Athar Waseem & Muhammad Iqbal & Kaleem Ullah & Sheraz Aslam, 2023. "Three-Pond Model with Fuzzy Inference System-Based Water Level Regulation Scheme for Run-of-River Hydropower Plant," Energies, MDPI, vol. 16(6), pages 1-29, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:6:p:2678-:d:1095693
    as

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    References listed on IDEAS

    as
    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. 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.
    3. Kaleem Ullah & Abdul Basit & Zahid Ullah & Fahad R. Albogamy & Ghulam Hafeez, 2022. "Automatic Generation Control in Modern Power Systems with Wind Power and Electric Vehicles," Energies, MDPI, vol. 15(5), pages 1-24, February.
    4. Jovan, David Jure & Dolanc, Gregor & Pregelj, Boštjan, 2022. "Utilization of excess water accumulation for green hydrogen production in a run-of-river hydropower plant," Renewable Energy, Elsevier, vol. 195(C), pages 780-794.
    Full references (including those not matched with items on IDEAS)

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