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Simulation-Based Coyote Optimization Algorithm to Determine Gains of PI Controller for Enhancing the Performance of Solar PV Water-Pumping System

Author

Listed:
  • Jouda Arfaoui

    (National School of Engineering of Tunis, University of Tunis ELMANAR, BP 37, Tunis 1002, Tunisia)

  • Hegazy Rezk

    (College of Engineering at Wadi Addawaser, Prince Sattam Bin Abdulaziz University, Al-Kharj 11991, Saudi Arabia
    Electrical Engineering Deprtment, Faculty of Engineering, Minia University, Al Minya 61519, Egypt)

  • Mujahed Al-Dhaifallah

    (Systems Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia)

  • Mohamed N. Ibrahim

    (Department of Electromechanical, Systems and Metal Engineering, Ghent University, 9000 Ghent, Belgium
    FlandersMake@UGent—Corelab EEDT-MP, 3001 Leuven, Belgium
    Electrical Engineering Department, Kafrelshiekh University, Kafr el-Sheikh 33511, Egypt)

  • Mami Abdelkader

    (Department of Physics, Faculty of Sciences, University Tunis El Manar, BP 37, Tunis 1002, Tunisia)

Abstract

In this study, a simulation-based coyote optimization algorithm (COA) to identify the gains of PI to ameliorate the water-pumping system performance fed from the photovoltaic system is presented. The aim is to develop a stand-alone water-pumping system powered by solar energy, i.e., without the need of electric power from the utility grid. The voltage of the DC bus was adopted as a good candidate to guarantee the extraction of the maximum power under partial shading conditions. In such a system, two proportional-integral (PI) controllers, at least, are necessary. The adjustment of (Proportional-Integral) controllers are always carried out by classical and tiresome trials and errors techniques which becomes a hard task and time-consuming. In order to overcome this problem, an optimization problem was reformulated and modeled under functional time-domain constraints, aiming at tuning these decision variables. For achieving the desired operational characteristics of the PV water-pumping system for both rotor speed and DC-link voltage, simultaneously, the proposed COA algorithm is adopted. It is carried out through resolving a multiobjective optimization problem employing the weighted-sum technique. Inspired on the Canis latrans species, the COA algorithm is successfully investigated to resolve such a problem by taking into account some constraints in terms of time-domain performance as well as producing the maximum power from the photovoltaic generation system. To assess the efficiency of the suggested COA method, the classical Ziegler–Nichols and trial–error tuning methods for the DC-link voltage and rotor speed dynamics, were compared. The main outcomes ensured the effectiveness and superiority of the COA algorithm. Compared to the other reported techniques, it is superior in terms of convergence rapidity and solution qualities.

Suggested Citation

  • Jouda Arfaoui & Hegazy Rezk & Mujahed Al-Dhaifallah & Mohamed N. Ibrahim & Mami Abdelkader, 2020. "Simulation-Based Coyote Optimization Algorithm to Determine Gains of PI Controller for Enhancing the Performance of Solar PV Water-Pumping System," Energies, MDPI, vol. 13(17), pages 1-17, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:17:p:4473-:d:406452
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    References listed on IDEAS

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    1. Ali, Ehab S., 2015. "Speed control of induction motor supplied by wind turbine via Imperialist Competitive Algorithm," Energy, Elsevier, vol. 89(C), pages 593-600.
    2. Mohamed, Mohamed A. & Zaki Diab, Ahmed A. & Rezk, Hegazy, 2019. "Partial shading mitigation of PV systems via different meta-heuristic techniques," Renewable Energy, Elsevier, vol. 130(C), pages 1159-1175.
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    Cited by:

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    2. Tawfik Guesmi & Badr M. Alshammari & Yasser Almalaq & Ayoob Alateeq & Khalid Alqunun, 2021. "New Coordinated Tuning of SVC and PSSs in Multimachine Power System Using Coyote Optimization Algorithm," Sustainability, MDPI, vol. 13(6), pages 1-18, March.
    3. Mohammed Yousri Silaa & Mohamed Derbeli & Oscar Barambones & Cristian Napole & Ali Cheknane & José María Gonzalez De Durana, 2021. "An Efficient and Robust Current Control for Polymer Electrolyte Membrane Fuel Cell Power System," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    4. Abderrazek Saoudi & Saber Krim & Mohamed Faouzi Mimouni, 2021. "Enhanced Intelligent Closed Loop Direct Torque and Flux Control of Induction Motor for Standalone Photovoltaic Water Pumping System," Energies, MDPI, vol. 14(24), pages 1-21, December.
    5. Ali, E.S. & Elazim, S.M. Abd & Balobaid, A.S., 2023. "Implementation of coyote optimization algorithm for solving unit commitment problem in power systems," Energy, Elsevier, vol. 263(PA).

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