IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i17p4473-d406452.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/17/4473/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/17/4473/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vladimir Prakht & Mohamed N. Ibrahim & Vadim Kazakbaev, 2023. "Energy Efficiency Improvement of Electric Machines without Rare-Earth Magnets," Energies, MDPI, vol. 16(8), pages 1-3, April.
    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).

    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. Rezk, Hegazy & AL-Oran, Mazen & Gomaa, Mohamed R. & Tolba, Mohamed A. & Fathy, Ahmed & Abdelkareem, Mohammad Ali & Olabi, A.G. & El-Sayed, Abou Hashema M., 2019. "A novel statistical performance evaluation of most modern optimization-based global MPPT techniques for partially shaded PV system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    2. Ehtisham Lodhi & Fei-Yue Wang & Gang Xiong & Ghulam Ali Mallah & Muhammad Yaqoob Javed & Tariku Sinshaw Tamir & David Wenzhong Gao, 2021. "A Dragonfly Optimization Algorithm for Extracting Maximum Power of Grid-Interfaced PV Systems," Sustainability, MDPI, vol. 13(19), pages 1-27, September.
    3. Tanveer, Waqas Hassan & Rezk, Hegazy & Nassef, Ahmed & Abdelkareem, Mohammad Ali & Kolosz, Ben & Karuppasamy, K. & Aslam, Jawad & Gilani, Syed Omer, 2020. "Improving fuel cell performance via optimal parameters identification through fuzzy logic based-modeling and optimization," Energy, Elsevier, vol. 204(C).
    4. Hegazy Rezk & Ziad Mohammed Ali & Omer Abdalla & Obai Younis & Mohamed Ramadan Gomaa & Mauia Hashim, 2019. "Hybrid Moth-Flame Optimization Algorithm and Incremental Conductance for Tracking Maximum Power of Solar PV/Thermoelectric System under Different Conditions," Mathematics, MDPI, vol. 7(10), pages 1-21, September.
    5. Mahdy, Ahmed & Hasanien, Hany M. & Helmy, Waleed & Turky, Rania A. & Abdel Aleem, Shady H.E., 2022. "Transient stability improvement of wave energy conversion systems connected to power grid using anti-windup-coot optimization strategy," Energy, Elsevier, vol. 245(C).
    6. Sairam, Seshapalli & Seshadhri, Subathra & Marafioti, Giancarlo & Srinivasan, Seshadhri & Mathisen, Geir & Bekiroglu, Korkut, 2022. "Edge-based Explainable Fault Detection Systems for photovoltaic panels on edge nodes," Renewable Energy, Elsevier, vol. 185(C), pages 1425-1440.
    7. Tian, B. & Loonen, R.C.G.M. & Bognár, Á. & Hensen, J.L.M., 2022. "Impacts of surface model generation approaches on raytracing-based solar potential estimation in urban areas," Renewable Energy, Elsevier, vol. 198(C), pages 804-824.
    8. Mohamed R. Gomaa & Hegazy Rezk & Ramadan J. Mustafa & Mujahed Al-Dhaifallah, 2019. "Evaluating the Environmental Impacts and Energy Performance of a Wind Farm System Utilizing the Life-Cycle Assessment Method: A Practical Case Study," Energies, MDPI, vol. 12(17), pages 1-25, August.
    9. Hegazy Rezk & Asmaa A. Elghany & Mujahed Al-Dhaifallah & Abo Hashema M. El Sayed & Mohamed N. Ibrahim, 2019. "Numerical Estimation and Experimental Verification of Optimal Parameter Identification Based on Modern Optimization of a Three Phase Induction Motor," Mathematics, MDPI, vol. 7(12), pages 1-13, November.
    10. Xu, Fangqiu & Liu, Jicheng & Lin, Shuaishuai & Dai, Qiongjie & Li, Cunbin, 2018. "A multi-objective optimization model of hybrid energy storage system for non-grid-connected wind power: A case study in China," Energy, Elsevier, vol. 163(C), pages 585-603.
    11. Malika Fodil & Ali Djerioui & Mohamed Ladjal & Abdelhakim Saim & Fouad Berrabah & Hemza Mekki & Samir Zeghlache & Azeddine Houari & Mohamed Fouad Benkhoris, 2023. "Optimization of PI Controller Parameters by GWO Algorithm for Five-Phase Asynchronous Motor," Energies, MDPI, vol. 16(10), pages 1-14, May.
    12. Dalia Yousri & Thanikanti Sudhakar Babu & Dalia Allam & Vigna. K. Ramachandaramurthy & Eman Beshr & Magdy. B. Eteiba, 2019. "Fractional Chaos Maps with Flower Pollination Algorithm for Partial Shading Mitigation of Photovoltaic Systems," Energies, MDPI, vol. 12(18), pages 1-27, September.
    13. Wang, Jianzhou & Hu, Jianming, 2015. "A robust combination approach for short-term wind speed forecasting and analysis – Combination of the ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vec," Energy, Elsevier, vol. 93(P1), pages 41-56.
    14. Adewuyi, Adeolu O. & Awodumi, Olabanji B., 2017. "Biomass energy consumption, economic growth and carbon emissions: Fresh evidence from West Africa using a simultaneous equation model," Energy, Elsevier, vol. 119(C), pages 453-471.
    15. Refaat, Ahmed & Ali, Qays Adnan & Elsakka, Mohamed Mohamed & Elhenawy, Yasser & Majozi, Thokozani & Korovkin, Nikolay V. & Elfar, Medhat Hegazy, 2024. "Extraction of maximum power from PV system based on horse herd optimization MPPT technique under various weather conditions," Renewable Energy, Elsevier, vol. 220(C).
    16. Hegazy Rezk & Kotb B. Tawfiq & Peter Sergeant & Mohamed N. Ibrahim, 2021. "Optimal Rotor Design of Synchronous Reluctance Machines Considering the Effect of Current Angle," Mathematics, MDPI, vol. 9(4), pages 1-18, February.
    17. Muhammad Hafeez Mohamed Hariri & Mohd Khairunaz Mat Desa & Syafrudin Masri & Muhammad Ammirrul Atiqi Mohd Zainuri, 2020. "Grid-Connected PV Generation System—Components and Challenges: A Review," Energies, MDPI, vol. 13(17), pages 1-28, August.
    18. Hegazy Rezk & N. Kanagaraj & Mujahed Al-Dhaifallah, 2020. "Design and Sensitivity Analysis of Hybrid Photovoltaic-Fuel-Cell-Battery System to Supply a Small Community at Saudi NEOM City," Sustainability, MDPI, vol. 12(8), pages 1-20, April.
    19. Nassef, Ahmed M. & Olabi, A.G. & Rodriguez, Cristina & Abdelkareem, Mohammad Ali & Rezk, Hegazy, 2021. "Optimal operating parameter determination and modeling to enhance methane production from macroalgae," Renewable Energy, Elsevier, vol. 163(C), pages 2190-2197.
    20. Ghazi A. Ghazi & Hany M. Hasanien & Essam A. Al-Ammar & Rania A. Turky & Wonsuk Ko & Sisam Park & Hyeong-Jin Choi, 2022. "African Vulture Optimization Algorithm-Based PI Controllers for Performance Enhancement of Hybrid Renewable-Energy Systems," Sustainability, MDPI, vol. 14(13), pages 1-26, July.

    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:13:y:2020:i:17:p:4473-:d:406452. 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.