IDEAS home Printed from https://ideas.repec.org/a/gam/jcltec/v6y2024i3p60-1259d1479916.html
   My bibliography  Save this article

A Methodology to Optimize PMSM Driven Solar Water Pumps Using a Hybrid MPPT Approach in Partially Shaded Conditions

Author

Listed:
  • Divya Shetty

    (Department of Electrical & Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India)

  • Jayalakshmi N. Sabhahit

    (Department of Electrical & Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India)

  • Ganesh Kudva

    (Department of Electrical & Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India)

Abstract

Solar water pumps are crucial for farmers, significantly reducing energy costs and providing independence from conventional fuels. Their adoption is further incentivized by government subsidies, making them a practical choice that aligns with sustainable agricultural practices. However, the cost of the required solar panels for the chosen power makes it essential to optimize solar water pumping systems (SWPS) for economic viability. This study enhances the efficiency and reliability of permanent magnet synchronous motor (PMSM)-driven SWPS in rural areas using hybrid maximum power point tracking (MPPT) algorithms and voltage-to-frequency (V/f) control strategy. It investigates the sensorless scalar control method for PMSM-based water pumps and evaluates various MPPT algorithms, including grey wolf optimization (GWO), particle swarm optimization (PSO), perturb and observe (PO), and incremental conductance (INC), along with hybrid combinations. The study, conducted using MATLAB Simulink, assesses these algorithms on convergence time, MPPT accuracy, torque ripple, and system efficiency under different partial shading conditions. Findings reveal that INC-GWO excels, providing higher accuracy, faster convergence, and reduced steady-state oscillations, thus boosting system efficiency. The V/f control strategy simplifies control mechanisms and enhances performance. Considering system non-idealities and maximum duty cycle limitations, PMSM-based SWPS achieve superior efficiency and stability, making them viable for off-grid water pumping applications.

Suggested Citation

  • Divya Shetty & Jayalakshmi N. Sabhahit & Ganesh Kudva, 2024. "A Methodology to Optimize PMSM Driven Solar Water Pumps Using a Hybrid MPPT Approach in Partially Shaded Conditions," Clean Technol., MDPI, vol. 6(3), pages 1-31, September.
    • Handle: RePEc:gam:jcltec:v:6:y:2024:i:3:p:60-1259:d:1479916
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2571-8797/6/3/60/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2571-8797/6/3/60/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Seyedmahmoudian, M. & Horan, B. & Soon, T. Kok & Rahmani, R. & Than Oo, A. Muang & Mekhilef, S. & Stojcevski, A., 2016. "State of the art artificial intelligence-based MPPT techniques for mitigating partial shading effects on PV systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 435-455.
    Full references (including those not matched with items on IDEAS)

    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. Shuhao Chang & Qiancheng Wang & Haihua Hu & Zijian Ding & Hansen Guo, 2018. "An NNwC MPPT-Based Energy Supply Solution for Sensor Nodes in Buildings and Its Feasibility Study," Energies, MDPI, vol. 12(1), pages 1-20, December.
    3. Haoming Liu & Muhammad Yasir Ali Khan & Xiaoling Yuan, 2023. "Hybrid Maximum Power Extraction Methods for Photovoltaic Systems: A Comprehensive Review," Energies, MDPI, vol. 16(15), pages 1-64, July.
    4. Pillai, Dhanup S. & Rajasekar, N., 2018. "Metaheuristic algorithms for PV parameter identification: A comprehensive review with an application to threshold setting for fault detection in PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3503-3525.
    5. Ahmad, Riaz & Murtaza, Ali F. & Sher, Hadeed Ahmed, 2019. "Power tracking techniques for efficient operation of photovoltaic array in solar applications – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 82-102.
    6. Belhachat, Faiza & Larbes, Cherif, 2017. "Global maximum power point tracking based on ANFIS approach for PV array configurations under partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 875-889.
    7. Tingting Pei & Xiaohong Hao & Qun Gu, 2018. "A Novel Global Maximum Power Point Tracking Strategy Based on Modified Flower Pollination Algorithm for Photovoltaic Systems under Non-Uniform Irradiation and Temperature Conditions," Energies, MDPI, vol. 11(10), pages 1-16, October.
    8. Rakeshkumar Mahto & Deepak Sharma & Reshma John & Chandrasekhar Putcha, 2021. "Agrivoltaics: A Climate-Smart Agriculture Approach for Indian Farmers," Land, MDPI, vol. 10(11), pages 1-28, November.
    9. Juan D. Velásquez & Lorena Cadavid & Carlos J. Franco, 2023. "Intelligence Techniques in Sustainable Energy: Analysis of a Decade of Advances," Energies, MDPI, vol. 16(19), pages 1-45, October.
    10. Alfredo Gil-Velasco & Carlos Aguilar-Castillo, 2021. "A Modification of the Perturb and Observe Method to Improve the Energy Harvesting of PV Systems under Partial Shading Conditions," Energies, MDPI, vol. 14(9), pages 1-12, April.
    11. Bustani Hadi Wijaya & Ramadhani Kurniawan Subroto & Kuo Lung Lian & Nanang Hariyanto, 2020. "A Maximum Power Point Tracking Method Based on a Modified Grasshopper Algorithm Combined with Incremental Conductance," Energies, MDPI, vol. 13(17), pages 1-19, August.
    12. Haidar Islam & Saad Mekhilef & Noraisyah Binti Mohamed Shah & Tey Kok Soon & Mehdi Seyedmahmousian & Ben Horan & Alex Stojcevski, 2018. "Performance Evaluation of Maximum Power Point Tracking Approaches and Photovoltaic Systems," Energies, MDPI, vol. 11(2), pages 1-24, February.
    13. Ko, Suk Whan & Ju, Young Chul & Hwang, Hye Mi & So, Jung Hun & Jung, Young-Seok & Song, Hyung-Jun & Song, Hee-eun & Kim, Soo-Hyun & Kang, Gi Hwan, 2017. "Electric and thermal characteristics of photovoltaic modules under partial shading and with a damaged bypass diode," Energy, Elsevier, vol. 128(C), pages 232-243.
    14. Danandeh, M.A. & Mousavi G., S.M., 2018. "Comparative and comprehensive review of maximum power point tracking methods for PV cells," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2743-2767.
    15. Verma, Ravikant & Gupta, Shubhrata & Yadav, Anamika, 2024. "Performance evaluation of different photovoltaic array configurations under partial shading," Renewable Energy, Elsevier, vol. 237(PC).
    16. Azhar Ul-Haq & Shah Fahad & Saba Gul & Rui Bo, 2023. "Intelligent Control Schemes for Maximum Power Extraction from Photovoltaic Arrays under Faults," Energies, MDPI, vol. 16(2), pages 1-24, January.
    17. Aljafari, Belqasem & Satpathy, Priya Ranjan & Thanikanti, Sudhakar Babu, 2022. "Partial shading mitigation in PV arrays through dragonfly algorithm based dynamic reconfiguration," Energy, Elsevier, vol. 257(C).
    18. Jun Yin Lee & Renuga Verayiah & Kam Hoe Ong & Agileswari K. Ramasamy & Marayati Binti Marsadek, 2020. "Distributed Generation: A Review on Current Energy Status, Grid-Interconnected PQ Issues, and Implementation Constraints of DG in Malaysia," Energies, MDPI, vol. 13(24), pages 1-40, December.
    19. Mehedi, I.M. & Salam, Z. & Ramli, M.Z. & Chin, V.J. & Bassi, H. & Rawa, M.J.H. & Abdullah, M.P., 2021. "Critical evaluation and review of partial shading mitigation methods for grid-connected PV system using hardware solutions: The module-level and array-level approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    20. Balamurugan, M. & Sahoo, Sarat Kumar & Sukchai, Sukruedee, 2017. "Application of soft computing methods for grid connected PV system: A technological and status review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1493-1508.

    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:jcltec:v:6:y:2024:i:3:p:60-1259:d:1479916. 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.