IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i12p4251-d834978.html
   My bibliography  Save this article

An Experimental Study of Drift Caused by Partial Shading Using a Modified DC-(P&O) Technique for a Stand-Alone PV System

Author

Listed:
  • Ashish Kumar Singhal

    (Electrical Engineering Department, Dr. A.P.J. Abdul Kalam Technical University, Lucknow 226031, Uttar Pradesh, India)

  • Narendra Singh Beniwal

    (Electronics and Communication Engineering Department, Bundelkhand Institute of Engineering and Technology, Jhansi 284128, Uttar Pradesh, India)

  • Ruby Beniwal

    (Electronics and Communication Engineering Department, Jaypee Institute of Information Technology, Noida 201309, Uttar Pradesh, India)

  • Krzysztof Lalik

    (Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, 30-059 Krakow, Poland)

Abstract

There is tremendous potential in solar energy to meet future electricity demands. Partial shading (PS) and drift are two major problems that must be addressed simultaneously to achieve the maximum power point (MPP) of a stand-alone PV system, which are discussed in this paper. Both of these factors contribute to the voltage drop due to heavy steady-state oscillation. The partial shading and drift problem are associated with severe rapid changes in the insolation. A modified drift-control perturbation and observation DC-(P&O) approach was investigated using a low-cost programmable hardware solution, i.e., the ARM Cortex M4 32-bit Microcontroller (MC) (STM32F407VGT6), with efficient embedded programming and Waijung block sets for real-time solutions. The experimental setup was accomplished on a 40-watt solar panel. It was found that the proposed method had a significant impact on drift control during abrupt changes in current and voltage caused by shading effects, with the controller conversion efficiency of 80.39% and 94.48% with percentage absolute errors of 7.3 and 7.2 for cases with and without PS and drift, respectively.

Suggested Citation

  • Ashish Kumar Singhal & Narendra Singh Beniwal & Ruby Beniwal & Krzysztof Lalik, 2022. "An Experimental Study of Drift Caused by Partial Shading Using a Modified DC-(P&O) Technique for a Stand-Alone PV System," Energies, MDPI, vol. 15(12), pages 1-21, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:12:p:4251-:d:834978
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/12/4251/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/12/4251/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Saravanan, S. & Ramesh Babu, N., 2016. "Maximum power point tracking algorithms for photovoltaic system – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 192-204.
    2. Ashish Kumar Singhal & Narendra Singh Beniwal & Khalid Almutairi & Joshuva Arockia Dhanraj & Ali Mostafaeipour & Alibek Issakhov & Prem Kumar Chaurasiya & Hossein Goudarzi & Vinod Kumar Singh, 2021. "Experimental Analysis of Modified DC-P&O Technique with Arm Controller for a Stand-Alone 40 W PV System," Energies, MDPI, vol. 14(19), pages 1-18, September.
    3. Mostafa Ahmed & Mohamed Abdelrahem & Ibrahim Harbi & Ralph Kennel, 2020. "An Adaptive Model-Based MPPT Technique with Drift-Avoidance for Grid-Connected PV Systems," Energies, MDPI, vol. 13(24), pages 1-25, December.
    4. Foster, Edward & Contestabile, Marcello & Blazquez, Jorge & Manzano, Baltasar & Workman, Mark & Shah, Nilay, 2017. "The unstudied barriers to widespread renewable energy deployment: Fossil fuel price responses," Energy Policy, Elsevier, vol. 103(C), pages 258-264.
    5. Benkercha, Rabah & Moulahoum, Samir & Taghezouit, Bilal, 2019. "Extraction of the PV modules parameters with MPP estimation using the modified flower algorithm," Renewable Energy, Elsevier, vol. 143(C), pages 1698-1709.
    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. Cabrera-Tobar, Ana & Bullich-Massagué, Eduard & Aragüés-Peñalba, Mònica & Gomis-Bellmunt, Oriol, 2016. "Review of advanced grid requirements for the integration of large scale photovoltaic power plants in the transmission system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 971-987.
    2. Horbach, Jens & Rammer, Christian, 2018. "Energy transition in Germany and regional spill-overs: The diffusion of renewable energy in firms," Energy Policy, Elsevier, vol. 121(C), pages 404-414.
    3. Daniel Ştefan Armeanu & Georgeta Vintilă & Ştefan Cristian Gherghina, 2017. "Does Renewable Energy Drive Sustainable Economic Growth? Multivariate Panel Data Evidence for EU-28 Countries," Energies, MDPI, vol. 10(3), pages 1-21, March.
    4. Memon, Mudasir Ahmed & Mekhilef, Saad & Mubin, Marizan & Aamir, Muhammad, 2018. "Selective harmonic elimination in inverters using bio-inspired intelligent algorithms for renewable energy conversion applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2235-2253.
    5. Fernandez Vazquez, Carlos A.A. & Vansighen, Thomas & Fernandez Fuentes, Miguel H. & Quoilin, Sylvain, 2024. "Energy transition implications for Bolivia. Long-term modelling with short-term assessment of future scenarios," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    6. Mohamed Abdel-Basset & Reda Mohamed & Ripon K. Chakrabortty & Michael J. Ryan & Attia El-Fergany, 2021. "An Improved Artificial Jellyfish Search Optimizer for Parameter Identification of Photovoltaic Models," Energies, MDPI, vol. 14(7), pages 1-33, March.
    7. Hwangbo, Soonho & Heo, SungKu & Yoo, ChangKyoo, 2022. "Development of deterministic-stochastic model to integrate variable renewable energy-driven electricity and large-scale utility networks: Towards decarbonization petrochemical industry," Energy, Elsevier, vol. 238(PC).
    8. Jiang, Joe-Air & Su, Yu-Li & Kuo, Kun-Chang & Wang, Chien-Hao & Liao, Min-Sheng & Wang, Jen-Cheng & Huang, Chen-Kang & Chou, Cheng-Ying & Lee, Chien-Hsing & Shieh, Jyh-Cherng, 2017. "On a hybrid MPPT control scheme to improve energy harvesting performance of traditional two-stage inverters used in photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1113-1128.
    9. Dhimish, Mahmoud & Holmes, Violeta & Dales, Mark, 2017. "Parallel fault detection algorithm for grid-connected photovoltaic plants," Renewable Energy, Elsevier, vol. 113(C), pages 94-111.
    10. Long, Wen & Wu, Tiebin & Xu, Ming & Tang, Mingzhu & Cai, Shaohong, 2021. "Parameters identification of photovoltaic models by using an enhanced adaptive butterfly optimization algorithm," Energy, Elsevier, vol. 229(C).
    11. Kofinas, P. & Doltsinis, S. & Dounis, A.I. & Vouros, G.A., 2017. "A reinforcement learning approach for MPPT control method of photovoltaic sources," Renewable Energy, Elsevier, vol. 108(C), pages 461-473.
    12. Nam, KiJeon & Hwangbo, Soonho & Yoo, ChangKyoo, 2020. "A deep learning-based forecasting model for renewable energy scenarios to guide sustainable energy policy: A case study of Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 122(C).
    13. 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.
    14. Sajid Sarwar & Muhammad Yaqoob Javed & Mujtaba Hussain Jaffery & Muhammad Saqib Ashraf & Muhammad Talha Naveed & Muhammad Annas Hafeez, 2022. "Modular Level Power Electronics (MLPE) Based Distributed PV System for Partial Shaded Conditions," Energies, MDPI, vol. 15(13), pages 1-39, June.
    15. Naoui Mohamed & Flah Aymen & Abdullah Altamimi & Zafar A. Khan & Sbita Lassaad, 2022. "Power Management and Control of a Hybrid Electric Vehicle Based on Photovoltaic, Fuel Cells, and Battery Energy Sources," Sustainability, MDPI, vol. 14(5), pages 1-20, February.
    16. Muhammad Affan Khan & Jaehong Kim, 2023. "Smart Sag Detection and Reactive Current Injection Control for a PV Microgrid under Voltage Faults," Energies, MDPI, vol. 16(19), pages 1-21, September.
    17. Luigi Costanzo & Massimo Vitelli, 2019. "A Novel MPPT Technique for Single Stage Grid-Connected PV Systems: T4S," Energies, MDPI, vol. 12(23), pages 1-13, November.
    18. Liu, Yun & Heidari, Ali Asghar & Ye, Xiaojia & Liang, Guoxi & Chen, Huiling & He, Caitou, 2021. "Boosting slime mould algorithm for parameter identification of photovoltaic models," Energy, Elsevier, vol. 234(C).
    19. Sheik Mohammed, S. & Devaraj, D. & Imthias Ahamed, T.P., 2016. "A novel hybrid Maximum Power Point Tracking Technique using Perturb & Observe algorithm and Learning Automata for solar PV system," Energy, Elsevier, vol. 112(C), pages 1096-1106.
    20. Mellor, P. & Lord, R.A. & João, E. & Thomas, R. & Hursthouse, A., 2021. "Identifying non-agricultural marginal lands as a route to sustainable bioenergy provision - A review and holistic definition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).

    More about this item

    Keywords

    partial shedding; MATLAB Simulink; PSIM; ARM Cortex M4 32-bit Microcontroller (STM32F407VGT6); modified DC-(P&O);
    All these keywords.

    JEL classification:

    • M4 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting

    Statistics

    Access and download statistics

    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:15:y:2022:i:12:p:4251-:d:834978. 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.