IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v82y2018ip3p2202-2217.html
   My bibliography  Save this article

Design and implementation of ANFIS-reference model controller based MPPT using FPGA for photovoltaic system

Author

Listed:
  • Aldair, Ammar A.
  • Obed, Adel A.
  • Halihal, Ali F.

Abstract

The aim of this work is to demonstrate the usefulness of Adaptive Neuro Fuzzy Inference System (ANFIS) for tracking Maximum Power Point (MPP) in stand-alone photovoltaic system. Maximum Power Point Tracking (MPPT) is one of approaches which boost efficiency of PhotoVoltaic (PV) cells by the load matching between the PV cells and the load. The key problem is that maximum power is not achieved because PV cells power is affected by weather conditions such as the solar irradiation and the temperature, thus, the MPP is changed during daylight hours and year seasons. Therefore, it is necessary to design an appropriate controller based on one of techniques to track MPP. These techniques are based on true or estimated searching mechanism to MPP. True searching mechanism based techniques like incremental conductance method and perturb and observe method are efficient but they are less stable, more oscillatory about MPP and sensitive to a high frequency noise. Generally, estimated searching mechanism based techniques like constant voltage method and fractional open circuit voltage method are less efficient, but they are stable and no sensitive to a high frequency noise. In this paper, the ANFIS-reference model method in addition to the incremental conductance method and constant voltage method have been studied, designed and implemented using Field Programmable Gate Array (FPGA) board to compare the performance of each method. The proposed ANFIS-reference model controller is efficient since it has been trained offline using Matlab tool with practical data sets. Based on our knowledge, this paper is the first paper which introduces practical implementation of ANFIS-reference model based MPPT for photovoltaic system using FPGA board. The results reveal that the ANFIS-reference model controller has more efficient and better dynamic response than the incremental conductance method and constant voltage method.

Suggested Citation

  • Aldair, Ammar A. & Obed, Adel A. & Halihal, Ali F., 2018. "Design and implementation of ANFIS-reference model controller based MPPT using FPGA for photovoltaic system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2202-2217.
    • Handle: RePEc:eee:rensus:v:82:y:2018:i:p3:p:2202-2217
    DOI: 10.1016/j.rser.2017.08.071
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032117312169
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2017.08.071?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mousazadeh, Hossein & Keyhani, Alireza & Javadi, Arzhang & Mobli, Hossein & Abrinia, Karen & Sharifi, Ahmad, 2009. "A review of principle and sun-tracking methods for maximizing solar systems output," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1800-1818, October.
    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. 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. Subramanian Vasantharaj & Vairavasundaram Indragandhi & Vairavasundaram Subramaniyaswamy & Yuvaraja Teekaraman & Ramya Kuppusamy & Srete Nikolovski, 2021. "Efficient Control of DC Microgrid with Hybrid PV—Fuel Cell and Energy Storage Systems," Energies, MDPI, vol. 14(11), pages 1-18, June.
    3. Mohammad Mahdi Forootan & Iman Larki & Rahim Zahedi & Abolfazl Ahmadi, 2022. "Machine Learning and Deep Learning in Energy Systems: A Review," Sustainability, MDPI, vol. 14(8), pages 1-49, April.
    4. Yılmaz, Mehmet & Kaleli, Alirıza & Çorapsız, Muhammed Fatih, 2023. "Machine learning based dynamic super twisting sliding mode controller for increase speed and accuracy of MPPT using real-time data under PSCs," Renewable Energy, Elsevier, vol. 219(P1).
    5. CH Hussaian Basha & C Rani, 2020. "Different Conventional and Soft Computing MPPT Techniques for Solar PV Systems with High Step-Up Boost Converters: A Comprehensive Analysis," Energies, MDPI, vol. 13(2), pages 1-27, January.
    6. Rami Alamoudi & Osman Taylan & Mehmet Azmi Aktacir & Enrique Herrera-Viedma, 2021. "Designing a Solar Photovoltaic System for Generating Renewable Energy of a Hospital: Performance Analysis and Adjustment Based on RSM and ANFIS Approaches," Mathematics, MDPI, vol. 9(22), pages 1-24, November.

    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. Zimmerman, Ryan & Panda, Anurag & Bulović, Vladimir, 2020. "Techno-economic assessment and deployment strategies for vertically-mounted photovoltaic panels," Applied Energy, Elsevier, vol. 276(C).
    2. Barbón, A. & Fortuny Ayuso, P. & Bayón, L. & Silva, C.A., 2023. "Experimental and numerical investigation of the influence of terrain slope on the performance of single-axis trackers," Applied Energy, Elsevier, vol. 348(C).
    3. Alphonsus, Ephrem Ryan & Abdullah, Mohammad Omar, 2016. "A review on the applications of programmable logic controllers (PLCs)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1185-1205.
    4. Rawat, Rahul & Kaushik, S.C. & Lamba, Ravita, 2016. "A review on modeling, design methodology and size optimization of photovoltaic based water pumping, standalone and grid connected system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1506-1519.
    5. Vieira, R.G. & Guerra, F.K.O.M.V. & Vale, M.R.B.G. & Araújo, M.M., 2016. "Comparative performance analysis between static solar panels and single-axis tracking system on a hot climate region near to the equator," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 672-681.
    6. Tibúrcio, B.D. & Liang, D. & Almeida, J. & Garcia, D. & Catela, M. & Costa, H. & Vistas, C.R., 2022. "Tracking error compensation capacity measurement of a dual-rod side-pumping solar laser," Renewable Energy, Elsevier, vol. 195(C), pages 1253-1261.
    7. Yeh, Pei-Ying & Yen, Po-Ching & Yen, Jia-Yush & Wu, Tsung-Tsong & Liu, Pei-Ling & Wu, Chia-Ling & Peng, Ching-Yu, 2011. "Focal point tracking system for concentration solar power collection," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 3029-3033, August.
    8. Mohammadi, Kasra & Khorasanizadeh, Hossein, 2015. "A review of solar radiation on vertically mounted solar surfaces and proper azimuth angles in six Iranian major cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 504-518.
    9. Iqbal, Jamshed & Khan, Zeashan Hameed, 2017. "The potential role of renewable energy sources in robot's power system: A case study of Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 106-122.
    10. Wu, Jie & Wang, Zhi-Xin & Xu, Lie & Wang, Guo-Qiang, 2014. "Key technologies of VSC-HVDC and its application on offshore wind farm in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 36(C), pages 247-255.
    11. Okoye, Chiemeka Onyeka & Bahrami, Arian & Atikol, Ugur, 2018. "Evaluating the solar resource potential on different tracking surfaces in Nigeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1569-1581.
    12. Pirayawaraporn, Alongkorn & Sappaniran, Sahapol & Nooraksa, Sarawin & Prommai, Chanon & Chindakham, Nachaya & Jamroen, Chaowanan, 2023. "Innovative sensorless dual-axis solar tracking system using particle filter," Applied Energy, Elsevier, vol. 338(C).
    13. Renzi, M. & Egidi, L. & Comodi, G., 2015. "Performance analysis of two 3.5kWp CPV systems under real operating conditions," Applied Energy, Elsevier, vol. 160(C), pages 687-696.
    14. Majedul Islam & Prasad Yarlagadda & Azharul Karim, 2018. "Effect of the Orientation Schemes of the Energy Collection Element on the Optical Performance of a Parabolic Trough Concentrating Collector," Energies, MDPI, vol. 12(1), pages 1-20, December.
    15. Kafka, Jennifer & Miller, Mark A., 2020. "The dual angle solar harvest (DASH) method: An alternative method for organizing large solar panel arrays that optimizes incident solar energy in conjunction with land use," Renewable Energy, Elsevier, vol. 155(C), pages 531-546.
    16. Ahmad, Naseer & Sheikh, Anwar K. & Gandhidasan, P. & Elshafie, Moustafa, 2015. "Modeling, simulation and performance evaluation of a community scale PVRO water desalination system operated by fixed and tracking PV panels: A case study for Dhahran city, Saudi Arabia," Renewable Energy, Elsevier, vol. 75(C), pages 433-447.
    17. Barbón, A. & Bayón-Cueli, C. & Bayón, L. & Rodríguez-Suanzes, C., 2022. "Analysis of the tilt and azimuth angles of photovoltaic systems in non-ideal positions for urban applications," Applied Energy, Elsevier, vol. 305(C).
    18. Carlos Morón & Daniel Ferrández & Pablo Saiz & Gabriela Vega & Jorge Pablo Díaz, 2017. "New Prototype of Photovoltaic Solar Tracker Based on Arduino," Energies, MDPI, vol. 10(9), pages 1-13, August.
    19. Kesler, Selami & Kivrak, Sinan & Dincer, Furkan & Rustemli, Sabir & Karaaslan, Muharrem & Unal, Emin & Erdiven, Utku, 2014. "The analysis of PV power potential and system installation in Manavgat, Turkey—A case study in winter season," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 671-680.
    20. Tong Liu & Li Liu & Yufang He & Mengfei Sun & Jian Liu & Guochang Xu, 2021. "A Theoretical Optimum Tilt Angle Model for Solar Collectors from Keplerian Orbit," Energies, MDPI, vol. 14(15), pages 1-17, 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:eee:rensus:v:82:y:2018:i:p3:p:2202-2217. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    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.