IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i6p1151-d216911.html
   My bibliography  Save this article

Improved Perturb and Observation Method Based on Support Vector Regression

Author

Listed:
  • Bicheng Tan

    (School of Optical and Electronic Information, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China)

  • Xin Ke

    (School of Optical and Electronic Information, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China)

  • Dachuan Tang

    (School of Optical and Electronic Information, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China)

  • Sheng Yin

    (School of Optical and Electronic Information, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China)

Abstract

Solar energy is the most valuable renewable energy source due to its abundant storage and is pollution-free. The output power of photovoltaic (PV) arrays will vary with external conditions, such as irradiance and temperature fluctuations. Therefore, an increase in the energy conversion rate is inseparable from maximum power point tracking (MPPT). The existing MPPT technology cannot either balance the tracking speed and tracking accuracy, or the implementation cost is too high due to the complexity of the calculation. In this paper, a new maximum power point tracking (MPPT) method was proposed. It improves the traditional perturb and observation (P&O) method by introducing the support vector regression (SVR) algorithm. In this method, the current maximum power point voltage is predicted by the trained model and compared with the current operating voltage to predict a reasonable step size. The boost DC/ DC (Direct current-Direct current converter) convert system applying the improved method and the traditional P&O was simulated in MATLAB-Simulink, respectively. The results of the simulation show that compared with the traditional P&O method, the proposed new method both improves the convergence time and tracking accuracy.

Suggested Citation

  • Bicheng Tan & Xin Ke & Dachuan Tang & Sheng Yin, 2019. "Improved Perturb and Observation Method Based on Support Vector Regression," Energies, MDPI, vol. 12(6), pages 1-11, March.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:6:p:1151-:d:216911
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/6/1151/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/6/1151/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Karami, Nabil & Moubayed, Nazih & Outbib, Rachid, 2017. "General review and classification of different MPPT Techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 1-18.
    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. Aranzazu D. Martin & Juan M. Cano & Reyes S. Herrera & Jesus R. Vazquez, 2019. "Wireless Sliding MPPT Control of Photovoltaic Systems in Distributed Generation Systems," Energies, MDPI, vol. 12(17), pages 1-16, August.
    2. Can Ding & Yiyuan Zhou & Qingchang Ding & Kaiming Li, 2022. "Integrated Carbon-Capture-Based Low-Carbon Economic Dispatch of Power Systems Based on EEMD-LSTM-SVR Wind Power Forecasting," Energies, MDPI, vol. 15(5), pages 1-27, February.
    3. Lan Li & Hao Wang & Xiangping Chen & Abid Ali Shah Bukhari & Wenping Cao & Lun Chai & Bing Li, 2019. "High Efficiency Solar Power Generation with Improved Discontinuous Pulse Width Modulation (DPWM) Overmodulation Algorithms," Energies, MDPI, vol. 12(9), pages 1-18, May.
    4. N. Kanagaraj & Hegazy Rezk & Mohamed R. Gomaa, 2020. "A Variable Fractional Order Fuzzy Logic Control Based MPPT Technique for Improving Energy Conversion Efficiency of Thermoelectric Power Generator," Energies, MDPI, vol. 13(17), pages 1-18, September.
    5. Efrain Mendez & Alexandro Ortiz & Pedro Ponce & Israel Macias & David Balderas & Arturo Molina, 2020. "Improved MPPT Algorithm for Photovoltaic Systems Based on the Earthquake Optimization Algorithm," Energies, MDPI, vol. 13(12), pages 1-24, June.
    6. Amjad Ali & K. Almutairi & Muhammad Zeeshan Malik & Kashif Irshad & Vineet Tirth & Salem Algarni & Md. Hasan Zahir & Saiful Islam & Md Shafiullah & Neeraj Kumar Shukla, 2020. "Review of Online and Soft Computing Maximum Power Point Tracking Techniques under Non-Uniform Solar Irradiation Conditions," Energies, MDPI, vol. 13(12), pages 1-37, June.

    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. Obeidi, Nabil & Kermadi, Mostefa & Belmadani, Bachir & Allag, Abdelkrim & Achour, Lazhar & Mesbahi, Nadhir & Mekhilef, Saad, 2023. "A modified current sensorless approach for maximum power point tracking of partially shaded photovoltaic systems," Energy, Elsevier, vol. 263(PA).
    2. 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).
    3. Abdulaziz Almutairi & Ahmed G. Abo-Khalil & Khairy Sayed & Naif Albagami, 2020. "MPPT for a PV Grid-Connected System to Improve Efficiency under Partial Shading Conditions," Sustainability, MDPI, vol. 12(24), pages 1-18, December.
    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. 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.
    6. Andrés Tobón & Julián Peláez-Restrepo & Juan P. Villegas-Ceballos & Sergio Ignacio Serna-Garcés & Jorge Herrera & Asier Ibeas, 2017. "Maximum Power Point Tracking of Photovoltaic Panels by Using Improved Pattern Search Methods," Energies, MDPI, vol. 10(9), pages 1-15, September.
    7. Carlos Robles Algarín & John Taborda Giraldo & Omar Rodríguez Álvarez, 2017. "Fuzzy Logic Based MPPT Controller for a PV System," Energies, MDPI, vol. 10(12), pages 1-18, December.
    8. Marcin Walczak & Leszek Bychto, 2023. "Transients in Input and Output Signals in DC–DC Converters Working in Maximum Power Point Tracking Systems," Energies, MDPI, vol. 16(12), pages 1-12, June.
    9. Nabil Obeidi & Mostefa Kermadi & Bachir Belmadani & Abdelkarim Allag & Lazhar Achour & Saad Mekhilef, 2022. "A Current Sensorless Control of Buck-Boost Converter for Maximum Power Point Tracking in Photovoltaic Applications," Energies, MDPI, vol. 15(20), pages 1-21, October.
    10. Ridha, Hussein Mohammed & Gomes, Chandima & Hizam, Hashim & Ahmadipour, Masoud & Heidari, Ali Asghar & Chen, Huiling, 2021. "Multi-objective optimization and multi-criteria decision-making methods for optimal design of standalone photovoltaic system: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    11. Vavilapalli, Sridhar & Umashankar, S. & Sanjeevikumar, P. & Ramachandaramurthy, Vigna K. & Mihet-Popa, Lucian & Fedák, Viliam, 2018. "Three-stage control architecture for cascaded H-Bridge inverters in large-scale PV systems – Real time simulation validation," Applied Energy, Elsevier, vol. 229(C), pages 1111-1127.
    12. Arshdeep Singh & Shimi Sudha Letha, 2019. "Emerging energy sources for electric vehicle charging station," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(5), pages 2043-2082, October.
    13. Julio López Seguel & Seleme I. Seleme & Lenin M. F. Morais, 2022. "Comparative Study of Buck-Boost, SEPIC, Cuk and Zeta DC-DC Converters Using Different MPPT Methods for Photovoltaic Applications," Energies, MDPI, vol. 15(21), pages 1-26, October.
    14. Sridhar, V. & Umashankar, S., 2017. "A comprehensive review on CHB MLI based PV inverter and feasibility study of CHB MLI based PV-STATCOM," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 138-156.
    15. 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.
    16. Victor Arturo Martinez Lopez & Ugnė Žindžiūtė & Hesan Ziar & Miro Zeman & Olindo Isabella, 2022. "Study on the Effect of Irradiance Variability on the Efficiency of the Perturb-and-Observe Maximum Power Point Tracking Algorithm," Energies, MDPI, vol. 15(20), pages 1-12, October.
    17. Gloria Milena Vargas Gil & Lucas Lima Rodrigues & Roberto S. Inomoto & Alfeu J. Sguarezi & Renato Machado Monaro, 2019. "Weighted-PSO Applied to Tune Sliding Mode Plus PI Controller Applied to a Boost Converter in a PV System," Energies, MDPI, vol. 12(5), pages 1-18, March.
    18. Nubia Ilia Ponce de León Puig & Leonardo Acho & José Rodellar, 2018. "Design and Experimental Implementation of a Hysteresis Algorithm to Optimize the Maximum Power Point Extracted from a Photovoltaic System," Energies, MDPI, vol. 11(7), pages 1-24, July.
    19. Zahra Bel Hadj Salah & Saber Krim & Mohamed Ali Hajjaji & Badr M. Alshammari & Khalid Alqunun & Ahmed Alzamil & Tawfik Guesmi, 2023. "A New Efficient Cuckoo Search MPPT Algorithm Based on a Super-Twisting Sliding Mode Controller for Partially Shaded Standalone Photovoltaic System," Sustainability, MDPI, vol. 15(12), pages 1-38, June.
    20. Vasudevan, Krishnakumar R. & Ramachandaramurthy, Vigna K. & Venugopal, Gomathi & Ekanayake, J.B. & Tiong, S.K., 2021. "Variable speed pumped hydro storage: A review of converters, controls and energy management strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).

    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:12:y:2019:i:6:p:1151-:d:216911. 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.