IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i11p2679-d363068.html
   My bibliography  Save this article

A Novel Maximum Power Point Tracking Control Strategy for the Building Integrated Photovoltaic System

Author

Listed:
  • Yuhang Liu

    (The Key Laboratory of Solar Thermal Energy and Photovoltaic System, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, China
    Institute of Electrical Engineering, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Xiangxin Liu

    (The Key Laboratory of Solar Thermal Energy and Photovoltaic System, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, China
    Institute of Electrical Engineering, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Jianwei Zhang

    (College of Electric Power, Inner Mongolia University of Technology, Hohhot 010051, China)

  • Yufeng Zhang

    (The Key Laboratory of Solar Thermal Energy and Photovoltaic System, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, China
    Institute of Electrical Engineering, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Ziyao Zhu

    (The Key Laboratory of Solar Thermal Energy and Photovoltaic System, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, China
    Institute of Electrical Engineering, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Thin-film photovoltaic technology has begun to be applied in building-integrated photovoltaics (BIPVs), and it is believed that thin-film photovoltaic technology has potential in building-integrated photovoltaic applications. In this paper, a hybrid approach was investigated which combined the maximum power point tracking (MPPT) algorithm of three-stage variable step size with continuous conduction mode (CCM)/discontinuous current mode (DCM). The research contents of this paper include the principle analysis of the maximum power point tracking algorithm, the design of the sampling period, and the design of a double closed-loop control system and correction factor. A system model was built in MATLAB/Simulink, and a comparative simulation was carried out to compare the performance of the proposed method with some traditional methods. The simulation results show that the proposed approach has the ability to fast-track and make the system run stably. Furthermore, it can make the system respond quickly to environmental changes. An experimental platform was built, and the experimental results validated and confirmed the advantages of the proposed method.

Suggested Citation

  • Yuhang Liu & Xiangxin Liu & Jianwei Zhang & Yufeng Zhang & Ziyao Zhu, 2020. "A Novel Maximum Power Point Tracking Control Strategy for the Building Integrated Photovoltaic System," Energies, MDPI, vol. 13(11), pages 1-23, May.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:11:p:2679-:d:363068
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/11/2679/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/11/2679/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jia, Teng & Dai, Yanjun & Wang, Ruzhu, 2018. "Refining energy sources in winemaking industry by using solar energy as alternatives for fossil fuels: A review and perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 278-296.
    2. Messalti, Sabir & Harrag, Abdelghani & Loukriz, Abdelhamid, 2017. "A new variable step size neural networks MPPT controller: Review, simulation and hardware implementation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 221-233.
    3. Bradai, R. & Boukenoui, R. & Kheldoun, A. & Salhi, H. & Ghanes, M. & Barbot, J-P. & Mellit, A., 2017. "Experimental assessment of new fast MPPT algorithm for PV systems under non-uniform irradiance conditions," Applied Energy, Elsevier, vol. 199(C), pages 416-429.
    4. Spiliotis, Konstantinos & Gonçalves, Juliana E. & Van De Sande, Wieland & Ravyts, Simon & Daenen, Michael & Saelens, Dirk & Baert, Kris & Driesen, Johan, 2019. "Modeling and validation of a DC/DC power converter for building energy simulations: Application to BIPV systems," Applied Energy, Elsevier, vol. 240(C), pages 646-665.
    5. Chun-Liang Liu & Jing-Hsiao Chen & Yi-Hua Liu & Zong-Zhen Yang, 2014. "An Asymmetrical Fuzzy-Logic-Control-Based MPPT Algorithm for Photovoltaic Systems," Energies, MDPI, vol. 7(4), pages 1-17, April.
    6. Jayathissa, P. & Luzzatto, M. & Schmidli, J. & Hofer, J. & Nagy, Z. & Schlueter, A., 2017. "Optimising building net energy demand with dynamic BIPV shading," Applied Energy, Elsevier, vol. 202(C), pages 726-735.
    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. Thomas Bröthaler & Marcus Rennhofer & Daniel Brandl & Thomas Mach & Andreas Heinz & Gusztáv Újvári & Helga C. Lichtenegger & Harald Rennhofer, 2021. "Performance Analysis of a Facade-Integrated Photovoltaic Powered Cooling System," Sustainability, MDPI, vol. 13(8), pages 1-21, April.

    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. Camilo, Jones C. & Guedes, Tatiana & Fernandes, Darlan A. & Melo, J.D. & Costa, F.F. & Sguarezi Filho, Alfeu J., 2019. "A maximum power point tracking for photovoltaic systems based on Monod equation," Renewable Energy, Elsevier, vol. 130(C), pages 428-438.
    2. Wang, Jian-jun & Deng, Yu-cong & Sun, Wen-biao & Zheng, Xiao-bin & Cui, Zheng, 2023. "Maximum power point tracking method based on impedance matching for a micro hydropower generator," Applied Energy, Elsevier, vol. 340(C).
    3. 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.
    4. Xiaoguang Liu & Yuefeng Wang, 2019. "Reconfiguration Method to Extract More Power from Partially Shaded Photovoltaic Arrays with Series-Parallel Topology," Energies, MDPI, vol. 12(8), pages 1-16, April.
    5. Yinxiao Zhu & Moon Keun Kim & Huiqing Wen, 2018. "Simulation and Analysis of Perturbation and Observation-Based Self-Adaptable Step Size Maximum Power Point Tracking Strategy with Low Power Loss for Photovoltaics," Energies, MDPI, vol. 12(1), pages 1-20, December.
    6. Spiliotis, Konstantinos & Gonçalves, Juliana E. & Van De Sande, Wieland & Ravyts, Simon & Daenen, Michael & Saelens, Dirk & Baert, Kris & Driesen, Johan, 2019. "Modeling and validation of a DC/DC power converter for building energy simulations: Application to BIPV systems," Applied Energy, Elsevier, vol. 240(C), pages 646-665.
    7. Yao, Ganzhou & Luo, Zirong & Lu, Zhongyue & Wang, Mangkuan & Shang, Jianzhong & Guerrerob, Josep M., 2023. "Unlocking the potential of wave energy conversion: A comprehensive evaluation of advanced maximum power point tracking techniques and hybrid strategies for sustainable energy harvesting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    8. 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).
    9. Abdelhakim Mesloub & Aritra Ghosh & Mabrouk Touahmia & Ghazy Abdullah Albaqawy & Emad Noaime & Badr M. Alsolami, 2020. "Performance Analysis of Photovoltaic Integrated Shading Devices (PVSDs) and Semi-Transparent Photovoltaic (STPV) Devices Retrofitted to a Prototype Office Building in a Hot Desert Climate," Sustainability, MDPI, vol. 12(23), pages 1-17, December.
    10. Dehwah, Ammar H.A. & Krarti, Moncef, 2021. "Energy performance of integrated adaptive envelope systems for residential buildings," Energy, Elsevier, vol. 233(C).
    11. Dong, Lijun & Kang, Xiaojun & Pan, Mengqi & Zhao, Man & Zhang, Feng & Yao, Hong, 2020. "B-matching-based optimization model for energy allocation in sea surface monitoring," Energy, Elsevier, vol. 192(C).
    12. Catrini, P. & Panno, D. & Cardona, F. & Piacentino, A., 2020. "Characterization of cooling loads in the wine industry and novel seasonal indicator for reliable assessment of energy saving through retrofit of chillers," Applied Energy, Elsevier, vol. 266(C).
    13. Kosorić, Vesna & Huang, Huajing & Tablada, Abel & Lau, Siu-Kit & Tan, Hugh T.W., 2019. "Survey on the social acceptance of the productive façade concept integrating photovoltaic and farming systems in high-rise public housing blocks in Singapore," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 197-214.
    14. Taveres-Cachat, Ellika & Lobaccaro, Gabriele & Goia, Francesco & Chaudhary, Gaurav, 2019. "A methodology to improve the performance of PV integrated shading devices using multi-objective optimization," Applied Energy, Elsevier, vol. 247(C), pages 731-744.
    15. 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.
    16. Piotr Michalak, 2023. "Simulation and Experimental Study on the Use of Ventilation Air for Space Heating of a Room in a Low-Energy Building," Energies, MDPI, vol. 16(8), pages 1-17, April.
    17. Kostas Bavarinos & Anastasios Dounis & Panagiotis Kofinas, 2021. "Maximum Power Point Tracking Based on Reinforcement Learning Using Evolutionary Optimization Algorithms," Energies, MDPI, vol. 14(2), pages 1-23, January.
    18. 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.
    19. Yang Du & Ke Yan & Zixiao Ren & Weidong Xiao, 2018. "Designing Localized MPPT for PV Systems Using Fuzzy-Weighted Extreme Learning Machine," Energies, MDPI, vol. 11(10), pages 1-10, October.
    20. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.

    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:11:p:2679-:d:363068. 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.