IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i10p2615-d173152.html
   My bibliography  Save this article

Designing Localized MPPT for PV Systems Using Fuzzy-Weighted Extreme Learning Machine

Author

Listed:
  • Yang Du

    (Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China)

  • Ke Yan

    (College of Information Engineering, China Jiliang University, Hangzhou 310018, China)

  • Zixiao Ren

    (Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China)

  • Weidong Xiao

    (School of Electrical and Information Engineering, The University of Sydney, Western Avenue, Sydney, NSW 2006, Australia)

Abstract

A maximum power point tracker (MPPT) should be designed to deal with various weather conditions, which are different from region to region. Customization is an important step for achieving the highest solar energy harvest. The latest development of modern machine learning provides the possibility to classify the weather types automatically and, consequently, assist localized MPPT design. In this study, a localized MPPT algorithm is developed, which is supported by a supervised weather-type classification system. Two classical machine learning technologies are employed and compared, namely, the support vector machine (SVM) and extreme learning machine (ELM). The simulation results show the outperformance of the proposed method in comparison with the traditional MPPT design.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2615-:d:173152
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/10/2615/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/10/2615/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Pashiardis, S. & Kalogirou, S.A. & Pelengaris, A., 2017. "Statistical analysis for the characterization of solar energy utilization and inter-comparison of solar radiation at two sites in Cyprus," Applied Energy, Elsevier, vol. 190(C), pages 1138-1158.
    3. Henrik Zsiborács & Nóra Hegedűsné Baranyai & András Vincze & István Háber & Gábor Pintér, 2018. "Economic and Technical Aspects of Flexible Storage Photovoltaic Systems in Europe," Energies, MDPI, vol. 11(6), pages 1-17, June.
    4. Henrik Zsiborács & Attila Bai & József Popp & Zoltán Gabnai & Béla Pályi & István Farkas & Nóra Hegedűsné Baranyai & Mihály Veszelka & László Zentkó & Gábor Pintér, 2018. "Change of Real and Simulated Energy Production of Certain Photovoltaic Technologies in Relation to Orientation, Tilt Angle and Dual-Axis Sun-Tracking. A Case Study in Hungary," Sustainability, MDPI, vol. 10(5), pages 1-19, May.
    5. Lv, You & Liu, Jizhen & Yang, Tingting & Zeng, Deliang, 2013. "A novel least squares support vector machine ensemble model for NOx emission prediction of a coal-fired boiler," Energy, Elsevier, vol. 55(C), pages 319-329.
    6. Kalogirou, S.A. & Pashiardis, S. & Pashiardi, A., 2017. "Statistical analysis and inter-comparison of the global solar radiation at two sites in Cyprus," Renewable Energy, Elsevier, vol. 101(C), pages 1102-1123.
    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. 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. Grażyna Frydrychowicz-Jastrzębska & Artur Bugała, 2021. "Solar Tracking System with New Hybrid Control in Energy Production Optimization from Photovoltaic Conversion for Polish Climatic Conditions," Energies, MDPI, vol. 14(10), pages 1-26, May.
    3. Ke Yan & Xudong Wang & Yang Du & Ning Jin & Haichao Huang & Hangxia Zhou, 2018. "Multi-Step Short-Term Power Consumption Forecasting with a Hybrid Deep Learning Strategy," Energies, MDPI, vol. 11(11), pages 1-15, November.
    4. Fabio Corti & Antonino Laudani & Gabriele Maria Lozito & Alberto Reatti, 2020. "Computationally Efficient Modeling of DC-DC Converters for PV Applications," Energies, MDPI, vol. 13(19), pages 1-18, September.
    5. Andrés Tobón & Julián Peláez-Restrepo & Jhon Montano & Mariana Durango & Jorge Herrera & Asier Ibeas, 2020. "MPPT of a Photovoltaic Panels Array with Partial Shading Using the IPSM with Implementation Both in Simulation as in Hardware," Energies, MDPI, vol. 13(4), pages 1-17, February.
    6. 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.
    7. Ke Yan & Yuting Dai & Meiling Xu & Yuchang Mo, 2019. "Tunnel Surface Settlement Forecasting with Ensemble Learning," Sustainability, MDPI, vol. 12(1), pages 1-11, December.
    8. 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.
    9. Ahmed Al Mansur & Md. Ruhul Amin & Kazi Khairul Islam, 2019. "Performance Comparison of Mismatch Power Loss Minimization Techniques in Series-Parallel PV Array Configurations," Energies, MDPI, vol. 12(5), pages 1-21, March.
    10. Abdelbasset Krama & Laid Zellouma & Boualaga Rabhi & Shady S. Refaat & Mansour Bouzidi, 2018. "Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm," Energies, MDPI, vol. 11(12), pages 1-26, December.
    11. 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.

    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. Hyunji Lee & Katherine A. Kim, 2018. "Design Considerations for Parallel Differential Power Processing Converters in a Photovoltaic-Powered Wearable Application," Energies, MDPI, vol. 11(12), pages 1-17, November.
    2. Xiaoyang Song & Yaohuan Huang & Chuanpeng Zhao & Yuxin Liu & Yanguo Lu & Yongguo Chang & Jie Yang, 2018. "An Approach for Estimating Solar Photovoltaic Potential Based on Rooftop Retrieval from Remote Sensing Images," Energies, MDPI, vol. 11(11), pages 1-14, November.
    3. Li, Shuai & Ma, Hongjie & Li, Weiyi, 2017. "Typical solar radiation year construction using k-means clustering and discrete-time Markov chain," Applied Energy, Elsevier, vol. 205(C), pages 720-731.
    4. Battisti, Felipe G. & Delsoto, Giovanni S. & da Silva, Alexandre K., 2018. "Transient analysis and optimization of a recuperative sCO2 Brayton cycle assisted by heat and mass storage systems," Energy, Elsevier, vol. 150(C), pages 979-991.
    5. Diane Palmer & Elena Koumpli & Ian Cole & Ralph Gottschalg & Thomas Betts, 2018. "A GIS-Based Method for Identification of Wide Area Rooftop Suitability for Minimum Size PV Systems Using LiDAR Data and Photogrammetry," Energies, MDPI, vol. 11(12), pages 1-22, December.
    6. Alin Lin & Ming Lu & Pingjun Sun, 2018. "The Influence of Local Environmental, Economic and Social Variables on the Spatial Distribution of Photovoltaic Applications across China’s Urban Areas," Energies, MDPI, vol. 11(8), pages 1-14, July.
    7. Tao Yi & Ling Tong & Mohan Qiu & Jinpeng Liu, 2019. "Analysis of Driving Factors of Photovoltaic Power Generation Efficiency: A Case Study in China," Energies, MDPI, vol. 12(3), pages 1-15, January.
    8. 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).
    9. Dimitar Bozalakov & Mohannad J. Mnati & Joannes Laveyne & Jan Desmet & Lieven Vandevelde, 2019. "Battery Storage Integration in Voltage Unbalance and Overvoltage Mitigation Control Strategies and Its Impact on the Power Quality," Energies, MDPI, vol. 12(8), pages 1-26, April.
    10. Iolanda Saviuc & Herbert Peremans & Steven Van Passel & Kevin Milis, 2019. "Economic Performance of Using Batteries in European Residential Microgrids under the Net-Metering Scheme," Energies, MDPI, vol. 12(1), pages 1-28, January.
    11. 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).
    12. Lv, You & Lv, Xuguang & Fang, Fang & Yang, Tingting & Romero, Carlos E., 2020. "Adaptive selective catalytic reduction model development using typical operating data in coal-fired power plants," Energy, Elsevier, vol. 192(C).
    13. 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.
    14. Milad Zeraatpisheh & Reza Arababadi & Mohsen Saffari Pour, 2018. "Economic Analysis for Residential Solar PV Systems Based on Different Demand Charge Tariffs," Energies, MDPI, vol. 11(12), pages 1-19, November.
    15. 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).
    16. 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.
    17. Tan, Peng & He, Biao & Zhang, Cheng & Rao, Debei & Li, Shengnan & Fang, Qingyan & Chen, Gang, 2019. "Dynamic modeling of NOX emission in a 660 MW coal-fired boiler with long short-term memory," Energy, Elsevier, vol. 176(C), pages 429-436.
    18. Zheng, Wei & Wang, Chao & Yang, Yajun & Zhang, Yongfei, 2020. "Multi-objective combustion optimization based on data-driven hybrid strategy," Energy, Elsevier, vol. 191(C).
    19. Tan, Peng & Xia, Ji & Zhang, Cheng & Fang, Qingyan & Chen, Gang, 2016. "Modeling and reduction of NOX emissions for a 700 MW coal-fired boiler with the advanced machine learning method," Energy, Elsevier, vol. 94(C), pages 672-679.
    20. P. Madasamy & V. Suresh Kumar & P. Sanjeevikumar & Jens Bo Holm-Nielsen & Eklas Hosain & C. Bharatiraja, 2019. "A Three-Phase Transformerless T-Type- NPC-MLI for Grid Connected PV Systems with Common-Mode Leakage Current Mitigation," Energies, MDPI, vol. 12(12), pages 1-25, June.

    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:11:y:2018:i:10:p:2615-:d:173152. 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.