IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i24p6656-d463598.html
   My bibliography  Save this article

An Adaptive Model-Based MPPT Technique with Drift-Avoidance for Grid-Connected PV Systems

Author

Listed:
  • Mostafa Ahmed

    (Institute for Electrical Drive Systems and Power Electronics, Technical University of Munich (TUM), 80333 Munich, Germany
    Electrical Engineering Department, Faculty of Engineering, Assiut University, Assiut 71516, Egypt)

  • Mohamed Abdelrahem

    (Institute for Electrical Drive Systems and Power Electronics, Technical University of Munich (TUM), 80333 Munich, Germany
    Electrical Engineering Department, Faculty of Engineering, Assiut University, Assiut 71516, Egypt)

  • Ibrahim Harbi

    (Institute for Electrical Drive Systems and Power Electronics, Technical University of Munich (TUM), 80333 Munich, Germany
    Electrical Engineering Department, Faculty of Engineering, Menoufia University, Shebin El-Koum 32511, Egypt)

  • Ralph Kennel

    (Institute for Electrical Drive Systems and Power Electronics, Technical University of Munich (TUM), 80333 Munich, Germany)

Abstract

In this article, a modified control structure for a single-stage three phase grid-connected photovoltaic (PV) system is presented. In the proposed system, the maximum power point tracking (MPPT) function is developed using a new adaptive model-based technique, in which the maximum power point (MPP) voltage can be precisely located based on the characteristics of the PV source. By doing so, the drift problem associated with the traditional perturb and observe (P&O) technique can be easily solved. Moreover, the inverter control is accomplished using a predictive dead-beat function, which directly estimates the required reference voltages from the commanded reference currents. Then, the reference voltages are applied to a space vector pulse width modulator (SVPWM) for switching state generation. Furthermore, the proposed inverter control avoids the conventional and known cascaded loop structure of the voltage oriented control (VOC) method by elimination of the outer PI controller, and hence the overall control strategy is simplified. The proposed system is compared with different MPPT techniques, including the conventional P&O method and other techniques intended for drift avoidance. The evaluation of the suggested control methodology depends on various radiation profiles created in MATLAB. The proposed technique succeeds at capturing the maximum available power from the PV source with no drift in comparison with other methods.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:24:p:6656-:d:463598
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/24/6656/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/24/6656/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Verma, Deepak & Nema, Savita & Shandilya, A.M. & Dash, Soubhagya K., 2016. "Maximum power point tracking (MPPT) techniques: Recapitulation in solar photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1018-1034.
    2. Zahedi, A., 2011. "Maximizing solar PV energy penetration using energy storage technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 866-870, January.
    3. Hassaine, L. & OLias, E. & Quintero, J. & Salas, V., 2014. "Overview of power inverter topologies and control structures for grid connected photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 796-807.
    4. Haidar Islam & Saad Mekhilef & Noraisyah Binti Mohamed Shah & Tey Kok Soon & Mehdi Seyedmahmousian & Ben Horan & Alex Stojcevski, 2018. "Performance Evaluation of Maximum Power Point Tracking Approaches and Photovoltaic Systems," Energies, MDPI, vol. 11(2), pages 1-24, February.
    5. Ai, B. & Yang, H. & Shen, H. & Liao, X., 2003. "Computer-aided design of PV/wind hybrid system," Renewable Energy, Elsevier, vol. 28(10), pages 1491-1512.
    6. Ibrahim Harbi & Mohamed Abdelrahem & Mostafa Ahmed & Ralph Kennel, 2020. "Reduced-Complexity Model Predictive Control with Online Parameter Assessment for a Grid-Connected Single-Phase Multilevel Inverter," Sustainability, MDPI, vol. 12(19), pages 1-23, September.
    7. Ishaque, Kashif & Salam, Zainal & Lauss, George, 2014. "The performance of perturb and observe and incremental conductance maximum power point tracking method under dynamic weather conditions," Applied Energy, Elsevier, vol. 119(C), pages 228-236.
    8. Mostafa Ahmed & Mohamed Abdelrahem & Ralph Kennel, 2020. "Highly Efficient and Robust Grid Connected Photovoltaic System Based Model Predictive Control with Kalman Filtering Capability," Sustainability, MDPI, vol. 12(11), pages 1-22, June.
    9. Ahmed, Jubaer & Salam, Zainal, 2015. "An improved perturb and observe (P&O) maximum power point tracking (MPPT) algorithm for higher efficiency," Applied Energy, Elsevier, vol. 150(C), pages 97-108.
    10. Bhatnagar, Pallavee & Nema, R.K., 2013. "Maximum power point tracking control techniques: State-of-the-art in photovoltaic applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 224-241.
    11. Hosseini, Seyed Ehsan & Wahid, Mazlan Abdul, 2016. "Hydrogen production from renewable and sustainable energy resources: Promising green energy carrier for clean development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 850-866.
    12. Zeb, Kamran & Uddin, Waqar & Khan, Muhammad Adil & Ali, Zunaib & Ali, Muhammad Umair & Christofides, Nicholas & Kim, H.J., 2018. "A comprehensive review on inverter topologies and control strategies for grid connected photovoltaic system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 1120-1141.
    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. 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.
    2. 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.
    3. Mostafa Ahmed & Ibrahim Harbi & Ralph Kennel & José Rodríguez & Mohamed Abdelrahem, 2022. "Evaluation of the Main Control Strategies for Grid-Connected PV Systems," Sustainability, MDPI, vol. 14(18), pages 1-20, September.
    4. Sachin Angadi & Udaykumar R. Yaragatti & Yellasiri Suresh & A. B. Raju, 2021. "System Parameter Based Performance Optimization of Solar PV Systems with Perturbation Based MPPT Algorithms," Energies, MDPI, vol. 14(7), pages 1-20, 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. Hassan M. H. Farh & Mohd F. Othman & Ali M. Eltamaly & M. S. Al-Saud, 2018. "Maximum Power Extraction from a Partially Shaded PV System Using an Interleaved Boost Converter," Energies, MDPI, vol. 11(10), pages 1-18, September.
    2. Başoğlu, Mustafa Engin & Çakır, Bekir, 2016. "Comparisons of MPPT performances of isolated and non-isolated DC–DC converters by using a new approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1100-1113.
    3. Hong, Ying-Yi & Beltran, Angelo A. & Paglinawan, Arnold C., 2018. "A robust design of maximum power point tracking using Taguchi method for stand-alone PV system," Applied Energy, Elsevier, vol. 211(C), pages 50-63.
    4. Boukenoui, R. & Ghanes, M. & Barbot, J.-P. & Bradai, R. & Mellit, A. & Salhi, H., 2017. "Experimental assessment of Maximum Power Point Tracking methods for photovoltaic systems," Energy, Elsevier, vol. 132(C), pages 324-340.
    5. Ramli, Makbul A.M. & Twaha, Ssennoga & Ishaque, Kashif & Al-Turki, Yusuf A., 2017. "A review on maximum power point tracking for photovoltaic systems with and without shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 144-159.
    6. Kebir, Anouer & Woodward, Lyne & Akhrif, Ouassima, 2019. "Real-time optimization of renewable energy sources power using neural network-based anticipative extremum-seeking control," Renewable Energy, Elsevier, vol. 134(C), pages 914-926.
    7. 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.
    8. 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.
    9. Suliang Ma & Mingxuan Chen & Jianwen Wu & Wenlei Huo & Lian Huang, 2016. "Augmented Nonlinear Controller for Maximum Power-Point Tracking with Artificial Neural Network in Grid-Connected Photovoltaic Systems," Energies, MDPI, vol. 9(12), pages 1-24, November.
    10. 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.
    11. Li, Shaowu, 2016. "Linear equivalent models at the maximum power point based on variable weather parameters for photovoltaic cell," Applied Energy, Elsevier, vol. 182(C), pages 94-104.
    12. Belkaid, A. & Colak, I. & Isik, O., 2016. "Photovoltaic maximum power point tracking under fast varying of solar radiation," Applied Energy, Elsevier, vol. 179(C), pages 523-530.
    13. Zeng, Zheng & Shao, Weihua & Chen, Hao & Hu, Borong & Chen, Wensuo & Li, Hui & Ran, Li, 2017. "Changes and challenges of photovoltaic inverter with silicon carbide device," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 624-639.
    14. Ahmed Ismail M. Ali & Zuhair Muhammed Alaas & Mahmoud A. Sayed & Abdulaziz Almalaq & Anouar Farah & Mohamed A. Mohamed, 2022. "An Efficient MPPT Technique-Based Single-Stage Incremental Conductance for Integrated PV Systems Considering Flyback Central-Type PV Inverter," Sustainability, MDPI, vol. 14(19), pages 1-15, September.
    15. Yousaf, Muhammad Zain & Koondhar, Mohsin Ali & Zaki, Zaki A. & Ahmed, Emad M. & Alaas, Zuhair Muhammed & Mahariq, Ibrahim & Guerrero, Josep M., 2025. "Improved MPPT of solar PV Systems under different Environmental conditions utilizes a Novel Hybrid PSO," Renewable Energy, Elsevier, vol. 244(C).
    16. Muhammed Y. Worku & Mohamed A. Hassan & Luqman S. Maraaba & Md Shafiullah & Mohamed R. Elkadeem & Md Ismail Hossain & Mohamed A. Abido, 2023. "A Comprehensive Review of Recent Maximum Power Point Tracking Techniques for Photovoltaic Systems under Partial Shading," Sustainability, MDPI, vol. 15(14), pages 1-28, July.
    17. Ali Bughneda & Mohamed Salem & Anna Richelli & Dahaman Ishak & Salah Alatai, 2021. "Review of Multilevel Inverters for PV Energy System Applications," Energies, MDPI, vol. 14(6), pages 1-23, March.
    18. Jately, Vibhu & Azzopardi, Brian & Joshi, Jyoti & Venkateswaran V, Balaji & Sharma, Abhinav & Arora, Sudha, 2021. "Experimental Analysis of hill-climbing MPPT algorithms under low irradiance levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    19. Çelik, Özgür & Teke, Ahmet & Tan, Adnan, 2018. "Overview of micro-inverters as a challenging technology in photovoltaic applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3191-3206.
    20. Singh, Bhuwan Pratap & Goyal, Sunil Kumar & Siddiqui, Shahbaz Ahmed & Saraswat, Amit & Ucheniya, Ravi, 2022. "Intersection Point Determination Method: A novel MPPT approach for sudden and fast changing environmental conditions," Renewable Energy, Elsevier, vol. 200(C), pages 614-632.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:13:y:2020:i:24:p:6656-:d:463598. 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.