IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i18p4669-d410457.html
   My bibliography  Save this article

Power Loss Analysis of Solar Photovoltaic Integrated Model Predictive Control Based On-Grid Inverter

Author

Listed:
  • Amit Kumer Podder

    (Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh)

  • Md. Habibullah

    (Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh)

  • Md. Tariquzzaman

    (Department of Electrical and Electronic Engineering, Jashore University of Science & Technology, Jashore 7408, Bangladesh)

  • Eklas Hossain

    (Department of Electrical Engineering & Renewable Energy, Oregon Renewable Energy Center (OREC), Oregon Institute of Technology, Klamath Falls, OR 97601, USA)

  • Sanjeevikumar Padmanaban

    (Department of Energy Technology, Aalborg University, 6700 Esbjerg, Denmark)

Abstract

This paper presents a finite control-set model predictive control (FCS-MPC) based technique to reduce the switching loss and frequency of the on-grid PV inverter by incorporating a switching frequency term in the cost function of the model predictive control (MPC). In the proposed MPC, the control objectives (current and switching frequency) select an optimal switching state for the inverter by minimizing a predefined cost function. The two control objectives are combined with a weighting factor. A trade-off between the switching frequency (average) and total harmonic distortion (THD) of the current was utilized to determine the value of the weighting factor. The switching, conduction, and harmonic losses were determined at the selected value of the weighting factor for both the proposed and conventional FCS-MPC and compared. The system was simulated in MATLAB/Simulink, and a small-scale hardware prototype was built to realize the system and verify the proposal. Considering only 0.25% more current THD, the switching frequency and loss per phase were reduced by 20.62% and 19.78%, respectively. The instantaneous overall power loss was also reduced by 2% due to the addition of a switching frequency term in the cost function which ensures a satisfactory empirical result for an on-grid PV inverter.

Suggested Citation

  • Amit Kumer Podder & Md. Habibullah & Md. Tariquzzaman & Eklas Hossain & Sanjeevikumar Padmanaban, 2020. "Power Loss Analysis of Solar Photovoltaic Integrated Model Predictive Control Based On-Grid Inverter," Energies, MDPI, vol. 13(18), pages 1-26, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4669-:d:410457
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/18/4669/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/18/4669/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jiefeng Hu & Ka Wai Eric Cheng, 2017. "Predictive Control of Power Electronics Converters in Renewable Energy Systems," Energies, MDPI, vol. 10(4), pages 1-14, April.
    2. Roh Chan & Sangshin Kwak, 2017. "Model-Based Predictive Current Control Method with Constant Switching Frequency for Single-Phase Voltage Source Inverters," Energies, MDPI, vol. 10(11), pages 1-21, November.
    3. Rui Qin & Chunhua Yang & Hongwei Tao & Tao Peng & Chao Yang & Zhiwen Chen, 2019. "A Power Loss Decrease Method Based on Finite Set Model Predictive Control for a Motor Emulator with Reduced Switch Count," Energies, MDPI, vol. 12(24), pages 1-25, December.
    4. Xiaotao Chen & Weimin Wu & Ning Gao & Jiahao Liu & Henry Shu-Hung Chung & Frede Blaabjerg, 2019. "Finite Control Set Model Predictive Control for an LCL-Filtered Grid-Tied Inverter with Full Status Estimations under Unbalanced Grid Voltage," Energies, MDPI, vol. 12(14), pages 1-22, July.
    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. Paolo Mercorelli, 2022. "Model Predictive Control for Energy Optimization in Generators/Motors as Well as Converters and Inverters for Futuristic Integrated Power Networks," Energies, MDPI, vol. 15(16), pages 1-4, August.
    2. Amit Kumer Podder & Sayma Afroza Supti & Sayemul Islam & Maria Malvoni & Arunkumar Jayakumar & Sanchari Deb & Nallapaneni Manoj Kumar, 2021. "Feasibility Assessment of Hybrid Solar Photovoltaic-Biogas Generator Based Charging Station: A Case of Easy Bike and Auto Rickshaw Scenario in a Developing Nation," Sustainability, MDPI, vol. 14(1), pages 1-27, December.
    3. Jaime A. Rohten & Javier E. Muñoz & Esteban S. Pulido & José J. Silva & Felipe A. Villarroel & José R. Espinoza, 2021. "Very Low Sampling Frequency Model Predictive Control for Power Converters in the Medium and High-Power Range Applications," Energies, MDPI, vol. 14(1), pages 1-18, January.

    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. Cheng-Kai Lin & Jen-te Yu & Hao-Qun Huang & Jyun-Ting Wang & Hsing-Cheng Yu & Yen-Shin Lai, 2018. "A Dual-Voltage-Vector Model-Free Predictive Current Controller for Synchronous Reluctance Motor Drive Systems," Energies, MDPI, vol. 11(7), pages 1-29, July.
    2. Ariel Villalón & Carlos Muñoz & Javier Muñoz & Marco Rivera, 2023. "Fixed-Switching-Frequency Modulated Model Predictive Control for Islanded AC Microgrid Applications," Mathematics, MDPI, vol. 11(3), pages 1-27, January.
    3. Ramon Guzmán & Luís García de Vicuña & Miguel Castilla & Jaume Miret & Antonio Camacho, 2017. "Finite Control Set Model Predictive Control for a Three-Phase Shunt Active Power Filter with a Kalman Filter-Based Estimation," Energies, MDPI, vol. 10(10), pages 1-14, October.
    4. Silvia Costa Ferreira & João Gabriel Luppi Foster & Robson Bauwelz Gonzatti & Rondineli Rodrigues Pereira & Guilherme Gonçalves Pinheiro & Bruno P. Braga Guimarães, 2023. "Online Adaptive Parameter Estimation of a Finite Control Set Model Predictive Controlled Hybrid Active Power Filter," Energies, MDPI, vol. 16(9), pages 1-22, April.
    5. Mohammad Alathamneh & Haneen Ghanayem & Xingyu Yang & R. M. Nelms, 2022. "Three-Phase Grid-Connected Inverter Power Control under Unbalanced Grid Conditions Using a Time-Domain Symmetrical Components Extraction Method," Energies, MDPI, vol. 15(19), pages 1-16, September.
    6. Yaqi Wang & Zhigang Liu, 2018. "Suppression Research Regarding Low-Frequency Oscillation in the Vehicle-Grid Coupling System Using Model-Based Predictive Current Control," Energies, MDPI, vol. 11(7), pages 1-21, July.
    7. Feras Alasali & Stephen Haben & Victor Becerra & William Holderbaum, 2017. "Optimal Energy Management and MPC Strategies for Electrified RTG Cranes with Energy Storage Systems," Energies, MDPI, vol. 10(10), pages 1-18, October.
    8. Mohammad Alathamneh & Haneen Ghanayem & Xingyu Yang & R. M. Nelms, 2022. "Three-Phase Grid-Connected Inverter Power Control under Unbalanced Grid Conditions Using a Proportional-Resonant Control Method," Energies, MDPI, vol. 15(19), pages 1-17, September.
    9. Yiwang Wang & Chun Gan & Kai Ni & Xinhua Li & Houjun Tang & Yong Yang, 2017. "A Multifunctional Isolated and Non-Isolated Dual Mode Converter for Renewable Energy Conversion Applications," Energies, MDPI, vol. 10(12), pages 1-17, November.
    10. Muhammad M. Fayyaz & Irtaza M. Syed & Yi Meng & Muhammad N. Aman, 2023. "Comprehensive Predictive Control Model for a Three-Phase Four-Legged Inverter," Energies, MDPI, vol. 16(6), pages 1-18, March.
    11. Bo Chen & Ping Wang & Yifeng Wang & Wei Li & Fuqiang Han & Shuhuai Zhang, 2017. "Comparative Analysis and Optimization of Power Loss Based on the Isolated Series/Multi Resonant Three-Port Bidirectional DC-DC Converter," Energies, MDPI, vol. 10(10), pages 1-26, October.
    12. Cheng-Shan Wang & Wei Li & Yi-Feng Wang & Fu-Qiang Han & Bo Chen, 2017. "A High-Efficiency Isolated LCLC Multi-Resonant Three-Port Bidirectional DC-DC Converter," Energies, MDPI, vol. 10(7), pages 1-22, July.
    13. Lynn Verkroost & Joachim Druant & Hendrik Vansompel & Frederik De Belie & Peter Sergeant, 2019. "Performance Degradation of Surface PMSMs with Demagnetization Defect under Predictive Current Control," Energies, MDPI, vol. 12(5), pages 1-20, February.
    14. Huakun Bi & Ping Wang & Zhishuang Wang, 2018. "Common Grounded H-Type Bidirectional DC-DC Converter with a Wide Voltage Conversion Ratio for a Hybrid Energy Storage System," Energies, MDPI, vol. 11(2), pages 1-22, February.
    15. Mohammad Alathamneh & Haneen Ghanayem & R. M. Nelms, 2022. "Bidirectional Power Control for a Three-Phase Grid-Connected Inverter under Unbalanced Grid Conditions Using a Proportional-Resonant and a Modified Time-Domain Symmetrical Components Extraction Method," Energies, MDPI, vol. 15(24), pages 1-23, December.
    16. Muhammad Yasir Ali Khan & Haoming Liu & Zhihao Yang & Xiaoling Yuan, 2020. "A Comprehensive Review on Grid Connected Photovoltaic Inverters, Their Modulation Techniques, and Control Strategies," Energies, MDPI, vol. 13(16), pages 1-40, August.
    17. Rui Qin & Chunhua Yang & Hongwei Tao & Tao Peng & Chao Yang & Zhiwen Chen, 2019. "A Power Loss Decrease Method Based on Finite Set Model Predictive Control for a Motor Emulator with Reduced Switch Count," Energies, MDPI, vol. 12(24), pages 1-25, December.
    18. Verica Radisavljevic-Gajic & Dimitri Karagiannis & Zoran Gajic, 2024. "Linear, Nonlinear, and Distributed-Parameter Observers Used for (Renewable) Energy Processes and Systems—An Overview," Energies, MDPI, vol. 17(11), 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:13:y:2020:i:18:p:4669-:d:410457. 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.