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Finite Control Set Model Predictive Control for an LCL-Filtered Grid-Tied Inverter with Full Status Estimations under Unbalanced Grid Voltage

Author

Listed:
  • Xiaotao Chen

    (Department of Electronic Engineering, Shanghai Maritime University, Shanghai 201306, China)

  • Weimin Wu

    (Department of Electronic Engineering, Shanghai Maritime University, Shanghai 201306, China)

  • Ning Gao

    (Department of Electronic Engineering, Shanghai Maritime University, Shanghai 201306, China)

  • Jiahao Liu

    (Department of Electronic Engineering, Shanghai Maritime University, Shanghai 201306, China)

  • Henry Shu-Hung Chung

    (Department of Electronic Engineering, City University of Hong Kong, Hong Kong 999077, China)

  • Frede Blaabjerg

    (Department of Energy Technology, Aalborg University, DK-9220 Aalborg, Denmark)

Abstract

This paper proposes a novel finite control set model predictive control (FCS-MPC) strategy with merely grid-injected current sensors for an inductance-capacitance-inductance (LCL)-filtered grid-tied inverter, which can obtain a sinusoidal grid-injected current whether three-phase grid voltages are balanced or not. Compared with the conventional FCS-MPC method, four compositions are added in the proposed FCS-MPC algorithm, where the grid voltage observer (GVO) and Luenberger observer are combined together to achieve full status estimations (including grid voltage, capacitor voltage, inverter-side current, and grid-injected current), while the sequence extractor and the reference generator are applied to eliminate the double frequency ripples of the active or reactive power, or the negative sequence component (NSC) of the grid-injected current caused by the unbalanced grid voltage. Simulation model and experimental platform are established to verify the effectiveness of the proposed FCS-MPC strategy, with full status estimations under both balanced and unbalanced grid voltage conditions.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:14:p:2691-:d:248128
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    References listed on IDEAS

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    1. Seung-Jin Yoon & Ngoc Bao Lai & Kyeong-Hwa Kim, 2018. "A Systematic Controller Design for a Grid-Connected Inverter with LCL Filter Using a Discrete-Time Integral State Feedback Control and State Observer," Energies, MDPI, vol. 11(2), pages 1-20, February.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.

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