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Model Predictive Virtual Synchronous Control of Permanent Magnet Synchronous Generator-Based Wind Power System

Author

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  • Yusheng Sun

    (School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China)

  • Yaqian Zhao

    (School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China)

  • Zhifeng Dou

    (School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China)

  • Yanyan Li

    (School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China)

  • Leilei Guo

    (School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China)

Abstract

As much wind power is integrated into the power grid through power electronic equipment, the use of wind power is increased rapidly. Wind power system makes the power grid lack inertia and damping, thereby reducing power grid stability; in severe cases, it may even be disconnected. virtual synchronous generator (VSG) has been put forward to enhance the anti-disturbance performance of power grid. However, conventional VSG adopts an outer power loop and inner-current loop control. The inner-current loop control needs a pulse width modulation (PWM) module and proportion integration (PI) parameter settings. In order to reduce the parameter settings and simplify control structures, in this study, model predictive control (MPC) is used instead of inner-current loop control. At the same time—for the overall stability and control flexibility of the back-to-back system—we further propose to use outer-voltage loop control (OVLC) and MPC to stabilize direct current (DC) voltage on the machine-side and to employ model predictive virtual synchronous controls to provide inertia and damping for the power grid. The proposed control method was simulated in Matlab/Simulink (MathWorks, Massachusetts, MA, 2016) and verified by experimental results.

Suggested Citation

  • Yusheng Sun & Yaqian Zhao & Zhifeng Dou & Yanyan Li & Leilei Guo, 2020. "Model Predictive Virtual Synchronous Control of Permanent Magnet Synchronous Generator-Based Wind Power System," Energies, MDPI, vol. 13(19), pages 1-14, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:19:p:5022-:d:418632
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    References listed on IDEAS

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    1. Giulio Vita & Anina Šarkić-Glumac & Hassan Hemida & Simone Salvadori & Charalampos Baniotopoulos, 2020. "On the Wind Energy Resource above High-Rise Buildings," Energies, MDPI, vol. 13(14), pages 1-23, July.
    2. Mateusz Andrychowicz, 2020. "Comparison of the Use of Energy Storages and Energy Curtailment as an Addition to the Allocation of Renewable Energy in the Distribution System in Order to Minimize Development Costs," Energies, MDPI, vol. 13(14), pages 1-20, July.
    3. Seok-Il Go & Sang-Yun Yun & Seon-Ju Ahn & Joon-Ho Choi, 2020. "Voltage and Reactive Power Optimization Using a Simplified Linear Equations at Distribution Networks with DG," Energies, MDPI, vol. 13(13), pages 1-23, June.
    4. Jieyan Chen & Chengxi Li, 2020. "Design Optimization and Coupled Dynamics Analysis of an Offshore Wind Turbine with a Single Swivel Connected Tether," Energies, MDPI, vol. 13(14), pages 1-26, July.
    5. Md Rasel Sarkar & Sabariah Julai & Chong Wen Tong & Moslem Uddin & M.F. Romlie & GM Shafiullah, 2020. "Hybrid Pitch Angle Controller Approaches for Stable Wind Turbine Power under Variable Wind Speed," Energies, MDPI, vol. 13(14), pages 1-19, July.
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    Cited by:

    1. Lintao Ren & Hui Guo & Zhenlan Dou & Fei Wang & Lijun Zhang, 2022. "Modeling and Analysis of the Harmonic Interaction between Grid-Connected Inverter Clusters and the Utility Grid," Energies, MDPI, vol. 15(10), pages 1-19, May.
    2. 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.

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