Journal of Shanghai Jiao Tong University

Journal of Shanghai Jiaotong University >

2025 , Vol. 59 >Issue 10: 1523 - 1532

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2023.499

New Type Power System and the Integrated Energy

Three-Vector Model-Free Predictive Current Control Method for Grid-Connected Inverters with Sampling Noise Compensation

  • CAO Wenping ,
  • WANG Yao ,
  • ZHANG Yue ,
  • LUO Kui ,
  • HU Cungang ,
  • RUI Tao
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  • 1 School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China
    2 China Electric Power Research Institute, Beijing 100192, China
    3 School of Internet, Anhui University, Hefei 230601, China

Received date: 2023-09-28

  Revised date: 2023-12-01

  Accepted date: 2024-01-29

  Online published: 2024-03-02

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Abstract

To address the issues of large current ripple, stagnant current gradient update, and sampling noise interference in the model-free predictive current control method for grid-connected inverters based on look-up table, a three-vector model-free predictive current control method with sampling noise compensation is proposed. First, the output current of each control period is predicted by using the current gradient corresponding to the three-voltage vectors, and the action time of each vector is determined by a cost function to reduce the current ripple. Then, based on the overlapping relationship between the coordinate components of the three vector and the basic vector, a two-step updating method is used to eliminate the stagnation phenomenon. Finally, according to the impact of sampling noise on current gradient updating, a second-order generalized integrator is employed to estimate and compensate the gradient error, thereby improving the accuracy of current gradient. The feasibility and effectiveness of the method proposed is verified by simulation and experiment.

Key words： grid-connected inverter; model-free predictive current control; three-vector; gradient update stagnation; sampling noise compensation

Cite this article

CAO Wenping , WANG Yao , ZHANG Yue , LUO Kui , HU Cungang , RUI Tao . Three-Vector Model-Free Predictive Current Control Method for Grid-Connected Inverters with Sampling Noise Compensation[J]. Journal of Shanghai Jiaotong University, 2025 , 59(10) : 1523 -1532 . DOI: 10.16183/j.cnki.jsjtu.2023.499

References

[1] 郭磊磊, 金楠, 李琰琰, 等. 并网逆变器无电网电压传感器模型预测控制[J]. 电工技术学报, 2020, 35(12): 2612-2622.
  GUO Leilei, JIN Nan, LI Yanyan, et al. Grid voltage sensorless model predictive control for grid-connected inverters[J]. Transactions of China Electrotechnical Society, 2020, 35(12): 2612-2622.
[2] 陈琢, 王琛琛, 成前. 基于单一矢量的两电平逆变器快速模型预测控制[J]. 电工技术学报, 2021, 36(Sup.2): 654-664.
  CHEN Zhuo, WANG Chenchen, CHENG Qian. Fast model predictive control of two-level inverter based on single vector[J]. Transactions of China Electrotechnical Society, 2021, 36(Sup.2): 654-664.
[3] 郭磊磊, 金楠, 李琰琰, 等. 电压源逆变器虚拟矢量模型预测共模电压抑制方法[J]. 电工技术学报, 2020, 35(4): 839-849.
  GUO Leilei, JIN Nan, LI Yanyan, et al. Virtual vector based model predictive common-mode voltage reduction method for voltage source inverters[J]. Transactions of China Electrotechnical Society, 2020, 35(4): 839-849.
[4] LEE K J, PARK B G, KIM R Y, et al. Robust predictive current controller based on a disturbance estimator in a three-phase grid-connected inverter[J]. IEEE Transactions on Power Electronics, 2012, 27(1): 276-283.
[5] TINAZZI F, CARLET P G, BOLOGNANI S, et al. Motor parameter-free predictive current control of synchronous motors by recursive least-square self-commissioning model[J]. IEEE Transactions on Industrial Electronics, 2020, 67(11): 9093-9100.
[6] BROSCH A, HANKE S, WALLSCHEID O, et al. Data-driven recursive least squares estimation for model predictive current control of permanent magnet synchronous motors[J]. IEEE Transactions on Power Electronics, 2021, 36(2): 2179-2190.
[7] SAFAEI A, MAHYUDDIN M N. Adaptive model-free control based on an ultra-local model with model-free parameter estimations for a generic SISO system[J]. IEEE Access, 2018, 6: 4266-4275.
[8] JIANG T, ZHANG Y C, JIAO J, et al. Model-free predictive current control of doubly fed induction generator based on ultra-local model[C]// 2020 IEEE 9th International Power Electronics and Motion Control Conference. Nanjing, China: IEEE, 2020: 3057-3062.
[9] NORAMBUENA M, GALVEZ D. Model free artificial neural network for an induction machine[C]// 2023 IEEE Conference on Power Electronics and Renewable Energy. Luxor, Egypt: IEEE, 2023: 1-6.
[10] LIN C K, LIU T H, YU J T, et al. Model-free predictive current control for interior permanent-magnet synchronous motor drives based on current difference detection technique[J]. IEEE Transactions on Industrial Electronics, 2014, 61(2): 667-681.
[11] LIN C K, YU J T, LAI Y S, et al. Improved model-free predictive current control for synchronous reluctance motor drives[J]. IEEE Transactions on Industrial Electronics, 2016, 63(6): 3942-3953.
[12] MA C W, LI H Y, YAO X L, et al. An improved model-free predictive current control with advanced current gradient updating mechanism[J]. IEEE Transactions on Industrial Electronics, 2021, 68(12): 11968-11979.
[13] FENG Z Z, CAO W P, RUI T, et al. A model-free predictive control method for grid-tied inverter based on discrete space vector[C]// 2021 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics. Jinan, China: IEEE, 2021: 634-639.
[14] ZHANG Y C, ZHANG S G, JIANG T, et al. A modified model-free predictive current control method based on an extended finite control set for DFIGs applied to a nonideal grid[J]. IEEE Transactions on Industry Applications, 2022, 58(2): 2527-2536.
[15] LIN C K, YU J T, AGUSTIN C A, et al. A two-staged optimization approach to modulated model-free predictive current control for RL-connected three-phase two-level four-leg inverters[J]. IEEE Access, 2021, 9: 147537-147548.
[16] REDDY V R, AGUSTIN C A, LIN C K, et al. Modulated dual-voltage-vector model-free predictive current controller for synchronous reluctance motor drives with online duty cycle calculation[J]. IEEE Access, 2022, 10: 97856-97867.
[17] LE V T, LEE H H. An enhanced model-free predictive control to eliminate stagnant current variation update for PWM rectifiers[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2021, 9(6): 6804-6816.
[18] YU F, ZHOU C H, LIU X, et al. Model-free predictive current control for three-level inverter-fed IPMSM with an improved current difference updating technique[J]. IEEE Transactions on Energy Conversion, 2021, 36(4): 3334-3343.
[19] LIN C K, AGUSTIN C A, YU J T, et al. A modulated model-free predictive current control for four-switch three-phase inverter-fed SynRM drive systems[J]. IEEE Access, 2021, 9: 162984-162995.
[20] 王朋帅. 基于可视化分析的永磁同步电机多矢量模型预测控制研究[D]. 郑州: 郑州轻工业大学, 2023.
  WANG Pengshuai. Research on multi-vector model predictive control of permanent magnet synchronous motor based on visualization analysis[D]. Zhengzhou: Zhengzhou University of Light Industry, 2023.
[21] 金胜赫, 张化光, 玄成哲, 等. 电网电压参数跳变时三相并网逆变器的同步方法[J]. 上海交通大学学报, 2017, 51(5): 585-591.
  JIN Shenghe, ZHANG Huaguang, XUAN Chengzhe, et al. Grid synchronization method of three-phase grid-connected inverter under grid voltage parameters jump conditions[J]. Journal of Shanghai Jiao Tong University, 2017, 51(5): 585-591.
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