A model-free direct predictive grid-current control strategy for grid-connected converter with an inductance-capacitance-inductance filter

• Autorzy: Guo Leilei , Zheng Mingzhe , Yu Changzhou , Xu Haizhen , Li Yanyan

Identyfikatory

DOI

10.24425/aee.2023.143688

• Języki publikacji: EN

Abstrakty

EN

The disadvantages of the conventional model predictive current control method for the grid-connected converter (GCC) with an inductance-capacitance-inductance (LCL) filter are a large amount of calculation and poor parameter robustness. Once parameters of the model are mismatched, the control accuracy of model predictive control (MPC) will be reduced, which will seriously affect the power quality of the GCC. The article intuitively analyzes the sensitivity of parameter mismatch on the current predictive control of the conventional LCL-filtered GCC. In order to solve these issues, a model-free predictive current control (MFPCC) method for the LCL-filtered GCC is proposed in this paper. The contribution of this work is that a novel current predictive robust controller for the LCL-filtered GCC is designed based on the principle of the ultra-local model of a single input single output system. The proposed control method does not require using any model parameters in the controller, which can effectively suppress the disturbances of the uncertain parameter variations. Compared with conventional MPC, the proposed MFPCC has smaller current total harmonic distortion (THD). When the filter parameters are mismatched, the control error of the proposed method is smaller. Finally, a comparative experimental study is carried out on the platform of Typhoon and PE-Expert4 to verify the superiority and effectiveness of the proposed MFPCC method for the LCL-filtered GCC.

Słowa kluczowe

EN

grid-connected converter; GCC; model-free predictive current control; MFPCC; parameter mismatch; robustness

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2023
• Tom: Vol. 72, nr 1
• Strony: 23--42
• Opis fizyczny: Bibliogr. 27 poz., rys., tab., wz.

Twórcy

autor

Guo Leilei

• Zhengzhou University of Light Industry, College of Electrical and Information Engineering China

autor

Zheng Mingzhe

• Zhengzhou University of Light Industry, College of Electrical and Information Engineering China

• https://orcid.org/0000-0003-1812-8013

autor

Yu Changzhou

• Hefei University, School of Advanced Manufacturing Engineering China

autor

Xu Haizhen

• Hefei University, School of Advanced Manufacturing Engineering China

autor

Li Yanyan

• Zhengzhou University of Light Industry, College of Electrical and Information Engineering China

Bibliografia

• [1] Aguero J. R., Takayesu E., Novosel D., Masiello R., Modernizing the grid: challenges and opportunities for a sustainable future, IEEE Power and Energy Magazine, vol. 15, no. 3, pp. 74–83 (2017), DOI: 10.1109/MPE.2017.2660819.
• [2] Wu W., Huang M., Blaabjerg F., Efficiency comparison between the LLCL and LCL-filters based single-phase grid-tied inverters, Archives of Electrical Engineering, vol. 63, no. 1, pp. 63–79 (2014), DOI: 10.2478/aee-2014-0005.
• [3] Reznik A., Simões M. G., Al-Durra A., Muyeen S. M., LCL filter design and performance analysis for grid-interconnected systems, IEEE Transactions on Industry Applications, vol. 50, no. 2, pp. 1225–1232 (2014), DOI: 10.1109/TIA.2013.2274612.
• [4] Falkowski P., Sikorski A., Finite control set model predictive control for grid-connected AC–DC converters with LCL filter, IEEE Transactions on Industrial Electronics, vol. 65, no. 4, pp. 2844–2852 (2018), DOI: 10.1109/TIE.2017.2750627.
• [5] Panten N., Hoffmann N., Fuchs F. W., Finite control set model predictive current control for grid-connected voltage-source converters with LCL filters: a study based on different state feedbacks, IEEE Transactions on Power Electronics, vol. 31, no. 7, pp. 5189–5200 (2016), DOI: 10.1109/TPEL.2015.2478862.
• [6] Xu J., Xie S., Tang T., Active damping-based control for grid-connected LCL-filtered inverter with injected grid-current feedback only, IEEE Transactions on Industrial Electronics, vol. 61, no. 9, pp. 4746–4758 (2014), DOI: 10.1109/TIE.2013.2290771.
• [7] Liu H., Xu D., Li L., Gao Q., A robust damping method for voltage source converter with LCL filter under weak grid, CSEE Journal of Power and Energy Systems, pp. 1–9 (2020), DOI: 10.17775/CS EEJPES.2019.02400.
• [8] Scoltock J., Geyer T., Madawala U. K., A model predictive direct current control strategy with predictive references for MV grid-connected converters with LCL-filters, IEEE Transactions on Power Electronics, vol. 30, no. 10, pp. 5926–5937 (2015), DOI: 10.1109/TPEL.2014.2375919.
• [9] Wang X., Wang Z., Xu Z., Wang W., Wang B., Zou Z., Deadbeat Predictive Current Control-Based Fault-Tolerant Scheme for Dual Three-Phase PMSM Drives, IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 9, no. 2, pp. 1591–1604 (2021), DOI: 10.1109/JESTPE.2020.2983691.
• [10] Kalla U. K., Kaushik H., Singh B., Kumar S., Adaptive control of voltage source converter based scheme for power quality improved grid-interactive solar PV–battery system, IEEE Transactions on Industry Applications, vol. 56, no. 1, pp. 787–799 (2020), DOI: 10.1109/TIA.2019.2947397.
• [11] Hu J., Shang L., He Y., Zhu Z.Q., Direct active and reactive power regulation of grid-connected DC/AC converters using sliding mode control approach, IEEE Transactions on Power Electronics, vol. 26, no. 1, pp. 210–222 (2011), DOI: 10.1109/TPEL.2010.2057518.
• [12] Tang M., Yang S., Zhang K. et al., Model predictive direct power control of energy storage quasi-Z-source grid-connected inverter, Archives of Electrical Engineering, vol. 71, no. 1, pp. 21–35 (2022), DOI: 10.24425/aee.2022.140195.
• [13] Karamanakos P., Liegmann E., Geyer T., Kennel R., Model predictive control of power electronic systems: methods, results, and challenges, IEEE Open Journal of Industry Applications, vol. 1, pp. 95–114 (2020), DOI: 10.1109/OJIA.2020.3020184.
• [14] Guo L., Jin N., Li Y., Luo K., A model predictive control method for grid-connected power converters without AC voltage sensors, IEEE Transactions on Industrial Electronics, vol. 68, no. 2, pp. 1299–1310 (2021), DOI: 10.1109/TIE.2020.2970638.
• [15] Geldenhuys J. M. C., du Toit Mouton H., Rix A., Geyer T., Model predictive current control of a grid connected converter with LCL-filter, 2016 IEEE 17th Workshop on Control and Modeling for Power Electronics (COMPEL), Trondheim, Norway, pp. 1–6 (2016), DOI: 10.1109/COMPEL.2016.755 6734.
• [16] Young H.A., Perez M.A., Rodriguez J., Analysis of finite-control-set model predictive current control with model parameter mismatch in a three-phase inverter, IEEE Transactions on Industrial Electronics, vol. 63, no. 5, pp. 3100–3107 (2016), DOI: 10.1109/TIE.2016.2515072.
• [17] Guo L., Xu Z., Jin N., Chen Y., Li Y., Dou Z., An inductance on-line identification method for model predictive control of V2G inverter with enhanced robustness to grid frequency deviation, IEEE Transactions on Transportation Electrification, DOI: 10.1109/TTE.2021.3128362.
• [18] Guo L., Xu Z., Li Y., Chen Y., Jin N., Lu F., An inductance online identification-based model predictive control method for grid-connected inverters with an improved phase-locked loop, IEEE Transactions on Transportation Electrification, vol. 8, iss. 2, pp. 2695-2709 (2022), DOI: 10.1109/TTE.2021.3135326.
• [19] Shen K., Zhang J., Modeling error compensation in FCS-MPC of a three-phase inverter, 2012 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), Bengaluru, India, pp. 1–6 (2012), DOI: 10.1109/PEDES.2012.6484341.
• [20] Mendez R., Sbarbaro D., Espinoza J., High dynamic and static performance FCS-MPC strategy for static power converters, 2016 IEEE Energy Conversion Congress and Exposition (ECCE), Milwaukee WI, USA, pp. 1–7 (2016), DOI: 10.1109/ECCE.2016.7855146.
• [21] Yang Y., Tan S., Hui S. Y. R., Adaptive reference model predictive control with improved performance for voltage-source inverters, IEEE Transactions on Control Systems Technology, vol. 26, no. 2, pp. 724–731 (2018), DOI: 10.1109/TCST.2017.2670529.
• [22] Jabbour N., Mademlis C., Online parameters estimation and autotuning of a discrete-time model predictive speed controller for induction motor drives, IEEE Transactions on Power Electronics, vol. 34, no. 2, pp. 1548–1559 (2019), DOI: 10.1109/TPEL.2018.2831459.
• [23] Lin C.K., Liu T. H., Yu J.T., Fu L. C., Hsiao C.F., Model-free predictive current control for interior permanent-magnet synchronous motor drives based on current difference detection technique, IEEE Transactions on Industrial Electronics, vol. 61, no. 2, pp. 667–681 (2014), DOI: 10.1109/TIE.2013.2253065.
• [24] Zhou Y., Li H., Zhang H., Model-free deadbeat predictive current control of a surface-mounted permanent magnet synchronous motor drive system, Journal of Power Electronics, vol. 18, no. 1, pp. 103–115 (2018), DOI: 10.6113/JPE.2018.18.1.103.
• [25] Yuan X., Zuo Y., Fan Y., Lee C. H. T., Model-free predictive current control of SPMSM drives using extended state observer, IEEE Transactions on Industrial Electronics, vol. 69, no. 7, pp. 6540–6550 (2022), DOI: 10.1109/TIE.2021.3095816.
• [26] Zhang Y., Jiang T., Jiao J., Model-free predictive current control of a DFIG using an ultra-local model for grid synchronization and power regulation, IEEE Transactions on Energy Conversion, vol. 35, no. 4, pp. 2269–2280 (2020), DOI: 10.1109/TEC.2020.3004567.
• [27] Xu J., Xie S., LCL-resonance damping strategies for grid-connected inverters with LCL filters: a comprehensive review, Journal of Modern Power Systems and Clean Energy, vol. 6, no. 2, pp. 292–305 (2018), DOI: 10.1007/s40565-017-0319-7.

Uwagi

This work was supported in part by the National Natural Science Foundation of China (51907046), in part by the Scientific and Technological Project in Henan Province (212102210021) in part by the Youth Talent Support Project of Henan Province (2019HYTP021).

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).