Nonlinear Adaptive Disturbance Rejection Control Strategy Based on VSG for Photovoltaic-Storage Grid-Connected Inverter

被引:4
作者
Kong, Fannie [1 ]
Zhang, Haochen [1 ]
Wu, Zhuolin [1 ]
Guo, Zhuangzhi [2 ]
机构
[1] Guangxi Univ, Sch Elect Engn, Nanning 530005, Peoples R China
[2] Henan Univ Engn, Sch Elect Informat Engn, Zhengzhou 450051, Peoples R China
基金
中国国家自然科学基金;
关键词
INDEX TERMS Adaptive; exact feedback linearization; grid-connected inverter; multi-input multi-output; nonlinear adaptive disturbance rejection control; virtual synchronous generator; voltage and current dual closed-loop strategy; DOUBLE CLOSED-LOOP; SYSTEM;
D O I
10.1109/ACCESS.2023.3341703
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, a nonlinear adaptive disturbance rejection control (NADRC) strategy is designed to overcome the limitations of the traditional virtual synchronous generator (VSG) control method in photovoltaic (PV) grid-connected energy storage systems. This strategy utilizes exact feedback linearization and linear optimal control theory to establish a nonlinear adaptive disturbance rejection control law based on the virtual synchronous generator. It achieves zero static error control and noise adaptive stabilization of the AC link in a multiple-input multiple-output system. Compared with the simulation results of the grid-connected inverter voltage and current double closed-loop (VACDCL) strategy, the nonlinear adaptive disturbance rejection control effectively mitigates the fluctuations in load current caused by the photovoltaic energy storage module. It ensures power tracking under variable power conditions and outperforms traditional PI dual-loop control in terms of dynamic and static regulation performance as well as grid-connected current quality. Furthermore, this strategy's anti-disturbance adaptive link can quickly respond to system disturbances like frequency drift, voltage oscillations, and load current variations, thereby improving system performance.
引用
收藏
页码:139534 / 139545
页数:12
相关论文
共 33 条
[21]  
Wu H., 2015, Proc. CSEE, V35, P6508
[22]   Deep reinforcement learning based parameter self-tuning control strategy for VSG [J].
Xiong, Kang ;
Hu, Weihao ;
Zhang, Guozhou ;
Zhang, Zhenyuan ;
Chen, Zhe .
ENERGY REPORTS, 2022, 8 :219-226
[23]   Impedance Modeling and Stability Analysis of VSG Controlled Grid-Connected Converters with Cascaded Inner Control Loop [J].
Xu, Yunyang ;
Nian, Heng ;
Wang, Yangming ;
Sun, Dan .
ENERGIES, 2020, 13 (19)
[24]  
Yan Binbin, 2018, Electric Power Automation Equipment, V38, P140, DOI 10.16081/j.issn.1006-6047.2018.10.022
[25]   A United Control Strategy of Photovoltaic-Battery Energy Storage System Based on Voltage-Frequency Controlled VSG [J].
Yan, Xiangwu ;
Wang, Chenguang ;
Wang, Ziheng ;
Ma, Hongbin ;
Liang, Baixue ;
Wei, Xiaoxue .
ELECTRONICS, 2021, 10 (17)
[26]  
Yang P., 2023, Grid Clean Energy, V39, P113
[27]   A visually driven nonlinear droop control for inverter-dominated islanded microgrids [J].
Zandi, Farshad ;
Fani, Bahador ;
Golsorkhi, Akbar .
ELECTRICAL ENGINEERING, 2020, 102 (03) :1207-1222
[28]  
Zeng Z., 2020, Control Techniques for Flexible Grid-Connect Inverter, P55
[29]   Voltage and frequency stabilization control strategy of virtual synchronous generator based on small signal model [J].
Zhang, Xin ;
Gong, Lijiao ;
Zhao, Xinyu ;
Li, Rongrong ;
Yang, Li ;
Wang, Bin .
ENERGY REPORTS, 2023, 9 :583-590
[30]   Grid-connected photovoltaic battery systems: A comprehensive review and perspectives [J].
Zhang, Yijie ;
Ma, Tao ;
Yang, Hongxing .
APPLIED ENERGY, 2022, 328