Model predictive control for a grid-connected inverter based on inductance identification resistant to frequency deviation

被引：0

作者：

Wu Z. ^{[1
]}

Liu Z. ^{[1
]}

Guo L. ^{[1
]}

Li Y. ^{[1
]}

Jin N. ^{[1
]}

Xie W. ^{[2
]}

机构：

[1] College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou

[2] Henan Jiuyu EPRI Electric Power Technology Co., Ltd., Zhengzhou

来源：

Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2023年 / 51卷 / 22期

基金：

中国国家自然科学基金;

关键词：

frequency robustness; grid-connected inverter; inductance identification; model predictive control; sliding mode observer;

D O I：

10.19783/j.cnki.pspc.230679

中图分类号：

学科分类号：

摘要：

The inductance parameter is crucial in realizing high precision model predictive control for a grid-connected inverter. The traditional inductance identification method is easily affected by grid frequency deviation and cannot be used when the active power is zero. To improve the frequency robustness of the inductance parameter in model predictive control, an online identification method based on MRAS is proposed. First, a second-order sliding mode observer is designed to observe the grid voltage. Second, without compensating for the observed voltage amplitude and phase deviation caused by the low-pass filter, the actual grid voltage also generates the same amplitude and phase deviation. Then, using the relationship between the voltage and inductance errors, an inductance identification model is established to overcome the impact of grid frequency deviation on the results, and the identification is also available when the active power is zero. Finally, by incorporating the identified parameter into the model predictive control algorithm, the control of the inverter can be more accurate. The effectiveness and accuracy of the proposed method is verified by experiment. © 2023 Power System Protection and Control Press. All rights reserved.

引用

页码：99 / 107

页数：8

共 28 条

[1]

LIU Renzhi, CHEN Zhuo, TANG Wenbo, Et al., Control strategy of an LCL type grid-connected inverter with the influence of a phase-locked loop under a weak power grid, Power System Protection and Control, 50, 5, pp. 178-187, (2022)

[2]

SINGH S, SAINI S, GUPTA S K, Et al., Solar-PV inverter for the overall stability of power systems with intelligent MPPT control of DC-link capacitor voltage, Protection and Control of Modern Power Systems, 8, 1, pp. 126-147, (2023)

[3]

YARIKKAYAY S, VARDAR K., Neural network based predictive current controllers for three phase inverter, IEEE Access, 11, pp. 27155-27167, (2023)

[4]

TANG Shengxue, SONG Shengyuan, YAO Fang, A transformerless current source photovoltaic grid-connected inverter for leakagecurrent suppression, Electrical Measurement & Instrumentation, 58, 1, pp. 54-61, (2021)

[5]

ZHANG Hongbo, CAI Xiaofeng, Output harmonic suppression of a grid-connected inverter with secondary ripple in DC voltage, Power System Protection and Control, 50, 15, pp. 119-128, (2022)

[6]

WU Bin, YANG Xuhong, Research on grid-connected three-phase inverter based on improved genetic PI and repetitive control, Journal of Electric Power Science and Technology, 36, 6, pp. 151-156, (2021)

[7]

CHEN Wei, ZHANG Yan, TU Yiming, Et al., Design of critical passive damping parameters for LCL-Type grid-connected inverter, Electric Power Construction, 43, 1, pp. 70-77, (2022)

[8]

ZHANG Y C, LIU J, YANG H T, Et al., Direct power control of pulse width modulated rectifiers without DC voltage oscillations under unbalanced grid conditions, IEEE Transactions on Industrial Electronics, 65, 10, pp. 7900-7910, (2018)

[9]

RAHOUI A, BECHOUCHE A, SEDDIKI H, Et al., Grid voltages estimation for three-phase PWM rectifiers control without AC voltage sensors, IEEE Transactions on Power Electronics, 33, 1, pp. 859-875, (2018)

[10]

RODRIGUEZ J, PONTT J, SILVA C, Et al., Predictive current control of a voltage source inverter, IEEE Transactions on Industrial Electronics, 54, 1, pp. 495-503, (2007)

← 1 2 3 →