基于RBF-LADRC的虚拟同步发电机控制策略

杨旭红, 杨一矜, 潘宇, 顾伟伟, 杨慧, 贾巍

太阳能学报 ›› 2024, Vol. 45 ›› Issue (3) : 319-325.

PDF(1779 KB)
欢迎访问《太阳能学报》官方网站,今天是
PDF(1779 KB)
太阳能学报 ›› 2024, Vol. 45 ›› Issue (3) : 319-325. DOI: 10.19912/j.0254-0096.tynxb.2022-1734

基于RBF-LADRC的虚拟同步发电机控制策略

  • 杨旭红1, 杨一矜1, 潘宇2, 顾伟伟2, 杨慧2, 贾巍3
作者信息 +

RBFNN BASED LINEAR ACTIVE DISTURBANCE REJECTION CONTROL FOR VIRTUAL SYNCHRONOUS GENERATOR CONTROL STRATEGY

  • Yang Xuhong1, Yang Yijin1, Pan Yu2, Gu Weiwei2, Yang Hui2, Jia Wei3
Author information +
文章历史 +

摘要

随着大规模分布式发电技术的出现,为支持微电网的稳定运行,提出虚拟同步发电机(VSG)技术。由于VSG常用的电压电流双闭环控制存在动态响应时间久、抗扰动能力弱的缺点,考虑LADRC对扰动具有更优异的动态响应速度,该文提出一种用于VSG电压外环控制的线性自抗扰控制方案,并采用RBF对LADRC中的关键参数进行在线整定,以实现控制器的实时优化。在Matlab/Simulink平台下搭建仿真模型,并对所提出的改进策略与传统控制策略进行仿真对照,结果显示该策略可有效提高并网环境下虚拟同步发电机功率和频率稳定性。

Abstract

With the emergence of large-scale distributed generation technology, a solution such as virtual synchronous generator (VSG) technology is proposed to support the stable operation of microgrids. Since the voltage-current dual closed-loop control commonly used in VSG has the shortcomings of long dynamic response time and weak perturbation resistance, considering that LADRC has a superior dynamic response speed to perturbations, this paper proposes a linear self-immunity control scheme for the voltage outer-loop control of VSG, and adopts the RBF for the on-line tuning of the key parameters in the LADRC in order to realize the optimization of the controller in real time. The simulation model is built under the MATLAB/Simulink platform and the proposed improved strategy is simulated against the traditional control strategy, and the results show that the strategy can effectively improve the power and frequency stability of the virtual synchronous generator under the grid-connected environment.

关键词

分布式发电 / RBF神经网络 / 线性自抗扰控制 / 虚拟同步发电机

Key words

distributed power generation / radial basis function networks / linear active disturbance rejection control / virtual synchronization generator

引用本文

导出引用
杨旭红, 杨一矜, 潘宇, 顾伟伟, 杨慧, 贾巍. 基于RBF-LADRC的虚拟同步发电机控制策略[J]. 太阳能学报. 2024, 45(3): 319-325 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1734
Yang Xuhong, Yang Yijin, Pan Yu, Gu Weiwei, Yang Hui, Jia Wei. RBFNN BASED LINEAR ACTIVE DISTURBANCE REJECTION CONTROL FOR VIRTUAL SYNCHRONOUS GENERATOR CONTROL STRATEGY[J]. Acta Energiae Solaris Sinica. 2024, 45(3): 319-325 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1734
中图分类号: TM615   

参考文献

[1] GOLSORKHI M S, SHAFIEE Q, LU D D C, et al. Distributed control of low-voltage resistive AC microgrids[J]. IEEE transactions on energy conversion, 2019, 34(2): 573-584.
[2] 李军, 胡传意, 颜辉, 等. 基于改进型虚拟同步发电机的功率控制[J]. 电测与仪表,2019, 56(3): 133-138.
LI J, HU C Y, YAN H, et al.Power control based on improved virtual synchronous generator[J]. Electrical measurement & instrumentation, 2019, 56(3):133-138.
[3] 郑天文, 陈来军, 陈天一, 等. 虚拟同步发电机技术及展望[J]. 电力系统自动化, 2015, 39(21): 165-175.
ZHENG T W, CHEN L J, CHEN T Y, et al.Review and prospect of virtual synchronous generator technologies[J]. Automation of electric power systems, 2015, 39(21): 165-175.
[4] ROCABERT J, LUNA A, BLAABJERG F, et al.Control of power converters in AC microgrids[J]. IEEE transactions on power electronics, 2012, 27, 4734-4749.
[5] WU H, RUAN X B, YANG D S, et al.Small-signal modeling and parameters design for virtual synchronous generators[J]. IEEE transactions on industrial electronics, 2016, 63(7): 4292-4303.
[6] LI X Q, FANG J, TANG Y, et al.Capacitor-voltage feedforward with full delay compensation to improve weak grids adaptability of LCL-filtered grid-connected converters for distributed generation systems[J]. IEEE transactions on power electronics, 2018, 33(1): 749-764.
[7] ARCO S, SUUL J A.Virtual synchronous machines-classification of implementations and analysis of equivalence to droop controllers for microgrids[C]//2013 IEEE Grenoble Conference. Grenoble, France, 2013: 1-7.
[8] 张芳, 陈晓凯. VSC-HVDC换流站二阶线性自抗扰控制器参数整定研究[J]. 电网技术, 2018, 42(11): 3744-3755.
ZHANG F, CHEN X K.Research on parameter tuning of second-order LADRC for VSC-HVDC converter station[J]. Power system technology, 2018, 42(11): 3744-3755.
[9] LI Z W, ZANG C Z, ZENG P, et al.Control of a grid-forming inverter based on sliding-mode and mixed {H2}/{H} control[J]. IEEE transactions on industrial electronics, 2017, 64(5): 3862-3872.
[10] MENG X, LIU J J, LIU Z.A generalized droop control for grid-supporting inverter based on comparison between traditional droop control and virtual synchronous generator control[J]. IEEE transactions on power electronics, 2019, 34(6): 5416-5438.
[11] TRIVEDI A, SINGH M.Repetitive controller for VSIs in droop-based AC-microgrid[J]. IEEE transactions on power electronics, 2017, 32(8): 6595-6604.
[12] ZHAO Q S, YE Y Q.A PIMR-type repetitive control for a grid-tied inverter: structure analysis and design[J]. IEEE transactions on power electronics, 2018, 33(3): 2730-2739.
[13] YARAMASU V, RIVERA M, NARIMANI M, et al.Model predictive approach for a simple and effective load voltage control of four-leg inverter with an output $LC$ filter[J]. IEEE transactions on industrial electronics, 2014, 61(10): 5259-5270.
[14] LEI Q, PENG F Z, YANG S T.Multiloop control method for high-performance microgrid inverter through load voltage and current decoupling with only output voltage feedback[J]. IEEE transactions on power electronics, 2011, 26(3): 953-960.
[15] SALEEM M, CHOI K Y, KIM R Y.Resonance damping for an LCL filter type grid-connected inverter with active disturbance rejection control under grid impedance uncertainty[J]. International journal of electrical power & energy systems, 2019, 109: 444-454.
[16] 赵顺利. RBF神经网络优化自抗扰在船舶航迹控制中的应用[D]. 大连: 大连海事大学, 2020.
ZHAO S L.RBF neural network to optimize ADRC in ship track application in control[D]. Dalian: Dalian Maritime University, 2020.
[17] 韩顺杰, 胡雪妍, 刘阳阳. 基于RBF神经网络的自抗扰控制器在光电稳定平台上的应用[J]. 长春工业大学学报, 2022, 43(S1): 413-418.
HAN S J, HU X Y, LIU Y Y.Application of ADRC based on RBFNN in optoelectronic stabilized platform[J]. Journal of Changchun University of Technology, 2022, 43(S1): 413-418.
[18] 杨立本, 汤裕民, 李泰国, 等. 基于RBF神经网络滑模自抗扰的四旋翼飞行器控制[J]. 云南大学学报(自然科学版), 2022, 44(5): 931-939.
YANG L B, TANG Y M, LI T G, et al.Control of quadrotor aircraft based on RBF neural network sliding mode active disturbance rejection[J]. Journal of Yunnan University (natural sciences edition), 2022, 44(5): 931-939.
[19] 颜笑. ADRC参数优化及其应用仿真研究[D]. 北京:华北电力大学, 2020.
YAN X.Research on ADRC parameter optimization and its application simulation[D]. Beijing: North China Electric Power University, 2020.

基金

国家自然科学基金(51777120); 上海市2021年度“科技创新行动计划”科技支撑碳达峰碳中和专项(第一批)(21DZ1207502)

PDF(1779 KB)

Accesses

Citation

Detail

段落导航
相关文章

/