摘要
为了探究短路容量比接近1.0的极弱电网下新能源跟网逆变器低频振荡的原因,该文建立描述逆变器动态行为的低频简化小信号模型,并以此深入分析了诱发低频振荡的主导因素。研究发现,极弱电网下逆变器交流侧电压控制与有功控制紧密耦合,这使得它们之间互相干涉,从而引起低频振荡。其中交流电压–无功闭环控制的快速性很大程度上决定了低频振荡是否发生。对此,该文提出一种暂态无功过补稳定性提升方法,通过前馈加快逆变器的无功响应,从而有效抑制了低频振荡,显著提升极弱电网下逆变器的稳定性。与已有稳定性提升方法相比,该方法具有参数整定简单、运算量小、不削弱逆变器功率调整动态性能的3个优点。最后,该文通过仿真和实验验证解析分析结论的准确性,论证暂态无功过补方法的有效性。
To investigate the low-frequency oscillation of renewable-energy grid-following inverters under very weak grid where the short circuit ratio is nearly 1.0,a simplified small-signal model that describes low-frequency dynamic of the inverter is established in this paper.Based on the model,the main factor that causes the oscillation is analyzed.Researching results suggest that under very weak grid,the AC voltage control(AVC)and active power control are tightly coupled to each other,which causes serious interference between them and results in the low-frequency oscillation.Whether the oscillation happens or not mainly depends on dynamic of AVC.This paper proposes a stabilizing method based on transient reactive-power over-compensation,which expedites AVC through feeding forward.The method effectively suppresses the low-frequency oscillation under very weak grid,which improves the stability apparently.Compared with previous stabilizing methods,the proposed one has three advantages,i.e.,easy parameter tuning,low calculating power requirement and never weakening the power control dynamic performance.At last,the analyzing results and stabilizing method are verified by both simulation and experiment.
作者
李雨果
易皓
姜鑫
卓放
卢大鹏
周洪伟
LI Yuguo;YI Hao;JIANG Xin;ZHUO Fang;LU Dapeng;ZHOU Hongwei(State Key Laboratory of Electrical Insulation and Power Equipment(Xi’an Jiaotong University),Xi’an 710049,Shaanxi Province,China;TBEA Xi’an Electric Technology Co.,Ltd.,Xi’an 710016,Shaanxi Province,China)
出处
《中国电机工程学报》
EI
CSCD
北大核心
2023年第2期482-495,共14页
Proceedings of the CSEE
基金
国家自然科学基金项目(51977172)。
关键词
并网逆变器
极弱电网
低频振荡
简化小信号模型
解析分析
稳定性提升
grid-connected inverter
very weak grid
low-frequency resonance
simplified small-signal model
analytical investigation
stability improving
