虚拟同步直驱风电场经MMC-HVDC并网的低频振荡特性分析

虚拟同步直驱风电场经功率同步环与模块化多电平换流器柔性直流(MMC-HVDC)输电互联,将存在低频振荡风险。考虑MMC-HVDC和直驱风机网侧换流器以及转子侧换流器内部的动态过程,首先建立虚拟同步直驱风电场经MMC-HVDC并网的小信号模型,并通过精细化电磁暂态仿真验证其准确性。随后,利用根轨迹方法,分析风电功率波动和交流系统强度变化对互联系统稳定性的影响,设计功率变化时虚拟同步直驱风电场的参数整定方法。结果表明,由于功率外环和MMC-HVDC送端整流站电压环作用,在风电场输出功率增大和交流系统强度降低的过程中,互联系统存在低频振荡现象。通过合理调整锁相环、虚拟同步机(VSG)有功环和MMC-HVDC送端整流站电压环的控制器参数、改变VSG阻尼项形式,可以抑制振荡并实现稳定运行。     

GaN压电半导体杆的非线性动态响应研究

利用有限元分析方法,研究了p型GaN压电半导体杆在简谐力作用下的拉伸振动问题,得到了位移、电势和空穴浓度非线性动态响应的数值解,并分析了简谐力对p型GaN压电半导体杆力电耦合性能的调控作用。研究结果表明,简谐力显著地影响压电半导体杆内力电场的分布情况:由于电流密度中的电非线性项,电场和空穴浓度的分布失去对称性或反对称性;力电场在简谐力驱动下表现为周期性变化,但空穴浓度的动态响应表现为明显的非对称波动。     

基于超级电容的新能源惯量-阻尼-电抗综合模拟控制方案

光伏、风电等新能源发电大规模接入电网逐步替代传统同步机,导致电网惯量和阻尼水平不断下降,威胁电网安全稳定运行。针对上述问题,提出了一种基于超级电容的新能源惯量阻尼电抗综合模拟控制(composite inertia-damping-impedance emulation control, IDIE)方案。通过联立同步机转子运动方程和超级电容功率动态方程,并结合同步机功率传输方程,设计了通过控制超级电容有功功率以综合模拟同步机旋转质量、阻尼绕组和绕组电抗三者物理特性的核心算法。并利用小信号稳定性分析对方案关键参数进行优化。最后,基于控制器硬件在环试验在各种暂态工况下对IDIE方案进行了评估。结果表明,IDIE方案在灵活模拟同步机惯量的同时,可通过配置优化模拟阻尼和模拟电抗,保障频率稳定性,支撑电网动态运行。     

Piezoelectric Nanostructured Surface for Ultrasound-Driven Immunoregulation to Rescue Titanium Implant Infection

Treating bacterial biofilm infections on implanted materials remains challenging in clinical practice, as bacteria can be resistant by weakening the host defense from immune cells like macrophages. Herein, a metal-piezoelectric hetero-nanostructure with mechanical energy-driven antimicrobial property is in situ constructed on the Ti implant. Under ultrasonic irradiation, the formed piezotronic Ti (piezoTi) can promote the generation of reactive oxygen species (ROS) by facilitating local charge transfer at the surface, thus leading to piezodynamic killing of Staphylococcus aureus (S. aureus) while downregulating biofilm-forming genes. In addition, the stimulated macrophages on piezoTi display potent phagocytosis and anti-bacterial activity through the activation of PI3K-AKT and MAPK pathway. As a demonstration, one-time ultrasound irradiation of piezoTi pillar implanted in an osteomyelitis model efficiently eliminates the S. aureus biofilm infection and rescues the implant with enhanced osteointegration. By the synergistic effect of ultrasound-driven piezodynamic therapy and immuno-regulation, the proposed piezoelectric nanostructured surface can endow Ti implants with highly efficient antibacterial performance in an antibiotic-free, noninvasive, and on-demand manner.     

Ultra-Damping Composites Enhanced by Yolk–Shell Piezoelectric Damping Mechanism

High-performance damping materials are significant toward reducing vibration and maintaining stability for industrial applications. Herein, a yolk–shell piezoelectric damping mechanism is reported, which can enhance mechanical energy dissipation and improve damping capability. With the addition of yolk–shell particles and carbon nanotube (CNT) conductive network, damping properties of various resin matrices are enhanced with the energy dissipation path of mechanical to electrical to heat energy. Particularly, the peak loss factor of epoxy composites reaches 1.91 and tan δ area increases by 25.72% at 20 °C. The results prove the general applicability of yolk–shell piezoelectric damping mechanism. Besides, the novel damping materials also exhibit excellent flexibility, stretchability, and resilience, offering a promising application toward damping coating, indicating broad scope of application in transportation and sophisticated electronics, etc.     

LCL型并网逆变器临界无源阻尼参数设计

LCL滤波器因其良好的滤波性能被广泛应用于并网逆变器系统中。然而,LCL滤波器的固有谐振特性以及数字控制延时会严重危及系统稳定性。为提高系统鲁棒性,工程上通常采用无源阻尼方法以抑制滤波器谐振。由于滤波器谐振问题受多种因素影响,阻尼电阻的选取标准通常是模糊的。为准确、高效地设计阻尼电阻,文章结合阻尼电阻与滤波电容串联和与滤波电容并联两种典型无源阻尼方法,推导分析了“临界阻尼”指标。当系统阻尼大于临界阻尼时,LCL滤波器幅频特性曲线上的谐振峰被完全抑制,同时以最少的无源阻尼损耗为代价,充分保证了基于LCL滤波器的并网逆变器系统稳定性。此外,文章在PLECS软件中进行三相并网逆变器系统仿真,仿真结果验证了理论分析的有效性和正确性。     

含光伏电站的电力系统低频振荡广域阻尼协同控制方法

大规模新能源接入电网增加了弱阻尼振荡模式被激发的风险。首先,考虑同步发电机和光伏的动态特性,建立了详细的小信号模型,分析了光伏对低频振荡模式的影响,提出了含光伏电站的电力系统低频振荡广域阻尼控制架构,实现光伏-同步机协调阻尼控制;然后,以特征值分析结果为依据,提出了广域阻尼控制参数的优化模型,并对控制参数进行优化整定;最后,在PSCAD/EMTDC平台中搭建了含光伏电站的四机两区域系统电磁暂态仿真模型,验证了所提广域阻尼控制方法的有效性。     

面向低频振荡分析的直驱风电机组阻尼转矩建模

针对直驱风电机组直流电压环和锁相环失稳问题,基于直驱风电机组电流源型线性化模型,分析了电网强度、直流电容输入功率以及控制参数对直驱风电机组稳定性的影响;建立了适用于直流电压环和锁相环稳定性分析的电流源型阻尼转矩模型,通过阻尼转矩法揭示了直驱风电机组失稳机理;进一步地将阻尼转矩法拓展至多机并联系统。研究结果表明：电网强度的减小、直流电容输入功率的增加、控制参数(直流电压环比例参数、锁相环比例参数)的减小会降低直驱风电机组低频振荡模式(直流电压环模式、锁相环模式)的阻尼系数,当阻尼系数小于0时,该模式下系统失稳,表现为直驱风电机组发生低频振荡。     

Optimal design of a tunable electromagnetic shunt damper for dynamic vibration absorber

Dynamic vibration absorber (DVA) is an effective device for suppressing resonant vibration of noisy machineries and structures. However, the optimum design of DVA requires precise tuning of the damping force in the DVA, which unfortunately is often not practical and prone to changes of working conditions. In this paper, a tunable electromagnetic shunt damper (EMSD) with different opposing magnet pairs configurations is tested for the optimum design of DVA. The optimum magnet pairs configuration is derived to provide the maximum damping force in the DVA. Both simulations and experiments are conducted to verify the damping coefficient variation with the number of magnet pairs in the EMSD. The experimental optimization procedure of the DVA is designed according to the fixed-points theory. The damping force generated by the EMSD can be readily adjusted by varying the external resistance of the EMSD. This is the first experimental implementation report of the optimization procedure described in the fixed-points theory. The proposed tunable EMSD can conveniently allow for onsite optimal tuning of DVA. The proposed design methodology provides fine tuning of the damping coefficient of EMSD to achieve robust optimal DVA performance, even when subject to changes of external parasitic damping.     

Power system transient stability assessment based on the multiple paralleled convolutional neural network and gated recurrent unit

In order to accurately evaluate power system stability in a timely manner after faults, and further improve the feature extraction ability of the model, this paper presents an improved transient stability assessment (TSA) method of CNN?+?GRU. This comprises a convolutional neural network (CNN) and gated recurrent unit (GRU). CNN has the feature extraction capability for a micro short-term time sequence, while GRU can extract characteristics contained in a macro long-term time sequence. The two are integrated to comprehensively extract the high-order features that are contained in a transient process. To overcome the difficulty of sample misclassification, a multiple parallel (MP) CNN?+?GRU, with multiple CNN?+?GRU connected in parallel, is created. Additionally, an improved focal loss (FL) function which can implement self-adaptive adjustment according to the neural network training is introduced to guide model training. Finally, the proposed methods are verified on the IEEE 39 and 145-bus systems. The simulation results indicate that the proposed methods have better TSA performance than other existing methods.