The small-signal model of the photovoltaic generation system was built in a few references,and the sensitivity study of the dynamics process was performed.However,the dynamic model of the photovoltaic(PV)cells was not...The small-signal model of the photovoltaic generation system was built in a few references,and the sensitivity study of the dynamics process was performed.However,the dynamic model of the photovoltaic(PV)cells was not considered in these references,and the small-signal stability analysis and controllers'parameters design were not carried out using the proposed small-signal model.Therefore,a complete small-signal model of the photovoltaic generation system containing PV panels,inverters,controllers and power grid was built.The stability of the system after suffering a small disturbance was analyzed according to the eigenvalues.By means of eigenvalues participation factors analysis,the sensitivity of each mode to state variables was learnt,thereby the origin and characteristics of each mode was disclosed.Then,the eigenvalues traces were calculated,according to which controller's parameters were designed.A simulation model of the system based on Matlab/Simulink was presented.The simulation results show that the system is stable after suffering small disturbance of solar radiation intensity step,the design of the controller's parameters is proper,and the system dynamic responses are consistent with the result of small-signal analysis,which proved that the small-signal modeling and analysis in this paper are correct.展开更多
Because of the increasing penetration of photovoltaic generation,the small-signal modeling and analysis of photovoltaic generation system has become a new research area.For studying the stability of a photovoltaic(PV)...Because of the increasing penetration of photovoltaic generation,the small-signal modeling and analysis of photovoltaic generation system has become a new research area.For studying the stability of a photovoltaic(PV)generation system after a small disturbance takes place and the parameters of the system are effectively designed,a complete small signal model of the system is built.展开更多
In the realm of high-speed railway bridge engineering,managing the intricacies of the track-bridge system model(TBSM)during seismic events remains a formidable challenge.This study pioneers an innovative approach by p...In the realm of high-speed railway bridge engineering,managing the intricacies of the track-bridge system model(TBSM)during seismic events remains a formidable challenge.This study pioneers an innovative approach by presenting a simplified bridge model(SBM)optimized for both computational efficiency and precise representation,a seminal contribution to the engineering design landscape.Central to this innovation is a novel model-updating methodology that synergistically melds artificial neural networks with an augmented particle swarm optimization.The neural networks adeptly map update parameters to seismic responses,while enhancements to the particle swarm algorithm’s inertial and learning weights lead to superior SBM parameter updates.Verification via a 4-span high-speed railway bridge revealed that the optimized SBM and TBSM exhibit a highly consistent structural natural period and seismic response,with errors controlled within 7%.Additionally,the computational efficiency improved by over 100%.Leveraging the peak displacement and shear force residuals from the seismic TBSM and SBM as optimization objectives,SBM parameters are adeptly revised.Furthermore,the incorporation of elastoplastic springs at the beam ends of the simplified model effectively captures the additional mass,stiffness,and constraint effects exerted by the track system on the bridge structure.展开更多
为研究大跨度悬索桥在随机车流作用下加劲梁纵向运动及纵向累计位移行程简化计算方法,基于移动荷载作用下加劲梁纵向运动特征,将悬挂加劲梁体系等效为单自度(single-degree-of-freedom,SDOF)振动体系,推导了基于SDOF振动体系的移动荷载...为研究大跨度悬索桥在随机车流作用下加劲梁纵向运动及纵向累计位移行程简化计算方法,基于移动荷载作用下加劲梁纵向运动特征,将悬挂加劲梁体系等效为单自度(single-degree-of-freedom,SDOF)振动体系,推导了基于SDOF振动体系的移动荷载作用下悬索桥加劲梁纵向振动方程和随机车流作用下加劲梁纵向振动方程,提出了一种快速计算随机车流作用下加劲梁纵向振动响应的方法。以某单跨悬索桥为实例,基于实测车流数据,采用蒙特卡罗抽样方法生成随机车流样本,将其等效为SDOF体系下随机荷载时程,进行SDOF体系振动方程求解得到纵向响应位移时程,并与基于ANSYS的全桥模型瞬态分析结果进行对比。结果表明:随机车流作用下,加劲梁发生纵向运动并形成巨大累计位移行程,累计位移包括静态位移和动态位移,后者对累计位移贡献更大;与有限元瞬态动力分析相比,基于简化SDOF体系获得的位移响应结果中除累计位移差别稍大(约13%~19%)外,其幅值和均方根值(root mean square,RMS)均差别很小(小于5%),简化振动模型能反映随机车流下加劲梁纵向运动特征规律,所提计算方法可极大地简化随机车流作用下加劲梁纵向运动分析,可用于结构设计阶段随机车流作用下加劲梁纵向运动评估及振动控制参数优化。展开更多
文摘The small-signal model of the photovoltaic generation system was built in a few references,and the sensitivity study of the dynamics process was performed.However,the dynamic model of the photovoltaic(PV)cells was not considered in these references,and the small-signal stability analysis and controllers'parameters design were not carried out using the proposed small-signal model.Therefore,a complete small-signal model of the photovoltaic generation system containing PV panels,inverters,controllers and power grid was built.The stability of the system after suffering a small disturbance was analyzed according to the eigenvalues.By means of eigenvalues participation factors analysis,the sensitivity of each mode to state variables was learnt,thereby the origin and characteristics of each mode was disclosed.Then,the eigenvalues traces were calculated,according to which controller's parameters were designed.A simulation model of the system based on Matlab/Simulink was presented.The simulation results show that the system is stable after suffering small disturbance of solar radiation intensity step,the design of the controller's parameters is proper,and the system dynamic responses are consistent with the result of small-signal analysis,which proved that the small-signal modeling and analysis in this paper are correct.
文摘Because of the increasing penetration of photovoltaic generation,the small-signal modeling and analysis of photovoltaic generation system has become a new research area.For studying the stability of a photovoltaic(PV)generation system after a small disturbance takes place and the parameters of the system are effectively designed,a complete small signal model of the system is built.
基金Project(2022YFC3004304)supported by the National Key Research and Development Program of ChinaProjects(52078487,U1934207,52178180)supported by the National Natural Science Foundation of China+2 种基金Project(2022TJ-Y10)supported by the Hunan Province Science and Technology Talent Lifting Project,ChinaProject(2023QYJC006)supported by the Frontier Cross Research Project of Central South University,ChinaProject(SKL-IoTSC(UM)-2024-2026/ORP/GA08/2023)supported by the Science and Technology Development Fund and the State Key Laboratory of Internet of Things for Smart City(University of Macao),China。
文摘In the realm of high-speed railway bridge engineering,managing the intricacies of the track-bridge system model(TBSM)during seismic events remains a formidable challenge.This study pioneers an innovative approach by presenting a simplified bridge model(SBM)optimized for both computational efficiency and precise representation,a seminal contribution to the engineering design landscape.Central to this innovation is a novel model-updating methodology that synergistically melds artificial neural networks with an augmented particle swarm optimization.The neural networks adeptly map update parameters to seismic responses,while enhancements to the particle swarm algorithm’s inertial and learning weights lead to superior SBM parameter updates.Verification via a 4-span high-speed railway bridge revealed that the optimized SBM and TBSM exhibit a highly consistent structural natural period and seismic response,with errors controlled within 7%.Additionally,the computational efficiency improved by over 100%.Leveraging the peak displacement and shear force residuals from the seismic TBSM and SBM as optimization objectives,SBM parameters are adeptly revised.Furthermore,the incorporation of elastoplastic springs at the beam ends of the simplified model effectively captures the additional mass,stiffness,and constraint effects exerted by the track system on the bridge structure.
文摘为研究大跨度悬索桥在随机车流作用下加劲梁纵向运动及纵向累计位移行程简化计算方法,基于移动荷载作用下加劲梁纵向运动特征,将悬挂加劲梁体系等效为单自度(single-degree-of-freedom,SDOF)振动体系,推导了基于SDOF振动体系的移动荷载作用下悬索桥加劲梁纵向振动方程和随机车流作用下加劲梁纵向振动方程,提出了一种快速计算随机车流作用下加劲梁纵向振动响应的方法。以某单跨悬索桥为实例,基于实测车流数据,采用蒙特卡罗抽样方法生成随机车流样本,将其等效为SDOF体系下随机荷载时程,进行SDOF体系振动方程求解得到纵向响应位移时程,并与基于ANSYS的全桥模型瞬态分析结果进行对比。结果表明:随机车流作用下,加劲梁发生纵向运动并形成巨大累计位移行程,累计位移包括静态位移和动态位移,后者对累计位移贡献更大;与有限元瞬态动力分析相比,基于简化SDOF体系获得的位移响应结果中除累计位移差别稍大(约13%~19%)外,其幅值和均方根值(root mean square,RMS)均差别很小(小于5%),简化振动模型能反映随机车流下加劲梁纵向运动特征规律,所提计算方法可极大地简化随机车流作用下加劲梁纵向运动分析,可用于结构设计阶段随机车流作用下加劲梁纵向运动评估及振动控制参数优化。
