This paper proposes to adopt SCADA and PLC technology for the improvement of the performance of real time signaling&train control systems in metro railways.The main concern of this paper is to minimize the failure...This paper proposes to adopt SCADA and PLC technology for the improvement of the performance of real time signaling&train control systems in metro railways.The main concern of this paper is to minimize the failure in automated metro railways system operator and integrate the information coming from Operational Control Centre(OCC),traction SCADA system,traction power control,and power supply system.This work presents a simulated prototype of an automated metro train system operator that uses PLC and SCADA for the real time monitoring and control of the metro railway systems.Here,SCADA is used for the visualization of an automated process operation and then the whole opera-tion is regulated with the help of PLC.The PLC used in this process is OMRON(NX1P2-9024DT1)and OMRON’s Sysmac studio programming software is used for developing the ladder logic of PLC.The metro railways system has deployed infrastructure based on SCADA from the power supply system,and each station’s traction power control is connected to the OCC remotely which commands all of the stations and has the highest command priority.An alarm is triggered in the event of an emergency or system congestion.This proposed system overcomes the drawbacks of the current centralized automatic train control(CATC)system.This system provides prominent benefits like augmenting services which may enhance a network’s full load capacity and networkflexibility,which help in easy modification in the existing program at any time.展开更多
With the increased availability of experimental measurements aiming at probing wind resources and wind turbine operations,machine learning(ML)models are poised to advance our understanding of the physics underpinning ...With the increased availability of experimental measurements aiming at probing wind resources and wind turbine operations,machine learning(ML)models are poised to advance our understanding of the physics underpinning the interaction between the atmospheric boundary layer and wind turbine arrays,the generated wakes and their interactions,and wind energy harvesting.However,the majority of the existing ML models for predicting wind turbine wakes merely recreate Computational fluid dynamics(CFD)simulated data with analogous accuracy but reduced computational costs,thus providing surrogate models rather than enhanced data-enabled physics insights.Although ML-based surrogate models are useful to overcome current limitations associated with the high computational costs of CFD models,using ML to unveil processes from experimental data or enhance modeling capabilities is deemed a potential research direction to pursue.In this letter,we discuss recent achievements in the realm of ML modeling of wind turbine wakes and operations,along with new promising research strategies.展开更多
信息通信技术的发展和智能设备的引入使电力系统逐渐演变为电力信息物理系统,而信息层与物理层之间的深度耦合也加剧了电力系统遭受网络攻击的风险。虚假数据注入攻击(false data injection attack,FDIA)作为一种兼具隐蔽性、灵活性和...信息通信技术的发展和智能设备的引入使电力系统逐渐演变为电力信息物理系统,而信息层与物理层之间的深度耦合也加剧了电力系统遭受网络攻击的风险。虚假数据注入攻击(false data injection attack,FDIA)作为一种兼具隐蔽性、灵活性和攻击导向性的网络攻击方式,对电力数据采集与监控(supervisory control and data acquisition,SCADA)系统的安全稳定构成很大威胁。为应对这一威胁挑战,学者们研究了各种各样的FDIA检测方法。该文对面向电力SCADA系统的FDIA检测方法进行综述,首先介绍了FDIA的攻击原理及构建方法,梳理了FDIA检测算法的发展历程,并按照模型驱动和数据驱动对算法进行了分类整理,针对模型驱动中的基于状态估计、图论、物理特性等检测方法和数据驱动中的有监督学习、无监督学习、半监督学习、对抗博弈学习和强化学习等检测方法分别进行了机理分析;然后对比分析了相关算法的检测性能、优缺点及其适用场景;最后,对FDIA检测防御的后续研究方向进行了展望。展开更多
For decades, the power system was highly centralized. With the growing integration of distributed generations into the system, there is a necessity for bi-directional communication methods to monitor and control the r...For decades, the power system was highly centralized. With the growing integration of distributed generations into the system, there is a necessity for bi-directional communication methods to monitor and control the remote assets. The primary objective of this paper is to develop a communication link for monitoring and controlling a grid-connected inverter in a remote location. Furthermore, the paper presents developments that have been incorporated to improve the communication link. The literature survey indicates that LoRa is superior compared to other technologies, but has some security and reliability issues. This paper also presents an encryption algorithm to improve the security of the LoRa link. Local data storage added to the system before transmitting data increases the system reliability. A display at the transmission end is added to improve the user-friendliness of the communication link. A Powerline Communication link is parallelly added to the LoRa link to improve the reliability. Finally, tests are conducted with an actual inverter and the results are presented. The tests show that the developed communication link has improved security and reliability, while its open nature makes it highly scalable and adaptable for employment in other smart grid applications.展开更多
振动信号是风电机组数据采集与监视控制(supervisorycontrol and data acquisition,SCADA)系统中的一类重要变量。对振动信号的建模和分析可以实现对机组重要部件如塔架、传动链、叶轮等的状态监测工作。采用非线性状态估计技术(nonline...振动信号是风电机组数据采集与监视控制(supervisorycontrol and data acquisition,SCADA)系统中的一类重要变量。对振动信号的建模和分析可以实现对机组重要部件如塔架、传动链、叶轮等的状态监测工作。采用非线性状态估计技术(nonlinear state estimate technique,NSET)作为建模方法,在对风电机组塔架振动特性及其影响因素进行细致分析的基础上,建立了塔架振动模型。该模型由额定风速以下和额定风速以上两部分子模型构成。同时,对非线性状态估计技术的物理意义及特点进行了深入的分析和探讨。在某风电机组2006年4至6月份SCADA数据的基础上,建立了覆盖其正常工作状态的塔架振动模型,并对该模型进行了验证。研究表明,基于NSET的塔架振动建模方法具有方法简单、物理意义明确和建模精度高等优点,为后续拟开展的风电机组振动状态监测和早期故障诊断打下了良好的基础,同时为风电机组振动分析提供了新的思路。展开更多
文摘This paper proposes to adopt SCADA and PLC technology for the improvement of the performance of real time signaling&train control systems in metro railways.The main concern of this paper is to minimize the failure in automated metro railways system operator and integrate the information coming from Operational Control Centre(OCC),traction SCADA system,traction power control,and power supply system.This work presents a simulated prototype of an automated metro train system operator that uses PLC and SCADA for the real time monitoring and control of the metro railway systems.Here,SCADA is used for the visualization of an automated process operation and then the whole opera-tion is regulated with the help of PLC.The PLC used in this process is OMRON(NX1P2-9024DT1)and OMRON’s Sysmac studio programming software is used for developing the ladder logic of PLC.The metro railways system has deployed infrastructure based on SCADA from the power supply system,and each station’s traction power control is connected to the OCC remotely which commands all of the stations and has the highest command priority.An alarm is triggered in the event of an emergency or system congestion.This proposed system overcomes the drawbacks of the current centralized automatic train control(CATC)system.This system provides prominent benefits like augmenting services which may enhance a network’s full load capacity and networkflexibility,which help in easy modification in the existing program at any time.
基金supported by the National Science Foundation(NSF)CBET,Fluid Dynamics CAREER program(Grant No.2046160),program manager Ron Joslin.
文摘With the increased availability of experimental measurements aiming at probing wind resources and wind turbine operations,machine learning(ML)models are poised to advance our understanding of the physics underpinning the interaction between the atmospheric boundary layer and wind turbine arrays,the generated wakes and their interactions,and wind energy harvesting.However,the majority of the existing ML models for predicting wind turbine wakes merely recreate Computational fluid dynamics(CFD)simulated data with analogous accuracy but reduced computational costs,thus providing surrogate models rather than enhanced data-enabled physics insights.Although ML-based surrogate models are useful to overcome current limitations associated with the high computational costs of CFD models,using ML to unveil processes from experimental data or enhance modeling capabilities is deemed a potential research direction to pursue.In this letter,we discuss recent achievements in the realm of ML modeling of wind turbine wakes and operations,along with new promising research strategies.
文摘信息通信技术的发展和智能设备的引入使电力系统逐渐演变为电力信息物理系统,而信息层与物理层之间的深度耦合也加剧了电力系统遭受网络攻击的风险。虚假数据注入攻击(false data injection attack,FDIA)作为一种兼具隐蔽性、灵活性和攻击导向性的网络攻击方式,对电力数据采集与监控(supervisory control and data acquisition,SCADA)系统的安全稳定构成很大威胁。为应对这一威胁挑战,学者们研究了各种各样的FDIA检测方法。该文对面向电力SCADA系统的FDIA检测方法进行综述,首先介绍了FDIA的攻击原理及构建方法,梳理了FDIA检测算法的发展历程,并按照模型驱动和数据驱动对算法进行了分类整理,针对模型驱动中的基于状态估计、图论、物理特性等检测方法和数据驱动中的有监督学习、无监督学习、半监督学习、对抗博弈学习和强化学习等检测方法分别进行了机理分析;然后对比分析了相关算法的检测性能、优缺点及其适用场景;最后,对FDIA检测防御的后续研究方向进行了展望。
文摘For decades, the power system was highly centralized. With the growing integration of distributed generations into the system, there is a necessity for bi-directional communication methods to monitor and control the remote assets. The primary objective of this paper is to develop a communication link for monitoring and controlling a grid-connected inverter in a remote location. Furthermore, the paper presents developments that have been incorporated to improve the communication link. The literature survey indicates that LoRa is superior compared to other technologies, but has some security and reliability issues. This paper also presents an encryption algorithm to improve the security of the LoRa link. Local data storage added to the system before transmitting data increases the system reliability. A display at the transmission end is added to improve the user-friendliness of the communication link. A Powerline Communication link is parallelly added to the LoRa link to improve the reliability. Finally, tests are conducted with an actual inverter and the results are presented. The tests show that the developed communication link has improved security and reliability, while its open nature makes it highly scalable and adaptable for employment in other smart grid applications.
文摘振动信号是风电机组数据采集与监视控制(supervisorycontrol and data acquisition,SCADA)系统中的一类重要变量。对振动信号的建模和分析可以实现对机组重要部件如塔架、传动链、叶轮等的状态监测工作。采用非线性状态估计技术(nonlinear state estimate technique,NSET)作为建模方法,在对风电机组塔架振动特性及其影响因素进行细致分析的基础上,建立了塔架振动模型。该模型由额定风速以下和额定风速以上两部分子模型构成。同时,对非线性状态估计技术的物理意义及特点进行了深入的分析和探讨。在某风电机组2006年4至6月份SCADA数据的基础上,建立了覆盖其正常工作状态的塔架振动模型,并对该模型进行了验证。研究表明,基于NSET的塔架振动建模方法具有方法简单、物理意义明确和建模精度高等优点,为后续拟开展的风电机组振动状态监测和早期故障诊断打下了良好的基础,同时为风电机组振动分析提供了新的思路。
