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
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
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
In this paper, a hybrid neural-genetic fuzzy system is proposed to control the flow and height of water in the reservoirs of water transfer networks. These controls will avoid probable water wastes in the reservoirs a...In this paper, a hybrid neural-genetic fuzzy system is proposed to control the flow and height of water in the reservoirs of water transfer networks. These controls will avoid probable water wastes in the reservoirs and pressure drops in water distribution networks. The proposed approach combines the artificial neural network, genetic algorithm, and fuzzy inference system to improve the performance of the supervisory control and data acquisition stations through a new control philosophy for instruments and control valves in the reservoirs of the water transfer networks. First, a multi-core artificial neural network model, including a multi-layer perceptron and radial based function, is proposed to forecast the daily consumption of the water in a reservoir. A genetic algorithm is proposed to optimize the parameters of the artificial neural networks. Then, the online height of water in the reservoir and the output of artificial neural networks are used as inputs of a fuzzy inference system to estimate the flow rate of the reservoir inlet. Finally, the estimated inlet flow is translated into the input valve position using a transform control unit supported by a nonlinear autoregressive exogenous model. The proposed approach is applied in the Tehran water transfer network. The results of this study show that the usage of the proposed approach significantly reduces the deviation of the reservoir height from the desired levels.展开更多
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。
文摘In this paper, a hybrid neural-genetic fuzzy system is proposed to control the flow and height of water in the reservoirs of water transfer networks. These controls will avoid probable water wastes in the reservoirs and pressure drops in water distribution networks. The proposed approach combines the artificial neural network, genetic algorithm, and fuzzy inference system to improve the performance of the supervisory control and data acquisition stations through a new control philosophy for instruments and control valves in the reservoirs of the water transfer networks. First, a multi-core artificial neural network model, including a multi-layer perceptron and radial based function, is proposed to forecast the daily consumption of the water in a reservoir. A genetic algorithm is proposed to optimize the parameters of the artificial neural networks. Then, the online height of water in the reservoir and the output of artificial neural networks are used as inputs of a fuzzy inference system to estimate the flow rate of the reservoir inlet. Finally, the estimated inlet flow is translated into the input valve position using a transform control unit supported by a nonlinear autoregressive exogenous model. The proposed approach is applied in the Tehran water transfer network. The results of this study show that the usage of the proposed approach significantly reduces the deviation of the reservoir height from the desired levels.
