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Full-Text Articles in Engineering
Upfc Control Employing Gradient Descent Search, William M. Siever, Radha P. Kalyani, Mariesa Crow, Daniel R. Tauritz
Upfc Control Employing Gradient Descent Search, William M. Siever, Radha P. Kalyani, Mariesa Crow, Daniel R. Tauritz
Electrical and Computer Engineering Faculty Research & Creative Works
Increasing demand coupled with limitations on new construction indicate that existing power transmission must be better controlled in order to continue reliable operation. Recent advances in FACTS devices provide a mechanism to better control power flow on the transmission network. One particular device, the unified power flow controller (UPFC), holds the most promise for maintaining operation even when the system has suffered partial failure (either naturally occurring, due to human error, or a malicious attack). In addition to the capital cost, the primary obstacles to widespread UPFC use are the combined problems of selecting the most cost effective locations for …
Control Interaction Mitigation For The Unified Power Flow Controller, Liangying Dong, Mariesa Crow
Control Interaction Mitigation For The Unified Power Flow Controller, Liangying Dong, Mariesa Crow
Electrical and Computer Engineering Faculty Research & Creative Works
This paper establishes that dynamic interactions can occur between multiple UPFCs installed in power systems. The existence of the dynamic interactions can adversely affect the overall system performance and lead to system instability. This paper identifies two types of interactions among FACTS controllers: low frequency inter-area interaction and high frequency controller interactions. Several control approaches are proposed to mitigate these interactions. The IEEE New England 10-machine 39-bus system is used to demonstrate the existence of the control interactions and illustrate the effectiveness of the proposed interaction mitigation controls.
Structured Object-Oriented Co-Analysis/Co-Design Of Hardware/Software For The Facts Powers System, Matt Ryan, Sojan Markose, Xiaoqing Frank Liu, Bruce M. Mcmillin
Structured Object-Oriented Co-Analysis/Co-Design Of Hardware/Software For The Facts Powers System, Matt Ryan, Sojan Markose, Xiaoqing Frank Liu, Bruce M. Mcmillin
Computer Science Faculty Research & Creative Works
There are several approaches to the hardware/software design in embedded systems, ranging from the traditional sequential methods which focus on the determination of the hardware architecture prior to software design, to newer object-oriented approaches that attempt to apply software engineering methods to hardware design without a systematic process. This paper discusses a structured object-oriented methodology for the integrated co-analysis and co-design of hardware/software systems using an extended high order object-oriented modeling technique (HOOMT). This methodology offers a uniform method for hardware and software developers to jointly develop the specifications for and partitioning of the hardware and software components of a …
Power Engineering Laboratory Facilities At The University Of Missouri--Rolla, Keith Corzine, Mariesa Crow
Power Engineering Laboratory Facilities At The University Of Missouri--Rolla, Keith Corzine, Mariesa Crow
Electrical and Computer Engineering Faculty Research & Creative Works
One of the significant niche areas at UMR is the area of electric power. For this reason UMR has invested in its power program over the years. The extent of this program ranges from power systems, motor drives, high-frequency effects in electric machines, acoustic noise of electric machines, FACTS device for electric utility applications, and naval propulsion power systems. The various laboratory facilities at UMR which supports these activities have been described in detail in this paper.
Optimal Dynamic Neurocontrol Of A Gate-Controlled Series Capacitor In A Multi-Machine Power System, Swakshar Ray, Ganesh K. Venayagamoorthy, Edson H. Watanabe, F. D. De Jesus
Optimal Dynamic Neurocontrol Of A Gate-Controlled Series Capacitor In A Multi-Machine Power System, Swakshar Ray, Ganesh K. Venayagamoorthy, Edson H. Watanabe, F. D. De Jesus
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents the design of an optimal dynamic neurocontroller for a new type of FACTS device - the gate controlled series capacitor (GCSC) incorporated in a multi-machine power system. The optimal neurocontroller is developed based on the heuristic dynamic programming (HDP) approach. In addition, a dynamic identifier/model and controller structure using the recurrent neural network trained with backpropagation through time (BPTT) is employed. Simulation results are presented to show the effectiveness of the dynamic neurocontroller and its performance is compared with that of the conventional PI controller under small and large disturbances.
Adaptive Critic Designs For Optimal Control Of Power Systems, Ganesh K. Venayagamoorthy, Ronald G. Harley
Adaptive Critic Designs For Optimal Control Of Power Systems, Ganesh K. Venayagamoorthy, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
The increasing complexity of the modern power grid highlights the need for advanced modeling and control techniques for effective control of excitation, turbine and flexible AC transmission systems (FACTS). The crucial factors affecting the modern power systems today is voltage and load flow control. Simulation studies in the PSCAD/EMTDC environment and realtime laboratory experimental studies carried out are described and the results show the successful control of the power system elements and the entire power system with adaptive and optimal neurocontrol schemes. Performances of the neurocontrollers are compared with the conventional PI controllers for damping under different operating conditions for …
A Dynamic Recurrent Neural Network For Wide Area Identification Of A Multimachine Power System With A Facts Device, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley
A Dynamic Recurrent Neural Network For Wide Area Identification Of A Multimachine Power System With A Facts Device, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
Multilayer perceptron and radial basis function neural networks have been traditionally used for plant identification in power systems applications of neural networks. While being efficient in tracking the plant dynamics in a relatively small system, their performance degrades as the dimensions of the plant to be identified are increased, for example in supervisory level identification of a multimachine power system for wide area control purposes. Recurrent neural networks can deal with such a problem by modeling the system as a set of differential equations and with less order of complexity. Such a recurrent neural network identifier is designed and implemented …