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Full-Text Articles in Engineering
Blue-Box Approach To Power Electronics And Machines Educational Laboratories, Robert S. Balog, Zakdy Sorchini, Jonathan W. Kimball, Patrick L. Chapman, Philip T. Krein, Peter W. Sauer
Blue-Box Approach To Power Electronics And Machines Educational Laboratories, Robert S. Balog, Zakdy Sorchini, Jonathan W. Kimball, Patrick L. Chapman, Philip T. Krein, Peter W. Sauer
Electrical and Computer Engineering Faculty Research & Creative Works
Our approach to laboratory education in power electronics and electric machines is presented. The approach centers upon "blue-box" laboratory components, that aid the student in rapid experiment assembly without disguising important aspects of the hardware. Several example experiments are presented. Schematics and construction techniques for the hardware are publicly available.
A Comparison Of Pso And Backpropagation For Training Rbf Neural Networks For Identification Of A Power System With Statcom, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Yamille Del Valle, Ronald G. Harley
A Comparison Of Pso And Backpropagation For Training Rbf Neural Networks For Identification Of A Power System With Statcom, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Yamille Del Valle, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
Backpropagation algorithm is the most commonly used algorithm for training artificial neural networks. While being a straightforward procedure, it suffers from extensive computations, relatively slow convergence speed and possible divergence for certain conditions. The efficiency of this method as the training algorithm of a radial basis function neural network (RBFN) is compared with that of particle swarm optimization, for neural network based identification of a small power system with a static compensator. The comparison of the two methods is based on the convergence speed and robustness of each method.
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 …
Optimal Control Parameters For A Upfc In A Multimachine Using Pso, Ganesh K. Venayagamoorthy
Optimal Control Parameters For A Upfc In A Multimachine Using Pso, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
The crucial factor affecting the modern power systems today is load flow control. The unified power flow controller (UPFC) is an effective means for controlling the power flow and can provide damping capability during transient conditions. The UPFC is controlled conventionally using PI controllers. The optimal design of the PI controllers for a UPFC is a challenging task and time consuming using the conventional techniques. This paper presents an approach using particle swarm optimization (PSO) for the design of optimal conventional controllers for a UPFC in a multimachine power system. Simulation results are presented to show the effectiveness of the …
Two Separate Continually Online-Trained Neurocontrollers For A Unified Power Flow Controller, Ganesh K. Venayagamoorthy, Radha P. Kalyani
Two Separate Continually Online-Trained Neurocontrollers For A Unified Power Flow Controller, Ganesh K. Venayagamoorthy, Radha P. Kalyani
Electrical and Computer Engineering Faculty Research & Creative Works
The crucial factor affecting the modern power systems today is load flow control. The Unified Power Flow Controller (UPFC) provides an effective means for controlling the power flow and improving the transient stability in a power network. The UPFC has fast complex dynamics and its conventional control is based on a linearized model of the power system. This paper presents the design of neurocontrollers to provide better damping during transient and dynamic control. Two separate neurocontrollers are used for controlling the UPFC, one neurocontroller for the shunt inverter and the other for the series inverter. Simulation studies carried out in …
Hardware Implementation Of A Mamdani Fuzzy Logic Controller For A Static Compensator In A Multimachine Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Satish Rajagopalan, Ronald G. Harley
Hardware Implementation Of A Mamdani Fuzzy Logic Controller For A Static Compensator In A Multimachine Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Satish Rajagopalan, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
A Mamdani based fuzzy logic controller is designed and implemented for controlling a STATCOM, which is connected to a 10 bus multimachine power system. Such a controller does not need any prior knowledge of the plant to be controlled and can efficiently provide control signals for the STATCOM during different disturbances in the network The proposed controller is implemented using the M67 DSP board and is interfaced to the multimachine power system simulated on a real-time digital simulator (RTDS). Experimental results are provided, showing that the proposed controller provides more effective damping than the conventional PI controller in a typical …
A Neural Network Based Optimal Wide Area Control Scheme For A Power System, Ganesh K. Venayagamoorthy, Swakshar Ray
A Neural Network Based Optimal Wide Area Control Scheme For A Power System, Ganesh K. Venayagamoorthy, Swakshar Ray
Electrical and Computer Engineering Faculty Research & Creative Works
With deregulation of the power industry, many tie lines between control areas are driven to operate near their maximum capacity, especially those serving heavy load centers. Wide area control systems (WACSs) using wide-area or global signals can provide remote auxiliary control signals to local controllers such as automatic voltage regulators, power system stabilizers, etc to damp out inter-area oscillations. This paper presents the design and the DSP implementation of a nonlinear optimal wide area controller based on adaptive critic designs and neural networks for a power system on the real-time digital simulator (RTDS©). The performance of the WACS as a …
An Adaptive Mamdani Fuzzy Logic Based Controller For A Static Compensator In A Multimachine Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley
An Adaptive Mamdani Fuzzy Logic Based Controller For A Static Compensator In A Multimachine Power System, Salman Mohagheghi, Ganesh K. Venayagamoorthy, Ronald G. Harley
Electrical and Computer Engineering Faculty Research & Creative Works
An adaptive Mamdani based fuzzy logic controller has been designed for controlling a static compensator (STATCOM) in a multimachine power system. Such a controller does not need any prior knowledge of the plant to be controlled and can efficiently control a STATCOM during different disturbances in the network. A model free approach using the controller output error is applied for training purposes that adaptively changes the controller output parameters based on a gradient descent method. Moreover, shrinking span membership functions are used for a more stable and accurate control performance. Simulation results show that the proposed controller outperforms the conventional …
Reactive Power And Voltage Control Of The Nigerian Grid System Using Micro-Genetic Algorithm, Ganesh K. Venayagamoorthy, G. A. Bakare, U. O. Aliyu
Reactive Power And Voltage Control Of The Nigerian Grid System Using Micro-Genetic Algorithm, Ganesh K. Venayagamoorthy, G. A. Bakare, U. O. Aliyu
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a micro-genetic based approach to the optimization of reactive power and voltage profiles improvement and real power loss minimization is presented. The reactive power control devices such as generators, tap positions of on-load tap changer of transformers, shunt reactors are used to correct voltage limits violations while simultaneously reducing the system real power losses. Genetic algorithms (GAs) are well-known global search techniques anchored on the mechanisms of natural selection and genetics. Because of the time intensive nature of the conventional GA, the micro-GA is proposed as a more time efficient alternative. The feasibility and effectiveness of the …