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Computer Sciences

Electrical and Computer Engineering Faculty Research & Creative Works

Power System Stability

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Full-Text Articles in Engineering

A Novel Approach To Interarea Oscillation Damping By Unified Power Flow Controllers Utilizing Ultracapacitors, Mahyar Zarghami, Mariesa Crow, Jagannathan Sarangapani, Yilu Liu, Stan Atcitty Feb 2010

A Novel Approach To Interarea Oscillation Damping By Unified Power Flow Controllers Utilizing Ultracapacitors, Mahyar Zarghami, Mariesa Crow, Jagannathan Sarangapani, Yilu Liu, Stan Atcitty

Electrical and Computer Engineering Faculty Research & Creative Works

This paper discusses a novel approach for damping interarea oscillations in a bulk power network using multiple unified power flow controllers (UPFCs) utilizing ultracapacitors, also known more generally as electrochemical capacitors (ECs). In this paper, a new control is introduced to mitigate interarea oscillations by directly controlling the UPFCs' sending and receiving bus voltages that better utilizes the stored energy in the ECs. The results of this controller are compared with and without ECs. The proposed control provides better interarea oscillation mitigation when applied to multiple UPFCs in the 118-bus IEEE test system.


An Improved Upfc Control For Oscillation Damping, Jagannathan Sarangapani, Mariesa Crow, Jianjun Guo Jan 2009

An Improved Upfc Control For Oscillation Damping, Jagannathan Sarangapani, Mariesa Crow, Jianjun Guo

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a new control approach for a unified power flow controller (UPFC) for power system oscillation damping. This control is simple to implement, yet is valid over a wide range of operating conditions. It is also effective in the presence of multiple modes of oscillation. The proposed control is implemented in several test systems and is compared against a traditional PI control.


Comparisons Of An Adaptive Neural Network Based Controller And An Optimized Conventional Power System Stabilizer, Wenxin Liu, Ganesh K. Venayagamoorthy, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes Oct 2007

Comparisons Of An Adaptive Neural Network Based Controller And An Optimized Conventional Power System Stabilizer, Wenxin Liu, Ganesh K. Venayagamoorthy, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes

Electrical and Computer Engineering Faculty Research & Creative Works

Power system stabilizers are widely used to damp out the low frequency oscillations in power systems. In power system control literature, there is a lack of stability analysis for proposed controller designs. This paper proposes a Neural Network (NN) based stabilizing controller design based on a sixth order single machine infinite bus power system model. The NN is used to compensate the complex nonlinear dynamics of power system. To speed up the learning process, an adaptive signal is introduced to the NN's weights updating rule. The NN can be directly used online without offline training process. Magnitude constraint of the …


Neural Network Based Decentralized Controls Of Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes Oct 2007

Neural Network Based Decentralized Controls Of Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a suite of neural network (NN) based decentralized controller designs for large scale power systems' generators, one is for the excitation control and the other is for the steam valve control. Though the control inputs are calculated using local signals, the transient and overall system stability can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system dynamics and the inter-connection terms, thus the requirements for exact system parameters are relaxed. Simulation studies with a three-machine power system demonstrate the effectiveness of the proposed controller designs.


Neural Network Stabilizing Control Of Single Machine Power System With Control Limits, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow Jul 2004

Neural Network Stabilizing Control Of Single Machine Power System With Control Limits, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow

Electrical and Computer Engineering Faculty Research & Creative Works

Power system stabilizers are widely used to generate supplementary control signals for the excitation system in order to damp out the low frequency oscillations. This paper proposes a stable neural network (NN) controller for the stabilization of a single machine infinite bus power system. In the power system control literature, simplified analytical models are used to represent the power system and the controller designs are not based on rigorous stability analysis. This work overcomes the two major problems by using an accurate analytical model for controller development and presents the closed-loop stability analysis. The NN is used to approximate the …