Date of Award
12-2010
Degree Type
Thesis
Degree Name
M.S.
Degree Program
Engineering
Department
Electrical Engineering
Major Professor
Rastgoufard, Parviz
Second Advisor
Leevongwat, Ittiphong
Third Advisor
Bourgeois, Edit J.
Abstract
The basic idea deals with detecting the voltage collapse ahead of time to provide the operators a lead time for remedial actions and for possible prevention of blackouts. To detect cases of voltage collapse, we shall create methods using pattern recognition in conjunction with real time simulation of case studies and shall develop heuristic methods for separating voltage stable cases from voltage unstable cases that result in response to system contingencies and faults. Using Real Time Simulator in Entergy-UNO Power & Energy Research Laboratory, we shall simulate several contingencies on IEEE 39-Bus Test System and compile the results in two categories of stable and unstable voltage cases. The second stage of the proposed work mainly deals with the study of different patterns of voltage using artificial neural networks. The final stage deals with the training of the controllers in order to detect stability of power system in advance.
Recommended Citation
Beeravolu, Nagendrakumar, "Pattern Recognition of Power Systems Voltage Stability Using Real Time Simulations" (2010). University of New Orleans Theses and Dissertations. 1279.
https://scholarworks.uno.edu/td/1279
Rights
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