Electronic Theses and Dissertations

Identifier

3747

Date

2016

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Electrical Engineering

Concentration

Power Systems

Committee Chair

Dr. Mohd. Hasan Ali

Committee Member

Dr. Russell Deaton

Committee Member

Dr. Eddie Jacobs

Committee Member

Dr. Dipankar Dasgupta

Abstract

This dissertation proposes the bridge type fault current limiter (BFCL) as well as parallel resonance type fault current limiter (PRFCL) to enhance the transient stability of multi-machine power system. Fuzzy logic controller as well as neural network predictive controller is proposed for controlling the operation of BFCL. Further, a nonlinear static controller is proposed for controlling the operation of PRFCL. An optimal reclosing technique of circuit breakers is adopted. In order to see the effectiveness of the proposed fault current limiters, their performance is compared wit that of other auxiliary devices.Moreover, the effects of cyber-attack on the performance of BFCL controllers to improve the power system stability are investigated.Genetic algorithm (GA) is applied to optimally tune the controller parameters. Simulations are performed by using the Matlab/Simulink software in different test power systems. Simulation results of both balanced and unbalanced permanent and temporary faults at different points of the test systems indicate that the proposed fault current limiters can enhance the transient stability of the power system well compared to the other auxiliary devices. Moreover, the performance of the PRFCL is better than that of the BFCL. Further, the neural network predictive controller performs better than the fuzzy logic controller for BFCL. It is noteworthy that cyber-attacks have profound effect on the controller performance and the system becomes fully unstable even with the presence of the proposed controllers of the fault current limiters.

Comments

Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to the local University of Memphis Electronic Theses & dissertation (ETD) Repository.

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