Masters Theses

Lisa L. Grant

Abstract

"As modern power systems continue to grow and evolve, accurate system stability analysis and oscillation control become increasingly important to guarantee system security. Network instability due to power system oscillations caused by the natural modes of the system is becoming a common occurrence. Modal analysis techniques can estimate the eigenvalues of large nonlinear systems from their dynamics responses. The extracted modal information can be applied to detect low frequency oscillations and assess stability margins for power system monitoring and preventive control. Modal information is also useful for low-frequency oscillation damping controller design. This thesis examines two techniques for modal identification based on their ability to accurately identify system modes in the presence of noisy signals and their potential for application to power system modal analysis. The methods investigated include Prony analysis, which has commonly been used in power system studies, and the Matrix Pencil method, which is more common in electromagnetics analysis. These two modal extraction techniques are often described as curve-fitting algorithms which can estimate the magnitude, frequency, phase, and damping parameters of a time-varying function from the eigenvalues of a system. Detailed descriptions of the procedures for performing both methods are included in this thesis to provide a comprehensive resource for implementing either technique in power system modal extraction applications. Simulations are presented using MATLAB for multiple case studies on signals with and without noise where noise is produced using a Gaussian random walk. Prony analysis has been shown to have difficulties extracting the modes of noisy signals, so the examples presented explore these shortcomings and compare them to the capabilities of the Matrix Pencil method. The advantages and disadvantages of both methods are discussed based on the MATLAB simulation results"--Abstract, pagef iii.

Advisor(s)

Crow, Mariesa

Committee Member(s)

Chowdhury, Badrul H.
Ferdowsi, Mehdi

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2011

Pagination

x, 63 pages

Note about bibliography

Includes bibliographical references (pages 60-62).

Rights

© 2011 Lisa Lorena Grant, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Subject Headings

EigenvaluesElectric power system stability -- Mathematical modelsOscillations

Thesis Number

T 9820

Print OCLC #

792748693

Electronic OCLC #

908692740

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