Degree Type

Dissertation

Date of Award

2005

Degree Name

Doctor of Philosophy

Department

Electrical and Computer Engineering

First Advisor

Venkataramana Ajjarapu

Abstract

This dissertation proposes novel algorithms for power system oscillatory stability assessment. An integration based eigenvalue tracing method is proposed to trace any specified eigenvalue of interest. Also a margin boundary tracing algorithm that can trace not only the oscillatory stability margin boundary, but also damping margin boundary is proposed. The eigenvalues tracing method can trace any eigenvalues of interest. An eigenvalue index is proposed to rank the eigenvalues. This index is helpful for identifying the rate of change of movement and the direction of movement for these eigenvalues with respect to change in any parameter of interest. This approach is used to identify Hopf bifurcation. It is also extended to satisfy minimum damping margin constraints. Eigenvalue and Eigenvector sensitivities are by-products of this approach. This method is faster and more robust than the secant method, especially for large scale systems.;The dissertation discusses the computational advantages of this algorithm in detail, and demonstrates the potential convergence problems with the secant method. Without the proposed margin boundary (both oscillatory and damping) tracing algorithm one has to repeat tracing the P-V curve for changing parameter values to get the oscillatory stability margin boundary and the damping margin boundary. The approach provides the relevant information about the nonlinear characteristics between margin and control parameters, by which one can find not only the control parameter values to maximize the margin, but also the control parameter perturbation tolerance, which can help keep the system more robust.;The eigenvalues tracing and margin boundary tracing methodologies proposed in this thesis will make contribution to future on-line stability assessment tools for large scale power systems.

DOI

https://doi.org/10.31274/rtd-180813-13223

Publisher

Digital Repository @ Iowa State University, http://lib.dr.iastate.edu

Copyright Owner

Xiaoyu Wen

Language

en

Proquest ID

AAI3184662

File Format

application/pdf

File Size

98 pages

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