Masters Theses

Keywords and Phrases

Bacteria foraging algorithm

Abstract

"Bio-inspired techniques are fields of study that are inspired from topics of connectionism, social behavior and emergence. Researchers have ventured into the intricacies involved with the techniques and devised algorithms based on their study. Such techniques are the focus of this thesis. The two bio-inspired techniques used for simultaneous design of power system stabilizers (PSSs) in this study are - Particle Swam Optimization (PSO) and Bacteria Foraging Algorithm (BFA). The work in this thesis is presented in three papers as follows: Paper 1 -This paper introduces an improved PSO called Small Population based PSO (SPPSO) with less number of particles and unique regeneration concept. The efficacy of the algorithm is evaluated for the simultaneous design of power system stabilizers (PSSs) on the two-area and 16 machine power systems. Paper 2 - The second paper presents a new algorithm - Bacterial Foraging Algorithm (BFA) for simultaneous tuning of multiple PSSs on a 16 machine power system. The variants of the BFA like the run length and the swarming are explored for better performance for two different design techniques and the results are compared. Paper 3 - The third paper compares SPPSO and BFA towards simultaneous tuning of multiple PSSs on two-area and Nigerian power system. This paper presents both algorithms as a first step towards online optimization and proposes to implement these algorithms in real power systems in near future"--Abstract, page iv.

Advisor(s)

Venayagamoorthy, Ganesh K.

Committee Member(s)

Corzine, Keith, 1968-
Wunsch, Donald C.

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering

Publisher

University of Missouri--Rolla

Publication Date

2007

Journal article titles appearing in thesis/dissertation

  • Computationally efficient SPPSO algorithm for design of power system stabilizers.
  • Bacterial foraging algorithm and its variants for the design of power system stabilizers.
  • Bio-inspired algorithms with small population.

Pagination

xv, 137 pages

Note about bibliography

Includes bibliographical references (pages 136-137).

Rights

© 2007 Tridib Kumar Das, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Library of Congress Subject Headings

Electric power system stability
Swarm intelligence -- Mathematical models
Mathematical optimization

Thesis Number

T 10255

Print OCLC #

863160971

Electronic OCLC #

863161335

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