Doctoral Dissertations
Keywords and Phrases
Wind-hydrothermal generators
Abstract
"This dissertation presents some challenging problems in power system operations. The efficacy of a heuristic method, namely, modified discrete particle swarm optimization (MDPSO) algorithm is illustrated and compared with other methods by solving the reliability based generator maintenance scheduling (GMS) optimization problem of a practical hydrothermal power system. The concept of multiple swarms is incorporated into the MDPSO algorithm to form a robust multiple swarms-modified particle swarm optimization (MS-MDPSO) algorithm and applied to solving the GMS problem on two power systems. Heuristic methods are proposed to circumvent the problems of imposed non-smooth assumptions common with the classical approaches in solving the challenging dynamic economic dispatch problem. The multi-objective combined economic and emission dispatch (MO-CEED) optimization problem for a wind-hydrothermal power system is formulated and solved in this dissertation. This MO-CEED problem formulation becomes a challenging problem because of the presence of uncertainty in wind power. A family of distributed optimal Pareto fronts for the MO-CEED problem has been generated for different scenarios of capacity credit of wind power. A real-time (RT) network stability index is formulated for determining a power system's ability to continue to provide service (electric energy) in a RT manner in case of an unforeseen catastrophic contingency. Cascading stages of fuzzy inference system is applied to combine non real-time (NRT) and RT power system assessments. NRT analysis involves eigenvalue and transient energy analysis. RT analysis involves angle, voltage and frequency stability indices. RT Network status index is implemented in real-time on a practical power system"--Abstract, page iv.
Advisor(s)
Venayagamoorthy, Ganesh K.
Committee Member(s)
Corzine, Keith, 1968-
Wunsch, Donald C.
Sarangapani, Jagannathan, 1965-
Dagli, Cihan H., 1949-
Department(s)
Electrical and Computer Engineering
Degree Name
Ph. D. in Electrical Engineering
Sponsor(s)
National Science Foundation (U.S.)
Publisher
Missouri University of Science and Technology
Publication Date
Fall 2010
Journal article titles appearing in thesis/dissertation
- Optimal generator maintenance scheduling using a modified discrete PSO
- Optimal maintenance scheduling of generators using multiple swarms-MDPSO framework
- Heuristic methods for static and dynamic economic dispatch with practical generator constraints
- Multi-objective combined economic and emission dispatch with uncertainty in wind power for a wind-hydrothermal system
- Generator maintenance scheduling for a wind-hydrothermal power system with uncertainty in wind power generation
- Real-time stability assessment of a power system
Pagination
xv, 207 pages
Note about bibliography
Includes bibliographical references.
Rights
© 2010 Yusuf Yare, All rights reserved.
Document Type
Dissertation - Open Access
File Type
text
Language
English
Subject Headings
Electric power distribution -- Maintenance and repairMaintenance -- Mathematical modelsMathematical optimizationService life (Engineering) -- ForecastingSwarm intelligence -- Mathematical models
Thesis Number
T 9796
Print OCLC #
775800742
Electronic OCLC #
756042324
Recommended Citation
Yare, Yusuf, "Intelligent power system operation in an uncertain environment" (2010). Doctoral Dissertations. 1895.
https://scholarsmine.mst.edu/doctoral_dissertations/1895