Doctoral Dissertations

Keywords and Phrases

Phasor measurement units; Power systems; Smart grid; Voltage stability control


"The electric power grid is a complex, non-linear, non-stationary system comprising of thousands of components such as generators, transformers, transmission lines and advanced power electronics based control devices, and customer loads. The complexity of the grid has been further increased by the introduction of smart grid technologies. Smart grid technology adds to the traditional power grids advanced methods of communication, computation and control as well as increased use of renewable energy sources such as wind and solar farms and a higher penetration of plug-in electric vehicles among others. The smart grid has resulted in much more distributed generation, bi-directional powerflows between customers and the grid, and the semi-autonomous control of subsystems. Due to this added complexity of the grid and the need to maintain reliable, quality, efficient, economical, and environmentally friendly power supply, advanced monitoring and control technologies are needed for real-time operation of various systems that integrate into the transmission and distribution network.

In this dissertation, the development of computational intelligence methods for on-line monitoring of voltage stability in a power system is presented. In order to carry out on-line assessment of voltage stability, data from Phasor Measurement Units (PMUs) is utilized. An intelligent algorithm for optimal location of PMUs for voltage stability monitoring is developed. PMU information is used for estimation of voltage stability load index in a power system with plug-in electric vehicle and wind farm included. The estimated voltage stability index is applied in the development of an adaptive dynamic programming based optimal secondary voltage controller to coordinate the reactive power capability of two FACTS devices"--Abstract, page iii.


Erickson, Kelvin T.

Committee Member(s)

Ferdowsi, Mehdi
Kimball, Jonathan W.
Crow, Mariesa
Dagli, Cihan H., 1949-


Electrical and Computer Engineering

Degree Name

Ph. D. in Electrical Engineering


National Science Foundation (U.S.)


Financial support of the National Science Foundation (EFRI # 1238097 and ECCS # 1231820)


Missouri University of Science and Technology

Publication Date

Fall 2015


xiv, 141 pages

Note about bibliography

Includes bibliographic references (pages 134-140).


© 2015 Kangombe Joseph Makasa, All rights reserved.

Document Type

Dissertation - Open Access

File Type




Subject Headings

Computational intelligence
Voltage regulators -- Evaluation -- Mathematical models
Electric power systems -- Mathematical models
Smart power grids
Electric power system stability
Renewable energy sources

Thesis Number

T 10830

Electronic OCLC #