On the analysis and design of genetic fuzzy controllers : An application to automatic generation control of large interconnected power systems using genetic fuzzy rule based systems.
Date
2013-07-15
Authors
Boesack, Craig D.
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Abstract
Frequency Control of large interconnected power systems is governed by means
of Automatic Generation Control (AGC), which regulates the system frequency
and tie line power interchange at its nominal parameter set points. Conventional
approaches to AGC controller design is centered around the Proportional, Integral
and Derivative (PID) controller structures, which have found widespread
application within industry.
However, the dynamic changes experienced throughout the life cycle of power
systems have many contributing factors, in part attributed to unknown knowledge
of system behavior, neglected process dynamics and a limited knowledge of
system interactions, which makes modeling for AGC systems particularly trying
for conventional AGC controller design approaches.
Therefore, in this study, Genetic - Fuzzy controllers (GA - Fuzzy) are applied as
plausible candidates for Automatic Generation Controller design and application.
In GA - Fuzzy controllers, genetic algorithms which are based on the foundation
of evolutionary heuristics are used as a global search method for FLC design.
This is particularly motivated by the fact that Fuzzy controllers, especially where
there are large data sets, unknown process knowledge and insu cient expert data
available, FLC controller design proves to be a daunting task.
Therefore, this thesis explores the automatic design of FLC controllers through
evolutionary heuristics and applies the designed controller to the AGC problem
of large interconnected power systems. The design methodology followed is to
understand power system interactions through power plant modeling and the
simulation power plant models for the basis for AGC controller design.
It is shown in this study that the performance of the GA - Fuzzy controller
have favourable characteristics in terms of robust performance, robustness properties
and compares favorably with conventional AGC controller techniques. The
analysis of the GA - Fuzzy controller shows that problem formulation and chromosome
encoding of the problem search space forms an important prerequisite
for controller design by evolutionary methods.
Therefore the study concludes by stating that GA - Fuzzy controllers are plausible
for application within the power industry because of its desirable attributes
and that future work would include extending this research into areas of renewable
energy for study and application.