الفهرس 
Motivation for automatic voltage regulator system
Modelling of Synchronous GeneratorOnly 14 pages are availabe for public view
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Abstract
Synchronous generators have been widely used to provide
electricity for most customers. One of the most significant
criteria that should be stabilized over the normal and abnormal
operation of the synchronous generator is the terminal voltage
of the synchronous generator. Automatic voltage regulators
(AVRs) are control circuits dedicated to stabilizing the terminal
voltage of the synchronous generator. However, such these
control circuits only manifest some deficiencies during steady-
state and transient responses.
Various control systems have been proposed to enhance
the output response of AVR. The Proportional-Integral-
Derivative (PID) controller is a control system that has been
used to improve the terminal voltage of the synchronous
generator. However, the most challenging technique with this
controller is how to tune these parameters properly. Some
strategies have been devoted to fine-tuning of PID.
The main contribution of this thesis is to enhance the
output response of the AVR control system employed with a
PID controller using various optimization techniques. In
addition to the deterministic techniques that have been
suggested to obtain fine-tuning of PID controller, meta-
heuristic algorithms are proposed in this thesis to investigate
the optimal design of PID controller which includes Whale
Optimization Algorithm (WOA), Water Cycle Algorithm
(WCA), and Moth-Flame Optimization (MFO) so as to
enhance the output response of AVR control system. To ensure
the effectiveness of these proposed algorithms with the AVR
control system, a comparison is performed between these
algorithms and Genetic Algorithm (GA) executing the same
VII itness function (F.F). The fitness function in this thesis is the
integral square error between the terminal voltage and the
reference voltage. The WCA shows better performance than
the GA, WOA, and MFO do. Also, the convergence towards
the optimal solution obtained by WCA is faster than GA,
WOA, and MFO. The AVR control system combined with the
PID controller is executed in MATLAB/Simulink. The
proposed algorithms employed to optimize the PID controller
parameters are also coded in MATLAB script file which
afterward are called for further optimization.
In addition to the meta-heuristic algorithms, Model
Predictive Control (MPC) is also proposed in this thesis to
enhance the output response of AVR control system. The
model predictive control, in this thesis, studies the state-space
of the automatic voltage regulator and depending on the
difference between the reference voltage and the output
response control signals are determined to match the input-
output characteristic. Also, for ensuring the performance of
AVR engaged with MPC, a comparison is implemented
between the MPC and the most efficient meta-heuristic
algorithm employed in this thesis, which is WCA. MPC and
AVR control system are executed in MATLAB toolbox and
MATLAB/Simulink.
Another contribution performed in this thesis is studying
the saturation characteristic of the DC exciter model. The
saturation characteristic of the exciter model is combined with
the AVR model to make the model more accurate and realistic.
By this overall model, the output response of the AVR control
system is analyzed.