الفهرس 
Title : Automatic Generation Control of an Interconnected Power System Using Fractional order PID Controller Based on Recent Optimization Techniques
SummaryOnly 14 pages are availabe for public view
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Abstract
In this thesis, different types of controllers (Integral, Proportional Integral and Fraction
order (FO-PI) are used to obtain the controller gain for Automatic Generation Control
(AGC) to represent the Simplified Egyptian Power System (SEPS) to achieve the growth
of electric power for the sustainable development of Egypt. The main task of AGC is to
bring back the frequency to its nominal set point and reduce power fluctuation due to
unscheduled tie-line power flows among neighboring control areas.
The suggested controllers are designed using real statistical data of the Egyptian Power
System (EPS) for minimum and maximum loading conditions of the EPS during winter
and summer of 2019-2020. The effectiveness of the proposed controller is illustrated by
applying the suggested controller and studying the effect of the outage of the largest
generation unit in the EPS like (South Helwan 650 MW) on the grid frequency.
First, the thesis explains the methodology for building the new model of SEPS as a
representation of updated EPS as well as presenting historical and updated models and
then applies the proposed controllers to this SEPS model.
As classical PID controllers practically suffer from some restrictions. These could be
insufficiency and low efficiency as well as inability to handle nonlinear systems. Recent
optimization approaches like Particle Swarm Optimization (PSO), Jellyfish Search
Optimizer (JSO) and Coyote Algorithm Optimization (COA) are considered to be
valuable for LFC, which can overcome the weakness of conventional or classical
controls.
The gains of Integral controller parameters in addition to the gains of Fractional Order
FO-PI controller parameters such as proportional, integral, and order of integrator (λ), are
optimized using different Particle Swarm Optimization (PSO) algorithms, Then the best
PSO gain is determined to compare with other recent algorithms such as Jellyfish Search
Optimizer (JSO) and Coyote Optimization Algorithm (COA) for different loading
scenarios.
The results present that the suggested controllers based on recent optimization
approaches provide the best dynamic response for a step load change. MATLABSimulink
software is used for obtaining the results. The obtained results are promising
and encouraging.