الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Large and/or sustained interconnection frequency deviations can cause underor
over-frequency relaying and force some loads and generator units out. Under
undesirable conditions, this may result in a cascading failure and system
frequency collapse that can lead to blackout. Therefore, the speed governing
systems of many large thermal generating units include auxiliary control
features designed to assist in limiting unit overspeed following load rejection.
These controls could adversely affect the performance of the units under system
disturbance conditions. Therefore, a local power station optimal frequency
controller is presented as a tool to ensure the sustainability of the formed
islands after uncontrollable system separation. Two-area single-reheat thermal
system is considered and it focused on an island with excess generation to be
equipped with PID controller. The PID controller is tuned using Genetic
Algorithm (GA) technique for optimal response. Results have been compared
with the conventional controller based on Zeigler-Nichols (ZN) method in order
to demonstrate the superior efficiency of the proposed (GA) technique in tuning
the PID controller. An adaptive PID frequency controller using Artificial
Neural Networks (ANN) is presented. PID controller parameters are tuned
using GA to minimize integral square error over a wide-range of tie line
interruptions. The values of the PID controller parameters obtained from GA
are used for ANN training. Therefore, the proposed technique could tune the
PID controller parameters online for optimal response at any other power
interruption. Testing of the developed technique shows that the proposed
controller could present optimal performance over a wide-range of tie line
interruptions and it capable of improving the transient frequency response of
thermal power plants. Results are provided in the form of time domain
simulations via MATLAB/SIMULINK tool.