PERFORMANCE ANALYSIS OF A NONLINEAR AUTOMATIC GENERATION CONTROL FOR AN
INTERCONNECTED ELECTRIC POWER SYSTEM USING FRACTIONAL ORDER SLIDING MODE
CONTROL
Abstract
The structure of the interconnected electric power system and the
increasing quality of energy have led to an increased importance of
Automatic Generation Control, or AGC. The tie line powers and frequency
must be maintained within the permitted standard values. This work
applies to Automatic Generation Control in a nonlinear model of an
interconnected electric power system using a fractional order sliding
mode controller. Three sections of a nonlinear interconnected electric
power system are controlled by a fractional order sliding mode
controller. The block diagram of the power plant model system considers
the nonlinearities that are physical limits, such as governor dead band
and generation rate constraints. In the presence of various load changes
(sudden load change frequency), parameter uncertainty (variation), and
the existence of physical constraints, the control’s goal is to manage
the frequency deviation (load frequency error) and tie-line power
deviation (tie-line power error) of the interconnected power system.
Three sections of an interconnected power system with nonlinearities are
used to simulate the fractional order sliding mode controller (FOSMC).
These designs display the best performance of the suggested FOSMC
controller, with numerical values for tie line power deviation of
2.9765e-5p.u. and frequency deviation of 6.8912e-4Hz. The suggested
system has reduced nominal values as compared to SMC for the frequency
deviation of 2.0762e-3Hz and tie line power deviation of 1.21754e-3p.u.,
as well as for PID controller frequency deviation of 3.5918e-3Hz and ti
line power deviation of 1.5602e-3p.u. These comparisons further
demonstrate that, even in the presence of parameter variation, load
changes, and nonlinearities in the system, FOSMC performs the best, with
reduced undershoot (5.4823e-4), overshoot (1.5545e-4), rising time
(1.00042e-8), and settling time (2.688). MATLAB/Simulink has been used
to create and simulate the controllers for the system model.