IEEE Systems, Man and Cybernetics Magazine - July 2021 - 33

compared with some of the existing methods from
the literature. The choices of literature for the comparative
study include different control and optimization
techniques.
In [16], the authors proposed a PI controller for the
considered load frequency control problem. The controller
gains are tuned through the FA. In [27], the author
proposed imperialist competitive algorithm (ICA)-based
fuzzy-assisted PID and PI controllers [FPIDF-(1 + PI)] for
the frequency control. In [35], the authors proposed an
adaptive PI controller and integrated population extremal
optimization (PEO) framework to obtain the gains of
the controller.
In [17], the author proposed a scaling factor-based
fuzzy PI controller with the ICA. In [20], the author proposed
an ICA-based fuzzy PID controller with a filter plus
a double integral controller for the LFC problem in the PV
integrated thermal system. Undershoot (),Us
(),ts
settling time
and ISE are considered to demonstrate the results.
A comparative performance of the system is tabulated
in Table 2. The value of the objective function
() .0 000198
ISE =
by the proposed method is improved significantly
in comparison to the PI-GA [16], PI-FA [16], adaptive
PI-PEO [35], FPI-ICA [17], FPIDF-II-ICA [20], and
FPIDF-(1 + PI)-ICA [27].
It is observed from Table 2 that undershoot of the frequency
responses of areas 1 and 2 as well as the power
deviations in the tie line is significantly improved versus
all of the cited references. The settling time of frequency
deviations in areas 1 and 2 as well as the power deviations
in the tie line are also improved. The frequency
responses of the system for area 1 are shown in Figure
2(a). The frequency responses of area 2 and the tieline
power deviations are shown in Figure S1(a) and (b),
respectively. Furthermore, the performance of the
system considering L3
as an objective function is available
in " Additional Information. "
Case B: Sensitivity Analysis of the Controller Against
Parametric Uncertainty in the System
A sensitivity analysis of the controller performance is
done when the PV integrated thermal power system is
subjected to the parametric uncertainties. Different
parameters of the power system change depending upon
different operating conditions in power systems [7], [27].
In situations like this, the controller should be robust
enough to tackle the variations.
In this study, different variations in system parameters
are considered. The robustness of the proposed controller
is tested against +25% or -25% variations in
KT Tt T ,sg
ps ps
,, ,
and R [27]. All such variations in the power system gain
and time constants are considered individually for each
parameter and also simultaneously. These parametric
variations are tested against the controller gains mentioned
in case A.
The performance of the system is obtained for a stepload
change of 10% in area 2 at time t 0s=
. The performance
indices considered in this case are the maximum
peak Mp
(in hertz or p.u. megawatt), settling time t ,ss
and
error index ISE. The results of the sensitivity of the controller
IEEE Systems, Man and Cybernetics Magazine - July 2021

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