CONTROL OF THREE AREA INTERCONNECTED POWER SYSTEM USING SLIDING MODE CONTROLLER

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CONTROL OF THREE AREA INTERCONNECTED POWER SYSTEM USING
SLIDING MODE CONTROLLER
LEKKALA PRASANTHI, V. MOUNIKA, K.T.PRASANTHI, V. BRAMHAIAH
---------------------------------------------------------------------***----------------------------------------------------------------------
ABSTRACT
Multi-area power systems are growing rapidly
due to deregulation, where several distant regions can
share a scheduled amount of power via tie lines.
Generally, a power system is considered to be a highly
nonlinear and large-scale multi-input multi-output
dynamical system with numerous variables, protection
devices, and control loops. Power system controls are
applied to keep the power system in a secure state, and
frequency control is an important control problem in
power system design and operation. Moreover, in view
of the power supply-and-demand issues in multi-area
power systems, load frequency control (LFC) is
extensively applied to balance the tie line power and
frequency despite of the load fluctuations. In the past
decades, considerable efforts have been made to solve
the LFC for multi-area power systems, and many
different control strategies have been proposed to
achieve the desired dynamic performance, such as PI and
PID controllers, with diverse function, simple structure,
and fixed control gain, have been widely applied.
However, these conventional approaches do not work
efficiently for all operating conditions, since multi area
power systems contain a large number of nonlinearities
and uncertainties, and the conventional controller
parameters are always estimated from the model
structure and parameters.
In addition, few new LFC based control
techniques have been proven to be much more effective
and robust, e.g., optimal control, robust decentralized
control, adaptive control, and sliding mode control
methods.
In this thesis, the design of an event-triggered
DSMC algorithm is proposed for the LFC system by
solving the sequential minimization problem with a
MATLAB simulink.
INTRODUCTION
The quantification of system reserve has, until
recently, been a relatively simple and largely
deterministic process. The city’s demand for electric
energy is enormous, especially in areas where industrial
and commercial activities have rapidly developed.
However, finding a suitable site for a new substation or
new transmission line is difficult because of protests by
the residents of potentially affected neighborhoods.
Expanding the capacity of a substation or transmission
line is also difficult in urban areas. The system security
of the substation is difficult to maintain when the
substation suffers from capacity shortages or is in a state
of emergency. A suitable load management scheme is,
therefore, needed to preserve the reliability of the
systems.
Frequency drifts, upwards or downwards, in a
power system is the main indicator of the momentary
imbalance between generation and demand. If, at any
instant, power demand (taken in this thesis to be active
power only) exceeds supply, then the system frequency
falls. Conversely, if power supply exceeds demand,
frequency rises. The system frequency fluctuates
continuously in response to the changing demand and
due to the practical impossibility of generation being
controlled to instantaneously track all changes in
demand.
The obvious challenge in including loads in
frequency control is the large increase in the number of
potential participants. Even in the largest control areas,
at most a few hundred large generators contribute to
frequency control. On the other hand, participation from
the demand side might involve tens of thousands if not
millions of consumers. Though this may appear
technically daunting and economically unrealistic, it has
to keep in mind that conventional primary frequency
control is a distributed control system that relies on the
availability of the frequency as a measure of imbalance
between load and generation. Indeed, the response of
each generating unit is determined by its droop
characteristic and a local frequency measurement, not by
a signal sent from a control center. Communication to
and from the control center is used only in the slower
secondary and tertiary control loops for better economic
optimization and network security. A load or consumer
thus does not have to be plugged into a communication
network to take part in primary frequency control.
LOAD FREQUENCY CONTROL TECHNIQUES
 Load frequency control based on different
techniques.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 09 Issue: 10 | Oct 2022 www.irjet.net p-ISSN: 2395-0072

 Load frequency control with AC – DC parallel tie
line.
 Consideration of communication delay in LFC
 Load frequency control of conventional sources
integrated with distributed energy sources.
 LFC of hybrid power system integrated with
renewable energy sources.
 Application of different learning techniques in
LFC.
 Application of power electronics devices in LFC.
LOAD FREQUENCY CONTROL BASED ON DIFFERENT
TECHNIQUES
In this category, different techniques used for
implementation of LFC are discussed. The primary focus
remains on the control strategies of parameters, which
are generally the gains of controllers normally used in
forward path where area control error is the input to the
controller. In some cases governor speed regulation (R)
and frequency bias (β) are also needed to be optimized.
Depending on the different control scheme this group is
further subdivided into following subgroups:
 LFC with different optimization Techniques
 LFC With Different Feedback Theory
 LFC with Application Of Observers
 LFC Using Internal Model Control
Load Frequency Control with Different Optimization
Techniques
In the last three decades, different soft
computing techniques have developed and successfully
implemented to different complex optimization problem.
Power system optimization is no exception to this trend.
Soft computing techniques which are successfully used
to solve load frequency control problem include Genetic
Algorithm (GA), Particle Swarm Optimization (PSO),
Bacterial Foraging Algorithm (BFA) and Differential
Evolution (DE). In order to solve the optimization
problem more effectively different artificial intelligence
techniques are combined in hybrid manner. For instance
a Fuzzy logic control scheme in combination with other
optimization technique is very useful to ensure the
robustness of the system.
Load Frequency Control with Different Feedback
Theory
Development is a never ending process. Application of
different development on feedback theory on LFC is also
reported [26] – [30]. In fact different feedback theories
were used as controlling tools in these LFC studies. A
robust decentralized LFC in deregulated environment is
presented in [26]. The LFC problem was solved as a
multi objective control problem using H2/H∞ control
technique. A robust controller was designed by reducing
the LFC problem in static output feedback control.
Rakhshani et al. designed a linear quadratic
regulator for load frequency control in a deregulated
environment in [27]. The proposed optimal output
feedback regulator overcame the necessity of measuring
all the state variables of the system. In the proposed
design only the measurable state variables within each
control area were required to use for feedback.
Comparison of the performance of the proposed
regulator with the performance of full state feedback and
state observer methods had also been carried out.
Role of novel robust decentralized controller
had been demonstrated to solve the load frequency
control (LFC) problem in a restructured power system
[28], [29]. Quantitative feedback theory (QFT) was used
here to construct the proposed controller. The main
feature of this modified dynamic model of LFC was that
in different contracted scenarios, the effects of the
possible contracts behaved as a set of new input signal.
Comparative study between the QFT based proposed
controllers and the conventional controller proved the
superiority of the first one. It had been proved that for a
large variation in system parameters proposed QFT
based controller is superior [29]. Proportional – integral
(PI) state feedback controller to solve the load frequency
problem. This study was aimed to find the proper
governor speed regulation parameter (R) and
participation factor in AGC for each generator. The study
was carried out on the system which consists of hydro,
thermal and gas generating units [30].
Load Frequency Control Using Observer
Load frequency control monitors a lot of component of
power system which are directly or indirectly related to
LFC. Hence observer takes a vital place in LFC as it
observes minute to minute condition of every
component that ensures frequency deviation remains
within the prescribed limit. The advantages of observer
concept were successfully used to solve load frequency
control problems [31] - [33].
Rakhshani et al constructed a reduced order
observer controller to eliminate the problem of
measuring and monitoring all the state variables at all
time. This proposed scheme was found effective when
the system runs with lesser numbers of sensors than
numbers of states. With the help of reduced order
observer multi area LFC problem was solved with
improved dynamic responses in deregulated
environment. LFC of a two area power system using a
global proportional – integral (PI) state feedback
controller based on quasi – decentralized functional

observers (QDFOs) theory was presented in another
work [32]. Unlike conventional observers which were
used as a centralized one for all areas in LFC, a low order
observer was used for each area. Though they are
completely decoupled from each other some outputs
were shared between them to get a global control. The
overall complexity of the system was reduced by using
the proposed method.
Moreover, a decentralized sliding mode control
scheme was also used [33] to solve LFC problem of three
area interconnected power system. The robust controller
was based on reaching law method to achieve better
performance and to make frequency deviation zero after
any load variation or any system variation.
Use of Internal Model Control in Load Frequency
Control
Internal model control is another control
method which provides a new methodology for solving
load frequency control problem. The primary concept of
this control method is similar to that of observers. This
control scheme is employed in LFC to reduce the
complexity of the problem. Recent trends towards
restructuring of power system and interconnected
system makes the load frequency control more complex.
As the area increases order of the system also increases
which in turn increases system complexity. Hence
internal model control (IMC) scheme is applied in LFC to
reduce the order of the system. Internal model control
(IMC) was successfully applied in AGC [34] - [37].
Successful application of IMC based on two – degree of
freedom concept in load frequency problem is presented
in [34], [35] in which second order plus dead time
(SOPDT) is used instead of full order system [35]. In a
model predictive control scheme for LFC [36], focus was
on neural network model predictive controller. The
performance of the proposed controller was investigated
over a wide range of system parameters. Another model
predictive control (MPC) scheme for AGC [37] was used
for a large control area. Each sub area consists of its own
MPC controller.
Consideration of Communication Delay in LFC
In restructured power system, the competitive
open access strategy makes the load frequency problem
more complex and its performance worse. To overcome
this unwanted situation open communication
infrastructure is needed. Unlike the traditional closed
communication network, time delays are not fixed for
the new open communication network. Hence, automatic
generation control achieves more perfection with the
consideration of communication time delay. Automatic
generation controls with delays are also presented.
Again some studies are done by considering a limit of
delay where some are without any margin. Hence LFC
study in this group is further subdivided as follows:
 Communication delay with no margin.
 Communication delay with margin
SIMULATION RESULTS
INTRODUCTION
In order to show some important features of the
proposed LFC model, the results of several different
simulation studies are reported in this Chapter for a
three-area power system. In order to make a fair
comparison, design procedure has been employed for
controller design for both systems. In order to validate
the proposed topology, simulation is carried out using
the Matlab/Simulink.
PROPOSED TOPOLOGY
Block-diagram representation of an ith area power
system model
The dynamic model of the multi area power
system as is shown in Fig.5.1. According to the LFC
scheme, both the frequency of the control area and the
interchange power through the tie-line should be kept in
the nominal values. Consequently, the measure of area
control error (ACE) is proposed.
We solved the LFC problem in multi-area power
system under the event-triggered SMC scheme, in which
the corresponding networked sliding mode dynamics are
given. First, sufficient conditions of performance analysis
are proposed to guarantee the networked sliding mode
dynamics to be asymptotically stable with a prescribed
energy-to-energy performance. Then, the discrete-time
sliding mode controller is designed for each subsystem.
SMC law is synthesized to guarantee that each
subsystem trajectories can be kept in the pre-specified
sliding mode region within a finite time.

SIMULATION RESULT ANALYSIS
Frequency variation of three area interconnected power
system
Fig.5.3: Tie-line response of three area interconnected
power system
The responses of Δfi and ΔPtie−i in the three areas
are shown in Figs. 5.2 and 5.3. It can be seen that the
frequency deviation and tie line power deviation reach
to zero with the designed event-triggered sliding mode
controller.
Fig.5.4: State responses of LFC scheme with ε = 0.1 for
Area 3
Fig.5.5: State responses of LFC scheme with ε = 0.6 for
Area 3
Figs.5.4 and 5.5 are given to show the different
responses of the state responses and the release instants
and release intervals for Area 3, under the conditions
that event-triggered parameters ε = 0.1 and ε = 0.6,
respectively.
CONCLUSIONS
A sliding mode controller was designed to
ensure that the each subsystem in the multi-area power
system was stable and robust to external disturbance,
including load variation and frequency fluctuation.
Finally, the feasibility and effectiveness of the proposed
design techniques were illustrated by example and
simulation. Further research in this area could further
improve the proposed algorithm, such as extending the
present methods to LFC of power systems against
delayed input cyber-attack, and handling the case where
some of the LFC system state components
REFERENCES
1. M. Alrifai, F. Hassan, and M. Zribi, “Decentralized
load frequency controller for a multi-area
interconnected power system,” Int. J. Elect. Power,
vol. 33, no. 2, pp. 198–209, Feb. 2011. doi:
10.1016/j.ijepes.2010.08.015.
2. C. K. Ahn, P. Shi, and M. V. Basin, “Two-dimensional
dissipative control and filtering for roesser model,”
IEEE Trans. Autom. Control, vol. 60, no. 7, pp. 1745–
1759, Jul. 2015. doi: 10.1109/TAC.2015.2398887.
3. C. K. Ahn, L.Wu, and P. Shi, “Stochastic stability
analysis for 2-D roesser systems with multiplicative
noise,” Automatica, vol. 69, pp. 356–363, Jul. 2016.
doi: 10.1016/j.automatica.2016.03.006.
0 5 10 15 20 25 30 35 40 45 50
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0.1
0.12
Time (s)
Delta
f
f1
f2
f3
0 5 10 15 20 25 30 35 40 45 50
-0.15
-0.1
-0.05
0
0.05
0.1
Time (s)
state
response
delta Ptie1
delta Ptie2
delta Ptie3
0 5 10 15 20 25 30 35 40 45 50
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0.1
Time (s)
State
response
delta f3
delta Pm3
delta Pg3
delta Ptie3
0 5 10 15 20 25 30 35 40 45 50
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0.1
0.12
Time (s)
State
response
delta f3
delta Pm3
delta Pg3
delta Ptie3

4. H. Bevrani, Robust Power System Frequency
Control. New York, NY, USA: Springer, 2009.
5. M. Chadli and M. Darouach, “Further enhancement
on robust H∞ control design for discrete-time
singular systems,” IEEE Trans. Autom. Control, vol.
59, no. 2, pp. 494–499, Feb. 2014. doi:
10.1109/TAC.2013.2273266.
6. M. Farahani, S. Ganjefar, and M. Alizadeh, “PID
controller adjustment using chaotic optimisation
algorithm for multi-area load frequency control,” IET
Control Theory Appl., vol. 6, no. 13, pp. 1984–1992,
Sep. 2012. doi: 10.1049/iet-cta.2011.0405.
7. F. Fang and Y. Xiong, “Event-driven-based water
level control for nuclear steam generators,” IEEE
Trans. Ind. Electron., vol. 61, no. 10, pp. 5480– 5489,
Oct. 2014. doi: 10.1109/TIE.2014.2301735.
AUTHORS
1. LEKKALA PRASANTHI,
M.Tech Scholar
Dept. of Electrical & Electronics Engineering,
TECH COLLEGE, TADIPATHRI.
2. V. MOUNIKA,
Assistant Professor,
3. K.T.PRASANTHI,
TECH COLLEGE,TADIPATHRI.
4. V. BRAMHAIAH

CONTROL OF THREE AREA INTERCONNECTED POWER SYSTEM USING SLIDING MODE CONTROLLER

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