IRJET- Stability Enhancement using Power System Stabilizer with Optimization Algorithm based PID Controller

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 05 | May 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 6712
Stability Enhancement using Power System Stabilizer with
Optimization Algorithm based PID Controller
R. Kavi priya1, Dr.R.Rajeswari2
1M.E II year, , Department of EEE, Government college of Technology, Coimbatore, India.
2 Associate Professor, Department of EEE, Government college of Technology, Coimbatore, India.
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Abstract - This paper proposes an intelligent optimization technique using Power System Stabilizer basedhybridizationwithPID
controller to enhance stability, in power system. PSS with PID Controller is used to damp inter area oscillations caused due to low
frequency electro mechanical oscillation. The problem of PID-PSS design is transformed as an optimization problem based on
performance index based Integral Absolute Error(IAE)where, MothFlameOptimization(MFO)Algorithmisemployedtoobtainthe
optimal controller parameters .The performance of the system with PSS based PI,PD,PID controller is studied and robustness of
controller is tested on a Single Machine Infinite Bus (SMIB) system under different disturbances in power system. By Simulation,
results show the effectiveness of PSS and PID performance for enhancement of power system stability. The functionality of the
proposed control strategy is verified using Matlab/Simulink
Key Words: PID, damping oscillation, power system stabilizer
1.INTRODUCTION
Power plant consists of numerous synchronous generators which are planned to convert the mechanical energy to
electrical energy which are supplied to the consumers. As there is an increase in the range of customer’s area per unit, the
load on the power system also increases. Due to this there is instability in transmission of power. The dilemma of strength
of steadiness is posed in a stern mode to promise a fine process of the generating system, and to damp the dilemma of
oscillations. In the Electromechanical systems by recovering the damping of the system (steadiness), for these purposes
signals stabilizers are introduced into the excitation system via its Terminal voltage. These helpful signals can turn
out the torques in the section with the speed variation of the generator for compensating for the section delay introduced
by the excitation system.
The power system stabilizers are beneficial in terms of cost and efficiency, are the usual means, not only to eliminate the
negative effects of Voltage regulators, butalsofordampingelectromechanicaloscillationsandsteadinessofthesystem.The
main purpose of PSS based PID is to produce an appropriate torque on the mechanical part of the generator and to
supply the better damping of power system. The PSS based PID design has formulated an optimization problem based
on various performance indices. To prove the applicability of this design, it has been validated on a SMIB power
system under different values of disturbances. The advantage of this method is that the system excitation is going to
be powerful to insert effective irrespective of disturbances. During transient condition the stabilizing signal is being
produced by PSS. Power system stabilizer isa combination of lead lag compensator, wash out filter and KPSS. Itshows
promise in many controlled environments that suffer from the classical problems of overshoot and resonance.
Thisarticle is organized as follows. Section 2 presents the description of a (SMIB)powersystem.3.Roleofpowersystem
stabilizer 4. Controlling mechanism by PID controller 5. Simulation and results 6. Conclusion of proposed work
II. POWER SYSTEM
A single machineconnected to an infinitebus through transmission line (SMIB) isconsidered in this study.The systemconsists
of synchronous generatorconnected to a power grid (infinitebus) througha transmission line. The generator isequippedwith
exciter Automatic Voltage Regulator (AVR). Fig. 1 shows the schematic line diagram of the Single-Machine Infinite Bus (SMIB)
system. Therefore, the turbine-governor dynamics is neglected. Phillips–Heffron block diagram is the linearized model of the
SMIB power system. Here, a fourth order model has been modeled. The system parameters and the nominal operating point is
given in Appendix. The modified Heffron-Phillip’s model comprises of six constants K1 to K6 and is related to the machine
parameters and the primary work state of the machine.

Figure.1. Heffron–Phillips block diagram for SMIB power system.
To calculate the values of gain, the torque, terminal voltage and the stimulation coil equations should be liberalized. And by
eliminating the Δiqs and the Δids and rewriting the equations on the basis of ΔE′q and Δδ, the coefficients are calculated.
Therefore, the m o d i f i e d constants K can now be computed based on l o c a l measurements only. In this model, as Vs
is not constant during linearization, three additional constants K1 to K3 are introduced at the torque, field voltage and
terminal voltage junction points as shown in Fig.2. The action of the PSS is effective through the transfer function block
GEP(s) as shown in Fig.2 between the electric torque and the reference voltage input with variation in the machine speed
assumed to be zero.
The expression for the transfer function GEP(s) is given by equation(1)
Where EXC(s) is the transfer function of the excitation system. It can be of any exciter, as system operational conditions
modification, the gain and phase characteristics of the transfer function GEP(s) change. Ideally, the PSS transfer
function should be the reciprocal of GEP(s) forproviding aprescribed amount of damping with speed input. This would
be strictly performing lead operation, which isnot physically realizable. Asensible approach is to own alead-lag circuit
that gives the adequate compensation over the specific variation of frequencies in the range of (0.1-2) Hz. Using the
modified K constants, stabilizers are designed using the tuning. The stabilizer considered is a simple lead-lag
compensator with a washout filter.
Table 1 Time Constant
Parameter Magnitude
Lead Time constant, T1 0.5
Lag Time constant, T2 0.05
Lead Time constant, T3 0.5
Lag Time constant, T4 0.05
Wash out Time Constant,
Tw
10
Timeconstants T1-T4 areusedinleadlagcompensator,toprovideappropriatephaseleadcharacteristic.Forphaselagbetween
exciter input and generator electrical torque, it’s a single order phase compensation circuit of frequency range of (0.1-2) HZ,
provides compensation over entire frequency range. Function of washout block is to work under only during transient
condition, during steady state condition constant Tw=0.

Table 2 Gain constants
III. POWER SYSTEM STABILIZER (PSS)
A power system is said to be stable if it remains in a state of functional equilibrium under normal operating conditions and
regain to an acceptable state of equilibrium after being subjected to a disturbance.
Figure.2. Functional block diagram of a synchronous generator excitation control system
Security of the facility systemdepends on its ability to survive any disturbances, which can occur with none interruption
within the services. Figure.3shows the practical diagramof a typical excitation system foranoutsizedsynchronousgenerator.
For the effective damping of oscillations of the rotor/turbine shaft, power system stabilizers are used. The improvement of
small signal stability could also be achieved through the facility system stabilizers. The input signal to the PSS may be rotor
speed, rotor angle, accelerating power, or a combination of these signals. The output signal of PSS is used as a supplementary
stabilizing signal. Anystabilizing signalshould turn out a torsion element in section with ∆ω,sopositivedampingcouldalsobe
made.
IV. PI CONTROLLER
Figure 3 shows the block diagram of PSS based PI controller. Proportional-plus-integral controller consist of two terms
producing an output which one is proportional to the input signal and other proportional to the integral of input signal. It
improves the relative stability and steady state tracking accuracy.
Figure.3.Block diagram of PSS-PI controller
PD CONTROLLER
Proportional- derivative controller produces an output which consists of two terms, where one is proportional to
input signal and other proportional to the derivative of input signal. The PD controller increases the damping of the
system which results in reducing the peak overshoot. Figure 2 shows the block diagram of PSS based PD controller.
Figure.4.Block diagram of PSS-PD controller
K1 1.0749 K2 1.2576
K3 0.3072 K4 1.7124
K5 -0.3988 K6 0.4657

PID CONTROLLER
PID controller stabilizes the gain, reduces the steady stateerrorandpeakovershootofthesystem.Figure3showsthe
block diagram of PSS based PID controller.
Figure.4.Block diagram of PSS-PID controller
V. PROPOSED ALGORITHM
In the proposed MFO algorithm, it’s a population-based algorithm. Where candidate solutions are moths and the
problem’s variables are the position of moths in the space. Therefore, the moths can fly in 1-D, 2-D, 3-D, or hyper
dimensional space with changing their position vectors. Since the moths and flames are both solutions. The difference
between them is the way we treat and update them in each iteration. The moths are actual search agents that move
around the search space, whereas flames are the best position of moths that obtains so far.
A logarithmic spiral as the main update mechanism of moths in this paper. However, any types of spiral can be
utilized here subject to the following conditions:
 Spiral’s initial point should start from the moth
 Spiral’s final point should be the position of the flame.
 Fluctuation of the range of spiral should not exceed from the search space.
Considering these points, I defined a logarithmic spiral for the MFO algorithm as follows:
Spiral movement is the main component of the proposed method because it dictates how the moths update their
positions around flames. The spiral equation allows a moth to fly “around” a flame and not necessarily in the space
between them.
Therefore, the exploration and exploitation of the search space can be guaranteed. The logarithmic spiral, space around
the flame, and the position considering different t on the curve are illustrated as follows
Figure.5. Logarithmic spiral
Formula to update the number of flames

The MFO algorithm is three-tuple that approximates the global optimal of the optimization problems and defined as
follows:
I function that generates a random population of moths and corresponding fitness values.
P function, which is the main function, moves the moths around the search space. This function receivedthematrix ofM
and returns its updated one eventually.
T function returns true if the termination criterion is satisfied and false if the termination criterion is not satisfied
With I, P, and T, the general framework of the MFO defined.
VI. SIMULATION RESULTS AND DISCUSSION
In order to demonstrate effectiveness of proposed PSS based PID, obtained dynamic responses are obtained by employing
PID-PSS. It is clear from Fig. 7 - 8 that the deviation profilesobtained by applying PSS based PI,PD,PID are significantly damped
with minimum peak error, the shortest settling time, and zero steady state error. It means that surpassing improvement in
damping characteristics and stability measures is obtained by employing the PSS based PID.
Figure.6. Simulation of PSS-PID
Simulation of PSS based PID controller in an SMIB system with AVRexciter, field circuit, inertial load, with mechanical
and electrical torque, PID provides a stabilizing signal to SMIB system. Kp,Ki,KdarevaluesofPIDcontroller,each value
of gain is used to determine the waveform. Values of PID control play a vital role in determining overshoot, peak time,
settling time. The fractional constants µ and are not integer ,they detect time of differentiation and integration.
Figure .7. Simulation with PSS-PI controller
SMIB system with PSS-PI controller as shown in fig 7 ,whereby change in rotor angle with respect to time ,oscillations are
high and time taken to reach settling time is high.

Figure .8. Simulation with PSS-PD controller
SMIB system with PSS –PD controller as shown in fig 8 ,derivative control plays a vital role in reducing peak overshoot and
damping out oscillations.
Figure .9. Simulation with PSS-PD controller
SMIB system with PSS –PID controller as shown in fig 9 ,integral and derivative control plays a vital role in reducing peak
overshoot and damping out oscillations and attaining equlibrium point.
VII. PERFORMANCE INDICES
The common Performance indices are used in practice is as below,
1) Integral Square Error ISE=∫e 2 (t)dt
2) Integral of the absolute magnitude of error IAE=∫│e (t)│dt
3) Integral Time-absolute error ITAE=∫ t.│ e (t) │dt
4) Integral Time-Square error (ITSE) ITSE=∫ e2 (t) dt
Here e(t) is the error response of a system. Generally limit of integration is from 0 to∞butintegrationuptoinfinityis
not practical and hence limit ∞ is replaced by T which is chosen sufficiently large so that e(t) for t >T is negligible.
Figure .10 Performance indices
VIII.CONCLUSION
This paper presents PSS based PID controller, optimized with MFO algorithm, to enhance damping of power systemlowfrequency
oscillation. Dynamic characteristics of SMIB equipped with PI,PD,PID-PSS have been evaluated by time domain simulations in
MATLAB/SIMULINK investigation of numerical simulations shows that the application ofproposed PSS based PID is more insightful.

Performance of controller are verified under sever disturbances. Since the PSS based PID outperforms the former stabilizers to obtain
superior dynamic performance and to give more robustness to the uncertainties. Future scope of this research can be directed towards
application of FOPID controller in flexible ac transmission system(FACTS)-based power oscillation damping (POD) controllers and its
coordinated design with the FOPID-PSS.
APPENDIX:
The parameters of the studied SMIB power system are taken from literature [1] as below:
Common system parameters:
Rated (Base) operating frequency ( xb) = 314 rad/s.
Rated complex power (Sb) = 160 MVA. Rated voltage (Vb) = 15 kV.
Synchronous generator parameters
Synchronous d-axis reactance (Xd) = 1.7 p.u.
Synchronous q-axis reactance (Xq) = 1.64 p.u. Transient d-axis reactance (X0
d) = 0.245 p.u.
Field open circuit time constant (T0
do) = 5.9 s.
Generator moment of inertia (H) = 2.37. Damping coefficient (D) = 0. Voltage regulator – exciter parameters
Exciter gain constant (KA) = 50.
Voltage regulator time constant (TA) = 0.05 s.
Transmission line parameters
Transmission line resistance (Re) = 0.02p.u. Transmission line reactance (Xe) = 0.4 p.u.
Nominal operating point
Real power (P) = 136 MW.
Reactive power (Q) = 83.2 MVAR.
Terminal voltage (Vt) = 17.3 kV 16.6.
Infinite bus voltage (Vinf) = 15 kV 0. Rotor angle (d) = 49.16.
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