Download ii. restructured environment

International Journal on Advanced Computer Theory and Engineering (IJACTE)
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Optimization and Simulation of AGC in Restructured system with
SMES and PID controllers using ITSE Technique
1
Athira Elizabeth Alex, 2Aju Thomas
P.G Student, Dept of EEE , Assistant Professor, Dept Of EEE
Email: 1athiraboaz@gmail.com, 2aju0016272@gmail.com
Abstract--- This work which considers some aspects of
AGC with the use of SMES and PID controllers in
restructured system. This article gives the importance of
SMES control technology and the applications of PID
controllers in an electric power system. Gain settings of the
PID controllers are optimized using Genetic Algorithm
(GA) by minimizing a quadratic performance index
following a step load disturbance in area1in restructured
system. Simulation ,optimization and comparison of
dynamic responses without SMES and PID controllers and
with SMES and PID controllers in deregulated
environment with the presence of GRC, that gives the
performance of SMES and PID controllers to damp out the
frequency and tie-line power deviations from their nominal
values after a step load disturbance.
Keywords--- AGC, ACE, Hydro-thermal, SMES.
I. INTRODUCTION
The Interconnected electric power utilities throughout the
world faces a problem of maintaining power system
frequency and tie-line power deviations from their
nominal values
after a load perturbation. Major
Restructuring process has been adapting for reducing the
energy problems of industrial sectors. The new
emergence of GENCO’s ,TRANSCO’s and DISCO’s in
the sector, they played a different role in the system.
Recent literature studies which ensures[1-6], the
simulation and optimization of AGC in the restructured
environment with two area system. This paper work
deals the market structure with integrated industry. Here
gives the feasibility of improving the performance of
AGC in Two area Hydro thermal system in deregulated
environment with capacitive energy storage system and
PID controllers.
II. RESTRUCTURED ENVIRONMENT
The deregulated environment used in such a way that the
GENCO’s which have contracts with Disco’s. Figure 1
shows that two GENCO’s which have contracts with two
DISCO’s. GENCO1 and GENCO2 which have contracts
with DISCO1 and DISCO2. After Tie-line GENCO3 and
GENCO4 have contracts with DISCO3 and DISCO4.[2-5]
GENCO’s are generation companies , DISCO’s are
distribution
companies
and
TRANSCO’s
are
transmission companies.
Fig.1 Schematic representation of Two area system in
Deregulated environment
The Disco Participation Matrix which is used in the two
area hydrothermal system by the equation makes the
realization of the contracts feasible
 cpf 11
cpf 21
I.
DPM  
 cpf 31

cpf 41
cpf 12
cpf 22
cpf 32
cpf 42
cpf 13
cpf 23
cpf 33
cpf 43
cpf 14 
cpf 24 
..............(1)
cpf 34 

cpf 44 
The case which selected here is
 0.5
 0.5
DPM  
 0

 0
0
0
0
0
0.5
0.5
0
0
0
0
 .................(2)
0

0
The sum of entries in a column should be one. Area
control error factors which is used here are apf11=0.5,
apf12=1-0.5=0.5, apf13=0.5 and apf14=1-0.5=0.5.
In the steady state condition, the generation of GENCO
should match with the demand of DISCO in contract
with it. The desired generation of GENCO in p.u Mw can
be expressed in terms of cpfs and total demand of
DISCOS as
PMgdi 
NUNIT

Cpfgdij  PLgdj................(3)
j 1
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International Journal on Advanced Computer Theory and Engineering (IJACTE)
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PLgdj is the total power demanded by DISCO j
NUNIT

cpfij  1.0, j  1, 2......NDISCO
i 1
Let us consider the case above, we will get the equations
such that
PMgd 1  0.5  PLgd 1  0.5  PLgd 3  0.1 p.u.Mw
III. SUPERCONDUCTING MAGNETIC
ENERGY STORAGE
The SMES which is used here to damp out the
oscillations of power and frequency caused by small
perturbations to the load. SMES is a technology based
on the ability of superconductors to carry high dc
currents with essentially and have no resistive loss in
the presence of significant magnetic fields, and directly
storing electrical energy.
Therefore
for the
implementation of SMES a power handling system is
needed. This is also called power conditioning system
(PCS).[6] SMES systems are almost connected to an ac
power system, but the superconducting coil is inherently
a dc device. Thus, some means of converting ac to dc
and back is necessary, which is accomplished by the
power conversion system with a 12 pulse converter and
a wye delta connected transformer arrangement [11].To
study the effect of SMES on AGC.. The voltage across
capacitor can be given as Ed. Assuming the losses to be
negligible.[4-6]. . The converter is an ac-to-dc rectifier
and dc-to-ac inverter that changes the alternating current
from the utility into the direct current that must flow
continuously in the coil.
Ed = 2Edo cos - Id RD -------------------------- (4)
Commutating Resistor
in the load demand, the stored energy is almost released
through the PCS to the power system as alternating
current. In this case, the coil immediately gets charged
towards its full value, thus absorbing some portion of the
excess energy in the system and as the system returns to
its steady state, the excess energy absorbed is released
and the coil current attains its normal value. The control
of the converter firing angle α provides the dc voltage
appearing across the inductor to be continuously varying
within a certain range of positive and negative values.
The inductor is initially charged to its rated current Id0 by
applying a small positive voltage. Once the current
reaches its rated value, it is maintained constant by
reducing the voltage across the inductor to zero since the
coil is superconducting [11-12].
As the governor and other control mechanism start
working to set the power system to new equilibrium
condition. Similarly, If there is a sudden rise in the
demand of load, the stored energy is almost immediately
released through the PCS to the grid. The bypass SCR’s
are used to provide a path for the current Id in the event
of a converter failure. A dc breaker allows Id to be
diverted into energy dump resistor RD if the converter
fails followed by reversal switch arrangement.
IV. BLOCK DIAGRAM FORMULATION
Figure 3 shows the formulation of hydrothermal system
with Super conducting magnetic energy storage system
in deregulated environment .The load changes whenever
the power demanded by DISCO changes, that will shows
in the area of local load according to the DISCO changes.
The capacitive energy storage system is connected to
both thermal and hydro area. The controller which is
used here is PID controller.
The GRC which is considered here is 10% minimum in
thermal area and about 270% per minimum for the
raising of generation and 360% per minimum for the
lowering of generation in hydro area.
Rc
DC Breaker
Ed
L
The advantages of PID controller which is used here
includes[2]

This done to improve the dynamic responses

Integral control action sometimes produce
oscillatory response and also increases the settling
time

The PID controller is a device which produces a
control signal consisting of three terms-one
proportional to error signal, another one
proportional to integral of error signal and the third
one proportional to derivative of error signal

Derivative action is sensitive to measurement noise

By the implementation of PID controllers the rate of
change of oscillations decreases with respect to
time.
Super
12 pulse
Transformer
Bypass
conducting
Thyristors
Coil
bridge
converter
Fig 2. SMES circuit diagram
By adjusting firing angle  the capacitor voltage Ed can
be made to vary from maximum negative value to
maximum positive value.
The superconducting coil can be charged to a set value
from the grid during normal operation of the power
system. Once the superconducting coil gets charged, it
conducts current with no losses as the coil is maintained
at extremely low temperatures. If there is a sudden rise
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International Journal on Advanced Computer Theory and Engineering (IJACTE)
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is carried out randomly and the search is utilized for the
next search.
ACE which is used here is apf11=0.5, apf12=1-0.5=0.5,
apf13=0.5 and apf14=1-0.5=0.5.
4
best fit
2
x 10 ga convergence for system without pid
1
0
0
10
20
30
40
generation
50
60
Fig.4 a. GA convergence of system without PID
Fig 4 a. shows the GA convergence using SMES
without PID.
ga convergence for system with pid
Fig 3. SMES Block diagram in restructured system
V. STATE SPACE REPRESENTATION OF
HYDROTHERMAL SYSTEM IN
DEREGULATED ENVIRONMENT
best fit
0.04
0
The state space representation of the system which is
used in figure 3 is,
X   f 1 f 2
X=AX+BU
X is the state vector,
ptie12 pg1 pg 2 pg 3 pg 4 
U  U1U 2
T
Where,
0.02
0
Genetic Algorithms which are used for the optimization
and learning based on mechanism of genetic evaluation.
This is a multitude of search technique. The search which
100
Figure shows the plot of best fit with generation.
Table 1 shows the values of integral gain settings of area
1 and area 2 without SMES and PID controllers and with
SMES and PID controllers in deregulated environment
TABLE 1
Optimum values of integral and PID gain settings of
objective function with and without SMES and PID
controllers for a step load disturbance of 1% in both areas
Step load
disturbance
The performance index,
The performance index is minimized for obtaining
optimum value of gain setting for two areas[9-10].
80
.
The integrator gain settings of hydrothermal area is
optimized by ITSE technique. The optimization tool
which is used here is Genetic Algorithm[6].
J  (f 12  f 2 2  ptie12 2 )t.dt...................(5)
40
60
generation
Fig 4 b. GA convergence with PID using SMES
B is the real constant matrix [3]
VI. OPTIMIZATION OF INTEGRAL GAIN
SETTINGS OF TWO AREA
HYDROTHERMAL SYSTEMS IN
DEREGULATED ENVIRONMENT
20
0.01p.uMw
Optimum
integral
gain
settings
of
thermal
and
hydro
area
without SMES
and
PID
controllers
Thermal area
K11=-0.6345
Hydro area
K12=-2.0184
Optimum integral gain
settings of thermal and
hydro area with SMES
and PID controllers
Thermal
area
KP1=1.3767
Ki1=10.7392
Kd1=1.2780
Hydro
area
KP2=
0.6408
Ki2=0.3151
Kd2=
2.7528
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International Journal on Advanced Computer Theory and Engineering (IJACTE)
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VII. DYNAMIC RESPONSES OF
TRAJECTORY SENSITIVES
the areas. The change in power generation (Pg1 and
Pg2 in area 1 and Pg3 and Pg4 in area 2) are plotted
and compared. Pg1 and Pg2 in which the change in
power settles at
0.005 Mw. There is no step load
disturbance in area2 soPg3 and Pg4 settles at 0Mw
Figure 5 shows the dynamic responses of trajectory
sensitives in two area hydrothermal system in
deregulated environment
It gives the dynamic responses of frequency deviation
and tie-line power deviations
in deregulated
environment without SMES and PID controllers and with
SMES and PID controllers in area 1 and area 2 for a step
load disturbance of 1%
Figure 5. The dynamic responses of trajectory ssensitives
with frequency deviations and tie line power deviations
for 1% step load perturbation in area 1 and area 2 with
and without SMES and PID controller in deregulated
environment
Figure 6 The dynamic responses of change in power
generation in both the areas following a 1% step load
perturbation in area 1 and area2
Figure 6 shows the dynamic responses of trajectory
sensitives with it’s change in power generation in both
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International Journal on Advanced Computer Theory and Engineering (IJACTE)
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VIII. CONCLUSION
TR1 = TR2 = 10 s
The paper work ,which is made for the comparison of
results with SMES and PID and without SMES and PID
controllers in the deregulated environment. Here the base
case has been examined and found that the system with
SMES and PID gives better results than the system
without SMES and PID. At the same time it is observed
like that AGC has been forced the power error and the
deviations of frequency to zero in steady state by the use
of these controllers.
KR1 = KR2 = 0.5
The control scheme of SMES has been proposed here to
make the power demand to their ACE participation
factors.
IX. APPENDIX
R1 = R2 = R3 = R4 = 2.4 Hz / p.u MW
D1 = D2 = 8.33×10-3 p.u MW / HZ
B1 = B2 = 0.425 p.u MW / Hz
TG1 = TG2 = TG3 = TG4 = 0.08 s
P1 = 0.01 p.u MW
P2 = 0 p.u MW
Kp1 = Kp2 = Ki1 = Ki2 = Kd1 = Kd2 = -0.5
(C) Capacitive Energy Storage Data
C = 1.0f
A) Nomenclature
i Subscript referred to area i (1, 2, 3,4,5).
KACE = 70kA/ unit MW
Hi = inertia constant of area i (MW/sec)
TDC = 0.05 s
PDi = Incremental load change in area i (p.u)
Kvd = 0.1 kA/kV
Di = Pdi / fi (p.u/Hz)
Edo = 2kV
Pri = Rated power of area i (MW)
Pgi = Incremental generation change in area i (p.u)
REFERENCES
[1]
Vaibhav Donde,M.A.Pai, "Simulation and
Optimization in an AGC System after
Deregulation", IEEE Transactions on Power
Systems, Vol.16,No.3 AUGUST 2001
[2]
H. A Peterson, N. Mohan, R. W Boom;
“Superconductive energy storage inductorconvertor units for power systems,” IEEE
Transactions on Power Apparatus and Systems,
vol.PAS-94, no.4, pp.1337-1348, July 1975.
[3]
Ibraheem, Prabhat Kumar, D.P. Kothari, " Recent
Philosophies of automatic generation control
strategies in power system", IEEE transactions on
power systems, vol. 20, No. 1, February 2005,
pp. 346-357.
[4]
L. PinKang, Z. Hengjun, L. Yuyun, “Genetic
algorithm optimization for AGC of multiarea
power systems,” Proceedings of IEEE
TENCON, pp.1818-1821, 2002 .
[5]
C.E. Fosha and 0.I. Elgead , "The megawatt
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[6]
S. C Tripathy, R. Balasubramanian, P. S
Chandramohanan
Nair,
“Effect
of
superconducting magnetic energy storage on
automatic
generation control considering
governor deadband and boiler dynamics,” IEEE
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Transactions on energy conservations 1991: 6:
579-585.
Ri = Governor Speed regulation parameter of area i.
(Hz/puMW)
Kri = Steam turbine reheat coefficient of area i
Tri = Steam turbine reheat time constant of area i (s)
Tgi = Steam governor time constant of area i (s)
Tti = Steam turbine time constant of area i (s)
Bi= Frequency bias of area i
f = Nominal system frequency (Hz)
Tpi = 2Hi / f. Di (s)
KPi= 1/Di (Hz/pu)
KIi = Integral gain of PID controller in area i
Kdi = Derivative gain of PID controller in area i
Kpi=Proportional gain of PID controller in area i
Βi = (Di+ 1/Ri) (i.e. Frequency response characteristics
of area i)ACEi=Area Control Error of area i
T = Simulation time (s)
Δfi = Incremental change in frequency of area i (Hz)
ΔPgi = Incremental generation of area i (p.u)
(B)System Data
PR1 = PR2 = 1200 MW
TP1 = TP2 = 20 s
KP1 = KP2 = 120 Hz / p.u MW

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