International Electrical Engineering Journal (IEEJ)
Vol. 5 (2014) No.12, pp. 1639-1648
ISSN 2078-2365
http://www.ieejournal.com/
Firefly Algorithm based Optimal Power Flow with
Static VAR Compensator for Improvement of Power
System Security under Network Contingency
B.Venkateswara Rao* , G.V.Nagesh Kumar *
*
GITAM University , Visakhapatnam, Andhra Pradesh, INDIA
Corresponding Author: gundavarapu_kumar@yahoo.com

Abstract— At present owing to the increase in power demand
power system have become more complex and heavily loaded,
and are subjected to unstable or insecure operations. In order to
provide a secure operation of the power system, it is needed to
enhance the level of a security margin to the power system. In
this paper Firefly algorithm based Optimal Power Flow used to
select the optimal sizing of SVC which minimizes the total real
power generation cost is proposed. New indices like Line
security index and voltage security index are defined for
measuring Power system security. This paper was also deals
with the impact of SVC under network contingency with Firefly
Algorithm based Optimal Power Flow. The results were
presented for 5 bus system and modified IEEE 30 bus system
without and with SVC in normal operating condition as well as
network contingency by using Firefly Algorithm based Optimal
Power Flow. The results obtained with Firefly optimization
technique was compared with Genetic Algorithm (GA).
Index Terms— Flexible AC Transmission System, Firefly
Algorithm, Optimal Power Flow, Static VAR Compensator..
I. INTRODUCTION
Power systems are becoming increasingly more complex due
to the interconnection of regional system and deregulation of
the overall electricity market. It has been required to better
utilize the existing power networks to increase capacities by
installing FACTS controllers. The variables and parameters
of the transmission line, which include line reactance, node
complex voltages are able to be controlled using FACTS
controllers in a fast and effective way. The benefits derived
from FACTS include improvement of the stability of power
system networks, such as voltage stability, line stability,
small signal stability, transient stability, and thus enhance
system reliability [1, 2]. However, controlling power flows is
the main function of FACTS. Transmission lines in
congested areas are often driven close to or even beyond their
limits in order to satisfy the increased electric power
consumption. So secure operation and reliable supply is
imperiling by the higher risks for faulted lines [3]. But the
construction of additional power lines is often difficult for
environmental problems, economical problems and political
problems. In these conditions the technology of FACTS
provides a significant opportunity [4]. Power system is a
complex network consisting of more number of generators,
transformers and transmission lines. Failures of one or more
transmission lines lead to outages. Outage of transmission
line is called network contingency [5, 6]. Out of the several
preventive and corrective measures suggested in literature to
protect power system networks against voltage collapse
because of line outage, the placement of FACTS controllers
has been established as an effective means. Out of all FACTS
devices static VAR compensator (SVC) has been widely used
in power systems. This is a shunt connected FACTS device.
They can provide rapid control of the susceptance and in turn
the reactive power supply to transmission lines, which
maintain the node voltages at or near a constant level and
enhancing the power transfer capability [7, 8]. The rapid
response feature of SVC also provides many other
opportunities for improving power system performance.
This paper presents a new Meta heuristic optimization
technique called Firefly Algorithm has been introduced to
find the optimal location of SVC device to improve power
system security. Its performance is compared with Genetic
Algorithm (GA) [9, 10] technique. The real and reactive
power generation values and voltage limits for buses are
taken as constraints, along with susceptance limits of the
SVC, during the optimization. Computer simulations using
MATLAB were done for the 5 bus system and modified
IEEE 30 bus system and active power losses, voltage profile
have been consider to compare the Genetic Algorithm based
Optimal Power Flow with Firefly Algorithm based Optimal
Power Flow. This paper also deals with SVC incorporated in
GA based Optimal Power Flow and Firefly Algorithm based
Optimal Power Flow in contingency analysis to reduce the
losses and minimize the total real power generation and to
enhance loading margin under severe contingencies.
1639
Venkateswara and Kumar
Firefly Algorithm based Optimal Power Flow with Static VAR Compensator for Improvement of Power System Security under Network Contingency
International Electrical Engineering Journal (IEEJ)
Vol. 5 (2014) No.12, pp. 1639-1648
ISSN 2078-2365
http://www.ieejournal.com/
II.
PROBLEM FORMULATION
2
The objective function is formulated to find optimal size of
the SVC device by minimizing the total active power
generation cost subjected to equality and inequality
constraints.
A. Objective function
The objective function is taken to minimize the active
power generation cost through the optimal set of generations
which is expressed as:
VSI  (kN1 Vk  Vkref )
2) Line Security Index (LSI)
Line security index indicates the security level of the
transmission lines. It can be expressed as
ntl
Sk 2
max )
S
k=1 k
LSI = (∑(
ng
2
min (∑ a i PGi
F=
+ bi PGi + ci )
(1)
i=1
where ng  no.of generator buses
a, b, c are the fuel cost coefficients of a generator unit
Susceptance of SVC has been added as a control variable
along with the real power generation of generator buses for
optimization problem and SVC limits are given as:
max
min
BSVC
≤ BSVC ≤ BSVC
N
N
∑ PGi = ∑ PDi + PL
i=1
N
∑ Q Gi = ∑ Q Di + Q L
i=1
(3)
i=1
N
(4)
i=1
Where i=1, 2, 3..... N and N = no. of. Buses
PL is total active power losses
QL is total reactive power losses
N is the total number of buses
2) Inequality constraints:
i.
Voltage limits:
Vimin ≤ Vi ≤ Vimax
(5)
Where i=1,2,3,.......,N and N = no.of. buses
ii.
The Real power generation limit:
min
max
PGi
≤ PGi ≤ PGi
(6)
iii.
Reactive Power limits:
max
Qmin
Gi ≤ Q Gi ≤ Q Gi
)
(9)
S k is the apparent power in line k and S maxk is the maximum
apparent power in line k.
The security Index consists of LSI relating to line flow, and
VSI relating to bus voltage. LSI is less means the number of
overloaded lines decreases. If the VSI value is near to zero
than we can say that power system is more stable and secure.
(2)
1) Equality constraints:
(8)
V k is the voltage magnitude at bus k
Vkref is the reference voltage magnitude at the bus k
III. STATIC VAR COMPENSATOR
Static VAR Compensator (SVC) is a shunt connected
FACTS controller used to regulate the voltage at a given bus
by modulating its equivalent reactance [11, 12].
SVC
normally includes a combination of mechanically controlled
and thyristor controlled shunt capacitors and reactors. The
most popular configuration for continuously controlled SVC
is the combination of fixed capacitor and thyristor controlled
reactor. The SVC is taken to be a continuous, variable
susceptance, which is adjusted in order to achieve a specified
voltage magnitude while satisfying constraint conditions [13,
14]. SVC total susceptance model represents a changing
susceptance. The SVC (Static Var Compensator) may have
inductive or capacitive, respectively to absorb or provide
reactive power. It may take values characterized by the
reactive power Qsvc injected or absorbed at the voltage of 1
p.u. The variable susceptance model and its equivalent circuit
is shown in Fig 1. SVC can be represented as an adjustable
reactance[15, 16].
(7)
B. Security Indices
The power system security is the ability to maintain
continuous power supply to customers without interruption
and with good quality. For the secure operation of the power
system, it is important to ensure the required level of security
margin. In this paper, the security margin indexes are defined
as follows:
1) Voltage Security Index (VSI)
Voltage Security Index indicates the security level of buses
in the power system.
Fig 1 Variable Shunt Susceptance
In general, the transfer admittance equation for the variable
shunt compensator is
I  jBV k
(10)
1640
Venkateswara and Kumar
Firefly Algorithm based Optimal Power Flow with Static VAR Compensator for Improvement of Power System Security under Network Contingency
International Electrical Engineering Journal (IEEJ)
Vol. 5 (2014) No.12, pp. 1639-1648
ISSN 2078-2365
http://www.ieejournal.com/
and the reactive power equation is,
Qk  V B
2
k
(11)
The current drawn by the SVC is
I svc  jBsvcVk
(12)
Reactive power drawn by the SVC, which is also reactive
power injected at bus k, is
Qsvc  Vk2 BSVC
(13)
The linearised equation of the SVC is given by the following
equation where the total susceptance Bsvc is taken to be the
state variable.
i
i

Pk  0 0   k



Q  0 Q 

k  B
 k 
/
B
 svc svc 
i
(14)
at the end of iteration i, the variable shunt susceptance Bsvc
updated according to the equation given below;
iteration limit. The basic steps of the FA can be summarized
as the pseudo code [19, 20].
Pseudo code of Firefly Algorithm
………………………………………………..
Objective function f(x), x = (x1,…,xd)T
Generate initial population of fireflies xii ( i=1, 2…, n)
Light intensity Iii at xii is determined by f(xii)
Define light absorption coefficient γ
while ( t < MaxGeneration)
for ii = 1: n all n fireflies
for jj = 1: ii all n fireflies
if (Ijj > Iii), More firefly ii towards jj in d-dimension; end if
Attractiveness varies with distance r
Evaluate new solutions and modify the light intensity
end for jj
end for ii
Rank all the fireflies and find the current best firefly
end while
Post process results and visualization
……………………………..
.
V. RESULTS AND DISCUSSIONS
i

 Bsvc
 B(i 1) svc
Bi svc  B(i 1) svc  
 B

(15)
 svc 
The changing susceptance represents the total SVC
susceptance necessary to maintain the nodal voltage
magnitude at the specified value that is 1.0pu.
In order to find the effectiveness of the proposed Firefly
Algorithm for Optimal Power Flow with SVC, 5 bus system
and IEEE30 bus system are taken. An OPF program using
Firefly algorithm is implemented in MATLAB software
without and with SVC. The results have been presented and
analysed. The input parameters of Firefly Algorithm for the
test system are given in the Table I.
IV. FIREFLY ALGORITHM
TABLE I
Input parameters of firefly ALGORITHM FOR 5 bus system
Firefly Algorithm (FA) was developed by Dr Xin-She
Yang at Cambridge University in 2007. FA is based on
natural phenomenal behaviour of the firefly which is
developed for solving the multimodal optimization problem
[17, 18]. Fireflies are also called as lighting bugs these are
one of the most special and fascinating creatures in nature.
There are about thousands of fireflies where the flashes often
unique on a particular firefly.
For simplicity, the following three ideal rules are
introduced in FA development those are 1) All the fireflies
are gender-free that is every firefly will attract the other
firefly substantive of their sex, 2) Attractiveness depend on
their brightness. The less bright one will move towards the
brighter one, 3) the landscape of the objective function
affects the firefly brightness. Let us consider the continuous
constrained optimization problem where the task is to
minimize cost function f(x). Firefly algorithm is a speedily
converging algorithm. The solution for the algorithm
depends on the selection of swarm size, maximum
attractiveness value, the absorption coefficient value and the
S.No
Parameters
Quantity
1
Number of fireflies
25
2
Maximum iteration
200
3
Alpha
0.25
4
Minimum value of beta
(attractiveness)
Gamma
(absorption
coefficient)
0.20
5
1
A. SVC Placement under normal operation for 5 bus system:In 5-bus system, bus 1 is considered as slack bus, bus 2 is
taken as PV bus and other buses are consider as a PQ buses.
Total active power load is considered as 165MW and total
reactive power load considered as a 85MVAR. A MATLAB
program is implemented for the system. Nodal complex
voltages of 5 bus system without and with SVC in Firefly
Algorithm based optimal power flow are tabulated in Table
II. The SVC Model has been tested at all 3 different locations
in the bus system. The solutions were compared in all the
1641
Venkateswara and Kumar
Firefly Algorithm based Optimal Power Flow with Static VAR Compensator for Improvement of Power System Security under Network Contingency
International Electrical Engineering Journal (IEEJ)
Vol. 5 (2014) No.12, pp. 1639-1648
ISSN 2078-2365
http://www.ieejournal.com/
10
9
8
7
6
5
4
3
2
1
0
GA-OPF
FA-OPF
Active Power Losses in MW
cases, as given in the Table III. It is observed that by placing
the SVC at bus 4 the losses are less and security indices are
improved as compared to place the SVC at other locations.
Initially, the optimal power flow solution i.e. active power
generation, cost and power loss for 5-bus system are
calculated using proposed Firefly Algorithm method without
SVC. Next, for the same system the Optimal Power Flow
solution is obtained using proposed Firefly Algorithm
method with SVC.
3
4
5
SVC placed BUS Number in different methods
Fig 2: single line diagram of 5-bus system
From Table II it is observed that by incorporating SVC in
Firefly Algorithm based OPF voltage profile has been
improved and by placing the SVC at bus number 4 its voltage
has been regulated to 1.0pu. Table III represents the
placement of SVC in three different locations those are bus
no 3, bus no 4 and bus no5. And also represents the total real
power generation and real power losses by incorporating
SVC in Genetic Algorithm based Optimal Power Flow
(GA-OPF), and Firefly Algorithm based Optimal Power
Flow(FA-OPF). From this table it is observed that real power
losses are less by placing SVC in bus number 4 as compared
to other locations in all methods. Real power losses are
decreased to 5.41MW from 6.2553MW by placing the SVC
in bus number 4 in FA-OPF.
Voltage Magnitude in p.u
Fig4: Comparison of Active power losses in a 5 bus system
1.08
1.06
1.04
1.02
1
0.98
0.96
0.94
0.92
0.9
FA OPF with SVC at bus no 4
FA OPF without SVC
1
2
3
4
5
BUS Number
Fig 3: Comparison of voltage profile of a 5 bus system.
Table II - Nodal complex voltages for 5 bus system without and with SVC
Bus
No
1
2
3
4
5
FA-OPF
FA-OPF with svc (svc
placed at bus no 3)
FA-OPF with svc (svc
placed at bus no 4)
FA-OPF with svc (svc
placed at bus no 5)
VM
Angle
VM
Angle
VM
Angle
VM
Angle
1.06
1
0.9638
0.9539
0.9613
0
-0.859
-3.388
-3.520
-4.524
1.06
1
1
0.9833
0.9714
0
-0.8336
-3.9566
-3.9553
-4.613
1.06
1
0.9997
1
0.977
0
-0.8317
-3.9286
-4.2454
-4.6897
1.06
1
0.9714
0.9636
1
0
-0.8657
-3.4977
-3.6672
-5.1451
1642
Venkateswara and Kumar
Firefly Algorithm based Optimal Power Flow with Static VAR Compensator for Improvement of Power System Security under Network Contingency
International Electrical Engineering Journal (IEEJ)
Vol. 5 (2014) No.12, pp. 1639-1648
ISSN 2078-2365
http://www.ieejournal.com/
Table: III- Incorporation of SVC MODEL in 3 Different Locations
Method
Bus No
Total real
power
generation
(MW)
0*
172.0022
3
171.8279
4
171.6463
5
172.4401
0*
171.2553
3
170.5941
4
170.41
5
171.173
Total real
power loss
(MW)
VSI
LSI
B SVC
7.0022
0.1214
1.6157
------
6.8279
0.0452
1.6912
0.5740
6.6463
0.0233
1.5618
0.6985
7.4401
0.0655
1.6758
0.4363
6.2553
0.1211
1.5280
-----
5.5941
0.0453
1.5567
0.5695
5.4100
0.0233
1.4050
0.6954
6.1730
0.0650
1.5341
0.4362
GA-OPF
FA-OPF
0*=without SVC
B. SVC Placement under normal operation for 30 bus
system:In IEEE 30 bus system bus no 1 is considered as a slack
bus and bus no’s 2, 5, 8,11,13,30 are considered as a PV
buses all other buses are considered as load buses. This
system has 41 interconnected lines. A MATLAB program is
coded for the test system and the results have been presented
and analysed. The Table IV represents the generators a
coefficient, minimum and maximum limits of real power
generation for generator buses.
Table IV - Generator Characteristics of IEEE 30 Bus System
Generator
BUS NO
1
2
5
8
11
13
a
b
c
𝑃𝐺𝑚𝑖𝑛 𝑃𝐺𝑚𝑎𝑥
0.00375
0.0175
0.0625
0.00834
0.025
0.025
2
1.75
1
3.25
3
3
0
0
0
0
0
0
50
20
15
10
10
12
Figure 5 shows that by placing the SVC in bus number 26 in
both GA-OPF and FA-OPF method voltage magnitude has
been improved and bus no 26 voltage has been regulated to
1.0pu from 0.6948pu. From Table VI it has been observed
that the real power generation and real power losses are less
by incorporating SVC in FA based OPF as compared to GA
based OPF. It shows that the effectiveness of the Firefly
Algorithm as compared to Genetic Algorithm.Table VII
indicates the voltage magnitudes in p.u by placing SVC at bus
no 26 in NR method, GA-OPF, and FA-OPF methods. It has
been observed that power system security has been improved
by incorporating SVC in FA based OPF.
300
80
50
35
30
40
Table V represents the complex voltages of 30 bus system
with GA based OPF and FA based OPF. From this table it is
observed that voltage profile has been improved by using FA
based OPF.
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Vol. 5 (2014) No.12, pp. 1639-1648
ISSN 2078-2365
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Voltage Magnitude in p.u
1.1
Fig 5: Comparison of voltage profile in IEEE 30 bus system without and with
SVC in GA-OPF and FA-OPF.
GA-OPF
1
0.9
0.8
0.7
0.6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
BUS Number
Table V - Nodal complex voltages for 30 bus system
GA based OPF
FA based OPF
GA based OPF
FA based OPF
VM
Angle
VM
Angle
Bus.No.
VM
Angle
VM
Angle
BUS.
NO
1
1.06000
0.0
1.06000
0.0
16
0.88734
-21.59
0.89713
-13.35
2
3
1.04300
1.01449
-7.96
-6.24
1.04300
1.02229
-3.16
-3.35
17
18
0.87574
0.83927
-21.53
-22.68
0.88565
0.84977
-13.32
-13.93
4
0.99376
-11.37
1.00118
-6.10
19
0.84267
-22.84
0.85323
-14.27
5
6
7
8
9
10
11
12
13
14
15
1.01000
1.00838
0.99668
1.01000
0.95641
0.89684
1.08200
0.92593
1.07100
0.86667
0.85945
-7.69
-10.90
-9.64
-12.56
-22.75
-19.98
-23.78
-21.13
-22.58
-24.48
-23.05
1.01000
1.01200
0.99854
1.01000
0.96331
0.90637
1.08200
0.93520
1.07100
0.87677
0.86948
-1.53
-4.66
-3.44
-1.96
-14.50
-11.82
-13.76
-12.87
-12.43
-15.84
-14.11
20
21
22
23
24
25
26
27
28
29
30
0.86124
0.85869
0.84711
0.82459
0.81753
0.80013
0.69327
0.92076
0.97055
0.94957
1.00000
-22.02
-21.40
-22.75
-24.49
-25.91
-28.91
-40.61
-22.55
-15.01
-22.89
-23.23
0.87151
0.86886
0.85712
0.83397
0.82530
0.80134
0.69478
0.92116
0.97557
0.94865
1.00000
-13.65
-12.60
-13.28
-14.25
-14.31
-13.67
-25.33
-4.07
-3.45
-1.18
1.45
Table VI - Power flows for 30 bus system without svc and with SVC placed at bus no 26
Without SVC
Total
‘P’ gen
(MW)
349.3076
Total
‘Q’ gen
(MVAR)
260.9467
Total
‘P’ loss
(MW)
49.3076
With SVC
341.5572
231.5908
41.5572
Without SVC
335.8315
219.4190
35.8315
With SVC
327.0835
186.9539
27.0835
Power Flow Solution
GA-OPF
FA-OPF
VSI
LSI
0.7759
4.6184
0.3967
4.1799
0.7674
4.4568
0.3859
3.8813
Table VII -Voltage magnitudes for 30 bus system with SVC placed at bus no 26 in GA-OPF and FA-OPF
Bus.No
1
2
GA OPF with SVC
(placed at bus no 26)
1.060
1.043
FA - OPF with SVC
(placed at bus no 26)
1.060
1.043
Bus.No
16
17
GA OPF with SVC
(placed at bus no 26)
0.91390
0.90546
FA - OPF with SVC
(placed at bus no 26)
0.92558
0.91751
502
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Vol. 5 (2014) No.12, pp. 1639-1648
ISSN 2078-2365
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3
4
5
6
7
8
9
10
11
12
13
14
15
1.01895
1.00119
1.01
1.01365
0.99935
1.010
0.9696
0.92826
1.082
0.94824
1.07100
0.89995
0.90133
1.02880
1.01074
1.010
1.018
1.00173
1.010
0.97818
0.94001
1.082
0.95919
1.07100
0.91169
0.91290
18
19
20
21
22
23
24
25
26
27
28
29
30
0.88058
0.88182
0.89708
0.90405
0.90465
0.89356
0.91088
0.95093
1.000
0.96936
0.98868
0.97430
1.00000
0.89286
0.89438
0.90956
0.91625
0.91633
0.90385
0.91878
0.94934
1.00
0.96493
0.99219
0.96941
1.00000
C. SVC Placement under network contingency for 5 bus system:In this contingency analysis the load flow is run each time removing a single line from the system. The Contingency analysis is
applied to the FA-OPF with SVC and SVC has been placed at bus no 4.
Table VIII - comparison of real power losses, COST, INDICES for different line outages with svc placed at bus no 4
SVC Rating
VSI
LSI
Total real power generation
Real Power losses
Total Generation Cost
SVC Rating
VSI
LSI
FA
FA-OPF without SVC
--0.1211
1.5280
171.2553
6.2553
465.6360
---0.1322
1.2850
FA-OPF with SVC
0.6954
0.0233
1.4050
170.4100
5.4100
463.3691
0.7544
0.0248
1.1022
Total real power generation
173.9853
172.6086
Real Power losses
8.9853
7.6086
Total Generation Cost
571.7822
468.0580
SVC Rating
VSI
LSI
Total real power generation
Real Power losses
Total Generation Cost
SVC Rating
VSI
LSI
Total real power generation
Real Power losses
Total Generation Cost
SVC Rating
VSI
LSI
Total real power generation
Real Power losses
----0.2010
1.5455
569.5202
7.7381
172.7381
---0.1694
1.4861
172.6027
7.6027
569.2603
----0.1862
1.6768
569.9616
7.9695
0.9468
0.0309
1.5132
466.5379
6.6303
171.6303
0.7256
0.0243
1.3139
171.2027
6.2027
465.4947
0.7260
0.0243
1.5073
465.6880
6.3826
Loading condition
Without
contingency
1-2 line outage
1-3 line outage
line 2-3 outage
line 2-4 outage
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Vol. 5 (2014) No.12, pp. 1639-1648
ISSN 2078-2365
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Total Generation Cost
SVC Rating
VSI
LSI
Total real power generation
Real Power losses
Total Generation Cost
SVC Rating
VSI
LSI
Total real power generation
Real Power losses
Total Generation Cost
SVC Rating
VSI
LSI
Total real power generation
Real Power losses
Total Generation Cost
line 2-5 outage
line 3-4 outage
line 4-5 outage
172.9695
----0.3553
2.0866
588.1972
14.5339
179.5339
-----0.1479
1.4625
171.9501
6.9501
567.4948
---0.1281
1.5164
171.4606
6.4606
566.1245
171.3826
1.0503
0.0857
1.8892
578.6406
11.0378
176.0378
0.7042
0.0248
1.3302
170.6965
5.6965
464.1284
0.6210
0.0385
1.3573
170.4655
5.4655
463.4549
Table IX - Active Power Losses under the Line Outage in Different Methods with SVC Placed At Bus No 4
Line outage
NR method
GA WITH SVC
FA WITH SVC
0*
SB* -EB*
7.5244
6.6463
5.4100
1
1-2
12.5178
10.4768
7.6086
2
1-3
10.0769
8.9403
6.6303
3
2-3
8.6715
7.2268
6.2027
4
2-4
9.0702
7.4266
6.3826
5
6
2-5
3-4
15.6346
8.4179
12.0590
7.1359
11.0378
5.6965
7
4-5
7.7672
6.7415
5.4655
0*=without line outage
SB=starting bus number
EB=ending bus number
Table VIII represents the indices, cost, real power generation and losses. From this table it has been observed that security
indices were improved and real power losses were minimized by using FA based OPF incorporating SVC. Table IX shows the
real power losses in different methods with network contingency. From this table it is observed that line no 5, that is connected
between bus no 2 and bus no5, is the most sever line under contingency.
Table X- Bus voltage Magnitudes in the Pre and Post contingency state for line 2-5 outage in Firefly Algorithm based Optimal
Power Flow with SVC (SVC at bus no 4)
Bus
No
Pre-contingency voltage (pu)
Post-contingency voltage(pu)
FA-OPF without
SVC
FA – OPF with
SVC
FA-OPF without
SVC
FA–OPF
SVC
1
1.06
1.06
1.06
1.06
2
1
1
1
1
3
0.9638
0.9997
0.9278
0.9989
with
1646
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International Electrical Engineering Journal (IEEJ)
Vol. 5 (2014) No.12, pp. 1639-1648
ISSN 2078-2365
http://www.ieejournal.com/
4
0.9539
1
0.9085
1
5
0.9613
0.977
0.8083
0.9155
Table X indicates the voltages of the 5 bus system corresponding to the pre contingency state and post contingency state under
the outage of line 5 connected between bus no 2 and bus no 5. Table XI indicates the active power flows of the 5 bus system
corresponding to the pre contingency state and post contingency state. From this table we can observe that outage in the line
connected between buses 2-5 and by incorporating the SVC in Firefly Algorithm based Optimal Power Flow the system is
stable but some of the lines were operating with over load.
Table XI - Active Power Flow in the Pre and Post Contingency State with Firefly Algorithm based Optimal Power Flow with
SVC (SVC at bus no 4)
Line
Line connected between
Pre contingency active power flow in Post contingency active power
no
Starting Bus MW
flow in MW
Ending Bus
FA-OPF
FA – OPF with SVC
FA-OPF
FA – OPF
without SVC
without SVC
with SVC
1
1-2
55.6955
54.9350
48.5464
46.2696
2
1-3
35.6150
35.5301
50.9996
49.7802
3
2-3
27.4599
27.3020
49.1533
47.9513
4
2-4
30.0108
30.0685
57.5224
56.4625
5
2-5
0
0
56.2505
55.5976
6
3-4
15.9393
16.2681
64.4938
63.4960
7
4-5
5.1487
5.7145
50.1482
49.3719
D. SVC Placement under network contingency for 30 bus system:Table XII indicates that the active power losses under SVC in bus no26 in FA based OPF. Voltage collapse can be
network contingency in FA based OPF without and with initiated due to increasing load as well as line outage. Under
SVC. These results indicates that by using Firefly Algorithm line outage placing SVC can improve the system security
based Optimal Power Flow with SVC(SVC placed at bus with fast and controlled injection of reactive power to the
no26) the active power losses are minimized and system system. From table XII it can be observed that under the
collapse states can be reduced that means by using this outage of line 35 in FA-OPF load flow majority of the bus
method power system security can be improved. Table XIII voltages are collapsed. It is also observed that under outage of
indicates the voltages of the IEEE 30 bus system line 35, placing the SVC at bus no 26 in Firefly Algorithm
corresponding to the pre contingency state and post based Optimal Power Flow can improve the voltage profile of
contingency state (outage of line 35 connected between bus all the buses and then enhance the system security.
no 25 and bus no 27 which is the most sever line) by placing
Table XII - Active power losses with outage of single line
Line No
Line Outage
Real Power losses (FA-OPF)
Real Power losses (FA-OPF with SVC)
1
Without line outage
1-2
54.8526
system collapse
27.0835
29.3411
6
2-6
system collapse
47.8147
11
6-9
system collapse
58.9583
12
6-10
system collapse
43.9506
15
4-12
system collapse
38.8070
33
24-25
system collapse
30.8537
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Vol. 5 (2014) No.12, pp. 1639-1648
ISSN 2078-2365
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35
25-27
system collapse
70.4155
36
28-27
system collapse
61.7065
38
27-30
system collapse
44.2167
31
22-24
63.9314
30.7533
17
12-14
63.6159
33.4078
25
10-20
62.5007
34.4383
30
15-23
61.8254
34.4515
2
1-3
61.2238
31.7556
4
3-4
60.9680
27.7177
28
10-22
60.5401
28.7422
Table XIII - Bus voltage Magnitudes in the Pre and Post contingency state in Firefly Algorithm based Optimal Power Flow with SVC
Bus
No
Pre-contingency
voltage (pu)
FA based OPF
with SVC
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
1.060
1.043
1.02880
1.01074
1.010
1.018
1.00173
1.010
0.97818
0.94001
1.082
0.95919
1.07100
0.91169
0.91290
Post-contingency
voltage(pu)
FA based FA based
OPF
OPF with
without
SVC
SVC
1.06
1.060
0.26
1.043
0.14
1.015
0.319
0.99
0.343
1.01
0.18
1.004
0.08
0.995
0.55
1.01
0.48
0.948
0.4
0.8773
0.614
1.082
0.17
0.914
0.81
1.071
0.58
0.85
0.589
0.841
VI. CONCLUSION
In this paper, firefly algorithm has been proposed to solve
Optimal Power Flow problem in the presence of SVC. The
results demonstrate the effectiveness and robustness of the
proposed method with SVC in contingency analysis. The
results obtained for 5 bus system and IEEE 30 bus system
using the proposed method without and with SVC are
compared and observations reveal that the losses are less with
SVC. In 5 bus system bus no 4 was the best location for SVC.
In IEEE 30 bus system SVC placed at bus no 26 the
simulation results were taken for both normal operations as
well as under network contingency. The results indicate that
with proposed Firefly Algorithm the system collapse states
Bus
No
Pre-contingency
voltage (pu)
FA based OPF
with SVC
Post-contingency
voltage(pu)
FA based FA based
OPF
OPF with
without
SVC
SVC
16
0.92558
0.13
0.8722
17
0.91751
0.08
0.858
18
0.89286
0.63
0.8196
19
0.89438
0.14
0.8221
20
0.90956
0.4
0.8406
21
0.91625
0.07
0.8352
22
0.91633
0.21
0.824
23
0.90385
0.08
0.8089
24
0.91878
0.11
0.8148
25
0.94934
0.08
0.878
26
1.00
0.277
1.00
27
0.96493
0.58
0.961
28
0.99219
0.19
0.9752
29
0.96941
0.32
0.9673
30
1.00000
0.9917
1.00
can be avoided and power system security under network
contingency also has been improved. By incorporating SVC
in Firefly Algorithm based Optimal Power Flow the system
performance has been improved. The comparative study of
the Firefly Algorithm based Optimal Power Flow with GA
based Optimal Power Flow in solving the optimal power flow
problem also reflected the effectiveness of the proposed
approach. The obtained results show that SVC is the most
effective shunt compensation device that can significantly
increase the security of the power system.
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http://www.ieejournal.com/
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