International Journal of Advances in Engineering & Technology, Nov. 2013.
©IJAET
ISSN: 22311963
IMPROVED TRANSMISSION LINE CONTINGENCY ANALYSIS
IN POWER SYSTEM USING FAST DECOUPLED LOAD FLOW
Amit Kumar Roy1, Sanjay Kumar Jain2
Asst.Professor, Department of Electrical Engineering,
JSS Academy of Technical Education, Noida, India
2
Associate Professor, Department of Electrical & Instrumentation Engineering,
Thapar University, Patiala, India
1
ABSTRACT
Contingency analysis technique is being widely used to predict the effect of outages in power systems, like
failures of equipment, transmission line etc. The off line analysis to predict the effect of individual contingency
is a tedious task as a power system contains large number of components. Practically, only selected
contingencies will lead to severe conditions in power system like violation of voltage and active power flow
limits. The process of identifying these severe contingencies is referred as contingency selection and this can be
done by calculating performance indices for each contingencies. In this paper, the contingency selection by
calculating two kinds of performance indices; active power performance index (PIP) and reactive power
performance index (PIV) for single transmission line outage have been done with the help of Fast Decoupled
Load Flow (FDLF) in MATLAB environment. The ranking of most severe contingency has been done based on
the values of performance indices. Simultaneously the value of bus voltages and active power flow before and
after the most severe transmission line contingency has been analyzed. The effectiveness of the method has been
tested on 5-Bus, IEEE-14 Bus and IEEE-30 Bus test systems. It can be seen from the results that, based on the
knowledge of PIP & PIV the most severe transmission line contingency can be identified and the effect of this
contingency on the rest of the system can also be seen via post contingency analysis.
KEYWORDS:
I.
Contingency, contingency selection, performance indices, fast decoupled load flow.
INTRODUCTION
It is well known that power system is a complex network consisting of numerous equipments like
generators, transformers, transmission lines, circuit breakers etc. Failure of any of these equipments
during its operation harms the reliability of the system and hence leading to outages. Whenever the
pre specified operating limits of the power system gets violated the system is said to be in emergency
condition. These violations of the limits result from contingencies occurring in the system. Thus, an
important part of the security analysis revolves around the power system to withstand the effect of
contingencies. The contingency analysis is time consuming as it involves the computation of complete
AC load flow calculations following every possible outage events like outages occurring at various
generators and transmission lines. This makes the list of various contingency cases very lengthy and
the process very tedious. In order to mitigate the above problem, automatic contingency screening
approach is being adopted which identifies and ranks only those outages which actually causes the
limit violation on power flow or voltages in the lines. The contingencies are screened according to the
severity index or performance index where a higher value of these indices denotes a higher degree of
severity. The importance of power system security assessment for prediction of line flows and bus
voltages following a contingency has been presented in [1-2]. The paper also details the challenges
faced for the practical implementation of security analysis algorithms. The approximate changes in
the line flow due to an outage in generator or transmission line is predicted based on distribution
factors [3-4]. The use of AC power flow solution in outage studies has been dealt in [5].Contingency
screening or contingency selection is an essential task in contingency analysis. This helps to reduce
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Vol. 6, Issue 5, pp. 2159-2170
International Journal of Advances in Engineering & Technology, Nov. 2013.
©IJAET
ISSN: 22311963
the numerous computations; the bounding method [6] reduces the number of branch flow computation
by using a bounding criterion that helps in reducing the number of buses for analysis and is based on
incremental angle criterion. The 1P-1Q method for contingency selection has been presented in [7]. In
this method the solution procedure is interrupted after an iteration of fast decoupled load flow.
Zaborzky et al. introduced the concentric relaxation method for contingency evaluation [8] utilizing
the benefit of the fact that an outage occurring on the power system has a limited geographical effect.
The use of fast decoupled load flow [9] proves to be very suitable for contingency analysis.
Contingency selection criterion based on the calculation of performance indices has been first
introduced by Ejebe and Wollenberg [10] where the contingencies are sorted in descending order of
the values of performance index (PI) reflecting their severity. The practical implementation of
contingency screening can be done by installing the phasor measurement units which are being used
to capture the online values of bus voltages and angles [11]. The fast estimation of voltages in power
system is essential for contingency analysis and this was proposed in [12]. Apart from performance
index other index like voltage stability criteria index can also be chosen contingency ranking [13].
Multiple contingency can occur in the power system at the same time, hence its identification and
analysis is a more complicated task, the multiple contingency screening in power system has been
illustrated in [14]. The analysis of power system contingency becomes more challenging when the
system is connected to a variable generation units like wind or solar systems, where the firm capacity
is variable. In [15] the contingency analysis by incorporating sampling of Injected powers has been
done.
In this paper, the values of active power performance index (PIP) and reactive power performance
index (PIV) have been calculated for 5-bus, IEEE-14 bus and IEEE-30 bus systems using the
algorithm implemented in MATLAB software. Based on the values of PIV, contingencies have been
ranked where a transmission line contingency leading to high value of PIV has been ranked 1 and a
least value of PIV have been ranked last. The load flow analysis following the most severe
transmission line contingency has been simulated and the results of active power flow in various
transmission lines and the bus voltages has been analyzed.
II.
CONTINGENCY ANALYSIS USING LOAD FLOW SOLUTION
2.1 Contingency Selection
Since contingency analysis process involves the prediction of the effect of individual contingency
cases, the above process becomes very tedious and time consuming when the power system network
is large. In order to alleviate the above problem contingency screening or contingency selection
process is used. Practically it is found that all the possible outages does not cause the overloads or
under voltage in the other power system equipments. The process of identifying the contingencies that
actually leads to the violation of the operational limits is known as contingency selection. The
contingencies are selected by calculating a kind of severity indices known as Performance Indices (PI)
[1]. These indices are calculated using the conventional power flow algorithms for individual
contingencies in an off line mode. Based on the values obtained the contingencies are ranked in a
manner where the highest value of PI is ranked first. The analysis is then done starting from the
contingency that is ranked one and is continued till no severe contingencies are found. There are two
kind of performance index which are of great use, these are active power performance index (PIP) and
reactive power performance index (PIV). PIP reflects the violation of line active power flow and is
given by (1)
P
PIP = ∑Li=1(P i )2n
(1)
imax
where,
Pi = Active Power flow in line i,
Pimax = Maximum active power flow in line i,
n is the specified exponent,
L is the total number of transmission lines in the system.
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International Journal of Advances in Engineering & Technology, Nov. 2013.
©IJAET
ISSN: 22311963
If n is a large number, the PI will be a small number if all flows are within limit, and it will be large if
one or more lines are overloaded, here the value of n has been kept unity. The value of maximum
power flow in each line is calculated using the formula
V ∗V
Pimax = i𝑋 j
(2) where,
Vi= Voltage at bus i obtained from FDLF solution
Vj= Voltage at bus j obtained from FDLF solution
X = Reactance of the line connecting bus ‘i’ and bus ‘j’
Another performance index parameter which is used is reactive power performance index
corresponding to bus voltage magnitude violations. It mathematically given by (3)
𝑁𝑝𝑞 2(𝑉𝑖−𝑉𝑖𝑛𝑜𝑚) 2
PIV=∑𝑖=1 [𝑉𝑖𝑚𝑎𝑥−𝑉𝑖𝑚𝑖𝑛]
(3)
where, Vi= Voltage of bus i, Vimax and Vimin are maximum and minimum voltage limits, Vinom is
average of Vimax and Vimin, Npq is total number of load buses in the system.
III.
ALGORITHM
LOAD FLOW
FOR
CONTINGENCY ANALYSIS
FAST DECOUPLED
USING
The AC power flow program for contingency analysis by the Fast Decoupled Power Flow (FDLF) [9]
provides a fast solution to the contingency analysis since it has the advantage of matrix alteration
formula that can be incorporated and can be used to simulate the problem of contingencies involving
transmission line outages without re inverting the system Jacobian matrix for all iterations.
Start
Start
Read the system bus
data and line data
Read Bus Data
&
Line Data
Set the contingency
counter K=0
Formulate the YBus matrix of the system
and set counter K=0
Set |V i |  1.0 and  i  0 for PQ bus and  i  0 for PV bus
Simulate the line
outage contingency
(0)
(0)
(0)
Calculate P i and Q and  P &  Q for load bus
(k )
Calculate the MW flows in all
the transmission line and PMax
using FDLF
(k )
(k )
(k )
i
i
i
Calculate PIP using (1)
Calculate Pi and  Pi for voltage-controlled buses
(k )
Calculate the voltage at all
the buses using FDLF
(k )
 P 
Calculate  
 |V | 
Calculate PIV using (2)
Yes
Last
contingency
reached ?
Yes
Increment counter
K=K+1 for next iteration
Does  P converge ?
No
No
Does  Q
Yes
converge ?
No
Calculate
Increment the counter
K=K+1
Rank the contingencies as per
the highest value of PIP & PIV
Do the power flow analysis for
the most severe contingency case
Print the results
'  P 
  [ B ]1  
 |V | 
Print
Results
Stop
 Q 
Calculate  | V | 
 
Yes
Does  P converge ?
Yes
Does  Q
converge ?
No
No
 Q 
V  [  B ]  
 |V | 
'' 1
Stop
Figure 1 Flow Chart for Contingency Analysis by FDLF
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Vol. 6, Issue 5, pp. 2159-2170
International Journal of Advances in Engineering & Technology, Nov. 2013.
©IJAET
ISSN: 22311963
Hence to model the contingency analysis problem the AC power flow method, using FDLF method
has been extensively chosen. Algorithm that is to be followed for calculating the load flow solution
using FDLF [9] has been summarized in form of a flow chart.
The algorithm steps for contingency analysis using fast decoupled load flow solution have been
summarized in pictorial form in the flow chart as shown in Figure 1.
IV.
RESULTS AND DISCUSSIONS
The algorithm described in Figure 1, has been programmed in MATLAB software and its results for
various test bus system has been summarized in the following subsections. For calculation of PIV, it is
required to know the maximum and minimum voltage limits, generally a margin of + 5% is kept for
assigning the limits i.e., 1.05 P.U. for maximum and 0.95 P.U. for minimum. It is to be noted that the
above performance indices is useful for performing the contingency selection for line contingencies
only. To obtain the value of PI for each contingency the lines in the bus system are being numbered as
per convenience, then a particular transmission line at a time is simulated for outage condition and the
individual power flows and the bus voltages are being calculated with the help of fast decoupled load
flow solution.
4.1 Results of 5-Bus System Case Study
The system as shown in Figure 2 consists a slack bus numbered 1 and 4 load buses numbered 2, 3, 4
and 5. It has total seven transmission lines and the active power flow in each transmission lines that
has been obtained using FDLF corresponding to the base case loading condition is shown in Figure 2,
this base case analysis is also referred a Pre- contingency state. The load flow analysis is then carried
out by considering the one line outage contingency at a time.
Table 1 Performance Indices & Contingency ranking using FDLF for 5-bus system
Outage Line No.
1
2
3
4
5
6
7
PIP
PIV
0.2800
0.3619
0.3377
0.3790
0.4221
0.2995
0.3036
3.1916
0.2699
0.6557
0.6173
0.2653
0.8599
0.8799
Ranking
1
6
4
5
7
3
2
The active and reactive power performance indices (PIP & PIV) are also calculated considering the
outage of only one line sequentially and the calculated indices are summarized in Table 1. It can be
inferred that outage of line number 1 is the most vulnerable in the whole system; the highest value of
PIV for this outage suggests that the highest attention be given for this line during the operation. It is
seen that the contingency in the line connected between buses (1-2) results in highest value of the
reactive power performance index and thus it is ranked first for the contingency selection, hence the
post contingency state of the system corresponding to this contingency has been analyzed. Since, the
value of PIV indicates the severity that is occurring in the system due to violation in voltage limit;
hence analysis of pre-contingency and the post contingency voltages at the buses of the entire system
have been detailed in Table 2. The MW flows corresponding to the pre contingency state and the post
contingency state have been detailed in Table 3.
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International Journal of Advances in Engineering & Technology, Nov. 2013.
©IJAET
ISSN: 22311963
5
(1.018 P.U)
6.33 MW
22.23 MW
4
4
(0.861 P.U)
5
54.82 MW
(1.060 P.U)
39.07 MW
1
27.93 MW
(0.891 P.U)
(1.047 P.U)
88.86 MW
40.72 MW
0 MW
143.63 MW
24.69 MW
2
1
15.33 MW
2
(1.060 P.U)
18.87 MW
3
4.00 MW
(0.880 P.U)
(1.024 P.U)
66.8 MW
3
(0.886 P.U)
(1.024 P.U)
Figure 2.Pre-Contingency State & Post Contingency state of 5-Bus system
Table 2 Bus voltages in the Pre and Post Contingency State
Bus Number
Pre-contingency
voltage (P.U)
Post-contingency
voltage (P.U)
1
2
3
1.060
1.047
1.024
1.060
0.891
0.886
4
1.024
0.880
5
1.018
0.861
Table 3 Active Power Flow in the Pre and Post Contingency State
Line No.
Start Bus
End Bus
Pre Contingency
MW flow
88.86 MW
40.72 MW
24.69 MW
Post Contingency
MW flow
0 MW
143.63 MW
15.33 MW
1
2
3
1
1
2
2
3
3
4
5
6
2
2
3
4
5
4
27.93 MW
54.82 MW
18.87 MW
4.00 MW
39.07 MW
66.80 MW
7
4
5
6.33 MW
22.23 MW
4.2 Results of 14-Bus System Case Study
The system has a total 20 number of transmission lines, hence we evaluate for 20 line contingency
scenarios by considering the one line outage contingency at a time. The performance indices are
summarized in the Table 4 where it can be inferred that outage in line number 16 is the most
vulnerable one and its outage will result a great impact on the whole system. The high value of PIV for
this outage also suggests that the highest attention be given for this line during the operation. The
contingencies have been ordered by their ranking where the most severe contingency is being ranked
1 and the least has been ranked 20. The values & variation of reactive performance index with their
ranking has been shown in the Figure 3. It is clear from the result of different PIV that the contingency
number 16 which the line outage contingency corresponding to the line connected between buses (910) is the most severe contingency. The system as shown in Figure 4 consists of 1 slack bus, 9 load
buses and 4 generator buses. There are three synchronous compensators used only for reactive power
support. The active power flow in each transmission lines that has been obtained using FDLF
corresponding to the base case loading condition is also shown in Figure 4. This state of the system
corresponds to the pre contingency state. The MW flows corresponding to the pre contingency state
and the post contingency state has been detailed in Table 5.
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Vol. 6, Issue 5, pp. 2159-2170
International Journal of Advances in Engineering & Technology, Nov. 2013.
©IJAET
ISSN: 22311963
Table 4 Performance Indices & Contingency Ranking using FDLF for 14-Bus System
Outage Line
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
PIP
PIV
1.1693
0.9807
1.1654
0.9999
0.9820
0.9640
0.9915
1.0747
0.9807
1.2396
1.0142
1.0127
1.0569
1.0072
1.0759
1.0114
1.0164
1.0030
1.0008
1.0076
Ranking
7.3032
7.6696
10.0014
7.3213
8.8759
13.2572
0.3566
1.1753
10.5776
1.6047
9.5907
1.8089
1.3669
10.4518
0.0844
13.3464
2.3482
10.5217
12.5538
2.2891
10
11
7
12
9
2
19
17
4
16
8
15
18
6
20
1
13
5
3
14
14
14
12
12
10
10
8
PIv
PIv
8
6
6
4
4
2
2
0
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14
Outage Line Number
15 16 17 18 19
20
0
1
2
3
4
5
6
7
8 9 10 11 12 13 14 15 16 17 18 19 20
Rank of Line outage Contingency
Figure 3 Values of PIV for 14-Bus system & Contingency Ranking and PIV of 14-Bus System
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International Journal of Advances in Engineering & Technology, Nov. 2013.
©IJAET
ISSN: 22311963
G
GENERATORS
G
GENERATORS
C
SYNCHRONOUS
COMPENSATORS
C
SYNCHRONOUS
COMPENSATORS
13
13
4.33 MW
6.14 MW
12
1.82 MW 18.2 MW
11
12
14
4.32 MW
16.67 MW
11
8.94 MW
10
7.93 MW
9
4.72 MW
8
44.74 MW
C
G
7
15.8 MW
6
9
0 MW
C
74.7 MW
10 10.7 MW
12.79 MW
G
C
9.09 MW
7.58 MW
7.96 MW
1
14
1.4 MW
1
7
14.9 MW
6
C
8
48.2 MW
4
75 MW
60.19 MW
4
57.6 MW
5
5
156.8 MW
157.3 MW
56 MW
56.3 MW
42.3 MW
42.03 MW
23 MW
23.19 MW
2
2
71.5 MW
71.6 MW
3
G
3
G
C
C
Figure 4 Pre-Contingency & Post-Contingency State of 14-Bus System
Table 5 Active Power Flow in the Pre and Post Contingency State
Line No.
Start Bus
End Bus
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
1
1
2
2
2
3
4
4
4
5
6
6
6
7
7
9
9
10
12
13
2
5
3
4
5
4
5
7
9
6
11
12
13
8
9
10
14
11
13
14
Pre contingency MW
flow
157.3 MW
74.7 MW
71.6 MW
56.3 MW
42.03 MW
23.19 MW
60.19 MW
27.38 MW
15.8 MW
44.74 MW
7.96 MW
7.93 MW
18.21 MW
0.0 MW
27.39 MW
4.72 MW
8.94 MW
4.32 MW
1.82 MW
6.14 MW
Post contingency MW
flow
156.8 MW
75 MW
71.5 MW
56 MW
42.3 MW
23 MW
57.6 MW
25.5 MW
14.9 MW
48.2 MW
12.79 MW
7.58 MW
16.67 MW
0.0 MW
25.5 MW
0 MW
10.7 MW
9.09 MW
1.4 MW
4.33 MW
4.3 Results of 30-Bus System Case Study
The IEEE-30 bus system has 6 PV buses, 24 PQ buses and 41 lines [38], hence for the PIP and PIV
calculation a total number of 41 line contingency cases are performed. The system consists of 41
transmission lines; the load flow analysis is carried out for 41 line contingency case considering one
line outage at a time. From Table 6 it can be inferred that outage of line number 9 is the most
vulnerable one and its outage will result a great impact on the whole system.
Table 6 Performance Indices & Contingency Ranking using FDLF for 30-Bus System
Outage Line No.
1
2
3
4
2165
PIP
1.5919
1.2754
1.2724
1.2740
PIV
3.9995
23.0290
24.5949
26.6730
Ranking
40
32
26
18
Vol. 6, Issue 5, pp. 2159-2170
International Journal of Advances in Engineering & Technology, Nov. 2013.
©IJAET
ISSN: 22311963
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
1.5029
1.2978
1.2982
1.2692
1.2803
1.3611
1.3691
1.2786
1.2996
1.3727
1.5285
1.2967
2.2972
1.3477
1.3084
1.2928
1.2964
1.3078
1.2983
1.3005
1.3081
1.3000
1.3183
1.2953
1.2954
1.3109
1.3086
1.2960
1.2948
1.9801
1.3111
1.4453
1.3073
1.3211
1.2893
1.2964
1.3282
30
23.3686
24.1327
23.0787
27.3376
29.5544
29.1055
26.2201
26.3051
18.6875
14.5771
9.6712
14.2764
0.3451
17.2591
24.5808
27.9804
27.6818
24.8931
27.8178
25.2770
20.4257
26.1714
24.0073
27.0173
28.2909
25.7308
27.1708
28.3973
29.1538
27.6726
26.1241
16.6797
27.8202
27.7249
28.0231
28.1952
28.1188
30
28
31
15
1
3
20
19
34
37
39
38
41
35
27
9
13
25
11
24
33
21
29
17
5
23
16
4
2
14
22
36
10
12
8
6
7
30
25
25
20
PIv
PIv
20
15
15
10
10
5
5
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41
Outage Line Number
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41
Rank of Line outage Contingency
Figure 5 PIV Values & Contingency ranking and PIV of 30-Bus system
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Vol. 6, Issue 5, pp. 2159-2170
International Journal of Advances in Engineering & Technology, Nov. 2013.
©IJAET
ISSN: 22311963
Figure 5 shows the contingency ranking of this system with respect to the PIV values. Since for the
IEEE-30 bus system contingency number 9 which is the line connected between buses (6-7) is the
most critical contingency, the post contingency analysis following the outage of this line has been
done and the power flow in the post contingency state has been detailed in Figure 6. Here the system’s
bus voltages corresponding to the pre contingency and the post contingency state has been obtained,
the results are detailed in Table 7. The active power flow in all the lines during the pre-contingency
and post contingency state has been detailed in Table 8.
1
G
177.77 MW
2
G
83.22 MW
45.71
MW
14
3
13
1.55 MW
C
7.89 MW
15
4
5.005
MW
17.82 MW
61.9
MW
12
16
83 MW
70.12 MW
23
24
7.20 MW
18
3.65 MW
2.78
MW
6.74
20 MW
9.02 MW
10
5
C
14.35
MW
17
9
7.09
MW
19
5.64
MW
15.73 MW
27
29
4.90
MW
22
7.58 MW
25
7
29.5
MW
3.70
MW
1.33
MW
21
6
37.52
MW
30
6.02 MW
28
11
C
18.81 MW
3.53 MW
26
0.57 MW
8
C
Figure 6 Pre & Post contingency state of the 30-Bus System
Table 7 Bus Voltages in the Pre and Post Contingency State
Bus Number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
2167
Pre-Contingency voltage
(P.U)
1.060
1.043
1.022
1.013
1.010
1.012
1.003
1.010
1.051
1.044
1.082
1.057
1.071
1.042
1.038
1.045
1.039
1.028
Post-contingency voltage (P.U)
1.060
1.043
1.024
1.016
1.010
1.015
0.988
1.010
1.053
1.047
1.082
1.059
1.071
1.044
1.039
1.046
1.041
1.030
Vol. 6, Issue 5, pp. 2159-2170
International Journal of Advances in Engineering & Technology, Nov. 2013.
©IJAET
ISSN: 22311963
19
20
21
22
23
24
25
26
27
28
29
30
1.025
1.029
1.032
1.033
1.027
1.022
1.019
1.001
1.026
1.011
1.006
0.995
1.027
1.031
1.034
1.035
1.029
1.024
1.021
1.004
1.028
1.013
1.009
0.997
Table 8 Active Power Flow in the Pre and Post Contingency State
Line No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
23
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
2168
Start Bus
1
1
2
3
2
2
4
5
6
6
6
6
9
9
4
12
12
12
12
14
16
15
18
19
10
10
10
10
21
15
22
23
24
25
25
28
27
27
29
8
6
End Bus
2
3
4
4
5
6
6
7
7
8
9
10
11
10
12
13
14
15
16
15
17
18
19
20
20
17
21
22
22
23
24
24
25
26
27
27
29
30
30
28
28
Pre contingency
MW flow
177.77 MW
83.22 MW
45.71 MW
78.01 MW
82.99 MW
61.91 MW
70.12 MW
14.35 MW
37.52 MW
29.5 MW
27.69 MW
15.82 MW
0.00 MW
27.69 MW
44.12 MW
0.00 MW
7.89 MW
17.82 MW
7.20 MW
1.55 MW
3.65 MW
6.02 MW
2.78 MW
6.74 MW
9.02 MW
5.37 MW
15.73 MW
7.58 MW
1.87 MW
5.00 MW
5.64 MW
1.77 MW
1.33 MW
3.53 MW
4.90 MW
18.18 MW
6.18 MW
7.09 MW
3.70 MW
0.57 MW
18.81 MW
Post contingency
MW flow
187.77 MW
74.80 MW
32.14 MW
70.13 MW
123.95 MW
43.81 MW
50.83 MW
23.06 MW
0 MW
29.55 MW
28.42 MW
16.25 MW
0.00 MW
28.42 MW
42.66 MW
0.00 MW
7.69 MW
17.23 MW
6.53 MW
1.43 MW
2.98 MW
5.65 MW
2.41 MW
7.10 MW
9.39 MW
6.03 MW
15.81 MW
7.63 MW
1.79 MW
4.59 MW
5.71 MW
1.36 MW
1.60 MW
3.54 MW
5.17 MW
18.45 MW
6.18 MW
7.08 MW
3.70 MW
0.55 MW
19.07 MW
Vol. 6, Issue 5, pp. 2159-2170
International Journal of Advances in Engineering & Technology, Nov. 2013.
©IJAET
ISSN: 22311963
V.
CONCLUSIONS
In this paper, the calculation of active and reactive power performance indices for contingency
selection has been done using FDLF for various test bus systems. The post-contingency analysis
following the most severe contingency, where the bus voltages and the power flow in the entire
system has been calculated. From the results of PIP and PIV it can be concluded that for the 5-bus test
system, outage in the transmission line number 1, in IEEE 14-bus system transmission line
contingency in line number 16 and for IEEE 30-bus system, a transmission line outage in line number
9 are the most critical contingencies. An outage in these lines has the highest potential to make the
system parameters to go beyond their limits. It can be further concluded that these lines require extra
attention which can be done by providing more advanced protection schemes or load shedding
schemes.
VI.
FUTURE WORK
The work discussed in this paper can be extended further by incorporating other kind of indices as
discussed in [12-13]. Calculation of the performance indices by using artificial intelligence techniques
like artificial neural networks [12] or by fuzzy logic can be taken up as future work. The contingency
analysis techniques can be further explored by considering multiple equipment failures or by
incorporating renewable energy sources in the power system.
REFERENCES
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[6] Brandwjn V and Lauby M.G, “Complete bounding method for A.C contingency screening”, IEEE
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[12] T.Jain, L.Srivastava, S.N. Singh and Arvind Jain, “Parallel Radial Basis Function Neural Network Based
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Deregulation, Restructuring and Power Technologies, Hong Kong, April 2004.
[13] F. Fatehi, M.Rashidinejad and A.A Gharaveisi, “Contingency Ranking Based on a Voltage Stability
Criteria Index”, IEEE Transactions in Power System, 2007
[14] Vaibhav Donde, Vanessa Lopex, Bernard Lesieutre, Ali Pinar, Chao Yang and Juan Meza, “Severe
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Power System Security Analysis”, IEEE Transactions on Power Systems, Vol.27, No.1, February 2012.
2169
Vol. 6, Issue 5, pp. 2159-2170
International Journal of Advances in Engineering & Technology, Nov. 2013.
©IJAET
ISSN: 22311963
AUTHORS BIOGRAPHIES
Amit Kumar Roy was born in West Bengal, India on February, 1988. He received his B.E
degree in Electrical & Electronics Engineering from Sathyabama University, Chennai in
2009 and M.E degree in Power Systems & Electric drives from Thapar University, Patiala
in 2011. He had secured Gold Medal in his M.E degree and 2 nd position in his B.E degree.
He is also a life member of Indian Society of Technical Education (ISTE), New Delhi. At
present he is working as an Assistant Professor in the Department of Electrical Engineering
at JSS Academy of Technical Education, Noida, U.P. where he is actively involved in the
academic activities and research work. His area of interest includes intelligent techniques applications to Power
Systems, Power Converters and Electric Drives.
Sanjay Kr. Jain was born in Madhya Pradesh, India on December, 1971. Awarded B.E.
(Electrical Engineering) from SGSITS Indore in 1992. Awarded M.E. (Power System) from
University of Roorkee (UOR), Roorkee in 1995. Awarded Ph.D. from IIT Roorkee in 2001.
Dr. Jain has a vast teaching experience of 13 years since 2001. At present he is working as
an Associate Professor in the Department of Electrical & Instrumentation Engineering at
Thapar University, Patiala, Punjab. His main area of interest lies in various techniques in
Powers System Optimization and modeling of Self Excited Induction Generators.
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