International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
Web Site: www.ijettcs.org Email: editor@ijettcs.org
Volume 3, Issue 5, September-October 2014
ISSN 2278-6856
Optimal location of Unified Power Flow
Controller (UPFC) to control active power
flows and congestion Management in a
transmission lines by using Fuzzy Based
Technique
RAJASEKAR THOTA1, SHAIK HAMEED2
1
M.TECH.ScholorDepartment of EEE,QCET, Nellore, India.
2
Associate ProfessorDepartment of EEE,QCET, Nellore, India.
Abstract
The objective of this paper which concentrates on the
application of Flexible Alternative Current Transmission
System (FACTS) controllers as a solution to the problem
of congestion(transmission system to operate beyond
transfer limits) management.In the emerging electric
power market, congestion management becomes
extremely important and it can impose barrier to electric
power trading. For thisFACTS also an alternative to
reduce the flows in heavily loaded lines, resulting low
system loss, improved stability of the network, reduced
cost of production and fulfilled contractual requirement
by controlling the power flow in the network.A line
utilization factor (LUF) is used to determine the level of
congestion in a transmission line. In this paper a Fuzzy
Based Technique is proposed in determining the optimal
location of unified-power-flow controller (UPFC) to
control active power flows and reduction of congestion in
a transmission line. This method is tested on IEEE 14bus system using MATLAB Simulation.
Keywords: Congestion Management, Electric Power
Trading, Flexible Alternative Current Transmission
System (FACTS), Line Utilization Factor (LUF), Unified
Power Flow Controller (UPFC), Thyristor Controlled
Series Capacitor (TCSC), Fuzzy Based Technique.
1. INTRODUCTION
1.1 Over View of a Power System
With the ongoing expansion and growth of the electric
utility industry, including deregulation in many countries,
numerous changes are continuously being introduced to a
once predictable business. Although electricity is a highly
engineered product, it is increasingly being considered and
handled as a commodity. Thus, transmission systems are
being pushed closer to their stability and thermal limits
while the focus on the quality of power delivered is greater
than ever. In the evolving utility environment, financial
and market forces are and will continue to, demand a more
optimal and profitable operation of the power system with
respect to generation, transmission, and distribution. Now,
more than ever, advanced technologies are paramount for
Volume 3, Issue 5, September-October 2014
the reliable and secure operation of power systems. To
achieve both operational reliability and financial
profitability, it has become clear that more efficient
utilization and control of the existing transmission system
infrastructure is required. Improved utilization of the
existing power system is provided through the application
of advanced control technologies. Power electronics based
equipment, or Flexible AC Transmission systems
(FACTS), provide proven technical solutions to address
these new operating challenges being presented today.
FACTS technologies allow for improved transmission
system operation with minimal infrastructure investment,
environment impact, and implementation time compared
to the construction of new transmission lines When
discussing the creation, movement, and utilization of
electrical power, it can be separated into three areas, which
traditionally determined the way in which electric utility
companies had been organized. These are illustrated in
and are:
 Generation
 Transmission
 Distribution
Although power electronic based equipment is prevalent in
each of these three areas, such as with static excitation
systems for generators and custom power equipment in
distribution systems, the focus of this paper and
accompanying presentation is on transmission that is,
moving the power from where it is generated to where it is
utilized
1.2 Power System Constraints
The limitations of the transmission system can take many
forms and many involve power transfer between areas
(referred to here as transmission bottlenecks) or within a
single area or region and may include one or more of the
following characteristics:
 Steady-state power transfer limit
 Voltage stability limit
 Dynamic voltage limit
 Transient stability limit
 Power system oscillation damping limit
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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
Web Site: www.ijettcs.org Email: editor@ijettcs.org
Volume 3, Issue 5, September-October 2014
 Inadvertent loop flow limit
 Thermal limit
 Short-circuit current limit
 Others
Each transmission bottleneck or regional constraint may
have one or more of these system-level problems. The key
to solving these problems in the most cost-effective and
coordinated manner is by thorough systems engineering
analysis.
1.3 Controllability of Power Systems
There are three main variablesthat can be directly
controlled in the power system to impact its performance.
These are:
 Voltage
 Angle
 Impedance
Once could also make the point direct control of power is a
fourth variable of controllability in power system? With the
establishment of “what” variables can be controlled in a
power system, the next question is “how” these variables
can be controlled. The answer is presented in two parts:
namely conventional equipment and FACTS controllers.
Examples of Conventional Equipment for Enhancing
Power System Control
 Series Capacitor
 Controls impedance
 Switched Shunt-Capacitor and Reactor
 Controls voltage
 Transformer LTC
 Controls voltage
 Phase Shifting Transformer
 Controls angle
 Synchronous Condenser
 Controls voltage
 Special Stability Controls
 Typically focuses on voltage control but can include
direct control of power
 Others (When Thermal Limits are Involved)
 Can included reconductoring, raising conductors,
dynamic lines monitoring, adding new lines, etc.
Example of FACTS Controllers for Enhancing Power
System Control
 Static Synchronous Compensator (STATCOM)
 Thyristor Controlled Series Capacitor (TCSC)
 Unified Power Flow Controller (UPFC)
 Static Var Compensator (SVC)
 Convertible Series Compensator (CSC)
 Inter-phase Power Flow Controller (IPFC)
 Static Synchronous Series Controller (SSSC)
ISSN 2278-6856
AC to DC voltage source converters operated from a
common DClink capacitor, Figure 2.1. First converter
(CONV1) is connected in shunt and the second one
(CONV2) in series with the line. The shunt converter is
primarily used to provide active power demand of the
series converter througha common DC link. Converter 1
can also generate or absorb reactive power,if it is desired,
and thereby provide independent shunt reactive
compensationfor the line. Converter 2 provides the main
function of the UPFC by injecting a voltage with
controllable magnitude and phase angle in series with
theline. The reactance Xs describes a reactanceseen from
terminals of the series transformer and is equal to
XS = XkR2max(SB/SS)
Where Xkdenotes the series transformer reactance, Rmax the
maximum perunit value of injected voltage magnitude, SB
the system base power, and SSthe nominal rating power of
the series converter.
Fig. 2.1. :Implementation of the UPFC by back-to-back
voltage source converters
2.2 The UPFC injection model is shown in the figure 2.2.
Fig. 2.2. : Injection model of UPFC
From the above figure,
(2.1)
(2.2)
(2.3)
(2.4)
Where r and γ are the control variables of the UPFC.
Besides the bus power injections, it is useful to have
expressions for power flows from both sides of the UPFC
injection model defined. At the UPFCshunt side, the active
and reactive power flows are given as
2. MODELLING OF UPFC:
2.1Modelling of UPFC
The UPFC can provide simultaneous control of all basic
power system parameters (transmission voltage, impedance
and phase angle). The controller can fulfill functions of
reactive shunt compensation, series compensation
andphase shifting meeting multiple control objectives.The
general structure of UPFC contains also a "back to back"
Volume 3, Issue 5, September-October 2014
Whereas at the series side they are
The UPFC injection model is thereby defined by the
constant series branch susceptance bs, which is included in
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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
Web Site: www.ijettcs.org Email: editor@ijettcs.org
Volume 3, Issue 5, September-October 2014
the system bus admittance matrix, andthe bus power
injections Psi, Qsi, Psj and Qsj. If there is a control
objectiveto be achieved, the bus power injections are
modified through changes of the UPFC parameters r, γ and
Qconv1. UPFC is probably the most powerful and versatile
FACTSdevice which combines the properties of TCSC,
TCPAR and SVC. It is only FACTS devicehaving the
unique ability to simultaneously control all three
parameters of power flow,voltage, line impedance and
phase angle. Hence the UPFC concept was recognized as
the most suitable and innovative FACTS device.
3. PROPOSED METHOD:
3.1 Sensitivity methods for congestion management
These approaches are based upon a new factor. With the
help of this factor, the level ofcongestion in transmission
line can be determined.
Line utilization factor (LUF)
It is the measure of utilization of a particular line or
overall system. It gives an idea abouthow much percentage
of the line is used for the power flow. If the value of
utilization is less,it means that less power has been
transferred and the system will be less congested and vice
versa.
LUFij = MVAij / MVAijMAX(3.1)
Where,
 LUFij is the line utilization factor (LUF) of the line
connected to bus- i and bus-j.
 MVAijMAX is the mega volt ampere (MVA) rating of
the line between bus- i and bus- j.
 MVAij is the actual MVA rating of the line between
bus- i and bus-j.
3.2 Step by step algorithm to relieve congestion for an
IEEE 14-bus system
Step 1: Run power flow for a standard IEEE 14-bus
system. The LUF for the test system iscalculated. Table
3.1 shows the LUF of each line in a 14-bus system. If
the utilization reaches a high value,it indicates that the
system is more congested.
Step 2: Conduct power flow analysis for the congested
lines before and after seriescompensation. In this paper,
50% of line compensation is used. The maximum
utilized andcongested lines 1 to 2, 3 to 4, and one of the
minimum utilized line 9 to 10 are considered.The UPFC
is placed on these lines individually and analysed. The
changes in line flow in theconsidered lines are shown in
Table 3.2. It is observed that line flows are reduced in
the maximum congested lines.However, no significant
effect is observed in the minimum congested line. The
above methodif applied for all the lines, involves a lot of
computation. Hence, fuzzy method is applied
forsimplifying the procedure.
Table 3.1. : Power Flows, LUF for IEEE 14-Bus System.
S.
No.
1
Line i-j
1-2
Line flow
(MW)
153.7100
Line
capacity
(MW)
184.155
% Line
utilization
factor
(LUF)
83.4677
Volume 3, Issue 5, September-October 2014
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
1-5
2-3
2-4
2-5
3-4
4-5
4-7
4-9
5-6
6-11
6-12
6-13
7-8
7-9
9-10
9-14
10-11
12-13
13-14
74.2483
72.4029
55.4654
41.0186
-23.0685
-60.4969
27.4016
15.6887
43.1135
7.5146
7.5630
16.8358
0.0065
27.4016
5.0713
8.5190
-3.9403
1.3945
5.5301
ISSN 2278-6856
128.816
129.989
98.350
60.000
-24.765
97.847
59.011
25.093
59.753
14.059
15.240
29.544
0.01809
53.602
13.189
15.058
-14.012
6.9959
15.129
57.6390
55.6992
56.3959
68.3643
93.1496
61.8280
46.4348
62.5222
72.1529
53.4507
49.6263
56.9857
35.9315
51.1206
38.4510
56.5748
28.1207
19.9333
36.5531
Table 3.2. : Power Flows, LUF for IEEE 14-Bus System.
Step 3: Applying fuzzy method for locating UPFC to
relieve congestion.
A) Fuzzification:
Fuzzification is a process where the inputs variables are
mapped intofuzzy variables. The Fuzzy input variables
considered in this paper are line flows beforecompensation
(Pline) and change in line flow after series compensation
(ΔPline). To relieve congestion, the location for placement
of UPFC is considered as a major issue.Hence, UPFC can
be placed where the low power loss occurs in the line.
Therefore, thechange in power loss (ΔPloss) is taken as an
output variable. The fuzzy variables for the testcase are
shown in Table 3.3.
B) Range selection for fuzzy subsets:
The ranges of input and output variables for the test case
are shown in Table 3.4.
C) Fuzzy control rules:
To begin with Pline and ΔPlinevalues will be converted into
fuzzy variables.
Page 79
International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
Web Site: www.ijettcs.org Email: editor@ijettcs.org
Volume 3, Issue 5, September-October 2014
ISSN 2278-6856
Table 3.3. : The Fuzzy inputs and outputs variable for
IEEE 14 Bus system.
S.
No.
Line
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
1-2
1-5
2-3
2-4
2-5
3-4
4-5
4-7
4-9
5-6
6-11
6-12
6-13
7-8
7-9
9-10
9-14
10-11
12-13
13-14
Input
variable
Line
flow(MW)
153.7100
74.2483
72.4029
55.4654
41.0186
-23.0685
-60.4969
27.4016
15.6887
43.1135
7.5146
7.5630
16.8358
0.0065
27.4016
5.0713
8.5190
-3.9403
1.3945
5.5301
Input
variable
Δ
Pline
(MW)
12.044
-13.533
3.447
3.867
5.505
3.248
7.768
-0.468
-0.401
0.906
0.477
0.135
0.294
-0.001
-0.468
-0.461
-0.408
-0.454
0.130
0.403
Output
variable
Δ PLoss
(MW)
0.075
0.063
0.065
0.066
0.067
0.065
0.070
0.063
0.063
0.064
0.064
0.064
0.064
0.064
0.063
0.063
0.063
0.063
0.064
0.064
After thefuzzification, fuzzy inputs enter to inference
mechanism level and with consideringmembership
function and rules; outputs are sent to defuzzification
tocalculate the finaloutputs.Each ruleof fuzzy control
follows the basic if then rule. In this paper, for both
theinputs Pline and ΔPline and the output ΔPloss, five
fuzzysubsets are used.
Table 3.4. : Ranges Of The Fuzzy Input And Output
Variable For IEEE 14-Bus System.
Fuzzy subsets
Small
Smallmedium
Medium
Medium high
High
Input
variable
Line
flows(MW
)
Input
variable
Change in
line flow
ΔPLine
(MW)
Output
variable
Change in
Power loss
ΔPLoss (MW)
< 20
10-50
40-80
70-110
>100
< 1.5
0.75-2.5
2-3.75
3.25-5.5
>5
< 0.2
0.1-0.4
0.3-0.6
0.5-0.75
>0.5
Fig. 3.2. : Input Membership function (Δ PLINE)
Fig. 3.3. : Output Membership function (Δ PLOSS)
They are S (small),SM (Small medium), M (Medium), MH
(Medium high) and H (High). The triangularmembership
functions are used for the above sub-sets as shown in
figures 3.1, 3.2 and 3.3.
D) Defuzzification
After evaluating inputs and applying them to the rule base,
the fuzzy-logic controller willgenerate a control signal.
The output variables of the inference system are
linguisticvariables. This will be evaluated forthe derivation
of the output control signal.
Fig. 3.4. : Surface diagram of membership functions
Table 3.4. : Fuzzy Control Rules.
∆Pl
S
SM
M
MH
H
S
S
S
S
S
S
SM
S
SM
SM
SM
SM
M
S
SM
M
M
M
MH
S
SM
M
MH
MH
H
S
SM
M
MH
H
Pl
This processis the defuzzification. The defuzzification has
been achieved using the centre of gravity(COG) method
Fig. 3.1. : Input Membership function (PLINE)
Volume 3, Issue 5, September-October 2014
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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
Web Site: www.ijettcs.org Email: editor@ijettcs.org
Volume 3, Issue 5, September-October 2014
and the output of the fuzzy coordinated controller is COG
(set of realnumbers).
COG(A) =
(3.2) Where; Xmin =1; Xmax =25; A(x) = Ploss, X =
Membership function. Corresponds to the value of
controlled output for which the membership values in the
outputsets are equal to unity. In this method ‘AND’
relationship between mappings of two variablesare
considered.
Step 4 (Analysis of the fuzzy method):
The output result of the proposed fuzzy method
isanalyzed. The defuzzyfied results are compared with
the change in power loss of each lineand optimized for
the location to place the UPFC to relieve congestion.
4. RESULTSAND DISCUSSIONS:
To minimize the congestion, the fuzzy based analysis is
carried out on standard IEEE 14-bus system. A MATLAB
simulation package version 7.12.0.635 is used for
simulations. Bylocating UPFC in the line 1 to 2, the
percentage of LUF has reduced from 83.4677% to
76.9279%. Priority list would capture the congested lines
as well as the neighbourhood lines that arelinked to the
congested lines through which the power can be diverted
after placement ofFACTS devices. The number of lines to
be considered for the priority list depends upon thesize of
the system, and has no hard and fast rule. Fuzzy rules have
been applied to the overloaded linesand results tabulated in
priority Table 4.1. The parameters of ΔPloss and ΔPline, are
beingconsidered for the optimum location of UPFC to
relieve congestion. Results obtained from fuzzy method,
the optimum location of FACTS device in between thelines
1 to 2, to relieve congestion for the considered power
system.It is observed frompriority table that the placement
of UPFC in the line 1 to 2 issuitablefor relieving
congestionin the transmission line.
Fig. 4.1. : IEEE 14-BUS System
If the first optimal location is not suited, then 2 or 3
optimallocations can be considered based on priority Table
4.1. The advantage of the proposed methodhelped to form
Volume 3, Issue 5, September-October 2014
ISSN 2278-6856
the priority list, for series FACTS device location to relieve
congestiondirectly from fuzzy results and avoid excessive
computation. Only few line in the priority listneed to be
examined in detail to assess the best location to relieve
congestion.
Table 4.1.: Fuzzy Based Priority Table for Location of
UPFC for IEEE 14-Bus system
S.
No.
1
2
3
UPFC
location
in line
1-2
2-3
2-4
%LUF
83.47
55.69
56.39
Priority for
placing
UPFC using
fuzzy
1
2
3
5. CONCLUSIONS
In this paper, we present an analytical framework for the
study of transmissioncongestion and the analysis and
design of effective congestion management schemes.
Congestion management is an important issue in power
systems. In this paper, fuzzy method is proposed for
optimal placement of UPFC (unified power flow
controller) to control the active power flow for congestion
management. The simulations are carried out successfully
on the IEEE 14-bus system. The proposed method
confirmed that improved efficiency and effectively used for
determining the optimal location of UPFC (unified power
flow controller) to solve congestion problem in a power
system network. The advantage of the proposed method is
to form the priority list, only few lines in the priority list
need to be examined in detail to assess the best location to
relieve congestion. Hence fuzzy method is an alternative
means of dealing with congestion and can be applied easily
to any number of buses to relieve congestion in a power
system.
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Web Site: www.ijettcs.org Email: editor@ijettcs.org
Volume 3, Issue 5, September-October 2014
ISSN 2278-6856
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Authors
Mr. Rajasekar Thota completed his B.Tech.
in Sree Vidyanikethan Engineering College,
affiliated by JNTU Anantapur, in the
department of Electrical and Electronics
Engineering in 2010. Now studying
M.Tech.(Electrical power systems) in QUBA Engineering
and Technology, Nellore, Affiliated by JNTU Anantapur
Mr. Shaik Hameed., completed his B.tech
in KU, M.tech in NIT durgapur. Now
working as Associate professor and Head of
the Department of EEE in QUBA
Engineering and Technology, Nellore,
Affiliated by JNTU Anantapur
Volume 3, Issue 5, September-October 2014
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