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Lovisal. C et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 3( Version 1), March 2014, pp.188-192
www.ijera.com 188 | P a g e
Fuzzy Optimization Using TCSC Device for Congestion
Management
Ms.Lovisal.C1
, Mr.E.Thangam2
Department of Electrical and Electronics Engineering Ranganathan Engineering College Coimbatore
Department of Electrical and Electronics Engineering Ranganathan Engineering College Coimbatore.
Abstract
The management of congestion is somewhat more complex in competitive power markets and leads to several
problems. It is one of the challenging tasks in power system deregulation. In a transmission line, congestion
occurs when there is an insufficient transmission capacity to simultaneously satisfy all constraints for
transmission in deregulated power market. Flexible alternative current transmission system (FACTS) devices
have been used for the enhancement of loadability by reducing the flows in heavily loaded lines. It also
improves the stability of the network, reduces the cost of production and fulfills all requirements by controlling
the power flow in the network. In the proposed work, a non-traditional optimization technique, Fuzzy logic (FL)
is used to optimize the various process parameters involved in introduction of FACTS devices in a power
system. The various parameters taken into consideration were the location of the device, their type, and their
rated value of the devices. The simulation was performed on a 14-bus power system with various types of
FACTS controllers, modeled for steady state studies. The effectiveness of the proposed method has been
demonstrated on IEEE 14-bus system.
Keywords-Congestion management, Deregulated electricity market, Thyristor Controlled Series Capacitors
(TCSC), Fuzzy logic controller.
I. INTRODUCTION
Transmission congestion may be defined as
the condition where more power is scheduled or
flows across transmission lines and transformers than
the physical limits of those lines and transformers.
The disputes of congestion in transmission network
are more pronounced in deregulated power
environment [1, 2].
The limitations of a power transmission
network arising from environmental and cost
problems are base to both bundled and unbundled
power systems. The generation pattern that results in
heavy flow tends to incur greater losses, and to
threaten stability and security, and finally the
generation patterns becomes economically
undesirable [3, 4].
To maintain system in a secure state,
Independent System Operator (ISO) can use some
techniques to relieve congestion.
1. Cost free methods: a) Out-ageing of congested
lines b) Operation of transformer taps/phase shifters
c) Operation of FACTS devices particularly series
devices.
2. Non-cost free methods: a) Re-dispatching the
generation amounts b) Curtailment of loads and the
exercise of load interruption options.
Among the above two methods, cost free means do
have advantages such that it does not touch the
economical matters, so GENCO and DISCO will not
be involved
Flexible alternating current transmission
systems (FACTS) technology has been applied for
controlling power and enhancing the usable capacity
of the transmission network in power market. By
installing these FACTS devices the utilization of
power system capabilities has been improved [5].
FACTS devices like TCSC are considered one such
technology that reduced the transmission congestion
and allows better utilization of the existing grid
infrastructure, along with many other benefits.
This paper deals with the optimal placement
of TCSC device to manage congestion in deregulated
electricity market. The optimal location of TCSC
device is based on static or dynamic performance of
the system. A sensitivity factor method is used for
optimal location of series FACTS devices [6] for static
congestion management. The approach is based on the
sensitivity of the reduction of total system VAR
power loss and real power performance index. A loss
sensitivity factor method is used in [7] to determine
the suitable location for FACTS device.
II. THYRISTOR CONTROLLED
SERIES CAPACITORS (TCSC)
Thyristor Controlled Series Capacitor as one
the best proposed devices in FACTS family and its
applications in power transmission system. Thyristor-
controlled series capacitors (TCSC) is a type of series
RESEARCH ARTICLE OPEN ACCESS

compensator that can provide many benefits for a
power system including controlling power flow in the
line, damping power oscillations, and mitigating sub
synchronous resonance. In TCSC, the capacitor is
inserted directly in series with the transmission line
and the thyristor-controlled inductor is mounted
directly in parallel with the capacitor [8]. Therefore,
no interfacing equipment like for example high
voltage transformers is required. This makes TCSC
much more economic than some other competing
FACTS technologies. Thus it makes TCSC simple
and easy to understand the operation.
III. MODELLING OF TCSC DEVICE
Power Injection Model can be used for static
application like congestion management using
FACTS devices. The injection model describes the
FACTS devices as a device that injects a certain
amount of active and reactive power to a node, so that
the FACTS devices are presented as PQ elements.
A simple transmission line represented by its
lumped  equivalent parameters connected between
bus-i and bus-j. Let complex voltages at bus-i and
bus-j with angle are i iV  and j jV  , respectively.
Bus-i ij ij ijY G jB  
Bus-j
shjB
shjB
Figure 1. Modelling of transmission line
A model of transmission line with one
TCSC which is connected between bus-i and bus-j as
shown in Fig.2.
Bus-i ij ij ijY G jB   cjx  Bus-j
shjB shjB
Figure.2 Modelling of transmission line with TCSC
The real and reactive power flow from bus-i
to bus-j can be written as
2
[ cos( ) sin( )]ij i ij i j ij ij ij ijP V G VV G B   
(1)
2
( ) [ sin( ) cos( )]ij i ij sh i j ij ij ij ijQ V B B VV G B     
(2)
where ij i j   

Similarly, the real and reactive power flow from
bus-j to bus-i is
2
cos( ) sin( )][ij j ij i j ij ij ij ijBP V G VV G   
(3)
2
sin( ) cos( )]( ) [ij j i j ij ij ij ijBQ V Bij Bsh VV G     

 (4)
The change in the line flow due to series
capacitance can be represented as a line without series
capacitance with power injected at the receiving and
sending ends of the line as shown in Fig.3.
ij ij ijZ r jx 

Bus-i
Bus-j
icS
jcS
Figure 3. Injection model of TCSC
The model of transmission line with a TCSC
connected between bus-i and bus-j is shown in Fig.3.
During the steady state the TCSC can be considered as
a static reactance -jxc. The real and reactive power
flow from bus-i to bus-j and from bus-j to bus-i of a
line having series impedance and a series reactance
are
2
' ( 'cos 'sin )c
ij i i j i j ij i j i j ijP V G VV G B   
(5)
2
( ' ) ( 'sin 'cos )c
ij i ij sh i j ij i j i j ijQ V B B VV G B     
(6)
2
' ( 'cos 'sin )c
ji j i j i j ij i j i j ijP V G VV G B   
 (7)
2
( ' ) ( 'sin 'cos )c
ji j ij sh i j ij i j i j ijQ V B B VV G B     
(8)
Where
2 2
'
( )
ij
ij ij c
r
Gij
r x x

 
2 2
( )
'
( )
ij c
ij ij c
x x
Bij
r x x
 

 
This model of TCSC is used to properly
modify the parameters of transmission lines with
TCSC for optimal location.
IV. OPTIMAL PLACEMENT USING FUZZY
The FACTS device can be used to change
the power system parameters. These parameters give
different results on the objective function (14). Also
various FACTS device locations, rated value and
types have influences on the objective function. The

above-mentioned parameters are very difficult to
optimize simultaneously by conventional
optimization methods. To solve this type of
combinatorial problem, fuzzy logic method is
proposed. The proposed methods are well developed
and utilized effectively for this work. For which C
computer coding are developed and for simulated
(15).
V. FUZZY LOGIC CONTROLLER
In 1965, Zadeh proposed Fuzzy logic; it has
been effectively utilized in many field of knowledge
to solve such control and optimization problems. In
power system area, it has been used to stability
studies, load frequency control, unit commitment, and
to reactive compensation in distribution network and
other areas. Fuzzy logic algorithm produce very good
results, as presented in [15].Further, it reduces the
computation time also. According to the situations,
rules are established and necessary actions to a
solution are determined. A process called
defuzzification, which consists in all variables
interaction through stochastic techniques, obtains
final values. In the FACTS device location problem,
rules are established to determine the convenience of
having a FACTS device installed in a particular bus
or not. The variables Bus voltage (BV) and Power
Loss (PL) are used to establish the group of fuzzy
rules. The relationship functions of these variables are
shown in Table I. Those variables indicate lack of
FACTS devices in the power system network and
determine the allocation sensibility degree of each
bus.The fuzzy rules are established by considering
first two extreme situations:
1. If low bus voltage and high MPL, where
FACTS devices essential.
2. If high voltage and low MPL, where FACTS
devices low attribute.
Fuzzy Logic approach for FACTS device location
1. Calculate bus voltages, power considering
power system without FACTS device.
2. Bus voltage (BV) is defined for each bus and
power loss(PL) is determined
3. Apply fuzzy logic to determine the subgroup
of bus in which the FACTS device locations
have more advantages,
TABLE I: FUZZY DECISION RULES
Voltage
low
Mediu
m low
mediu
m
Mediu
m high
highPower
loss
Low
mediu
m low
mediu
m low low low low
Mediu
m low
mediu
m
mediu
m low
mediu
m low
low low
Mediu
m
mediu
m
mediu
m
mediu
m low low low
Mediu
m high
mediu
m
high
mediu
m high
mediu
m
mediu
m low low
High high
mediu
m high
mediu
m
mediu
m low
mediu
m low
Sensitivity of each line was determined using
fuzzy decision rules. If bus voltage is low and power
loss is medium high, then FACTS devices are
essential.
VI. RESULTS AND DISCUSSIONS
The analysis has been implemented on IEEE
14 bus system to find the optimal locations of TCSC,
which is shown in the Fig.4. The FACTS device
should be placed on the most sensitive line.
Optimizations are carried out with a fuzzy tool
developed in MATLAB language. Power flows are
solved with a modified version of the free MATLAB
power simulation package MATPOWER 2.0.
Table II showed that standard power flow in
the IEEE 14 bus system. Table III showed the power
flow after the line outage 2-3. System power flow
result after placing TCSC in line-5 is shown in Table
IV.

Figure.4 IEEE 14 bus system
TABLE II
POWER FLOW OF IEEE 14 BUS SYSTEMS
Line i-j
Power
Flow(Mw)
Line i-j
Power
Flow(Mw)
1 1-2 130 11 6-11 30
2 1-5 130 12 6-12 30
3 2-3 130 13 6-13 30
4 2-4 120 14 7-8 30
5 2-5 120 15 7-9 40
6 3-4 120 16 9-10 30
7 4-5 120 17 9-14 30
8 4-7 100 18 10-11 30
9 4-9 60 19 12-13 30
10 5-6 60 20 13-14 30
TABLE III
AFTER LINE OUTAGE 2-3
Line i-j
Power
Flow(Mw)
Line i-j
Power
Flow(Mw)
1 1-2 148.95 11 6-11 9.76
2 1-5 94.92 12 6-12 8.24
3 2-3 0 13 6-13 19,1
4 2-4 93.9 14 7-8 0.1
5 2-5 69.47 15 7-9 25.6
6 3-4 -94.2 16 9-10 2.9
7 4-5 -100 17 9-14 7.7
8 4-7 25.6 18 10-11 -6.06
9 4-9 14.6 19 12-13 2.05
10 5-6 48.29 20 13-14 7.363
After applying fuzzy logic to determine the
subgroup of bus in which the FACTS device has to be
located. If bus voltage is low and power loss is
medium high, FACTS devices are essential. Second
line (1-5) satisfied the fuzzy rule, shows higher
sensitivity. So TCSC device has been placed in (1-5)
line and after placing TCSC congestion has been
relieved.
TABLE IV
AFTER PLACING TCSC IN LINE (1-2)
Line i-j
Power
Flow(M
w)
Line i-j
Power
Flow(Mw)
1 1-2 128.31 11 6-11 10.034
2 1-5 115.92 12 6-12 8.271
3 2-3 0 13 6-13 19.234
4 2-4 93.911 14 7-8 0.100
5 2-5 58.624 15 7-9 25.318
6 3-4 -94.2 16 9-10 2.667
7 4-5
-
107.582
17 9-14 7.567
8 4-7 25.318 18 10-11 -6.333
9 4-9 14.418 19 12-13 2.084
10 5-6 48.739 20 13-14 7.529
From Table IV., it is observed that
congestion has been relieved after placing the TCSC
in line-2 and it also reduced the total system reactive
power loss but it will be less effective than placing a
TCSC in other lines.
TABLE V
REAL POWER LOSS COMPARISION
Total Real Power Loss
Without TCSC
Total Real Power Loss With
TCSC
P(Mw) P(Mw)
24.865 20.601
Figure.5 Real Power Loss Comparison

TABLE VI
REACTIVE POWER LOSS COMPARISION
Total Reactive Power Loss
Without TCSC
Total Reactive Power
Loss With TCSC
Q (MVAr) Q (MVAr)
87.971 76.263
Figure.6 Reactive Power Loss Comparison
VII. CONCLUSION
Congestion management is an important
issue in deregulated power systems. FACTS devices
such as TCSC by controlling the power flows in the
network can help to reduce the flows in heavily
loaded lines. Because of the considerable costs of
FACTS devices, it is important to obtain optimal
location for placement of these devices. In this report
sensitivity of each line is computed through fuzzy
logic and determined the optimal location of
placement of TCSC in an electricity market. Test
results obtained on IEEE 14-bus power system show
that TCSC cost could be effectively used for
determining optimal location of TCSC. The optimal
solution is determined using Optimization tool in
MATLAB.
REFERENCES
[1] H. Y. Yamin and S. M. Shahidehpour,
“Transmission congestion and voltage
profile management coordination in
competitive electricity markets,”
International Journal of Electrical Power &
Energy Systems, vol. 25, pp. 849-861, Dec.
2003.
[2] Xiao-Ping Zhang, (2007) “Congestion
Management – Challenges and Solutions”
Report of Touch Briefings.
[3] Vries L.J. Capacity allocation in a
restructured electricity market: technical and
economic evaluation of congestion
management methods on interconnectors. In:
Proceedings of the 2001 IEEE Porto power
tech conference.
[4] Lommerdal M, Soder L. Simulation of
congestion management methods. In:
Proceedings of the 2003 Bologna power
tech.
[5] Galiana GD. Assessment and control of the
impact of FACTS devices on power system
performance. IEEE Trans Power Syst
1996;11(4):1931–6.
[6] S. N. Singh and A. K. David, “Optimal
location of FACTS devices for congestion
management,” Electr. Power Syst. Res., vol.
58, pp. 71–79, June 2001.
[7] P.Preedavichit and S. C. Srivastava,
“Optimal reactive power dispatch
considering FACTS devices,” Electr. Power
Syst. Res., vol. 46, pp. 251– 257, Sep.1998.
[8] Naresh A, Mithulananthan N (2006).
Locating Series Facts Devices For
Congestion Management In Deregulated
Electricity Markets. Electric Power Systems
Research.
[9] A. J. Wood and B. E. Wollenberg, Power
generation, operation and control, 2nd ed.,
New York: Wiley Interscience, 1996.
[10] Fuerte-Esquivel C.R, Acha E, and Ambriz-
PBrez H,(2000) “A Thyristor Controlled
Series Compensator Model for the Power
Flow Solution of Practical Power
Networks” IEEE transactions on power
systems. vol. is, no. 1.
[11] De Oliveira E.J., Lima W.M., 1999
Allocation of FACTS devices in a
competitive environment, 13th
PSCC, 1184-
1190.
[12] Verma K.S., Singh S.N., Gupta H.O., 2001
FACTS devices location for enhancement of
total transfer capability, Power Engineering
Society Winter Meeting, IEEE, Vol. 2: 522-
527.
[13] R.S. Fang and A.K. David, “Transmission
Congestion Management in an Electricity
Market,” IEEE Trans. On Power Systems,
Vol. 14, No. 3, Aug. 1999, pp. 877-883.
[14] Grigg,C.,”The IEEE Reliability Test
System:1996", The 1996 version of the
Reliability Test System ,Paper96 WM 326-9
PWRS, IEEE Winter Power meeting 1996
[15] Desouza. B.A .et.al. Micogeneticalalgorithm
and Fuzzy logic applied to the optimal
placement of capacitor banks in distribution
networks “IEEE Trans,Vol 19,May 2004

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