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Engineering, Technology & Applied Science Research Vol. 13, No. 4, 2023, 11490-11496 11490  
 

www.etasr.com Rajderkar & Chandrakar: Security Enhancement through the Allocation of a Unified Power Flow … 

 

Security Enhancement through the Allocation of 

a Unified Power Flow Controller (UPFC) in a 

Power Network for Congestion Management 
 

Vedashree P. Rajderkar  

Department of Electrical Engineering, G H Raisoni College of Engineering, India 

vedashree.rajderkar@raisoni.net (corresponding author)  

 

Vinod K. Chandrakar 

Department of Electrical Engineering, G H Raisoni College of Engineering, India 

v12k5c63@gmail.com 

Received: 31 May 2023 | Revised: 22 June 2023 and 7 July 2023 | Accepted: 8 July 2023 

Licensed under a CC-BY 4.0 license | Copyright (c) by the authors | DOI: https://doi.org/10.48084/etasr.6075 

ABSTRACT 

The electricity demand is continuously increasing, so a most efficient use of the current power system's 

capacity is desired. Flexible AC Transmission Systems (FACTSs), a recently developed transmission 

technology, are widely used to boost the power transfer ability of long-distance transmission line networks 

and to enhance the consistency of the transmission systems. The use of FACTS devices can lead to reduced 

flows on heavily loaded lines, targeted bus voltage levels, and better power network stability. In this study, 

an optimization method based on the optimal position of the Unified Power Flow Controller (UPFC) is 

suggested to boost system security. It is decided that the real power flow is the best place for the UPFC in 

this instance. The optimal placement during congestion has been determined using the Genetic Algorithm 

(GA) and the sensitivity to the useful power flow index. Congestion is produced on the network and system 

performance is evaluated. The proposed solutions are evaluated in the IEEE 30 bus network before being 

implemented in MATLAB. In the case of congestion, the security of the network is evaluated after 

connecting the UPFC. The effectiveness of the proposed solution was verified with the help of the Power 

World Simulator 16.0.  

Keywords-UPFC; sensitivity to useful power flow index; genetic algorithm; location optimization; security 

I. INTRODUCTION  

Modern large and complex networks are delivering under 
stress as a result of the ongoing increase in demand. The 
utilities are forced to deal with continuous I

2
R loss, line 

overloads, and variations in bus voltage. Power transmission 
systems require more capacity, flexibility, reliability, and 
security. Electric utility companies search for various strategies 
to effectively use the existing transmission lines up to their 
working capacity. However, this has the side effect of raising 
the possibility of system instability while security issues 
emerge. On improving the network security, techniques that 
relieve stress have received much attention. Line overloads 
have been addressed using load shedding and generation 
rescheduling methods. Load shedding is frequently regarded as 
the last choice because it will interrupt the power supply of 
some customers. The operational costs associated with 
generation rescheduling are fairly substantial. The use of 
FACTS devices to redistribute power is preferred in order to 
solve line overload problems since it offers a financially 
appealing technique of resolving line overloads without 
switching off power. FACTS devices are frequently applied in 

networks to ensure steady state and secure operation. FACTS 
devices can alter system settings such as useful power, MVAR 
power, and node voltage and are incorporated in the electrical 
networks to improve their flexibility, stability and security. 
UPFC is considered to be a part of the most recent generation 
of FACTS. The UPFC efficiently redistributes power within 
the power network. Additionally, an existing transmission line 
can have a UPFC built on it, something that requires less space 
than adding a new transmission corridor. Due to the extremely 
high power flow control speeds of UPFCs, overloads brought 
on by component failures or intermittent generation can 
potentially be immediately relieved. However, the number of 
UPFC devices and the complexity of the power system enhance 
combinatorically the viable zone and the constraints to be taken 
into consideration in optimization approaches. Authors in [1] 
explain that the line loading is tracked in real-time performance 
and can be kept under their thermal tolerance by a quick and 
effective dynamic response management of the UPFC. In [2], 
the authors describe the SCOPF simulation used to decide the 
appropriate place for UPFC in the standard network under 
higher load circumstances According to [3], the use of UPFC 
may effectively decrease the N-1 congestion issue of 



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transmission channels running North to South and has a 
significant cost superiority over the old method. Authors in [4] 
suggest incorporating a UPFC into a Newton-Raphson load 
flow method. The created UPFC model is based on a power 
injection strategy that considers four control modes to manage 
the voltage amplitude of a given node, the useful and MVAR 
powers flow in a line concurrently or selectively. In [5], the 
best place of a DPFC in a network was suggested, followed by 
the optimum placement of two DPFCs in a system. The 
artificial algae method is used for the optimal placement of the 
DPFC in the electrical system. In [6], the authors present and 
execute a 161 kV UPFC model on an 11-bus network. The 
weakest bus is located by using FVSI, and the most vital line 
was identified using MLA. Authors in [7] examine dynamic 
stability, proposing a method that uses a hybrid strategy to 
identify the best placement and size of the UPFC. Authors in 
[8] utilized the conventional strategy to place the TCSC and 
UPFC in the best possible location for boosting system security 
under various operating situations and at the best FACTS 
parameter values. Authors in [9] discuss various methods for 
reducing congestion, such as load shedding, GA, PSO, MINLP, 
SFLA, and Fuzzy Logic Systems. The best location for DG, 
Nodal Pricing, and cost-free methods are also discussed. In 
[10], the authors suggested a full-featured, reliable and 
adaptable model for ESS and UPFC together after briefly 
reviewing the models that are now in use, including the 
decoupled, power injection, and voltage source models. In 
order to reduce total grid losses, authors in [11], use the Tabu 
search algorithm based on an improved HS method to represent 
an optimization challenge for an I grid. Authors in [12], discuss 
how FACTS devices can enhance a transmission line's ability 
to handle power and maintain Voltage. Numerous researches 
have discussed the ideal location for UPFC [13–16]. However, 
they are not concerned with the verification of the software-
based congestion forecast. 

The location of UPFC based on congestion management by 
using sensitivity based methods and GA in order to relive the 
congestion and to enhance the power system security and 
reliability is discussed in this paper. The results are validated 
by using Power World Simulator (PWS). This investigation 
offers the ideal positioning for UPFC based on the useful 
power flow performance index approach. The fact that the 
active power flow assessment index is a reliable indication of 
useful power security, a decrease in Performance Indicator (PI) 
caused by the placement of the FACTS controller will improve 
network security. The location of these devices in the network 
was determined using the sensitivity of PI with regard to the 
FACTS control variables which is comparable to UPFC 
location determined by GA, for strengthening the security of 
system during congestion management. The decision on the 
placement of the UPFC is made in accordance with the results, 
and verified was with the PWS, 

II. UPFC DESIGN 

For steady state conditions, UPFC static modeling was 
created. Series and shunt converters were combined to create 
UPFC. Voltage (VS), Insertion angle in a series with line (ϕs), 
and an element of shunt current (Iq), which is in quadrature 
with voltage Vi at the UPFC's i

th
 bus, are the three control 

parameters for UPFC [8]. The equivalent circuit of the line 
incorporating the UPFC is described in Figure. 1. When a line 
includes UPFC, its apparent powers are expressed as: 

��� =
−�����	 − 2�� �� ��	 cos�∅� − ��� + �	 �� ���	 cos�∅� − �	 � +
��	 sin�∅� − �	 ��      (1) 

��� =  
�� �� + �� �� ���	 sin�∅� − �� � + ��	 cos�∅� − �� �� (2) 
�	� = �	 �� ���	 cos�∅� − �	 � − ��	 sin�∅� − �	 ��  (3) 
�	� = −�	 �� ���	 sin�∅� − �	 � + ��	 cos�∅� − �	 �� (4) 

 

��  = !� +  "�  

#�$  # $
 

Fig. 1.  FACTS controller model. 

A. Power World Simulator Software based UPFC Model  

A systematic approach is developed to simultaneously 
control real power, MVAR power, and bus voltages [10]. The 
useful power, MVAR power, or the voltage of each node can 
be used to secure the network. If the bus element is neutral to 
the bus parameters, the power flow solution is constant. UPFC 
is connected in the line and always maintains the voltage (VEt) 
in sending bus i and injects PBt-QBt at the receiving end to bus j 
as illustrated in Figure 2. Under loss-free UPFC, the power 
values for bus i and bus j would be equal as indicated in Figure 
3. The UPFC sending end's known values are PEt and VEt. 
When UPFC is implemented at the sending, according to the 
design, an additional bus must be added to the network in the 
PWS [10]. If a UPFC is developed in the center of the line, the 
network will need to add two buses. 

 

 

Fig. 2.  UPFC power flow model. 

 

Fig. 3.  UPFC static model. 



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III. UPFC CONTROLLER PLACEMENT 
METHODOLOGY 

The reserve capacity of the transmission system has a 
partial representation in load ratio. Additionally, the reserve 
capacity increases as the load rate decreases. Therefore, 
increasing the transmission capacity of overloaded lines could 
meet the needs of increasing load. Regarding accident 
prevention, both the stability state and the typical power flow 
of the system are examined. After that, the system starts to use 
congestion management. Here, the real power flow 
performance index and GA are used to calculate the maximum 
power flow and the most suitable position for placing the 
UPFC is selected. The system returns to regular operation and 
security is enhanced after attaching the UPFC. 

A. Sensitivity-Based Method 

The performance of the line under routine and emergency 
circumstances affects the active power flow Performance 
Indicator (PI). The active power flow PI [8] technique can be 
used to describe the loadability of the system's functionality: 

�� = ∑ &'�( )
*+'

*+'',-
.

�(/+
012    (5) 

where, wm =1, Nl is the total number of lines in the system, wm 
is a real non-negative weighting coefficient, �30045  is the 
maximum load capacity of the line, �30  is the actual power 
flow in the line, and n = 2. 

The degree of severity is determined by the system's 
loading circumstances in both normal and emergency 
situations. The sensitivity technique is used to analyze the 
system's performance. Low PI value means an operation within 
thermal limits under steady state conditions. The value of PI 
rises when an overloaded condition is reached. In this article, 
the active power flow performance indicator approach is used 
to decide where to allocate UPFC in relation to series insertion 
angle (ϕs) as shown below: 

6�7  = 8*9:;8∅<   =∑ =0�30>/+012 ) 2*+'',-.
? 8*+':<8∅<  (6) 

The real power injection in the line is taken into 
consideration when computing DC power flow equation [8] : 

�30 = @∑ #0( �(                       ABC D E F,
/(12(H�∑ #0( �(/(12(H� � �	            ABC D = F  (7) 

According to Figure 1, the UPFC is situated in line k, which 
connects buses i and j. Pj is the additional electrical power that 
UPFC in the system injects into the line. The network has N 
buses, and Smn is the mn

th
 part of the power flow matrix [S]. 

The following equation can be created by combining (6) and 
(7): 

8*+':<8∅< = @
I#0� 8*J<:<8∅< � #0	 8*K< :<8∅<L                ABC D E FI#0� 8*J<:<8∅< � #0	 8*K< :<8∅<L � 8*K< :<8∅<   ABC D = F

   (8) 
where: 

8*J<:<8∅<M∅� 1N = �2�� ��	 cos�∅� � �� � � �	 ���	 cos�∅� ��	 � � ��	 sin�∅� � �	 ��  
O� $

�$ O∅$P∅$ =0 = � I�� RB$� � �� $�S� L      
Due to its cost effectiveness, the useful power flow PI is 

derived using the aforementioned equation with regard to the 
series insertion angle as an installed UPFC control variable in 
each line individually. It should be put in an ideal position. The 
optimum allocation for UPFC placement is in the line with the 
most negative sensitivity index to improve system security, but 
other criteria may also be used to decide that UPFC should not 
be situated close to a producing transformer, despite the most 
negative sensitivity index.   

B. Genetic Algorithm 

GAs are methods for conducting a global search that are 
based on natural selection and genetics. They don't need any 
specialized knowledge or characteristics of the goal function 
and they can look for multiple potential solutions 
simultaneously. They are also excellent techniques for finding 
an effective answer to a complex problem since they 
consistently deliver high-quality solutions. Furthermore, they 
are useful algorithms that are simple to apply to the analysis of 
power systems. 

The ratio of a line's actual power flow to its maximum 
power flow is known as the line's sensitivity factor. It is helpful 
in figuring out the severity of the line, where high severity 
indicates the line has a significant chance of collapsing soon. 
The fitness function to be maximized [16] is: 

∑ ) *JK*JK',-./T�	12                      (9) 
where ��	  is the flow of power on line ij, ��	045  is the maximum 
flow of power in line ij, and NL is the number of lines. 

For the best allocation of UPFC, the line with the highest 
fitness value is taken into account.  

 

 

Fig. 4.  Flowchart of the UPFC device optimal allocation process. 



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The GA begins with the initial population being generated 
at random and continues with selection, crossover, and 
mutation before the maximum generation is attained. Each 
string that relates to a location is used to construct the initial 
population, which is the transmission line's number where the 
FACTS is supposed to be placed. The position value differs for 
each string. Every member of the population will then have its 
objective function (fitness) evaluated. GAs have limitations to 
finding the objective function's largest positive value. In the 
process of reproduction, an individual is chosen to become part 
of a new generation based on its fitness. The primary goal of 
crossover is to combine the knowledge of two distinct 
individuals to create a new one. To prevent an early 
convergence to a local optimum, mutation is used to inject 
some type of artificial diversification into the population. 
Figure 4 summarizes the suggested optimization method. The 
"Arrangement of the FACTS locations" procedure is required 
to guarantee that each line has only one FACTS device. 

IV. SIMULATION RESULTS 

On a modified IEEE 30 bus network [11], the suggested 
technique for using UPFC in the most effective way was 
employed using MATLAB. Bus no. 1 was used as a reference. 
According to load flow analysis, line 4-6 has reached its 
maximum thermal limit. 

A. Sensitivity Approach 

The most suitable allocation of the UPFC was computed 
based on active power flow. With regard to the insertion angle 
in series with line as a control variable, the UPFC was put in 
each line for similar operational circumstances in order to 
decrease system's overloads without modifying the network's 
topology or without rescheduling generation. Table I shows the 
PI sensitivity indicator in relation to UPFC. According to Table 
I, line 5-7 has the largest negative sensitivity index with respect 
to ϕs. Therefore, it is appropriate to install the UPFC in line 5-7 
to prevent overloading and improve system security. 

TABLE I.  SENSITIVITY BASED ON PI ON AN IEEE 30 BUS 
NETWORK WITH OVERLOAD AT LINE 4-6  

Line no UVW = XYZ[\X∅\  
1-3 -1.149867577 

2-4 -1.378312267 

2-5 -2.943605844 

2-6 -4.151895176 

3-4 -2.198711769 

5-7 -7.896648528 

 

B. Genetic Algorithm 

In this paper, we try to discover the optimal location for the 
UPFC using GA. The best fitness function findings for UPFC 
are displayed in Table II. Table II shows that the fitness values 
in lines 2-4 and 2-5 are the highest, however the installation for 
UPFC location in lines 2-4 and 2-5 does not relieve the 
congestion. So, line 5-7 is the optimum location for the 
placement of UPFC because it can control the useful power 
flow in line and enhance the security of the network. 

 

TABLE II.  OVERLOAD IN LINE 4-6: GA BASED LOCATION 
FOR UPFC ON IEEE 30 BUS NETWORK 

Line no Best fitness value 

1-3 0.933 

2-4 1.0453 

2-5 1.0443 

2-6 0.9674 

3-4 0.9304 

5-7 0.9515 

 

C. Power World Simulator 

Despite having certain UPFC properties that increase power 
system effectiveness, there is a limitation related to active 
power injection. This capability's implementation greatly 
improves UPFC steady-state performance. The simple UPFC 
parameters calculation and steady state UPFC model 
simulation clearly demonstrate its superiority to other models. 
UPFC parameters can be simply calculated without the need 
for initial values and their limits may be easily altered. The 
results would be more reliable if these investigations were 
conducted using the provided model in a real network rather 
than a simplified one as shown in Table III. Figure 5 illustrates 
the system's congestion situation under steady state conditions. 
According to Figure 6, adding a UPFC to line 1-3 reduces 
overloading from 104% to 101% on line 4-6. Figure 6 depicts 
the line loading limit of 101%. According to Figure 7, even 
though overloading decreased after installing UPFC in lines 2–
6, from 104% to 97%, according to PWS, the situation is still 
dangerous because the power flow in lines 4-6 is indicated by a 
red arrow, indicating that the thermal limit has not yet been 
obeyed. The power flow illustrated by the green arrows in 
Figure 8 shows that it runs within its thermal limit and 
decreases line 4-6 overloading from 104% to 97%. Therefore, 
line 5-7 is an excellent location for UPFC insertion according 
to the sensitivity indicator, GA, and the PWS has verified this 
location for improving system security. 

TABLE III.  LOCATION FOR UPFC ON THE IEEE 30 BUS 
NETWORK USING PWS. LINE 4-6 IS OVERLOADED BY 

104% 

UPFC placement in 

line no 

% loading reduces in line 4-6 after UPFC 

placement 

1-3 101 

2-4 101 
2-5 100 

2-6 97 (congestion not relieved completely) 

3-4 101 

5-7 97 ( completely relieved) 

 

V. DISCUSSION 

On a large power network, congestion is the most 
frequently occurring problem. Such problems can be avoided 
using UPFC. Simulation results indicate that the conventional 
sensitivity approach, based on coding methods, for determining 
the best location of UPFC is line 5-7 in an IEEE 30 bus 
network. The derived location is verified by the result of GA. 
The validation of the result is done by PWS. The network 
security is significantly enhanced by UPFC optimal location at 
line 5-7. 



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Fig. 5.  System overload on line 4-6 of a modified IEEE 30 bus. 

 

Fig. 6.  UPFC located in line 1-3. 

 

Fig. 7.  UPFC located in line 2–6 (line 4-6 is shown in red despite 97% capacity). 



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Fig. 8.  UPFC located in line 5-7 (green indicates the flow in line 4-6 displays 97% loading). 

VI. CONCLUSION 

In this study, a sensitivity-based technique and GA have 
been developed for determining the most appropriate location 
for placing a UPFC device. Test results demonstrate that the 
sensitivity factor or GA can be utilized to successfully deploy 
UPFCs in response to the desired objectives. The position of 
UPFC can be chosen if there is congestion. With the use of 
PWS, a comprehensive model of UPFC must be taken into 
consideration after choosing the appropriate location in order to 
relieve congestion and improve system security. Line 5-7 is the 
resulting suitable placement for UPFC by both GA and active 
power flow performance indicator methods and this result was 
validated by PWS software. 

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