A Review on Power Flow Analysis with UPFC and its Applicability

A Review on Power Flow Analysis with UPFC and its Applicability

Adit Pandita Dr. Sanjay K. Jain

M.E Student, Associate Professor,

Electrical and Instrumentation Electrical and Instrumentation Engineering Department, Engineering Department,

. Thapar University, Patiala. Thapar University, Patiala.

Abstract

The unified power flow controller (UPFC) is an advanced member of flexible AC transmission systems (FACTS) group. This paper is focused on three techniques for inclusion of the steady state models of the UPFC in power flow programs. This paper also presents a review of various benefits and applications of UPFC in power flow studies such as minimization of loss, enhancement of loadability, voltage stability etc. using various optimization techniques. A case study is also shown to analysis effect of UPFC using comprehensive NR method based power flow.

Keywords: Unified Power Flow Controller (UPFC), Newton Raphson method, Steady state analysis, loadability, voltage stability.

1. Introduction

   Power flow calculations are performed in power systems for planning, operational planning, and operation/control. Power flow equations, commonly referred to as power flow are the backbone of power system analysis and design. The power flow problem consists of the calculation of power flows and

   The Unified Power Flow Controller (UPFC) is, arguably, the most comprehensive device to have emanated so far from the FACTS initiative. UPFC is capable of providing active and reactive power control, as well as adaptive voltage magnitude control.

   UPFC is a versatile FACTS device which can independently or simultaneously control the active power, reactive power, and the bus voltage to which it is connected. This controller offers substantial advantages for the static and dynamic operation of power system. However, to achieve such functionality it is important to find the optimal location of this device to be installed in power system with appropriate parameters. The active power loss reduction, the stability margin improvement, the power transmission capacity increasing, and the power blackout prevention, are some factors that can be considered in selecting the optimal installation and optimal parameters of UPFC. This controller also helps in increasing the loadability of the power system and providing better security and reliability to a power system network. It also helps in providing better voltage stability by setting appropriate control parameters. Fig.1 shows the schematic diagram of UPFC and its working.

   V

   V

   voltages of a network for a specified terminal or bus

   conditions. Appropriate steady state model of power Vk m

   system is needed for writing the computer programs. I1

   VcR

   The model includes non-linear algebraic equations, which must be solved iteratively. Power flow calculations are needed for both steady state analysis and initializations of different dynamic analysis.

   Flexible AC Transmission systems (FACTS) is a concept based on power-electronic controllers, which

   Ik

   IvR

   VvR

   Shunt Converter I2 I3

   VDC

   Im

   Series Converter

   enhance the value of transmission networks by increasing the use of their capacity. These controllers

   VvR vR

   VcR

   cR

   are used for enhancing dynamic performance of power systems in terms of voltage/angle stability while improving the power transfer capability and voltage profile in steady state.

   Fig.1: UPFC Schematic diagram

   This paper presents a review on various benefits which UPFC provides in a power system, including

   improving steady state, transient stability, damping power swings, enhancing system loadability, which is provided by optimally locating and setting UPFC parameters. This paper also focuses on study of various UPFC models for power flow studies.

2. Benefits of UPFC

   In past, researchers have used various techniques in power flow studies to incorporate UPFC to minimize losses, generation costs and maximize loadability, social welfare etc. To seek optimal allocation and parameter settings of UPFC in power system various evolutionary techniques have been applied recently. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) techniques have been used to find out optimal location and parameter setting of UPFC device to minimize active power losses in a power system. Various such benefits have been surveyed herewith.

   1. Minimization of Generation Cost

      In the normal operation state of power system, the production costs of active power can be minimized by economic power dispatch, and delivery costs due to transmission system loss can be also minimized by active power control of UPFC, incorporated with minimization of production cost.

      Lim et al. [3] presented UPFC operation for minimization of delivery cost and power production in normal operation state. The delivery cost due to transmission loss can be minimized by active power control of UPFC using uncoupled model of UPFC in power flow.

      Vijayakumar et al. [4] developed an algorithm to simultaneously find the real power allocation of generators and to choose the type and the best location of UPFC device such that overall cost function which includes the generation cost of power plants and investment cost of FACTS is minimized. The combinatorial analysis is solved using Hybrid Genetic Algorithm on IEEE 9 bus system. The Optimal Power Flow problem formulated is as follow,

      Minimize CTotal = C1 (f) + C2 (PG) (1)

      Subjected to E (f,g) = 0 (2)

      B1 (f) < b1, B2 (g) < b2 (3)

      E (f, g) is the conventional power flow equations. B1

      (f) and B2 (g) are the inequality constraints for UPFC and the conventional power flow respectively.

      Taher et al. [5] presented the application technique to find the optimal location of UPFCs (with installation cost) for getting minimum total active reactive power production cost of generators, and congestion management. Simulations were performed on IEEE-

      14 and IEEE-30 bus test systems and the optimal solutions found by IA were better than those of standard Genetic Algorithm (GA) and Particle Swarm Optimization (PSO).

      Kiran et al. [6] proposed Particle swarm optimization method to solve the optimal power flow problem on power system by finding a location for UPFC device. The proposed algorithm is an effective method for finding the optimal choice and location of UPFC controller and also minimizing the overall system cost, which comprises of generation cost and the investment cost of the UPFC controller using PSO and conventional Newton Raphsons power flow method by verifying it on IEEE 14 bus test system.

   2. Enhancement of System Loadability

      Estimating loadability of a generation/transmission system is a generalized mathematical programming problem. It is not a standard mathematical programming problem because some of the constraints (specifically, dynamic security constraints) have to be expressed not in algebraic forms but in the form of differential equations. Loadability of power systems is dependent upon the pattern of load increasing.

      Saravanan et al. [7] proposed the application of Particle Swarm Optimization to find the optimal location, settings, type and number of FACTS devices including UPFC to minimize its cost of installation and to improve system loadability for single and multi-type FACTS devices. While finding the optimal location, thermal limit for the lines and voltage limit for the buses are taken as constraints. This has been tested on IEEE 6 and IEE 30 bus test systems. It is observed that system loadability cannot be improved further after placing certain number of devices. In IEEE test systems, UPFC gives maximum system loadability but the cost of installation is high when compared with all other cases.

      Singh et al. [8] proposed a new variant to Genetic Algorithm, specialized in multi-objective optimizations problem known as Non-Dominated Sorting Genetic Algorithm II (NSGA II), to obtain optimal allocation of UPFC for enhancing loadability of the system within security and stability margins. This method to optimize the objective function of

      maximizing loadability is tested on IEEE 30 bus system with effective results.

      Singh et al. [9] suggested the suitable locations of UPFC to enhance system loadability and tested it on IEEE 14 bus system. A sensitivity based approach has been developed for finding suitable placement of UPFC. The optimal power flow problem involves a nonlinear objective function and a set of nonlinear equality and inequality constraints. Sequential Quadratic Programming (SQP) has been used to obtain OPF solutions.

      Shaheen et al. [10] presented application of evolutionary optimization techniques for optimal location and parameter setting of multiple UPFC devices for maximizing loadability and minimizing installation cost in power system with respect to line thermal limits and bus voltage magnitude limits. This proposed method was tested on IEEE 6 and IEEE 14 bus test power system with desired results. The results obtained by GA and PSO has stable convergence characteristic and good computational efficiency as the system loadability can be increased significantly by certain load factor by installing UPFC.

   3. Minimization of Power Losses

      One of the capabilities of UPFC is the power loss reduction in the power system. Farhangfar et al. [11] presented an injection model of UPFC to investigate its effect on power flow and loss reduction in power system. The best place for UPFC for loss reduction is in the main transmission line. It can be achieved by two methods. The first method is to increase the transition power in lines, which have low impedance. This can be implemented by inserting series voltage in phase with the sending end bus voltage. In this method, because of the increased transmission power, the size of the UPFC is greater, which makes it expensive. Another method is to decrease the transmission power in lines with high impedance. Hence, inverse series voltage with respect to the voltage of the sending end bus should he inserted to the line. Finally in order to decrease the loss in the power system, it is more economical to install UPFC in the lines with high impedances that are usually long lines.

      Kothari et al. [12] formulated voltage phasor method and loss minimization including UPFC as an optimization problem. PSO is applied for real power loss minimization including UPFC and is tested with IEEE 14 and IEEE 57 bus test systems. The algorithm is easy to implement and is capable of

      finding the global optimum solution for the loss minimization giving decision about the minimal loss location is the location of the UPFC. For large power systems PSO could have a significant advantage compared to the exhaustive and other methods, by giving better solutions with less computational effort.

      Rashed et al. [13] presented a Differential Evolutionary (DE) algorithm for finding the optimal location and the best parameter setting of Unified Power Flow Controller (UPFC) for minimizing the active and reactive power losses in the power system. Simulations have been implemented in MATLAB and the IEEE 14-bus and IEEE 30-bus systems have been used as a case study. Also for the purpose of comparison the proposed technique was compared with another optimization technique namely Particle Swarm Optimization (PSO). The results we have obtained indicate that DE is an easy to use, robust, and powerful optimization technique compared with particle swarm optimization (PSO). Installing UPFC in the optimal location determined by DE can significantly minimize the active and reactive power loss in the network.

   4. Voltage Stability and Maximization of Transmission Capability

      The voltage deviation due to load variation and power transfer limitation were observed due to reactive power unbalances has drawn attention to better utilize the existing transmission line. It also causes a higher impact on power system security and reliability in power system network. Thus UPFC plays a vital role in maintaining stable voltage profile and also maximizing the transmission capability of power system network without the need of building new transmission lines.

      Abdullah et al. [14] presented the application of evolutionary computation technique for monitoring voltage profile of the power system network when UPFC is incorporated in the network. Evolutionary Programming and Artificial Immune system method have been applied in IEEE 30 bus RTS system to maintain stable voltage profile and minimize losses while increasing the power transfer capability.

      Mori et al. [15] proposed a new method Two- Layered Tabu Search (TLTS) method for optimal allocation of UPFC. UPFC is employed to control power flows so that the transmission capability is maximized in different power system conditions. The proposed method is based on two layered tabu search (TLTS) that is effective for the nonlinear mixed integer problem. TLTS evaluates better solutions by

      repeating the process that Layer 1 determines the optimal integer variables while Layer 2 computes the optimal continuous ones. The proposed method was successfully applied to the IEEE 14-node system. A comparison was made between the proposed and the conventional methods in terms of solution accuracy and computational time.

      Yap et al. [16] presented an effective utilization of UPFC in power flow control to improve existing transmission capability of the power system network. The IEEE 14-bus network system operating with common loads and generators is used to demonstrate the available controllability in the UPFC through computational monitoring.

      Chen et al. [17] discussed control of UPFC to improve power system voltage stability. A dynamical UPFC model is presented. The impact of the UPFC model on voltage stability is clarified through bifurcation analysis. Robust techniques are employed for the series and shunt branches control and the DC capacitor voltage control. Different roles of the series and shunt branches of UPFC in voltage stability are studied on a three-machine power system. The effects of the UPFC controllers on voltage stability enhancement are examined on the three-machine power system. Bifurcation analysis shows that the feasibility region is significantly affected by the proposed UPFC control.

   5. Power system Security and Transient Stability

      Kim et al. [18] presented a new UPFC operation algorithm to find the operating point of UPFCs for the system security level Enhancement. The proposed algorithm iteratively minimizes the security index which indicates the overload level of transmission lines. The sensitivity representing the change of the index for a given set of changes in the UPFC real power outputs is derived. In each iteration, with this sensitivity, the proposed algorithm finds a new UPFC operating point that reduces the index or increases the security margin. The algorithm is verified by IEEE 39 bus system with multiple UPFCs. The proposed algorithm is tested with 3 UPFCs on the normal operating system and on the same system with a line fault. The study results show two things. The first is UPFCs operated by the algorithm can provide the normal operating system with the relief of the power flow congestion in the system and enhance the system security level. And the second is by applying the algorithm the UPFCs with a proper capacity can enlarge the security margin to prevent the overload problem of the system in an increased load or faulted condition.

      Gerbex et al. [19] presented a comparison between three heuristic methods (Simulated Annealing, Tabu Search method, Genetic Algorithms) applied to the optimal location of UPFC in order to enhance the system security. The optimizations are made on three parameters: the location of the UPFC, their types and their sizes. The three methods lead to similar results, but generally Tabu Search method and Genetic Algorithm converge faster than Simulated Annealing. IEEE 118 bus test system is applied for the comparative study.

      Taki et al. [20] discussed the application of neuro fuzzy controlled UPFC to improve transient stability of power system. Neuro-fuzzy control method the membership function parameters of fuzzy controller can be computed with learning information about a data set. This Adaptive Network Fuzzy Inference System (ANFIS) can track the given input-output data the best. The process of training data generation is based on maximizing the energy function of UPFC. Proposed method is tested on a single machine infinitive bus system to confirm its performance through simulation. The purpose of maximizing the transient stability margin has been achieved by maximizing the injected energy of UPFC by using its energy function. Consequently, the ANFIS controller operation is based on energy function optimization. By keeping the series (shunt) branch inactive, UPFC can operate as a STATCOM (SSSC) and the corresponding behavior is also evaluated and compared. The superiority of the proposed controlled UPFC over a STATCOM or a SSSC in improving transient stability of a single machine infinitive bus has been demonstrated.

      Hosseini et al. [21] proposed a transient model and control system of UPFC to enhance the voltage regulation and transient stability of a radial AC transmission system using UPFC. The control scheme has the fast dynamic response and therefore, improves the transient behavior of power system after a transient condition. Simulation results demonstrate that the presented control system acts properly in steady state and transient condition. The presented UPFC control system can regulate line active and reactive power flow and voltage at line midpoint. The presented control system of UPFC not only responses to the step changing in the active and reactive power, but also is able to exchange the direction of line active power flows. Also, the proposed control system is regulating the DC link capacitor voltage. The simulation results indicate the fast dynamic response, validity and effectiveness of the presented control scheme.

   6. Damping Power Swings

      Tambey et al. [22] suggested a comprehensive approach to the design of UPFC controllers (power- flow controller, DC Voltage regulator and damping

      K m

      Ik VcR Im

      ZcR

      controller). Studies reveal that damping is adversely affected by the incorporation of a DC-voltage regulator. Investigations were carried out to understand the relative effectiveness of modulation of the UPFC control signals mB, B, mE and E on damping of the system oscillations, using a controllability index. Dual damping controller based on simultaneous modulation of UPFC control signals

      Vk ZvR

      VvR

      Vm

      Re{-VvRII*vR+VcRI*m}=0

      mB and E is proposed. Investigations reveal that alternative damping controllers (damping controller mB, damping controller E and dual damping controller) provide robust dynamic performance under wide variations in loading condition and system parameters.

      Gharibpour et al. [23] presents the control methods to damp the power swings using UPFC. The first control algorithm is based on energy and equivalent energy criterion that works only at the presence of disturbance. The second one is adding an active damper to the system and affecting on the system damping. In this algorithm in order to increase the damping of a system of the machine. This function is used to determine the angle in which a proper damping is added to the system. This angle can be set as the reference and by using the angle compensation mode, the voltage injection is done in that angle. In this algorithm by using an angle feedback it doesn't need to exchange a lot of information which is used in other algorithms. Finally the power swing is observed in the simulation by selecting a power flow model for UPFC.

3. UPFC models for Power Flow Studies

   There are various techniques for inclusion of steady state models of the UPFC in power flow programs. This paper is focused on three techniques for

   Fig.2: Equivalent Circuit of UPFC

   to regulate the nodal voltage magnitude at node k. in this situation, assuming a loss free UPFC operation and neglecting the resistance in voltage source impedances, the UPFC and coupling transformers can be modeled by means of a load at bus k and a generator at bus m. This is shown in figure (3).

   The sending end of UPFC is transformed into a PQ bus, while the receiving end is transformed into PV bus. The active and reactive power loads in PQ bus are set to the values being controlled by UPFC. The standard power flow solution is carried out with an equivalent model given by fig.3 (b). After power flow convergence a set of non-linear equations is solved by iteration to compute the UPFC parameters.

   Fig.3 (a): UPFC model schematic

   incorporating UPFC in power flow studies. They are: Decoupled UPFC model, Injection UPFC model and comprehensive NR UPFC model. A comparative study is also presented in this paper for the mentioned models.

   1. Decoupled UPFC Model

      A sequential UPFC power flow model proposed by Nabavi-Niaki and Iravani [24] is capable of

      k PV – type V

      Pmk

      m

      Pmk Qmk

      PQ – type

      regulating the power flow from node m to node k and

      Fig.3 (b) UPFC model equivalent

      1. Drawbacks of Decoupled UPFC Model

         Although this sequential method is simple but it is not clear from it how the model can be used in situations when the UPFC is not controlling the voltage magnitude, line active power and line reactive power simultaneously. Moreover since UPFC parameters are computed after power flow converged, there is no way of knowing during this iterative process whether or not the UPFC parameters are within limits. The UPFC parameters are computed iteratively by Newton-Raphson method, no guidelines are given to select suitable UPFC parameters starting values.

   2. UPFC Injection Model

      Reference [25] presents an approach of modelling the UPFC as a series fixed reactance Xs together with a set of active and reactive nodal power injections at each end of the series reactance Psi , Qsi , Psj , Qsj .

      These powers are expressed as a function of the terminal, nodal voltages, and a voltage of a series source, which represents the UPFC series converter. The fig. (4) Shows complete injection model of UPFC connected between buses i and j. The series voltage source Vser is taken equal to rVi where 0

      < r < rmax and o < < 2. r and represent the control parameters of UPFC.

      1. Advantages of UPFC Injection Model

         The attraction of this formulation is that it can be implemented easily in existing power flow program and UPFC can be adjusted to work as a voltage regulator, series compensator or phase shifter.

      2. Drawbacks of UPFC Injection Model

         The major drawback of this model is that all important aspect of the automatic UPFC parameter adjustment has not been addressed. Also the series voltage course parameters are adjusted by trial and error in order to achieve certain power flow solution, which will match the target power flow.

   3. Comprehensive NR UPFC Model

Trying to circumvent the limitations in the decoupled and injection UPFC model, reference [26] developed a new and comprehensive UPFC model. This model is straightforward extension of the power flow equations and hence, it is suitable for incorporation into an existing Newton-Raphson power flowalgorithm. The UPFC equivalent circuit used to derive this steady state is shown in fig. (2). The equivalent circuit consists of two ideal voltage sources representing the fundamental Fourier series of the switched voltage waveforms at the AC converter terminals. The source impedances included in the model represent the positive sequence leakage

V

Vjj

inductances and resistances of the coupling UPFC

i i transformers. The ideal voltage sources are:

Xs V

V cos

• jsin

4

vr vr vr vr

Vcr

Vcr

coscr jsincr 5

Here

VvR

and

vR

are the controllable magnitude

Psi rbsViVj sin(ij )

VvRmin

VvR

VvRmax

and 0 vR

2

phase

Psj rbsViVj sin(ij )

angle of the voltage source representing the shunt converter. The magnitude V and phase angle of

cR cR

si s i

si s i

Q rb V 2 cos

Qsj rbsViVj cos(ij )

the voltage source representing the series converter are controlled between these limits

Fig.4: UPFC Injection model

: VcRmin

VcR

VcRmax

and 0

cR

2 .

The UPFC injection model is implemented into a full Newton-Raphson power flow program by adding the UPFC power injections and their derivatives with respect to the AC network state variables, i.e., nodal voltage magnitude and angles, at the appropriate locations in the mismatch vector and Jacobian matrix. The original dimensions of the mismatch vector and Jacobian matrix are not altered at all.

Assuming a loss free converter operation, the UPFC neither absorbs nor injects active power with respect to the AC system. The DC link voltage, Vdc, remains constant. The active power associated with the series converter becomes the DC power. The shunt converter must apply an equivalent amount of DC power to maintain Vdc constant. Hence the active power supplied to the shunt converter, must satisfy the active power demanded by the the series converter,

PvR PcR 0 (6)

magnitude increment at node k, Vk / Vk ,. In this

The UPFC linearized power equations are combined with the linearized system of equations corresponding to the rest of the network,

Where,

case, VvR is maintained at a fixed value within prescribed limits, VvRmin VvR VvRmax .

1. Advantages of Comprehensive NR Model

   The main advantages that this UPFC model has over the Decoupled and injection model is that UPFC state variables are incorporated inside the Jacobian and mismatch equations leading to very robust iterative

   f x P P Q Q Q P T

   solution. In this unified solution, the UPFC state

   k m k m mk bb

   (8)

   variables are adjusted simultaneously with the nodal network state variables in order to achieve the

   Pbb is the power mismatch given by equation (6) and superscript T indicates the transposition. X is

   the solution vector and J is the Jacobian matrix. The power mismatch equations are used as the guiding principle for conducting limit revisions. The mismatch provides an accurate indicator for determining the activation of limits revision for a controllable device parameters. The revision criterion of the UPFC is based on its active power converter mismatch. For the case when the UPFC controls voltage magnitude at the AC shunt converter terminal (node k), active power flowing from node m to node k and reactive power injected at node m, and assuming that node m is PQ-type, the solution vector and Jacobian matrix are,

   V V V T

   specified control targets. Hence, the interaction between the network and UPFC is better represented and the UPFC state variables can be identified inside the power flow program. This model also gives the ability to control the active and reactive power simultaneously as well as the voltage magnitude. The losses of the UPFC coupling transformers are taken into consideration.

2. Drawbacks of Comprehensive NR UPFC Model

The drawback of this model is that the UPFC cannot be adjusted to work in voltage regulation, impedance compensation, and phase shift mode. Moreover, the model needs good initial conditions for UPFC state variables for better convergence. Bad initial

vR

vR

X k m

vR m

V V cR

cR

V

(9)

conditions may cause divergence.

vR m cR

4 Case Study

Pk Pk

Pk V

Pk V Pk

Pk V

Pk

V vR

V m

V cR

A small five- node network [27] has been used to

k m vR m cR cR vR

show quantitavely, how the UPFC performs. We

Pm Pm 0 Pm V Pm Pm V 0

V m

V cR

have modified the original network to include a

k m m cR cR

Q Q Q Q Q Q Q

k k V k V k k V k

k

k

UPFC which compensates the transmission line

V vR

V m

V cR

k m vR m cR cR vR

connected between Nodes Lake and main in case 1

Q Q Q Q Q

J m m 0

m V

m m V 0

cR

cR

m

m

and, between Main and Elm for case 2. This is shown

k

P

m

P

Vm

P

cR

P

VcR

P

in Fig. (5) and Fig. (6) respectively. The UPFC shunt

mk mk 0

mk V mk mk V 0

converter is set to regulate the Lakes nodal voltage

V m

V cR

k m m cR cR

at 1 p.u. Initial conditions of UPFC voltage sources

Qmk Qmk 0

Qmk V Qmk

Qmk V 0

V m

V cR

are, VvR = 1 p.u , vR = 0°, VcR= 0.04 p.u, vR = –

k m m cR cR

P P P

P P P

V

V

bb bb bb

vR

Pbb Pbb Pbb

V V

V V

m cR

P

P

bb

87.13°. The source impedance has values of XcR=XvR

= 0.1 p.u. Convergence in case 1 and case 2 was

k m Vm

Vm cR VcR

vR

(10)

attained in 5 iterations to a power mismatch tolerance of 10-12. The UPFC upheld its target values.

If the UPFC voltage control is deactivated, the third column of eqn. (10) is replaced by partial derivatives of the nodal and UPFC mismatch powers with respect to the nodal voltage magnitude Vk. Moreover, the shunt source voltage magnitude increment in

eqn.(9),

VvR / VvR

, is replaced by the nodal voltage

Case -1

North

Lake

Main

Table 2: Nodal Complex Voltage of Modified Network for case 2

1 3 4

UPFC

UPFC

2

South

5

Elm

After the convergence in five iteations the UPFC sending end active and reactive power from node 4 is 40MW and 34.31MVARs respectively. Also the active and reactive receiving end power at node 5 is 40MW and 2MVARs. Moreover, after five iterations the value of voltage sources of series and shunt converter are, VcR = 0.075 p.u, cR = -88.99°, VvR =

Fig. (5): Modified Test Network for Case 1.

Table 1: Nodal Complex Voltage of Modified Network for case 1

After the convergence in five iterations the UPFC sending end active and reactive power from node 3 is 40MW and 21.68MVARs respectively. Also the active and reactive receiving end power at node 4 is 40MW and 2MVARs. Moreover, after five iterations the value of voltage sources of series and shunt converter are, VcR = 0.046 p.u, cR = -94.947°, VvR =

1.023 p.u, vR = -5.090°. Table 1 shows the voltage magnitudes and voltage angles at all the nodes when UPFC is incorporated between node 3 and node 4.

Case 2

1. p.u. vR = -6.128°. Table 2 shows the voltage magnitudes and voltage angles at all the nodes when UPFC is incorporated between node 4 and node 5.

   Conclusion

   This paper gives the review of UPFC device, its benefits and various optimization techniques used for optimal allocation of UPFC converter for damping oscillations, power loss minimization, enhancement of system loadability, power transfer capability etc. The three steady state models namely UPFC Decoupled model, UPFC injection model and UPFC comprehensive NR model are compared. A case study is also presented to show the effectiveness of UPFC device to regulate voltage magnitude and also controls the power flow between the two busses. It is expected that this review will be helpful to researchers working in the area of power flow and optimal allocation of UPFC.

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   North

   Lake

   Main

   1 3

   2

   South

   4

   UPFC

   UPFC

   5

   Elm

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