Download Improvement of Performance of Transmission System Using Optimal

Improvement of Performance of Transmission System
Using Optimal Allocation of UPFC Device by GA and
PSO Algorithms
A. Haritha, Hameed.S.K
Abstract: Power losses and voltage instability are major
problems in present power systems. It has become more complex
day by day due to less security and reliability. Flexible AC
transmission systems (FACTS) controllers have been mainly used
for solving various power system steady state control problems.
Flexible AC transmission systems or FACTS are devices which
allow the flexible and dynamic control of power systems and
enhancement of system stability using FACTS controllers. UPFC
is the one of the most important device in FACTS controllers. It
is in multiple line compensation are integrated into a generalized
power flow controller that is able to maintain prescribed, and
independently controllable, real and reactive power flow in the
line. Based on PSO algorithm is an effective method for finding
the optimal choice and location of FACTS controllers. It also
increases loadability of the line and minimizes losses. This paper
presents comparative study of GA and PSO algorithms for one of
the FACTS controller i.e., UPFC device. The suggested algorithm
has been applied to 30 bus tested data.
Keywords: — Voltage Stability, FACTS Devices, Optimal
Allocation, Genetic Algorithm.
I. INTRODUCTION
Modern, power systems are prone to widespread failures. With
increased loading of existing power-transmission systems,
operation of power system becomes more complex and power
system will become less secure. Operating environment,
conventional planning and operating methods can leave
systems exposed to instabilities. Voltage instability is one of
the phenomena which have result in a major blackout.
Besides, with the electricity market deregulation, number of
unplanned power exchanges increases due to the competition
among utilities and direct contracts concluded between
generation companies and costumers. If these exchanges are
not controlled, some lines may become overloaded.
1Haritha.A,
M.Tech Student, Department of EEE, JNTUA,
Anantapur/ Quba College of Engineering and Technology,
Venkatachalam, SPS Nellore district, Andhra Pradesh, India, (email: [email protected]).
2Hameed.S.K,
Associate Professor, HOD, Department of EEE,
JNTUA/ Anantapur/ Golden Valley Integrated Campus (GVIC),
Angallu, madanaplli, Chittor district, Andhra Pradesh, India, (email: [email protected]).
Because many of the existing transmission lines could not
cope with increasing power demand, the problem of voltage
stability and voltage collapse has also become a major concern
in planning and operation of deregulated power systems. So
control of power flow in order to have more efficient, reliable,
and secure system is in the interest of the transmission system
operator (TSO). To overcome this problem, FACTS devices
are introduced.
FACTS devices can regulate the active and reactive-power
control as well as adaptive to voltage magnitude control
simultaneously by their fast control characteristics and their
continuous compensating capability and so reduce flow of
heavily loaded lines and maintain voltages in desired level.
Besides, FACTS devices can improve both transient and
small signal stability margins. Controlling the power flows in
the network, under normal and abnormal conditions of the
network, can help to reduce flows in heavily loaded lines,
reduce system power loss, and so improve the stability and
performance of the system without generation rescheduling or
topological changes in the network [1]. Because of the
considerable costs of the FACTS devices, it is so mementos to
find out the optimal location for placement of these devices to
improve voltage stability margins and enhance network
security [2-7]. reliability and loadability has been studied
according to proper control objectives [5-15]. Some of papers
have been tried to find suitable location for FACTS devices to
improve power system security and loadability [14-17].
Optimal allocation of these devices in deregulated power
systems has been presented in [18-19].
Some of papers use heuristic approaches and intelligent
algorithms to find suitable location of FACTS devices [16-19].
In [20], voltage stability index has been used to find the
suitable location of UPFC to improve power system
security/stability after evaluating the degree of severity of
considered contingencies. This paper presents a novel
heuristic method based on GA to find optimal location of
multi-type FACTS devices to enhance voltage stability level
considering investment cost these devices and power system
losses.
Genetic Algorithm is previously used for many
optimization problems like optimal power flow, economic
dispatch and controller optimization, congestion management
and etc in power systems [21-23]. Proposed method is tested
on IEEE 30 bus system and results are presented.
26]. Models integrated into transmission line for TCSC and
UPFC and SVC is modeled is incorporated into the bus as
shunt element of transmission line. Mathe-matical models for
FACTS devices are implemented by MATLAB programming
language.
II. FACTS DEVICES MODEL
TCSC. TCSC acts as the capacitive or inductive compensator by modifying reactance of transmission line. This
changes line flow due to change in series reactance.
A. FACTS Devices
In this paper, three different FACTS devices have been
selected to place in suitable location to improve voltage
stability margins in power system. These are: TCSC (Thyristor
Controlled Series Capacitor), SVC (Static VAR Compensator)
and UPFC (Unified Power Flow Controller). These are shown
in Fig. 1.
In this paper TCSC is modeled by changing transmission line
reactance as below:
Xij = Xline + XTCSC
………………….. (2)
XTCSC = rTCRC. Xline ………………… (3)
where Xline is reactance of transmission line and is
compensation factor of TCSC. Rating of TCSC is depended
on transmission line where it is located. To prevent
overcompensation, TCSC reactance is chosen between -0.7
Xline to 0.2 Xline.
SVC:
SVC can be used for both inductive and capacitive
compensation. In this paper SVC is modeled as an ideal
reactive power injection at bus:
∆Qi = ∆QSVC ……………….. (4)
Figure: 1 Considered FACTS Devices (a) TCSC (b) SVC (c)
UPFC.
Power flow through the transmission line i-j namely is
depended on line reactance, bus voltage magnitudes, and
phase angle between sending and receiving buses. This is
expressed by Eq. 1
………………….. (1)
TCSC can change line reactance and SVC can be used to
control reactive power in network. UPFC is the most versatile
member of FACTS devices family and can be applied in order
to control all power flow parameters (i.e. line impedance, bus
voltage, and phase angle). Power flow can be controlled and
optimized by changing power system parameters using
FACTS devices. So optimal choice and allocation of FACTS
devices can result in suitable utilization in power system.
UPFC: Two types of UPFC models are reported in papers
[26-29]. One is coupled model [26] and other is decoupled
model [27-29]. In the first type, UPFC is modeled with series
combination of a voltage source and impedance in the
transmission line. In decoupled model, UPFC is modeled with
two separated buses. First model is more complex compared
with the second one because modification of Jacobian matrix
in coupled model is inevitable.
While decoupled model can be easily implemented in
conventional power flow algorithms without modification of
Jacobian matrix elements, in this paper, decoupled model used
for modeling UPFC in power flow study (Fig. 2).
B. Mathematical Model of FACTS Devices
In this paper steady state model of FACTS devices are
developed for power flow studies. So TCSC is modeled
simply to just modify the reactance of transmission line. SVC
and UPFC are modeled using the power injection models [24-
Figure:2 Decoupled model for UPFC
Although UPFC can control the power flow, but cannot
generate the real power. So:
maximum voltage stability margin. For a given network, with
the increase in load/generation, the voltage magnitude and
angles change near maximum-power-transfer condition and
the propensity of voltage-stability is to be close to unity,
indicating that the system is close to voltage collapse. The L
index gives a scalar number to each load bus. Among the
various indices for voltage-stability and voltage-collapse
prediction, the L index gives fairly compatible results. The L
indices for given loads conditions are calculated for all the
load buses and the maximum of the L indices gives the
proximity of the system to voltage collapse.
Pu1 + Pu2 = 0 ………………. (6)
IV. PROPOSED GENETIC ALGORITHM
UPFC controls power flow of the transmission line where is
installed. To obtain UPFC model in load flow study, it is
represented by four variables: Pu1, Qu1, Pu2, and Qu2.
Assuming UPFC to be lossless, real power flow from bus i to
bus j can be expressed as:
Pij = Pu1 ……………. (5)
Each reactive power output of UPFC, Qu1 Qu2can be set to
an arbitrary value depend on rating of UPFC to maintain bus
voltage.
III. VOLTAGE STABILITY INDEX
Consider a power network where n is the total number of
buses with 1, 2, …, g generator buses, and g+1, …, n
remaining (n – g) buses. For a given system operating
condition, using the load-flow (state-estimation) results, the
voltage-stability L index is obtained as [20, 30]:
Genetic Algorithm (GA) is one of the most famous metaheuristic optimization algorithms witch is based on natural
evolution and population. Genetics which is usually used to
reach to a near global optimum solution. In each iteration of
GA (referred as generation), a new set of string (i.e.
chromosomes) with improved fitness is produced using
genetic operators (i.e. selection, crossover and mutation).
A. Chromosome’s structure
Chromosome structure of GA is shown in Fig. 3. This
involves rating and location of FACTS devices.
…………………. (7)
where j = g+1, …, n and all the terms inside the sigma on the
right-hand side of (7) are complex quantities. The complex
values of Fij are obtained from the Y-bus matrix of power
system. For a given operating condition:
Figure:3 A typical chromosome.
B. Selection
……………………… (8)
where IG, IL, and VG, VL, represent complex current and
voltage vectors at the generator nodes and load nodes. [YGG],
…[YGL], …, [YLL], and [YlG] are corresponding partitioned
portions of the Y-bus matrix. Rearranging (8),
………………. (9)
For stability, the index Lj must not be more than one for any
of the nodes j. Hence, the global index L demon-strating the
stability of the complete sub-system is given by L= maximum
of Lj for all j (load buses). An L-index value far away from 1
and close to 0 indicates improved voltage stability. For an
unloaded system with genera-tor/load buses voltages, the L for
load buses are close to zero, indicating that the system has
In proposed GA, method of tournament selection is used for
selection [31-32]. This method chooses each parent by
choosing (tournament size) players random-ly and choosing
the best individual out of that set to be a parent. In this paper is
chosen tntn.4=tn
C. Cross Over
Cross over allows the genes from different parents to be
combined in children by exchanging materials between two
parents. Cross over function randomly selects a gene at the
same coordinate from one of two parents and assign it to the
child. For each chromosome, a random number is selected. If
this number is between 0.01 and 0.3, two parents are
combined; else chromosome is transferred with no cross over.
D. Mutation
GA creates mutation children by randomly changing the
genes of individual parents. In this paper, GA adds a random
vector from a Gaussian distribution to the parents. For each
chromosome, random number is selected. If this number is
between 0.01 and 0.1, mutation process is applied; else
chromosome is transferred with no mutation.
E. FACTS devices Cost Function
Using Siemens AG Database [33], cost function for SVC,
TCSC and UPFC are developed as follows:
And Particle Swarm Optimization (PSO) Optimization
techniques are used to find the placement of Unified Power
Flow Controller (UPFC) to reduce the power losses.
Simulation studies were done for different scenarios in 30 bus
tested data.
Scenario 2: one TCSC is installed
Scenario 3: one SVC is installed
TCSC:
……….. (10)
Scenario 4: one UPFC is installed
Scenario 5: Multi-type (TCSC, SVC and UPFC)
FACTS devices are installed.
SVC:
…………… (11)
UPFC:
………. (12)
Where s is the operating range of the FACTS devices in
MVAR and CTCSC, CSVC and CUPFC are in (USD/kVAR). These
cost functions are shown in Fig. 4.
Power system considering cost function of FACTS devices.
So these devices should be place to prevent congestion in
transmission lines and transformers and maintain bus voltages
close to their reference value.
The first scenario is normal operation of network without
installing any device. In second, third and forth scenario just
installation of one device is considered. Each device is placed
an optimal location obtained by GA introduced in Chapter IV.
Multi-type FACTS devices installation is considered in 5th
scenario. In this case three different kinds of FACTS devices
(shunt, series and combinational compensation device) are
used to place in optimal location to enhance voltage stability
margin of power system.
Power losses with and without UPSC shown in below figure.
Power Losses
M
33
30
27
24
21
18
15
129
6
3
0
Without
UPFC
UPFC with
GA
Voltage stability index introduced in Chapter III, were used
in objective function considering cost function of FACTS
devices and power system losses. Fitness function is expressed
as below:
……… (13)
Figure: 5 Real power losses with and without UPFC
TABLE I
REAL POWER LOSSES WITH AND WITHOUT UPFC
Scenarios
Total power losses (MW)
Without UPFC
29.3900
UPFC GA
UPFC PSO
23.0900
22.8591
The coefficient a1 to a3 are optimized by trial and error to
2.78, 0.1 and 2.05 respectively.
V. SIMULATION RESULTS
In this project, MATLAB code have been developed for
Load flow analysis and by using Genetic Algorithm (GA)
This results show the power losses at different Scenarios by
using GA and PSO.
[7] S. Sung-Hwan, L. Jung-Uk, M. Seung-Il, “FACTS Operation Scheme for
Enhancement of Power System Security,“ in Proc of IEEE Power Tech
Conference, Bologna, 2003, Vol. 3, pp. 36-41.
[8] K. Sun-Ho, L. Jung-Uk, M. Seung-Il, “Enhancement of Power System
Security Level Through the Power Flow Control of UPFC,” in Proc. of the
IEEE Power Engineering Society Summer Meeting, 2000, Vol. 1, pp. 38 – 43.
[9] A. Kazemi, H.A. Shayanfar, A. Rabiee, J. Aghaie, “Power System
Security Improvement using the Unified Power Flow Controller,“ in Proc.of
the IEEE Power India Conference, 2006, pp. 1-5.
Figure 6: Voltage profile with UPFC and without UPFC using GA
The above figure show the comparison the Voltage profile in
between UPFC GA and without UPFC. Here we absorbed,
after placement of UPFC with GA voltage profile improved .
Figure 7: Voltage Profile without UPFC and UPFC using PSO.
The above figure shows the comparison the voltage profile
in between UPFC PSO and without UPFC. Here we absorbed,
after placement of UPFC with PSO voltage profile improved.
VI. CONCLUSION
In this paper, performance of transmission system with
UPFC device is studied using Particle Swarm Optimization
(PSO) and Genetic Algorithm (GA). It is concluded that with
PSO the performance studies in terms of voltage profile and
power loss are more accurate compared with GA. Using PSO
accurate results can be obtained. Case Study was conducted on
30 bus tested data. So it says that performance of transmission
system with UPFC device should be increased in PSO
algorithm.
REFERENCES
[1] F.D. Galiana, K. Almeida, M. Toussaint, J. Griffin, and D. Atanackovic:
“Assessment and Control of the Impact of FACTS Devices on Power System
Performance”, IEEE Trans. Power Systems, Vol. 11, No. 4, Nov 1996
[2] N.G. Hingurani, L. Gyugyi, Understanding FACTS: Concepts and
Technology of Flexible AC Transmission Systems, IEEE Press, New York,
2000.
[3] M. Noroozian, L. Angquist, M. Ghandhari, G. Anderson, "Improv-ing
Power System Dynamics by Series-connected FACTS De-vices," IEEE Trans.
on Power Delivery, Vol. 12, No.4, October 1997.
[4] M. Noroozian, L. Angquist, M. Ghandhari, "Use of UPFC for Optimal
Power Flow Control," IEEE Trans. on Power Delivery,Vo1.12, No.4, October
1997.
[5] R. Billinton, M. Fotuhi-Firuzabad, O.S. Faried, S. Aboreshaid, "Impact of
Unified Power Flow Controllers on Power System Reliability," IEEE Trans.
on Power Systems, Vo1.15, No.1, February 2000.
[6] J.A. Momoh, J. Zhu, G.D. Boswell, S. Hoffman, "Power System Security
Enhancement by OPF with Phase Shifter," IEEE Trans. on Power Systems,
Vol. 16, No.2, May 2001.
About Authors
A.Haritha received the B.Tech
Degree
in
Electrical
and
Electronics Engineering from
Siddharth Institute of Engineering
and Technology, puttur, University
of JNTUA in 2010.She is currently
working towards the Master’s
Degree in Electrical Power
Systems, in Quba College of
Engineering and Technology,
University of JNTUA. Her interest
lies in the areas FACTS, Control
Systems.
Hameed.S.K Received B.Tech
and
M.Tech
Degrees
in
Electrical
and
Electronics
Engineering from Kakatheya
University and NIT durgapur in
2000
&2002
respectively.
Currently He is a Associate
Professor and HOD in the
Department of Electrical and
Electronics Engineering at Quba
College of Engineering and
Technology –SPS Nellore.
His current interests include FACTS and Neural networks