Intern
ati
o
n
a
l
Jo
u
r
n
a
l
of
P
o
we
r El
ec
tr
on
i
c
s
an
d D
r
i
v
e
S
y
stem
(I
JPE
D
S)
V
o
l.
11
, N
o
. 2, Jun
e
20
20
, pp
. 88
6
~
89
4
I
SSN
:
208
8-8
6
9
4
, D
O
I:
10.
115
91
/i
jp
e
d
s.v
1
1
.i2
.
p
p88
6-8
94
8
86
Jo
urn
a
l
h
o
me
pa
ge
: h
t
t
p
:/
/ijpe
d
s.
i
a
e
s
c
o
re.
c
o
m
Op
timal loca
tion of un
ified po
wer flow controller geneti
c
algorithm based
San
a
Kh
al
i
d
Abd
u
l
H
a
ss
an
, Fi
ras
M
o
h
a
mm
ed
Tu
ai
m
a
h
Electrical
En
g
i
n
eerin
g
D
e
par
t
men
t
, Un
iv
ers
i
ty
of
Bagh
dad
,
Ir
aq
A
r
ticle In
fo
A
B
S
T
RAC
T
A
r
tic
le
h
i
st
o
r
y:
Rec
e
i
v
ed
Se
p 1
7
, 2
019
Re
vi
se
d N
o
v
9
,
20
19
Acc
e
pt
e
d
Fe
b 7, 2
0
2
0
No
w-
a-
day
s
t
h
e
F
l
exib
le
A
C
Tr
a
n
s
m
is
sion Systems (FACTS
)
technology i
s
very
eff
e
c
t
iv
e
in
im
p
r
ov
in
g th
e
pow
er flow
alon
g the
tr
an
smis
sion
lin
e
s and
makes
th
e p
o
w
e
r s
y
s
t
em
more
f
l
ex
ib
le
and
con
t
rollab
le.
This
p
a
p
e
r
de
als
with
ov
erlo
ad
trans
m
is
sion s
y
s
t
em
pro
b
l
e
ms
su
ch
as (
i
ncr
eas
e
the
to
tal
lo
ss
es, raise th
e
rate of po
w
e
r g
e
neration
,
and
th
e tran
sm
is
sion
li
ne may
b
e
exp
o
s
e
d to
s
hut d
o
w
n
wh
en the
lo
ad de
man
d
incr
eas
e
fro
m
th
e th
erma
l
l
i
mit
of
trans
m
is
sion
line) an
d h
o
w
c
a
n
s
o
lve this p
r
ob
lem b
y
ch
oo
sing
th
e
op
ti
m
a
l
lo
ca
ti
on
an
d p
a
r
a
me
ter
s
of
Uni
f
i
e
d
Po
wer Fl
ow
Cont
rol
l
er
s
(UPFCs).
w
h
i
c
h
was
s
p
ecifi
ed ba
s
e
d on Gen
e
tic
Algo
rith
m (GA)
op
tim
i
za
tion
m
e
thod
,
it was
u
t
i
liz
e
d
t
o
se
a
r
ch
for o
p
ti
m
u
m
FACT
pa
ra
me
ters se
t
t
i
ng a
nd loc
a
tio
n b
a
se
d
to
achi
e
ve
th
e
f
o
llo
w
in
g o
b
j
e
c
ti
ves:
imp
r
ov
e
vo
ltag
es p
r
ofile
,
re
du
ce
po
wer
lo
ss
es, tre
a
tm
ent
of po
wer
flo
w
i
n
ov
erlo
aded
tra
n
smiss
i
o
n
lines
a
n
d red
u
c
e
p
o
we
r
g
e
ne
ra
ti
on.
M
A
T
L
AB was
u
s
e
d
for ru
nn
ing b
o
t
h
th
e GA
pro
g
ra
m a
n
d
New
t
o
n
R
a
ph
so
n
met
h
o
d
f
o
r
s
o
lv
in
g
th
e
load
f
l
ow
of
th
e
s
y
s
t
em.
Th
e
p
r
op
ose
d
a
p
proa
c
h
i
s
e
x
a
m
in
ed a
n
d
te
ste
d
on
IE
EE 30-bu
s
syste
m
. Th
e
p
r
a
c
t
i
c
al
pa
rt
ha
s be
e
n
sol
v
ed
th
ro
ug
h Po
we
r Syste
m
S
i
mu
la
t
i
o
n
f
o
r
En
gine
ers (P
S
S
\E) so
ftw
a
r
e
Ver
s
ion
32.
0 (T
he
Po
w
e
r
Sys
t
e
m
S
i
m
u
l
a
t
o
r f
o
r
En
gine
ering
(P
S
S
/E) so
ftw
a
re
c
r
eated fro
m S
i
e
m
ens
P
T
I
to
p
r
ov
ide a
s
y
s
t
em
o
f
c
o
m
p
u
t
er progra
m
s
a
n
d
stru
c
t
ure
d
d
a
ta fi
le
s de
si
gn
e
d
t
o
ha
n
d
le
t
h
e b
a
sic
fu
nc
t
i
o
n
s of powe
r
syste
m
pe
rform
a
n
ce si
m
u
la
t
i
o
n
wo
rk
,
su
ch
a
s
p
o
we
r
flo
w
,
opt
ima
l
p
o
w
er flow,
fau
lt an
alys
is
, dy
na
mic
sim
u
latio
n
s
.
..et
c.)
.
Th
e
Comp
arativ
e
res
u
lts
b
e
tween
th
e
exp
e
rim
e
nta
l
a
n
d
p
r
a
c
tical
p
a
rts
o
b
tain
ed
fro
m
a
d
o
p
tin
g
t
h
e
UPFC wh
e
r
e to
o cl
ose a
nd
a
l
mo
st
the sa
m
e
u
nde
r d
i
ffe
re
n
t
l
o
ading
conditions,
which ar
e (5
%,
10%,
15% and
20%) of
the t
o
tal
l
o
ad.
can
sh
ow
th
at th
e
to
tal a
c
tiv
e
po
wer
lo
ss
es for
the
s
y
stem
reduc
e
at
69.
59
4%
at
no
rmal c
a
se
aft
e
r
add
the
U
P
F
C
d
e
v
i
ce
to
the
s
y
stem
. Also
,
th
e r
e
a
c
tiv
e
po
wer los
s
es re
d
u
ce b
y
7
5
.
4
8
3
%
at th
e s
a
m
e
cas
e as w
e
ll as f
o
r th
e
res
t
o
f
th
e cas
es. in
th
e o
t
h
e
r h
a
nd
can
n
o
ted
the
s
y
stem
w
i
ll no
t h
a
v
e
an
y ov
erlo
a
d
li
nes
af
ter
ad
d
U
P
F
C
to
th
e
sy
st
e
m
wi
th
su
it
ab
l
e
par
a
m
e
ter
s
.
Ke
yw
ords:
FA
CTS
,
GA
,
Lo
ad
ab
ilit
y
,
MATLAB
,
PS
S\
E,
UP
FC
,
Th
is
is a
n
o
p
en
acces
s a
r
ticle
un
d
e
r the
C
C
B
Y
-SA
licens
e
.
Corres
p
o
n
din
g
A
u
t
h
or:
Sa
na
K
h
al
id A
b
d
u
l Hassa
n,
MSc
.
S
t
ude
nt
, E
l
e
c
t
r
i
c
a
l
Engi
ne
eri
n
g
D
e
part
ment
, C
o
l
l
e
ge
of En
gine
e
r
i
n
g
,
Uni
v
ersi
t
y
o
f
Ba
ghda
d,
C
o
l
l
e
ge of
Engi
ne
e
r
i
n
g, U
n
ive
r
si
ty of
B
a
g
hda
d,
Ira
k
.
Ema
i
l
:
S
a
n
a
.sno
o90
@g
m
a
il
.co
m
1.
IN
TR
O
DUCTION
It
is i
m
po
r
t
an
t
t
o
ta
k
e
in
to
co
nsi
d
er
a
t
ion
in
ou
r l
i
f
e
t
h
e
in
cr
e
a
s
e
i
n
de
ma
nd
th
i
s
w
i
ll
n
e
ed
to
i
n
cre
a
si
ng i
n
t
h
e ra
t
e
of
e
l
ect
ri
c po
we
r, s
o
t
h
i
s
wi
l
l
make
po
we
r net
w
o
r
k
s
a
r
e
o
p
erat
i
n
g
un
der hi
g
h
st
re
ss an
d
com
p
l
e
x
p
r
e
ssure
co
n
d
it
i
ons
. Thi
s
c
o
mpl
e
x
i
t
y
an
d
i
n
c
r
ea
s
e
i
n
ene
r
gy
s
uppl
y
re
qui
re
s
p
r
o
v
idi
n
g
t
h
e
sy
st
em
wi
th
mo
de
rn
c
ont
rol
de
vi
ce
s tha
t
hel
p
i
n
t
h
e
de
vel
o
p
m
ent
o
f
the
e
l
e
c
t
r
i
c
a
l
net
w
o
r
k
s
[1
, 2]
.
F
A
C
T
S
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t
J
P
o
w
Elec
& Dri
Sy
st
I
SSN
: 208
8-8
6
9
4
O
p
tima
l
lo
ca
tio
n o
f
un
if
ie
d
po
w
e
r
fl
o
w
con
t
ro
lle
r
g
e
n
e
tic
a
l
go
rit
h
m
b
a
s
ed
(Sa
n
a
K
h
a
lid
Abdu
l
Ha
ssan)
8
87
te
ch
no
l
o
g
i
e
s
an
d its a
d
v
a
n
t
ag
e
s
lik
e
c
a
n
be
u
s
e
d
a
s
p
o
we
r
f
l
o
w
co
n
t
ro
l
,
max
i
mu
m tra
n
sm
issio
n
c
a
p
ab
i
lity
,
v
o
lta
g
e
r
e
g
u
l
atio
n
,
re
a
c
ti
v
e
p
o
w
e
r
c
o
mp
ensa
tio
n
,
sta
b
ili
ty
imp
r
o
v
e
me
nt,
P
o
w
e
r
qu
al
ity
im
prov
e
m
en
t
a
n
d
Pow
e
r cond
itio
n
i
ng
.
[3
]
U
n
i
f
ie
d
Po
w
e
r
Flo
w
C
o
n
t
ro
lle
r
(U
PF
C) i
s
a v
e
r
s
a
tile
a
n
d
f
l
e
x
ib
le de
v
i
c
e
in
th
e
F
A
CTS
f
a
mily
of
c
ont
r
o
ll
er
s
w
h
i
c
h
has
t
h
e
a
b
i
l
i
t
y
t
o
the
sim
u
l
t
a
n
eou
s
a
n
d
i
nde
pe
nde
nt
c
o
n
t
r
o
l
of
t
h
e
b
u
s
vol
ta
ge
a
n
d t
h
e
r
e
a
l
a
n
d
re
ac
ti
ve
t
r
ansmi
s
si
on
-l
i
n
e pow
e
r
fl
o
w
s.
[4
,
5]
The
p
r
ob
l
e
m o
f
opt
i
m
iz
ing t
h
e l
o
c
a
t
i
o
n
,
n
u
m
b
er
an
d
siz
e
of
F
A
C
T
S
de
vi
ce
s
ha
ve
bec
o
me
an i
m
p
o
r
t
a
n
t
re
q
u
ir
eme
n
t
f
o
r a
be
st a
d
va
nt
age
of t
h
ese
de
vi
ces i
n
o
r
der t
o
a
c
hi
eve
a n
u
m
ber
o
f
a
desi
re
d
obj
ect
i
v
e
f
u
nct
i
on
.
Ge
net
i
c
al
go
ri
t
h
ms
(
GAs
),
w
h
i
c
h
a
r
e
pr
oba
bi
l
i
st
i
c
gl
o
b
al
opt
i
m
i
z
a
t
io
n te
chni
que
s
i
n
s
p
ir
ed
b
y
a
na
t
u
r
a
l
-
sel
e
c
t
ion
pr
oce
s
s an
d
t
h
e
sol
v
i
n
g of c
o
mple
x o
p
t
i
mi
za
ti
on
pr
obl
e
m
s.
[
6
,
7]
. T
h
i
s
re
sear
ch
deal
s w
i
t
h
usin
g t
h
e
G
A
t
o
s
o
l
v
e
t
h
e
o
p
t
i
mal
UP
F
C
-
l
oc
at
i
on p
r
obl
e
m
s f
o
r
re
d
i
st
rib
u
t
ed
po
w
e
r
sy
ste
m
s in
c
o
n
s
id
er
ati
o
n
of
th
e
sy
s
t
em lo
a
d
ab
ilit
y
,
imp
r
ov
e
vo
lt
age
s
p
r
o
f
ile
, re
duc
e
to
ta
l
po
we
r l
o
ss
es,
c
ont
rol
of
p
o
w
e
r
f
l
ow
i
n
o
v
er
l
o
a
d
e
d
t
r
a
n
smi
s
sion
li
nes
a
n
d
r
e
duce
p
o
w
e
r
g
e
nera
ti
o
n
[8
,
9]
.
In
thi
s
pa
pe
r
w
e
ha
ve
rel
i
e
d
o
n
t
h
e
use
of
G
A
to
ac
hie
v
e
t
h
e f
o
l
l
o
wi
ng:
sh
ow
th
at
a
ll c
o
n
t
r
o
l
p
a
r
a
m
e
ter
s
o
f
U
P
F
C
s i
n
ea
ch
c
a
s
e
ar
e
w
i
t
h
in th
ei
r li
mits
.
To
in
sta
lle
d
t
h
e
U
P
F
C
dev
i
ce i
n
e
ach
ca
se i
n
r
i
gh
t p
o
s
i
tion
w
ith
sa
f
e
ly
op
e
r
a
tio
n
wha
t
st
ren
g
t
h
e
n
s
t
h
e
p
e
r
f
o
rma
n
ce
i
n
di
cat
o
r
of G
A
sea
r
ch
pr
oce
s
s
i
n
fi
n
d
i
ng
t
h
e opti
m
a
l
l
o
c
a
t
i
ons
o
f
U
P
F
C
d
e
v
i
ce
s w
i
th
r
e
sp
e
c
tin
g
i
t
s
limi
t
s
G
A
m
a
k
e
s the
ca
lc
u
l
a
tion
s
limi
t
e
d
w
i
th
in
a
n
a
rr
ow sp
ac
e
wi
th mi
n
i
ma
l tim
e, the
r
e
f
o
r
f
a
cil
ita
te
s
th
e
se
a
r
ch
fo
r
o
p
tima
l
n
u
mb
er
, op
tim
al
p
l
a
cem
en
t
an
d si
ze
of
UPF
C
d
e
v
i
ce
s.
In
[
1
0
]
t
h
e
aut
h
o
r
f
o
u
nd
b
y
a
ppl
yi
ng
t
h
e
ge
net
i
c
al
go
ri
t
h
m
(
G
A
)
i
n
t
h
e
st
anda
r
d
I
E
E
E
1
4
bus
t
e
st
sy
ste
m
c
a
n
d
e
t
e
r
m
in
e
th
e op
tim
al
nu
mb
e
r
, o
p
tim
al p
l
ac
eme
n
t
an
d s
i
ze
o
f
U
P
F
C
d
e
v
i
ce
to
en
h
a
n
ce
vo
lta
g
e
s
pr
o
f
i
l
e
a
n
d re
duce
ove
ral
l
s
y
ste
m
l
o
sses.
genet
i
c
a
l
go
r
i
t
h
m (
G
A
)
ca
n be
c
o
nsi
d
e
r
ed
a
ne
w
t
e
c
hni
q
u
e
fo
r
th
e
i
n
sta
lla
ti
o
n
o
f
FA
CTS
de
v
i
c
e
s
in
t
h
e
t
r
an
sm
issi
on
syste
m
by
li
mit th
e op
ti
ma
l p
l
a
c
e
m
e
n
t
o
f
FA
CTS
d
e
v
i
ce
s in a
tran
sm
issio
n
n
e
t
w
or
k c
a
n
i
n
c
r
e
a
se
d
l
o
a
d
ab
i
lity
o
f
th
e
p
o
w
e
r syste
m
a
s
w
e
l
l
as to
m
i
n
i
m
i
z
e
the
t
r
a
n
smi
ssi
on
lo
ss,
t
h
is
was
me
nti
one
d i
n
[
1
1
]
.
2.
MOD
ELI
NG
O
F
U
P
FC
T
h
e
U
n
if
ied
Po
w
e
r
F
l
o
w
Co
n
t
r
o
lle
r
con
cep
t
ca
ll
ed
UPFC
is
a
po
w
e
r
ele
c
t
r
o
n
i
c
s
-base
d
sy
ste
m
w
h
ich
ca
n pr
ov
id
e
simu
lta
n
e
o
u
s
con
t
ro
l of
th
e
tr
an
sm
issi
on
lin
e
imp
e
d
a
nc
e,
ph
a
s
e an
g
l
e
,
vo
lta
g
e
magn
itu
d
e
an
d
a
c
t
i
v
e
an
d r
e
ac
tiv
e
p
o
w
e
r
fl
ow
[1
2,
13
].
I
t
’
s
h
a
s
to volt
a
g
e
so
ur
ce co
nv
er
to
r
:
Th
e sh
un
t
c
onv
er
ter
a
c
t
s
lik
e a STA
T
CO
M an
d th
e ser
i
es conv
er
ter
acts
lik
e a SSSC
.
Th
e
ser
i
es
co
nv
er
ter co
n
t
ro
ls th
e ph
as
o
r
v
o
l
tag
e
in
se
r
i
e
s
w
ith
t
h
e
l
i
n
e
.[1
4
] Th
e
tr
a
n
smissi
on
l
i
n
e
cu
rre
n
t
f
l
ow
s
t
h
ro
ugh
th
is
vo
lt
ag
e
sou
r
ce
re
su
lt
ing
in
re
a
l
a
n
d
rea
c
t
i
ve
p
o
we
r e
x
c
h
an
g
e
b
e
t
w
een
i
t
and
t
h
e
ac
syst
em [
1
5]
.
In
addi
t
i
on,
t
h
e
s
h
u
n
t
c
onve
rt
er
c
a
n
i
nde
pe
n
d
e
n
t
l
y
excha
n
ge rea
c
t
i
ve
p
o
we
r wit
h
the
syst
em
t
h
r
o
u
g
h
the
t
r
a
n
sf
or
mer c
o
n
n
ec
t
i
ng it
wi
th t
h
e
p
o
w
e
r
sy
ste
m
. Bo
th
co
nv
er
te
rs
a
r
e con
n
e
c
t
ed
t
h
ro
ugh
b
y
a
d
c
ca
p
a
cit
o
r.
Th
e con
t
ro
lle
rs
for
b
o
t
h
th
e ser
i
e
s
a
nd
sh
un
t con
v
er
ter
s
a
r
e
u
s
e
d
[16
]
. Th
e
c
o
n
t
rol
l
er
ca
n co
n
t
rol ac
ti
v
e
an
d
re
ac
ti
v
e
pow
e
r
in th
e tr
ans
m
iss
i
o
n
lin
e
[17
]
.
A
s
it
is
sh
o
w
n
in
F
i
gu
r
e
1
,
th
e
b
a
s
i
c st
ru
ctu
r
e
of
UPF
C
d
e
v
i
ce
is a c
o
mb
in
a
tio
n
of
two
co
mp
ens
a
to
rs
[1
8]
:
on
e conn
ec
ted
in
p
a
r
a
ll
el
ca
ll
ed
S
t
a
tic
Co
mp
en
sato
r
(S
T
A
T
C
OM
)
an
d th
e
o
t
h
e
r
i
n
s
e
r
i
e
s
ca
ll
ed
S
t
at
ic
Sy
n
c
hr
ono
u
s
S
e
r
i
e
s
C
o
mp
ens
a
t
o
r (SS
S
C
)
. B
o
th co
mp
e
n
sato
rs a
r
e
c
onn
e
c
ted
w
i
th "D
C"
li
n
k
to
e
x
cha
n
ge
t
h
e r
e
a
l
po
we
r
bet
w
e
e
n
t
h
e
o
u
t
put
te
rmina
l
s
of
S
T
ATC
O
M
a
n
d
SS
SC
[
1
2
,
19
]
.
F
i
gu
r
e
1.
The
s
c
he
ma
ti
c
di
agr
a
m o
f
U
P
F
C
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
: 2
088
-86
94
I
n
t J
P
o
w
El
ec
&
D
r
i S
y
st
,
V
o
l
.
11,
N
o
.
2,
J
u
ne
20
2
0
:
8
8
6
– 89
4
88
8
The e
qui
val
e
nt
c
i
r
c
ui
t
o
f
U
P
F
C
i
s
pr
ese
n
t
e
d
in Fi
g
u
re
2.
Th
e ser
i
e
s
pa
r
t
i
s
mo
del
e
d
by a c
ont
rol
l
a
bl
e
vol
t
a
ge
so
ur
ce
,
an
d
t
h
e
shu
n
t
par
t
is m
o
del
e
d
b
y
a
c
ont
rol
l
abl
e
c
u
r
r
e
n
t
s
o
urc
e
.
UP
F
C
ha
s t
h
ree
c
o
nt
r
o
l
l
a
bl
e
pa
ra
met
e
r
s
na
me
l
y
: v
o
l
t
a
ge
mag
n
i
t
ude
,
p
h
a
se
a
ngl
e
of
t
h
e v
o
l
t
a
g
e a
n
d
shu
n
t
r
e
a
c
t
i
ve
cur
r
e
nt
[
2
,
19
, 2
0
]
,
B
a
sed
o
n
t
h
e
e
qui
val
e
nt
ci
rc
u
i
t
of
U
P
F
C
sh
o
w
n
i
n
F
i
gu
r
e
2.
the
a
c
t
i
ve
a
n
d
re
ac
ti
ve
po
we
r
i
n
j
ect
i
o
n
e
q
u
a
t
i
on
s
a
t
bu
ses k a
n
d
m are
gi
ven
b
y
t
h
e f
o
ll
o
w
i
n
g e
xpr
essi
on
s
[
2
1,
2
2
]
.
F
i
gu
r
e
2.
e
q
uiv
a
le
nt ci
rc
uit
of
UP
FC
mo
del
a
t
bu
s k:
(1
)
(2
)
at
b
u
s
m:
(3
)
(4
)
3.
THE
I
M
P
L
E
M
EN
TED
IEEE
3
0
BU
S ELEC
T
R
IC
AL N
E
TWORK
The imple
m
e
n
ta
tion of UPFC
in IEEE
30 bus
a
s
a
te
st system. T
h
e syste
m
co
nsists of
6
ge
ne
ra
tor
s
,
30 buse
s,
21 l
o
ads a
nd
41 line
s
[23]. i
n
Fi
gure
3.
c
a
n s
h
ow De
pe
ndi
ng on t
h
e P
S
SE
program
,
t
h
e
IEEE-30
ne
tw
or
k ca
n
b
e
re
prese
n
t
e
d
a
s
we
ll
as t
h
e
i
m
pl
eme
n
t
a
t
i
o
n
of
U
P
FC
a
n
d
c
onne
ct
i
n
g it
wi
t
h
t
h
e
t
r
a
n
s
m
i
s
si
on
lin
e
on
th
e
on
e
h
a
nd
to
r
e
p
r
e
s
en
t t
h
e
SSS
C p
a
r
t
a
nd w
ith
t
h
e bu
s o
n
th
e
o
t
h
e
r to
r
e
p
r
e
s
en
t
t
h
e p
a
r
t
ST
A
T
C
O
M
as sh
own
i
n
F
i
gu
r
e
4
.
Th
e pr
og
ram i
s
th
e
p
r
ac
ti
ca
l p
a
rt of th
e
re
se
ar
ch
w
h
ere its
re
su
l
t
s a
r
e
co
mp
ar
ed w
ith
th
e r
e
su
l
t
s
ob
tai
n
ed
from
t
h
e
GA a
nd know
th
e ex
ten
t
of
its i
m
p
a
ct on t
h
e
d
i
str
i
bu
t
i
on
of
po
we
r
i
n
a ba
la
nce
d
an
d
get
t
h
e hig
h
e
s
t t
o
l
e
ra
nc
e
[10
]
.
4.
GEN
E
TIC ALGO
RI
T
H
M
PROC
ES
S
A
N
D PROBLEM
FO
R
M
U
L
A
T
ION
G
e
n
e
t
i
c
A
l
go
r
ith
m
(
GA) is co
n
s
i
d
e
r
e
d
as
on
e
o
f
th
e
most
i
m
po
r
t
an
t ev
olu
tio
n
a
r
y
al
go
rith
ms
b
a
se
d
on
me
cha
n
i
s
m
of
na
t
u
r
a
l
se
le
ct
ion
an
d
ge
n
e
t
i
c
s
for
s
o
l
v
i
n
g t
h
e
c
onst
r
ai
n
e
d
an
d
unc
o
n
st
ra
i
n
e
d
o
p
t
i
m
i
z
a
t
i
o
n
p
r
o
b
l
em
s. It
is wo
r
t
h no
ti
ng
t
h
a
t
GA
c
a
n
sea
r
c
h
si
mu
lta
neo
u
s
l
y
s
e
v
e
ral
po
ssib
l
e
so
lu
tion
s
w
ith
ou
t re
qu
ir
e
t
o
pr
i
o
r
kn
o
w
l
e
d
g
e o
r
s
p
eci
a
l
p
r
o
p
er
ti
e
s
of t
h
e
obj
ec
t
i
ve
fu
nc
ti
on.
A G
A
i
s
a
simpl
e
an
d
pr
ac
ti
c
a
l
a
l
gor
it
h
m
t
h
at
c
a
n
be
easi
l
y
i
m
pl
eme
n
t
e
d
in
a
p
o
w
er
s
y
st
e
m
A
G
A
ha
ve
thr
e
e
imp
o
r
t
a
n
t
pa
r
t
,
f
o
l
l
o
we
d
b
y
,
cr
oss
o
ve
r
ra
te
,
a
n
d
m
u
t
a
t
i
on
o
p
er
at
io
ns t
h
a
t
a
r
e ca
r
r
i
e
d
o
u
t
unt
i
l
t
h
e
best
p
o
p
u
l
a
t
i
on
i
s
f
oun
d a
n
d p
o
pul
a
t
i
on siz
e
.
[
6
]
.
In t
h
i
s
p
a
p
e
r t
h
e
ob
jec
tiv
e
(f
itn
e
s
s)
fun
c
ti
on
o
f
th
e GA
is re
ac
h
t
o
t
h
e
m
i
n
i
mum l
o
sse
s
wi
th ma
x
i
mu
m lo
ada
b
ili
ty
an
d
c
o
n
t
r
o
lle
r p
o
w
e
r
flo
w
. Ta
k
i
ng
i
n
to
c
o
ns
id
e
r
a
tion
t
h
e
t
o
tal
nu
mb
er
of
U
P
FC
s t
h
at
ca
n
b
e
in
sert
e
d
i
n
a
p
o
w
e
r
sy
st
em
is li
mite
d
,
du
e
t
o
th
e
co
st
o
f
th
e
d
e
v
i
c
e
s
a
nd t
h
e i
n
fl
u
e
n
c
e
s
on
th
e
op
e
r
a
tin
g ch
ar
ac
te
ri
st
ic
s o
f
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t
J
P
o
w
Elec
& Dri
Sy
st
I
SSN
: 208
8-8
6
9
4
O
p
tima
l
lo
ca
tio
n o
f
un
if
ie
d
po
w
e
r
fl
o
w
con
t
ro
lle
r
g
e
n
e
tic
a
l
go
rit
h
m
b
a
s
ed
(Sa
n
a
K
h
a
lid
Abdu
l
Ha
ssan)
8
89
th
e
p
o
w
e
r sy
st
em
.[24
]
.
A
l
s
o
,
i
n
th
is a
l
go
r
i
t
h
m to
ac
h
i
ev
e th
e t
a
rg
e
t
f
u
n
c
tio
n th
e
f
l
ow
ing
c
o
n
s
t
r
a
i
n sho
u
l
d
b
e
spec
i
f
i
e
d:
[2
5,
26
].
Loc
a
t
i
on o
f
UP
FC
:
N
o
m
o
re
t
h
a
n
o
n
e
UPF
C
ca
n be
i
n
sta
l
l
e
d
i
n
o
n
e br
a
n
c
h
of
p
o
we
r
-
f
l
o
w
c
o
mput
at
i
o
ns,
a
l
so ca
n
n
ot
c
o
nnec
t
UP
F
C
de
vi
ce
wi
t
h
P
Q
b
u
ses.
C
ont
r
o
l
p
a
ra
me
te
rs:
Th
e
per
f
or
manc
e
o
f
t
h
e
G
A
de
pen
d
s
on
t
h
e
co
nt
r
o
l
par
a
met
e
r
s
suc
h
as
po
p
u
la
ti
on
siz
e
,
c
r
o
s
so
v
e
r
p
r
ob
a
b
ilit
y
,
a
n
d
mu
t
a
t
i
o
n
p
r
ob
a
b
il
ity
.
The
opt
imal
lo
c
a
t
i
on
a
n
d si
ze
of t
h
e U
P
F
C
d
e
vi
ce
t
h
a
t
ca
n
be
u
s
ed i
n
I
E
E
E
-3
0 bu
s net
w
or
k i
s
gi
ve
n
i
n
MAT
L
A
B
c
odi
ng at
in t
h
e
fol
l
o
wi
n
g
st
e
p
s
be
lo
w
base
d
o
n
Ge
net
i
c
Al
g
o
r
i
t
h
m:
[
2
]
Ste
p
1
:
I
n
iti
al
ize
th
e p
opu
l
a
ti
o
n
si
ze
o
f
GA
an
d th
e p
a
rameters
of
U
P
FC dev
i
ce.
Ste
p
2
:
Ru
n the
prog
r
a
m o
f
po
w
e
r f
l
ow
(
N
ewt
o
n
R
a
p
h
s
on
)
.
Ste
p
3
:
For al
l th
e ind
i
v
i
du
a
l
’s
ob
j
e
c
t
i
v
e
v
a
l
u
es are
c
a
l
cu
la
ted
.
S
t
ep 4: B
a
se
d
on t
h
e o
b
je
c
t
i
v
e val
u
es
,
se
le
ct
a new p
o
pul
at
i
o
n
f
r
o
m
t
h
e ol
d
p
o
p
u
l
a
t
i
on base
d
o
n
t
h
e
c
a
l
c
ul
at
i
on fu
n
c
ti
on.
S
t
ep
5:
G
A
o
p
er
at
ors
,
c
r
oss
ove
r a
nd
mut
a
t
i
on a
r
e
a
ppl
i
e
d
t
o
the
p
o
p
u
la
t
i
on t
h
at
has
be
en sel
e
c
t
e
d
t
o
cre
a
t
e
new sol
u
tions.
S
t
ep 6:
F
o
r
ne
w
c
h
r
o
mos
o
me
s
t
h
e
o
b
je
ct
i
v
e va
l
u
es
a
r
e c
a
l
c
ula
t
e
d
a
n
d
u
s
in
g it
int
o
the
p
o
pul
at
io
n.
S
t
ep 7:
If
t
h
e t
i
m
e done
, st
op
GA
p
r
og
r
a
m
a
nd p
r
i
n
t
t
h
e
be
st i
ndi
vi
d
u
al
,
whi
l
e
i
f
n
o
t
go
t
o
st
ep
4
.
Th
e op
ti
miz
a
t
i
o
n s
t
r
a
te
gy
is
su
mm
a
r
iz
ed
in
Fi
g
u
re
5
[
6
]
.
Fi
gu
re
3.
The
c
o
n
f
i
g
urat
i
o
n I
E
E
E
3
0
b
u
se
s el
ec
tr
ic
al
ne
tw
or
k
Fi
gu
re
4.
Re
p
r
ese
n
t t
h
e
U
P
F
C
i
n
PS
S/
E pr
ogr
a
m
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
: 2
088
-86
94
I
n
t J
P
o
w
El
ec
&
D
r
i S
y
st
,
V
o
l
.
11,
N
o
.
2,
J
u
ne
20
2
0
:
8
8
6
– 89
4
89
0
F
i
gu
re
5.
O
p
ti
mi
zat
i
on
pr
oc
e
ss f
l
o
w
c
h
art
of
UP
FC
pl
ac
e
m
ent
ba
sed
o
n
G
A
5.
RE
S
U
LT
S
A
N
D
DI
SC
US
S
I
ON
:
As
p
r
evi
o
u
s
l
y
expl
ai
ne
d,
t
h
e
pr
o
pose
d
ge
net
i
c
a
l
g
o
r
i
thm
(
G
A
)
an
d
the
m
a
xi
mu
m n
u
mb
e
r
of
F
A
C
T
S
de
vic
e
s a
r
e
ap
pl
ie
d to t
h
e
3
0
-
b
u
s
po
wer t
e
s
t
syst
e
m
i
n
or
d
e
r t
o
fi
nd t
h
e
o
p
t
i
m
a
l
nu
mbe
r
, siz
e
and l
o
ca
t
i
on
of
UP
FC
d
e
vi
ces
t
o
r
eac
h
a
l
l t
a
rge
t
s:
i
n
c
r
ea
s
i
ng
l
i
ne
t
o
l
e
r
a
nce
a
n
d ba
la
n
ced
p
o
we
r
di
st
ri
but
i
o
n
a
n
d
r
e
duci
ng
to
ta
l
lo
sse
s
i
n
F
i
v
e
d
i
ff
er
en
t c
a
s
es
(
n
o
r
ma
l c
a
s
e
a
n
d
in
cr
e
a
se
o
v
e
ra
ll
lo
ad
in
(M
VA)
a
t
(5
%
,
10
%
,
15%
an
d
20
%)
.
I
n
Ta
ble
1, i
t
ha
s be
e
n
i
n
cl
ude
d t
h
e
ove
ra
ll
syst
e
m
l
o
ss
rat
e
a
n
d the
num
ber
of tr
ans
m
issi
o
n
li
n
e
s
e
x
p
o
se
d to
ove
r
l
oa
d
a
r
e
i
n
cl
u
d
ed i
n
al
l
c
a
ses wi
t
h
o
u
t a
ddi
ng
UPF
C
t
o
t
h
e syst
e
m
.
Ca
n
not
e
d
t
h
at
the
syst
em
at
th
e
no
r
m
a
l
c
a
se
(
283
.4
MW
) wh
ic
h
is
rep
r
esen
t
th
e
t
o
t
a
l
r
a
te
l
o
ad
in
g
o
f
th
e
sy
ste
m
,
th
e
a
c
t
i
v
e
a
n
d
r
e
a
c
tive
t
o
t
a
l
l
o
sse
s
t
o
t
h
e
net
w
or
k
e
qual
to
(
1
7.
5
MW a
n
d
6
7
.
6
M
v
a
r
)
wi
t
h
one
o
v
erl
o
a
d
l
i
ne.
The
s
e
r
e
s
u
lt
s a
r
e
co
ns
iste
n
t
w
ith th
e
pr
ac
ti
ca
l re
su
lt
s
t
a
k
e
n
f
r
om th
e
pro
g
r
a
m. Th
e
ra
te
o
f
the
s
e to
t
a
l lo
ss
es w
ill b
e
in
cr
ea
se
a
n
d
the loada
b
ility
o
f
th
e
transmis
sions
line will be decr
eases
when the s
y
stem
is e
xpos
e
d
to
increase
in the rate
of
dema
nd
.
Th
i
s
is
ob
se
r
v
ed
whe
n
t
h
e
t
o
t
a
l
loa
d
i
n
c
r
e
a
ses
by
(
5
%
,
1
0
%
,
1
5
%,
2
0
%)
.
H
o
weve
r,
whe
n
a
dde
d
t
h
e
UP
FC
t
o
t
h
e
syst
em
wit
h
op
ti
mal
posi
t
i
o
n
sel
e
c
t
i
on a
nd s
i
ze
by
sel
e
c
t
i
n
g opt
i
m
al
va
lu
e
s
b
y
usi
n
g ge
net
i
c
a
l
go
r
i
t
h
ms as s
h
o
w
n
i
n
Ta
bl
e
2
a
n
d
Ta
b
l
e
3
.
The
o
v
er
loa
d
l
i
ne i
n
30-
B
u
s
syste
m
has
be
e
n
red
u
c
e
d
, i
t
i
s
po
ssi
b
l
e
t
o
obse
r
ve t
h
e
ex
t
e
nt
o
f
t
h
e
e
ffe
ct
o
f
t
h
e
UPF
C
i
n
F
i
g
u
r
e
6 a
n
d Fi
g
u
r
e
7.
t
h
e
A
ppl
ic
at
ion i
n
t
h
e
P
S
S
/
E p
r
o
g
ra
ms b
y
u
s
in
g c
ont
ou
rs
obs
er
ved t
h
at
whe
n
t
a
ke t
h
e
fi
ve
case
as
exa
m
pl
e (at
2
0
% i
n
c
r
ease
i
n
l
o
a
d
) the
fo
ur l
i
n
es a
r
e u
p
t
o
t
h
e
maxi
m
u
m
de
g
r
ee
s of
the
o
v
er
l
o
adi
n
g mor
e
t
h
an
1
00%
.
W
h
il
e
Fi
gure
7.
s
h
o
w
s t
h
e l
o
adi
ng
of t
h
e same
l
i
n
es
af
te
r
th
e a
d
d
i
tio
n of
U
P
F
C
d
e
v
i
c
e
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J Po
w El
ec
&
Dr
i
S
y
st
IS
SN:
208
8-8
6
9
4
O
p
ti
ma
l l
o
c
a
t
i
o
n
o
f
un
ifie
d
po
we
r
flo
w
con
t
ro
l
l
e
r
g
e
n
e
tic
a
l
go
rith
m b
a
s
ed
(
San
a
Kha
l
id
Abdu
l
Ha
ssan)
8
91
F
i
gu
re
6.
The
l
o
adi
ng i
n
IEE
E
3
0
bus t
r
a
n
s
m
issi
on
l
i
ne w
i
t
h
o
u
t
U
P
FC
de
vic
e
F
i
gure
7.
t
h
e l
o
adi
n
g
i
n
i
e
e
e
3
0
b
u
s
t
r
a
n
smi
s
s
i
on li
ne
wi
t
h
u
p
fc
de
vi
ce
2.mi
ni
mini
ng
t
o
t
a
l
losses
wi
th mini
mu
m n
u
m
be
r of
u
p
f
c
.
a
s show
n
i
n
fig
u
re
8
a
nd
fi
g
u
re 9. t
h
e
tot
a
l
ac
ti
ve
an
d re
ac
t
i
v
e p
o
we
r l
o
s
s
e
s
ha
ve
be
en
re
d
u
ce
d
aft
e
r a
ddi
ng
u
p
fc
t
o
t
h
e s
y
st
em.
wh
e
r
e i
t
i
s
red
u
c
e
d
t
h
e
a
c
t
i
v
e
pow
e
r
lo
ss
es from
(
17.
5
mw
) to (5
.31
2
mw
)
a
l
so
t
h
e
r
e
ac
ti
v
e
pow
er lo
sses it i
s
redu
c
e
d fro
m
(67
.
6
m
v
a
r) t
o
(1
6.
5
7
3
m
v
a
r
) a
f
te
r a
d
d
t
h
e
u
p
fc
to
the
s
y
s
t
em
.
as
we
l
l
as
t
h
e
re
m
a
inde
r
c
a
s
e
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
: 2
088
-86
94
I
n
t J
P
o
w
El
ec
&
D
r
i S
y
st
,
V
o
l
.
11,
N
o
.
2,
J
u
ne
20
2
0
:
8
8
6
– 89
4
89
2
F
i
gu
r
e
8.
Ef
fec
t
addi
ng
U
P
FC
o
n
the
a
c
t
i
ve
p
o
we
r
l
o
sses
a
t
fi
ve ca
se
s wi
t
h
usi
ng G
A
F
i
g
u
r
e
9
.
Eff
ect
ad
d
UPF
C
on
th
e
to
t
a
l r
e
a
c
tiv
e
p
o
w
e
r
lo
sse
s
a
t
fiv
e
ca
se
s
w
i
th
u
s
ing
GA
A
s
sh
own
in
F
i
g
u
r
e
.
10
and
fi
gu
re.
11
th
e b
u
s
e
s v
o
lta
g
e
is k
e
p
t
wi
th
in
th
e
no
rm
al
lim
it a
n
d
n
o
t
de
via
t
i
o
ns
f
r
o
m o
r
i
g
i
n
al
va
l
u
e
s
.
F
i
gur
e
1
0
. V
o
l
t
a
ge
s
i
n
per
u
n
i
t
(
p
.
u
) f
o
r f
i
ve
l
o
adi
n
g
c
a
ses
w
i
t
hout
UP
FC
Fi
gu
re
1
1
.
V
o
l
t
a
g
es
i
n
pe
r
uni
t
(
p
.
u
)
f
o
r
fi
ve
loa
d
i
n
g
cas
e
s
w
i
t
h
UP
FC
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J Po
w El
ec
&
Dr
i
S
y
st
IS
SN:
208
8-8
6
9
4
O
p
ti
ma
l l
o
c
a
t
i
o
n
o
f
un
ifie
d
po
we
r
flo
w
con
t
ro
l
l
e
r
g
e
n
e
tic
a
l
go
rith
m b
a
s
ed
(
San
a
Kha
l
id
Abdu
l
Ha
ssan)
8
93
Ta
b
l
e 1
.
MA
TLA
B
an
d P
S
S
\
E
re
su
lt
w
i
t
hout
U
P
F
C
MATL
AB
re
sult
P
S
S
\
E re
s
u
lt
NO.
OF
C
A
SE
S
LOAD
ING
IN (
M
W)
T
O
TA
L
LIN
E
LO
S
S
E
S
TO
TA
L LI
N
E
L
O
SS
ES
OVE
RL
O
A
D
LI
N
E
MW
Mv
a
r
MW
Mv
a
r
No
r
m
al
ca
s
e
283.
4
17.
5
67.
6
17.
5
67.6
(
1
-2)
I
n
cr
ea
se
(5
%
)
297.
6
19
77
19
75
(
1
-2)
,
(
6
-8)
I
n
cr
ea
se
(
10%)
311.
74
21.
855
85.
978
21.
8
83.9
(
1
-2)
,
(
6
-8)
I
n
cr
ea
se
(
15%)
325.
91
24.
1
94.
6
24.
2
92.9
(
1
-
2
),
(
6
-8)
(
2-
6)
I
n
cr
ea
se
(
20%)
340
26.
86
105.
6
26.
7
102
(
1
-
2
),
(
2
-6)
(4
-
6
)
,
(
6
-8)
Tabl
e
2.
M
A
T
L
AB a
n
d
PS
S\
E
r
e
s
u
lt
wi
th
U
P
F
C
wi
t
h
G
A
MAT
L
AB
re
su
lt
PS
S
\
E r
e
s
u
l
t
NO
.
O
F
CA
SE
S
N
U
PFC
\
LO
CA
T
I
ON
UP
FC
SI
Z
E
TO
TA
L L
I
N
E
LO
S
S
ES
TO
TA
L LI
N
E
LO
SS
ES
O
V
ER
L
OAD
LI
N
E
MW Mv
ar
MW
Mv
a
r
No
rma
l
Case
N
U
P
F
C
=1br
anc
h
(4
)
b
et
we
en
b
us 3-
4
Vc
r =
0
.
9947,
δ
c
r
=-0.
0985,
V
v
r =
1
.
0987,
δ
vr
=-
0.
00887
5.
312
16.
573
5.
5
18.6
N
O
N
E
I
n
cr
ea
se
(5
%)
N
U
P
F
C
=1br
anc
h (
6
) be
tw
ee
n
b
us(6-
2
)
Vc
r =
0
.
245,
δ
c
r
=
-
0.
0084
2
V
v
r =
0
.
001,
δ
vr
=-0.
0002
1,
6.
6
23.
076
6.
0
2
4
.
1
N
O
N
E
I
n
cr
ea
se
(
10%
)
NU
PF
C=
1Bra
nc
h (5)
B
e
t
we
en
b
us(5-
2
)
Vc
r=
0.
893,
δ
c
r
=-
0
.
00091
3
V
v
r=
0.
984,
δ
vr
=-
0.
0177
5.
87
20.
032
5.
9
20.5
N
O
N
E
I
n
cr
ea
se
(
15%
)
N
U
P
F
C
=1br
anc
h
(5
)
b
et
we
en
bus(5-
2
)
Vc
r=
0.
0068,
δ
c
r
1=-0.
00588
V
v
r1=
0
.
8958
,
δ
vr
1
=
-
0.
0033
8
7.
364
24.
467
7
24.6
N
O
N
E
I
n
cr
ea
se
(
20%
)
N
U
PFC
=21.
bra
n
c
h
(5
)
Be
t
w
ee
n
bus (5-
2
)
2.
br
anc
h
28
be
tw
ee
n
bus 10-
21)
Vc
r1=
0
.
0117,
δ
c
r
1=
-0.
0015
V
v
r
1
=0.
077,
δ
vr1
=
0.
0046
Vc
r2=
0
.
1345,
δ
c
r
2=
-0.
0664
vr
2=0.
0799,
δ
vr2=
0.
0
0
6
7.
039
23.
763
7.
2
23.5
N
O
N
E
Tabl
e
3.
App
r
o
p
ri
at
e Pa
ramet
e
rs Used
in
GA c
ode
Pa
ra
met
e
rs
V
a
l
u
e
Nu
mb
e
r
o
f
g
ene
r
a
t
ions
100
p
opulati
on si
ze
50
C
r
ossove
r f
r
a
c
tion
0.
8
Fi
tness l
i
mit
1
Ti
me
li
m
i
t
∞
6.
CO
NCL
U
S
I
O
NS:
In t
h
is wo
rk
,
e
x
a
m
in
e th
e e
f
f
e
c
t
of
U
P
F
C
i
n
enh
a
n
c
ing
p
o
w
e
r sy
s
t
e
m
p
e
rf
or
man
ce usi
n
g in the
I
EEE-3
0
bu
s sy
ste
m
as
a
c
a
se study
.
a
f
ter i
n
se
rt
ing th
e
UPF
C
d
e
v
i
ce
th
e
to
ta
l ac
tiv
e
pow
er loss
of t
h
e
sy
ste
m
is
r
e
du
c
e
d
by
6
9
.
594
% a
n
d
po
w
e
r
tr
an
sfer
cap
a
b
il
ity
o
f
th
e
sy
ste
m
is i
m
pr
ov
e
d
by
mak
i
n
g
al
l pow
e
r
tra
n
sfe
r
ove
r t
h
e tra
n
s
m
i
ssi
on
l
i
ne
s wi
t
h
i
n
the
n
o
r
m
a
l
ra
ti
ng
.so t
h
is wi
ll
ma
ke
use
t
h
e sa
me l
i
ne
f
o
r
t
r
a
n
s
f
err
i
ng m
o
re
po
we
r
wi
t
h
out
any e
x
t
r
a
c
o
s
t
. Si
mul
t
ane
ousl
y
the
vol
t
a
ge
profil
e
o
f
t
h
e
syste
m
i
s
ke
p
t
wi
t
h
n
o
rma
l
l
i
mi
t
.
Al
so d
u
e t
o
t
h
e
com
p
le
xit
y
o
f
po
we
r
s
y
st
ems
a
nd
hi
gh c
o
st
t
h
at
the
i
n
st
al
la
ti
on
of
t
h
e
UP
F
C
devi
c
e
de
pe
nde
d
on
t
h
e
ge
ne
ti
c
a
l
go
ri
t
h
m (G
A
)
it
was
gi
ve
s b
e
t
t
er
res
u
lt
s (c
ont
rol
t
h
e
vol
t
a
ge ma
g
n
it
u
d
e,
vol
t
a
ge
p
h
ase
a
ngle
,
and
im
pe
da
nc
e)
a
n
d
c
a
n
ge
t
t
h
e
best
l
o
c
a
t
ion
an
d
the
rig
h
t
si
z
e
wit
h
t
h
e
l
e
a
s
t t
i
me
t
h
i
s
wi
l
l
a
c
h
ie
ve
d
dec
r
ea
se
s
ove
rloa
d
l
i
n
es a
nd
mini
miz
e
s s
y
st
emi
c
p
o
we
r
l
o
s
s
es.
RE
FERE
NC
E
[1]
L
.
Gyugyi
,
“Unified Power Fl
ow
Control
l
er
(U
PFC),”
A
d
v.
Solut. Power Syst.
HVD
C
, FACT
S
,
AI
T
ech.
,
vo
l. 2, no.
12
, p
p
.
559
–6
28
,
20
16
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
: 2
088
-8
6
94
Int
J
P
o
w
Ele
c
& D
r
i
S
y
st, V
o
l
.
1
1
,
N
o
.
2, Ju
ne
20
2
0
:
8
8
6
–
894
89
4
[2]
G. A.
S
a
l
m
an
,
M.
H
.
A
l
i
,
an
d
A. N.
A
bdu
ll
ah,
“Imp
lemen
t
a
t
io
n optim
al loc
a
ti
on
an
d si
zing
o
f
U
P
F
C
on
Iraq
i
po
wer s
y
stem g
r
id (1
32
kV) u
s
ing
gen
e
tic
algo
rithm
,
”
In
tern
atio
na
l Jo
urn
a
l of
Po
wer Electr
o
n
i
cs
and
Dr
ive
S
y
st
e
m
s
(
I
J
P
E
DS.
,
v
o
l.
9
,
n
o
.
4
,
p
p
.
160
7–
16
15
,
20
18
.
[3
]
G. S.
Ya
da
v
,
A.
Agra
wa
l
,
a
n
d D.
K. Si
ng
h, “
P
o
w
e
r
Fl
ow
P
r
ob
lem Re
d
u
c
e
d
Usin
g
Un
ifi
e
d Po
we
r F
l
ow
C
o
n
t
ro
lle
r,”
vo
l. 4
,
no
.
6
,
pp
. 28
71
–2
87
4,
2
0
1
5
.
[4]
T.
K
a
lyan
i, T.
R
.
Ku
mar
,
an
d
G. S
.
P
r
asad, “P
o
w
er
F
l
ow
Co
ntrol
and
V
o
ltag
e P
r
o
f
ile
I
m
pro
v
e
m
en
t U
s
ing
Un
ified
Po
we
r Fl
ow Con
t
r
o
l
l
er (UPFC) i
n
a
Gri
d
Ne
twork
,
”
I
n
t
.
J.
El
ec
t
r
o
n
.
El
ec
t
r
. En
g.
,
vo
l.
4, n
o
.
6
,
pp.
48
2–
48
7
,
2
0
1
6
.
[5
]
S.
N.
W
a
gha
de a
n
d C.
Go
wder,
“
E
n
h
a
n
ce
m
e
n
t
o
f
Po
we
r Fl
ow Ca
pa
b
i
l
i
t
y
i
n
Po
we
r
Sy
ste
m
u
s
i
n
g
UPFC-
A
Review,
”
n
o
.
M
a
y
,
p
p
.
11
46
–11
50
, 2
019
.
[6]
M.
Mez
a
ach
e,
K.
Chikhi,
and
C
.
Fe
tha,
“UPFC
devi
ce:
Optimal
location
and parameter settin
g to
reduce losses in
ele
c
tric-po
w
er
sy
stem
s
using
a
ge
ne
tic
-a
lg
ori
t
hm m
e
th
od,
”
Tran
s.
Ele
c
t
r.
E
l
ec
t
r
on.
Mate
r
.
,
v
o
l.
1
7
, no
.
1,
pp
.
1–
6
,
20
16
.
[
7
]
V. K
r
is
hn
asamy
,
“G
enet
ic
al
go
r
i
th
m f
o
r
so
lv
in
g
op
ti
ma
l p
o
wer
f
l
ow
pr
ob
le
m wi
t
h
UP
F
C
,”
Int.
J.
Soft
w
.
Eng.
i
t
s
Ap
pl
.
,
vol. 5, n
o
. 1, pp
. 39
–5
0, 201
1.
[8]
E
.
Ghahremani
and I
.
Kamwa, “O
pt
imal
Pl
acement of
Multip
le-
T
ype
FACT
S Devices t
o
Maximi
ze Po
wer Syst
em
Lo
adab
ili
t
y
Us
in
g a
G
e
neri
c Gra
p
hical U
s
er In
ter
f
ace
,”
pp
. 1
–
1
5
,
2
0
1
2
.
[9]
A.
Mathemat
ics,
“MIN
IMIZ
IN
G
POW
E
R LO
SSES AN
D POWER QU
ALITY
IMPRO
V
EMEN
T USING
BI
ST ,
Bh
a
r
a
t
h Insti
t
u
t
e
of Hi
g
h
er E
duca
t
i
on a
nd Re
se
a
r
c
h
, Bha
r
a
t
h
Univ
e
r
si
ty
,”
v
o
l. 118,
n
o
.
18,
p
p
. 2
9
1
–
2
9
9
,
2
0
18.
[1
0]
S.
Hoc
i
n
e
a
n
d
L.
Dja
m
el, “
O
pti
m
al
nu
m
b
e
r
an
d l
o
ca
ti
on o
f
UPFC d
e
v
i
c
e
s
t
o
e
nhe
nc
e
vo
lta
g
e
p
r
ofi
l
e
a
n
d
m
i
ni
miz
i
n
g
lo
sse
s
in
e
l
e
c
t
rica
l
p
o
we
r
syste
m
s,”
vo
l.
9, n
o
.
5
,
pp.
39
81
–3
9
9
2
,
2
019.
[11
]
A.
B. Bh
a
t
tach
ar
yy
a and
B
.
S.
K.
Go
sw
am
i,
“
O
P
T
IM
AL p
l
a
c
e
m
e
n
t o
f
F
A
CTS
de
v
i
ces
by
gen
e
tic
alg
o
rith
m
fo
r th
e
i
n
creased load
abil
it
y
of
a
power
system,”
W
o
r
l
d
A
c
ad.
S
c
i.
En
g.
T
ech
no
l.
,
vo
l.
7
5
, no
.
M
a
rc
h
20
1
1
,
p
p
.
18
6–
19
1
,
20
11
.
[12]
B.
Abdel
k
r
i
m an
d Y.
Merzoug, “Robus
t
st
abi
lity
power i
n
the tr
ansm
issi
on
l
i
ne w
i
th the
use of a
UPFC
sy
st
em
an
d
neu
r
al co
nt
roll
er
s b
a
sed
adap
tive
con
t
ro
l,”
vol.
1
0
,
no
.
3,
20
19
.
[13]
S.
Ahmad
,
F.
M
.
Al
bats
h,
S
.
Mekhil
ef
,
and H
.
M
o
khl
i
s,
“An
appr
oach
to
i
m
prov
e act
i
ve power
flow capabilit
y
by
us
in
g dy
nami
c
unified
po
wer f
l
o
w
con
t
ro
ller,
”
in
20
14 IEEE
Inn
o
v
a
t
i
v
e
S
m
a
r
t Gri
d
T
e
c
h
n
o
l
ogi
e
s
-A
si
a (I
SGT
A
S
IA
)
,
201
4,
pp
.
24
9–
25
4.
[14
]
Z. V O
l
u
w
agb
a
de an
d S
.
T.
W
a
ra,
“Eff
ec
t o
f
Un
if
ied P
o
wer
F
l
o
w
Co
ntroller
on Pow
e
r Sys
t
em Performan
c
e
: A
Case S
t
ud
y o
f
M
a
ryland
132
/ 33
/
11
kV
Tran
sm
is
sion
S
t
ation
,
”
v
o
l. 5
,
no
. 6
,
p
p
.
3
5
5
–
3
64,
20
15
.
[1
5]
A.
P
r
of, F. Moh
a
m
m
e
d
, a
nd Y.
Na
dh
um
,
“
O
pt
im
a
l
L
o
c
a
tio
n
of St
a
t
i
c
Sy
nc
h
r
onou
s Com
p
e
n
sa
t
o
r ( ST
AT
COM )
fo
r IEEE 5
-
Bus
Sta
n
da
r
d
Syst
em Usin
g Ge
net
i
c
Alg
o
r
it
hm,
”
vol
.
2
1
, no
. 7, pp
.
7
2–8
4,
20
15.
[1
6]
F.
O.
Ak
po
je
dje,
A.
O.
Ol
om
o,
E
.
C
.
M
o
rm
a
h
,
a
n
d E
.
M
.
Ok
a
h
,
“
O
p
t
i
m
a
l
Power Fl
ow Co
nt
ro
l
o
n
Powe
r Sy
st
e
m
Tran
smis
sion
Ne
two
r
k u
s
ing
UP
F
C
,”
In
t.
J.
En
g
.
T
r
end
s
Tech
no
l.
, v
o
l.
3
3
, n
o
.
3
,
pp.
11
8–
12
5, 2
016.
[1
7]
U.
Uni
f
i
e
d
a
n
d
P
.
Flo
w
, “
I
SSN
: 23
47-6
5
3
2
IS
S
N
: 2
347
-65
3
2
,
” v
o
l
.
4
,
no
. 2
,
pp
. 7
2–8
5,
20
16
.
[18]
R.
H
.
AL
-Rubay
i
a
n
d L.
G.
Ibrah
i
m,
“E
nhancement
t
r
an
s
i
en
t stab
ility of pow
er
s
y
st
e
m
usin
g UPFC
wit
h
M-PSO,
”
In
do
ne
s.
J
.
E
l
e
c
t
r.
E
ng.
Co
mpu
t
. Sc
i
.
,
vo
l.
17,
no
.
1
,
pp
. 6
1
–
6
9
,
20
19
.
[
1
9
]
I
.
P
r
es
s, P
.
M
.
A
nder
s
on
, M
.
E
d
e
n
, P
.
L
a
p
l
ant
e
,
a
n
d
W.
D.
R
eev
e,
U
n
d
e
rstan
ding
FACTS
. .
[20
]
P
.
S
o
ng,
Z. Xu,
and
H
.
Don
g
,
“U
P
F
C
-based
lin
e
ov
erlo
ad
con
t
r
o
l
for
pow
er
sy
s
t
em se
curity
enh
a
n
c
e
m
ent
,
”
IE
T
Gener. Tr
ansm
. Distrib.
,
vo
l.
11
,
no
.
1
3
,
pp.
33
10
–33
17
, 2
0
1
7
.
[2
1]
E
.
Ac
ha
, C. R
.
Fue
r
t
e
-E
sq
ui
ve
l,
H.
Am
bri
z
-P
e
r
ez
,
a
n
d
C.
Ang
e
le
s-Ca
m
a
c
h
o,
FACT
S: mo
delling
a
nd s
i
mu
la
tion
i
n
p
o
we
r ne
t
w
ork
s
.
Jo
hn
Wi
ley
& S
o
n
s
,
200
4.
[22
]
S
.
C. S
.
A
.
P
a
ndey
,
“Rea
l
an
d Rea
c
tiv
e
P
o
w
e
r F
l
ow
An
alys
is
& S
i
mul
a
tion
with U
P
F
C
Co
nn
ected
to
a
Tr
an
smis
si
on
Li
ne,”
Int. J.
Sci.
Res.
,
vo
l.
4,
no
.
4,
pp
.
2
178
–2
18
3,
2
0
1
5
.
[23
]
H.
S
aad
at,
P
o
we
r sy
s
t
e
m
an
a
l
y
s
is
. 19
99.
[2
4]
L
.
H. Ha
ssa
n
,
M
.
Mo
gh
a
v
v
e
mi
, H.
A.
F.
Alm
u
ri
b,
a
nd
O. Ste
i
n
m
a
y
e
r
, “
A
pp
li
ca
ti
o
n
of g
e
n
e
tic
a
l
g
o
rith
m in
op
timization
o
f
un
ified
po
wer
fl
ow con
t
ro
ller p
a
ram
e
te
rs
and
its locati
on in
t
h
e
power
system
network,”
In
t
.
J.
El
e
c
tr
.
Po
w
e
r
E
n
er
gy S
y
st
.
,
v
o
l
.
46
, p
p
.
89
–97
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