Int
ern
at
i
onal
Journ
al of Ele
ctrical
an
d
Co
mput
er
En
gin
eeri
ng
(IJ
E
C
E)
Vo
l.
8
, No
.
6
,
Decem
ber
201
8
, p
p.
5472
~
5483
IS
S
N: 20
88
-
8708
,
DOI: 10
.11
591/
ijece
.
v8
i
6
.
pp5472
-
54
83
5472
Journ
al
h
om
e
page
:
http:
//
ia
es
core
.c
om/
journa
ls
/i
ndex.
ph
p/IJECE
Optimi
zation
of t
he Thyr
i
stor Con
trolled P
hase Sh
ifting
Tra
ns
for
mer Usi
ng PSO Alg
or
ith
m
Ha
di
Su
yono
1
,
R
ini
Nu
r
Has
anah
2
, P
ar
ami
ta D
w
i Pu
tri
P
ranyat
a
3
1,2
Depa
rtment
of
Elec
tr
ical
Engi
n
ee
ring
,
Fa
cul
t
y
o
f
Engi
n
ee
ring
,
Brawij
a
y
a
Univ
er
sit
y
,
Indon
esia
3
PT.
Infin
eon Technologies,
Indo
nesia
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
Dec
2
9
, 201
7
Re
vised
Ju
l
2
8
,
201
8
Accepte
d
Aug
21
, 201
8
The
inc
r
ea
se
of
power
s
y
stem
demand
le
ads
to
the
cha
nge
in
voltage
profile
,
rel
i
abi
l
ity
req
ui
rement
and
s
y
stem
robustness
aga
inst
distur
banc
e
.
Th
e
volt
ag
e
profi
le
ca
n
b
e
improved
b
y
provid
ing
a
source
of
react
iv
e
powe
r
through
the
a
ddit
ion
of
ne
w
power
plants,
ca
p
ac
i
tor
banks,
or
implementa
t
ion
of
Flexi
ble
AC
Tra
nsm
ission
Sy
stem
(FA
CTS)
d
evi
c
es
such
as
Stat
i
c
VA
R
Com
pensa
tor
(SV
C),
Unifie
d
P
ower
Flow
Control
(UP
FC
),
Th
y
r
istor
Contr
oll
ed
Serie
s
Ca
pac
i
tor
(TCSC),
Th
y
ristor
Cont
roll
ed
Phase
Shifti
ng
Tr
ansform
er
(TCPS
T),
and
m
an
y
o
the
r
s.
Dete
rm
in
a
ti
on
of
opti
m
al
loc
a
ti
on
and
si
z
ing
of
d
evi
c
e
i
nje
c
ti
on
is
par
a
m
ount
to
produ
ce
the
best
improvem
ent
of
volt
age
prof
il
e
and
power
losses
red
uct
i
on.
In
thi
s
pape
r
,
opti
m
iz
ation
of
the
combined
a
dvant
ag
es
of
T
CP
ST
and
TCSC
has
bee
n
inve
stigated
usi
ng
Parti
c
l
e
Sw
arm
Optimiza
tion
(PS
O)
al
gorit
hm
,
bei
ng
appl
i
ed
to
the
30
-
bus
sy
stem
IEE
E
stand
ard
.
The
eff
e
ct
iv
en
ess
of
the
pla
c
ement
and
s
iz
ing
of
TCPS
T
-
TCSC
combinat
ion
has
be
en
c
om
par
ed
to
the
implement
a
ti
on
of
c
apa
c
itor
banks.
The
result
show
ed
tha
t
th
e
combinat
ion
of
TCPS
T
-
TCSC
result
ed
in
m
ore
eff
e
ctive
improvem
ent
o
f
s
y
stem
power
lo
ss
es
condi
ti
on
t
han
the
implementation
of
ca
p
a
ci
tor
b
anks.
The
power
losses
red
uct
ion
of
46.
47%
and
42.
0
3%
have
bee
n
obta
in
ed
using
of
TCPS
T
-
TCSC c
om
bina
ti
on
a
nd
ca
p
ac
i
tor
ban
ks re
spec
t
ive
l
y
.
The
TCPS
T
-
TCSC
and
Cap
a
ci
tor
B
ank
impl
ementa
t
ions
b
y
using
PS
O
al
gorit
hm
have
al
so
be
en
comp
are
d
wi
th
th
e
i
m
ple
m
ent
at
ion
of
Stat
i
c
VA
R
Com
pensa
tor
(SV
C)
using
Art
ifi
cial
B
ee
Colo
n
y
(ABC)
Algor
it
hm
.
The
imple
m
ent
at
ion
of
the
TCSC
-
TCP
ST
compensat
io
n
with
PS
O
algorithm
have
g
ave
a
be
tt
er
result
tha
n
using
the
ca
p
ac
i
tor
bank
with
PS
O
a
lgori
thm
and
SV
C
with
the
ABC a
lgorithm
.
Ke
yw
or
d:
Ca
pacit
or
Ba
nk
Loss
es
r
e
duct
ion
PSO al
gorithm
TCPST
TCSC
Vo
lt
age
pr
of
il
e
i
m
pr
ovem
ent
Copyright
©
201
8
Instit
ut
e
o
f Ad
vanc
ed
Engi
n
ee
r
ing
and
S
cienc
e
.
Al
l
rights re
serv
ed
.
Corres
pond
in
g
Aut
h
or
:
Had
i
Su
y
ono,
Dep
a
rtm
ent o
f El
ect
rical
En
gi
neer
i
ng, F
ac
ulty
o
f
Enginee
ri
ng,
Brawijaya
U
niv
ersit
y, Ma
la
ng
-
Ind
on
e
sia
Jl. MT.
Har
y
ono 1
67 Mal
an
g 6
5145
Ind
on
e
sia
.
Em
a
il
: had
is@
ub.ac.id
1.
INTROD
U
CTION
The
inc
rease
in
el
ect
ric
pow
er
dem
and
is
in
ge
ner
al
pro
portio
nal
to
th
e
popula
ti
on
gro
wth
of
a
country.
T
he
load
inc
rease
usual
ly
req
ui
res
the
add
it
ion
of
new
powe
r
pl
ants,
both
in
te
rm
s
of
the
num
ber
of
un
it
s
an
d
the
gen
e
rated
pow
er
capaci
ty
.
Con
s
eq
ue
ntly
,
fu
rt
her
ad
diti
on
and
ex
pa
ns
io
n
of
transm
issio
n
a
nd
distrib
ution
syst
e
m
s
infr
ast
r
uctu
re
are
require
d.
T
he
sys
tem
beco
m
es
m
or
e
com
plex
and
s
us
ce
ptible
to
interfe
ren
ce
.
C
on
ti
nuit
y
of
se
rv
ic
e
m
us
t
al
so
sat
isfy
te
c
hni
cal
and
eco
no
m
ic
al
req
uire
m
ents
.
Lo
ad
c
hanges
,
com
po
sit
ion
of
ge
ne
rati
ng
unit
s
in
op
e
rati
on
as
well
as
t
he
c
hanges
i
n
netw
ork
c
onfi
gurati
on
ha
ve
a
gr
eat
i
m
pact
on
the
ov
e
rall
var
ia
ti
on of volta
ge
le
vels and
power l
os
ses
in the
s
yst
e
m
.
V
oltage
p
r
of
il
e
im
pr
o
vem
ent
to
f
ulfill
the
assigne
d
op
e
rati
on
sta
ndar
d
of
the
entire
syst
e
m
has
so
m
e
i
m
pacts
to
decre
ase
powe
r
los
s
es
in
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
Elec
&
C
om
p
En
g
IS
S
N: 20
88
-
8708
Op
ti
miz
atio
n o
f t
he
T
hyristor
Con
tr
olled P
hase
Shif
ti
ng
Tr
an
sf
ormer
Usi
ng P
SO Alg
or
i
thm
(
H
adi
Su
y
ono
)
5473
the
syst
e
m
[1
]
-
[
2].
V
oltage
f
luctuat
io
n
can
al
so
be
co
ntr
olled
thr
ough
powe
r
syst
e
m
com
pen
sat
ion.
Th
e
com
pen
sat
ion
bo
t
h
in
tra
nsm
issi
on
an
d
di
stribu
ti
on
syst
e
m
s
can
be
pe
rfor
m
ed
us
i
ng
ei
the
r
c
onve
ntion
al
capaci
tor
ba
nk
s
or
Fle
xib
le
A
lt
ern
at
ing
Cu
rrent
Tra
ns
m
issio
n
Syst
em
s
(F
ACTS)
dev
ic
e
s
[
3
]
-
[
6].
T
he
FA
CT
S
dev
ic
es
im
plem
entat
ion
s
in
cl
ud
e
Stat
ic
VA
R
C
om
pen
sat
or
(S
VC
)
[7
]
-
[
9]
,
T
hyristor
C
on
t
ro
ll
ed
Serie
s
Ca
pacit
or
(TC
SC)
[
10
]
,
Thyr
ist
or
Co
ntr
olled
P
hase
S
hiftin
g
Tra
nsfo
rm
er
(TCPST
)
[
11]
,
Un
i
fied
P
ower
Flow
Con
tr
ol
(
UP
F
C)
[12]
,
Dyn
a
m
ic
Vo
lt
age
Re
store
r
(DVR)
[13]
and
m
any
oth
ers
[
14]
.
So
m
e
research
resu
lt
s
al
so
showe
d
that
the
us
e
of
distrib
uted
ge
ne
rati
on
c
ou
l
d
ov
e
rc
om
e
the
vo
lt
age
prof
il
e
pr
oble
m
and
powe
r
losses
i
n
distribu
ti
on
syst
e
m
,
an
d
al
s
o
cl
ai
m
ed
to
im
pr
ov
e
the
distrib
ution
syst
em
per
f
or
m
ances
in
te
rm
s
of
powe
r qu
al
it
y
[
13
]
,
r
e
li
abili
ty
[15
-
16]
, a
nd stabil
it
y [
17
]
-
[
18
].
This
pa
per
pr
e
sents
the
in
ve
sti
gation
res
ults
on
the
us
e
of
c
om
bin
at
ion
of
two
F
AC
TS
de
vices,
wh
ic
h
are
a
TCPST
an
d
a
TCSC
,
to
ov
e
rc
om
e
the
vo
lt
ag
e
pr
ofi
le
pro
ble
m
.
The
TCSC
is
sp
eci
fical
ly
us
e
d
to
com
pen
sat
e
th
e
reacta
nce
of
the
tra
ns
m
issi
o
n
li
ne
a
nd
c
om
m
on
ly
us
ed
on
lo
ng
tra
nsm
issi
on
li
ne.
T
he
m
ai
n
issues
e
xp
l
or
e
d
in
the
st
udy
wer
e
t
he
optim
al
locat
ion
a
nd
siz
ing
for
the
place
m
ent
of
TCP
ST
-
TCSC
com
bin
at
ion
.
Com
par
ison
to
the
us
e
of
c
onve
ntio
nal
ca
pa
ci
tor
banks
h
as
bee
n
pe
rform
ed
to
justi
fy.
The
re
hav
e
bee
n
m
a
ny
m
et
ho
ds
propose
d
to
s
olve
the
op
ti
m
iz
a
ti
on
pro
blem
,
i
nclu
ding
the
he
ur
ist
ic
pro
babi
li
sti
c
and
a
rtific
ia
l
i
ntell
igent
m
eth
ods.
Ge
netic
Algorithm
(AG)
m
et
ho
d
wa
s
exp
l
or
e
d
to
determ
ine
the
op
ti
m
a
l
locat
ion
of
m
ul
ti
-
ty
pe
FA
CTS
[19]
an
d
t
o
c
ontr
ol
the
vo
lt
ag
e
an
d
reacti
ve
powe
r
[
20
]
-
[
21]
.
Ther
e
we
re
m
any
oth
e
r
arti
fici
al
intel
li
gen
t
m
e
thods
su
c
h
as
Ar
ti
fici
al
Be
e
Colo
ny
al
go
rit
hm
[8
]
,
[2
2],
Si
m
ulate
d
Anneali
ng
[23],
F
uzzy
E
P
al
gorithm
[24],
an
d
oth
e
rs
popula
ti
on
al
gorithm
[25],
be
ing
st
ud
ie
d.
I
n
this
pa
per
,
P
arti
cl
e
Sw
arm
O
pti
m
iz
at
ion
(
PS
O)
al
gorithm
is
us
e
d
t
o
s
olve
the
optim
izati
on
pro
blem
.
H
ow
e
ve
r,
t
he
PS
O
al
gorithm
has
been
us
e
d
in
m
any
app
li
cat
ion
s
i
nclu
ding
the
SV
C
locat
i
on
op
ti
m
iz
ation
[
26
]
.
PS
O
al
gorithm
is
a
m
et
ho
d
ad
op
ti
ng
the
s
oci
al
beh
a
vio
r
of
bir
ds
w
he
n
fly
ing
t
og
et
her
in
search
of
foo
d.
Perfor
m
ance
of
th
e
PSO
al
gorithm
to
con
tr
ol
the
vo
lt
age
prof
il
e
and
po
wer
los
ses
hav
e
been
te
ste
d
on
the
30
-
bus
syst
e
m
I
EEE
sta
nd
a
rd d
at
a.
2.
POWER
S
YST
EM COM
P
ENSA
TI
ON
2.1.
Thyrist
or C
ontrolle
d P
hase
Shift
in
g
Tr
ansfo
r
mer (T
CP
ST)
TCPST
is
a
dev
ic
e
with
ch
aracte
risti
cs
sim
il
ar
to
con
ve
ntion
al
P
hase
Angle
Re
gu
l
at
or
s
(PAR)
,
bein
g
co
nn
ect
e
d
in
series
to
netw
ork
.
T
he
m
ai
n
diff
ere
nc
e
li
es
in
the
fact
that
the
ta
p
change
r
is
cont
ro
l
le
d
us
in
g
thyrist
or
to
achieve
fas
te
r
op
e
rati
on
[
14
]
.
T
he
volt
age
on
the
pri
m
ary
side
is
inj
e
ct
ed
thu
s
the
phase
sh
ifte
d,
an
d
th
eref
or
e
the
t
ransm
issi
on
an
gle
can
be
c
on
t
ro
l
le
d.
The
m
od
el
ing
of
power
i
nj
ect
io
n
at
the
i
th
and
j
th
bus
es
is s
hown in Fi
gure
1.
P
s
i
+
j
Q
s
i
P
s
j
+
j
Q
s
j
Figure
1. Mo
de
li
ng
of TCPS
T in
j
ect
ion
The
P
si
,
Q
si
,
P
sj
, and
Q
sj
par
am
et
ers
can
b
e
de
te
rm
ined
as
f
ollow
s:
Si
=
s
i
j
sin
(
ij
+
)
(1)
Si
=
2
s
i
2
−
s
i
j
cos
(
ij
+
)
(2)
Sj
=
−
s
i
j
sin
(
ij
+
)
(3)
Sj
=
−
s
i
j
cos
(
ij
+
)
(4)
wh
e
re
=
|
S
|
|
i
|
,
s
=
1
s
,
and
γ
is
the
ang
le
to
be
co
ntr
olled
by
TCPS
T.
The
volt
age
phase
-
a
ngle
wh
ic
h
ca
n
be
con
t
ro
ll
ed
by
TCPST
is
i
n
t
he
range
betw
een
-
5°
a
nd
5°
.
Fig
ure
2
in
di
cat
es
the
m
od
e
li
ng
of
TCPST i
n
the
tra
ns
m
issi
on
li
ne
[14
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8708
In
t J
Elec
&
C
om
p
En
g,
V
ol.
8
, N
o.
6
,
Dece
m
ber
2
01
8
:
5472
-
5483
547
4
j
i
Z
L
i
n
e
Ū
T
C
P
S
T
Ū
T
C
P
S
T
=
V
m
i
n
∠
±
9
0
°
~
V
m
a
x
∠
±
9
0
°
Figure
2. The
TCSC
m
od
el
in
tra
ns
m
issi
on
li
ne
2.2.
Thyrist
or C
ontrolle
d
Seri
es
Capa
ci
to
r
(
T
CSC)
TCSC
is
one
t
ype
of
F
ACTS
de
vices
wh
ic
h
com
bin
es
a
T
hyristo
r
Co
ntr
olled
Re
act
or
(
TCR
)
wit
h
capaci
tor
[14].
The
TCR
consi
sts
of
in
du
ct
or
bein
g
co
nnect
ed
in
series
with
thyrist
or.
TCSC
is
capab
le
to
adjust
reacta
nc
e
of
tra
ns
m
issio
n
li
ne
by
cont
ro
ll
ing
the
t
hy
ristor
firi
ng
-
a
ng
le
.
Fi
gure
3
rep
re
sents
a
s
i
m
ple
m
od
el
ing
of
s
eries
TCSC
.
T
o
av
oid
over
com
pen
sat
ion,
the
in
j
ect
ion
of
TC
SC
is
s
et
on
20%
in
du
ct
iv
e
(0.2
X
line
)
up t
o 70% ca
pacit
ive (
-
0.7
X
line
)
of t
he
li
ne react
an
ce [
28
]
, suc
h
t
hat:
r
TCSC
m
in
=
-
0.
7
a
nd
r
TCSCm
a
x
=
0.
2
(5)
i
X
c
R
i
j
+
j
X
i
j
T
C
S
C
j
Figure
3. The
m
od
el
ing
of
T
CSC
The
TCSC
m
od
el
ing
w
hich
e
nab
le
s
t
he
reac
ta
nce
co
ntr
ol
of
the
tra
ns
m
issio
n
li
ne
is
s
how
n
in
Fi
gur
e
4 [28]. T
he rel
at
ion
s
hip
betw
een th
e
TCSC
rati
ng to
t
he
tra
ns
m
issi
on
li
ne react
ance is
express
ed
as
fo
ll
ow
s:
tot
a
l
=
lin
e
+
TC
S
C
(6)
TC
S
C
=
TC
S
C
×
lin
e
(
7)
wh
e
re
X
line
is t
he
li
ne react
an
ce an
d
r
TCSC
is
the co
m
pen
sat
i
on r
at
in
g of T
CSC
.
i
j
X
T
C
S
C
Z
L
i
n
e
X
T
C
S
C
=
X
m
i
n
-
X
m
a
x
Figure
4. The
TCSC
m
od
el
ing
in
the t
ran
sm
issi
on
syst
em
3.
PAR
TI
CLE S
WA
RM OPTI
MIZ
ATION (
PSO)
Partic
le
Sw
ar
m
Op
tim
iz
ation
(PSO
)
al
gori
thm
is
an
op
ti
m
iz
at
ion
te
chni
qu
e
within
a
pro
blem
sp
ace
wh
ic
h
ad
op
ts
the
be
hav
i
or
of
bird
s
or
fishe
s
in
find
in
g
f
ood.
I
n
ge
ner
al
,
the
PSO
al
go
rithm
pr
ocess
to
so
lv
e
an
op
ti
m
iz
ation
prob
le
m
can
be
re
pr
ese
nte
d
us
in
g
a
flo
wch
a
rt
s
how
n
in
Fi
gure
5.
The
ste
ps
t
o
f
ind
t
he
op
ti
m
u
m
v
al
ue
u
si
ng the
PS
O
algorit
hm
can be
descr
i
bed as
foll
ow
s:
1.
In
it
ia
li
ze the pa
rtic
le
p
os
it
io
ns ra
ndom
ly
w
ith
in a
pr
ob
le
m
sp
ace.
Evaluation Warning : The document was created with Spire.PDF for Python.
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8708
Op
ti
miz
atio
n o
f t
he
T
hyristor
Con
tr
olled P
hase
Shif
ti
ng
Tr
an
sf
ormer
Usi
ng P
SO Alg
or
i
thm
(
H
adi
Su
y
ono
)
5475
_
=
_
+
(
_
−
_
)
×
(
1
,
_
)
(8)
2.
In
it
ia
li
ze the ve
locit
y of
eac
h partic
le
:
max
=
(
_
−
_
)
(9)
_
=
(
max
−
min
)
×
(
1
,
_
)
+
min
(10)
3.
Evaluate t
he o
bj
ect
iv
e f
unct
ion o
f
eac
h part
ic
le
.
4.
Ca
lc
ulate
the best
posit
ion
/l
oc
at
ion
(
P
best
)
a
nd the
b
e
st gl
obal
p
osi
ti
on
(
G
be
st
).
5.
U
pdat
e
vel
ocity
and
posit
io
n
of
a
pa
rtic
le
,
as
sh
ow
n
in
Equ
at
io
n
(
13
)
an
d
(
14).
In
this
sta
ge,
th
e
acce
le
rati
on
c
oe
ff
ic
ie
nt
c
1
an
d
c
2
being
us
e
d
are
ge
ner
al
ly
within
the
valu
es
of
0
to
4.
A
weig
ht
functi
on
(w),
in
the
ra
nge
of
0.4
to
0.9,
is
al
so
us
e
d
to
con
tr
ol
the
exp
l
or
at
io
n
of
global
an
d
loc
al
par
ti
cl
es.
Th
e
i
m
pr
ovem
ent o
f
the
w
e
i
gh
t
functi
on can
be
done
usi
ng E
quat
ion
(11).
6.
(
t
)
=
(
max
−
min
)
×
(
m
ax
−
(
t
)
m
ax
)
+
min
(11)
id
(
t
+
1
)
=
(
t
)
×
id
(
t
)
+
1
×
1d
(
t
)
×
(
best
id
(
t
)
−
id
(
t
)
)
+
2
×
2d
(
t
)
×
(
bestd
(
t
)
−
id
(
t
)
)
(12)
id
(
t
+
1
)
=
id
(
t
)
+
id
(
t
)
(13)
wh
e
re
t
is
the
i
te
rati
on
ste
p,
V
id
(t)
is
the
current
vel
ocity
of
the
pa
rtic
le
i
in
the
dim
ensi
on
d
at
it
erati
on
ste
p
t
,
V
id
(t
+
1)
is
t
he
vel
ocity
of
the
par
ti
c
le
i
in
the
dim
ensio
n
d
at
it
erati
on
ste
p
t
+
1
,
X
ID
(t)
is
th
e
current posit
io
n
of
pa
rtic
le
i
in
the
dim
ensio
n
d
at
th
e
it
erat
i
on
step
t
,
X
ID
(
t
+
1)
is
th
e p
osi
ti
on
o
f
pa
rtic
le
i
in
di
m
ension
d
at
it
erati
on
t
+
1
,
c
1
is
the
acce
le
rati
on
co
ns
ta
nt
1
(
cogniti
ve
co
nst
ant),
c
2
is
the
acce
le
rati
on
c
onsta
nt
2
(s
ocia
l
con
sta
nt)
,
T
1D
(t)
an
d
T
2D
(t)
are
ra
ndom
nu
m
ber
s
unif
orm
ly
distribu
t
ed
betwee
n
0
an
d
1,
P
bestid
(t)
is
the
local
best
posit
ion
of
pa
rtic
le
i
in
dim
ension
d
at
it
erati
on
t
,
a
nd
G
bestid
(
t)
is t
he
local
bes
t posi
ti
on
of th
e g
lo
bal at i
te
r
at
ion
t
.
7.
Evaluate t
he o
bj
ect
iv
e f
unct
ion val
ue on t
he
n
e
xt it
erati
on.
8.
Determ
ine the
final
of
P
best
an
d
G
best
9.
Evaluate
wh
et
her
t
he
so
l
utio
n
is
opti
m
a
l,
i
f
a
co
nver
gence
has
be
en
a
chieve
d
the
n
it
com
es
to
end,
oth
e
rw
ise
goin
g back
to st
ep 3.
Figure
5. Steps
to follo
w usin
g
the
PSO al
gorithm
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
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:
2088
-
8708
In
t J
Elec
&
C
om
p
En
g,
V
ol.
8
, N
o.
6
,
Dece
m
ber
2
01
8
:
5472
-
5483
5476
The
fl
ow
c
har
t
of
the
PS
O
a
lg
ori
thm
i
m
pl
e
m
entat
ion
is
sh
ow
n
in
Fig
ure
6,
wh
e
reas
the
co
ntro
l
par
am
et
ers
us
e
d
is
giv
e
n
Ta
bl
e 1
.
Figure
6. PS
O soluti
on
Table
1.
T
he
P
SO
c
ontr
ol p
a
r
a
m
et
ers
Para
m
eter
V
alu
e
Nu
m
b
e
r
o
f
Par
ti
cle
50
Maxi
m
u
m
I
te
ratio
n
20
Nu
m
b
e
r
o
f
V
ari
ab
le
3
c
1
an
d
c
2
4
weig
h
t (
w
)
0
,4
r
T
C
SC
m
ax
i
m
u
m
0
,2
X
lin
e
r
T
C
SC
m
in
i
m
u
m
-
0
,7
X
li
n
e
δ
T
C
P
S
T
m
ax
i
m
u
m
5°
δ
T
C
P
S
T
m
in
i
m
u
m
-
5°
Ob
jectiv
e Fun
ctio
n
Min F
=
m
in
P
lo
s
s
4.
RESU
LT
S
AND DI
SCUS
S
ION
In
this
st
ud
y,
the
pro
po
se
d
so
luti
on
has
been
sim
ulate
d
an
d
te
ste
d
us
in
g
30
-
bus
syst
e
m
IEEE
sta
nd
a
rd
data.
The
res
ults
of
the
po
wer
flo
w
a
naly
sis
ha
ve
bee
n
ob
ta
ine
d
f
r
om
so
m
e
scenari
os
incl
uding
t
he
conditi
ons
without
a
ny
in
j
ec
ti
on
of
com
pen
sat
io
n,
t
he
c
onditi
on
with
i
nject
ion
of
opti
m
u
m
capaci
tor
ba
nk
com
pen
sat
ion, and
the c
on
diti
on
with inj
ect
i
on
of
opti
m
u
m
TCPST
-
TCSC
co
m
pen
sat
ion
.
Th
e PSO
alg
ori
thm
i
m
ple
m
entat
io
n
to
determ
ine
the
op
ti
m
u
m
l
ocati
on
a
nd
siz
ing
of
the
com
pensat
ion
us
in
g
the
TCPST
-
TCSC
com
bin
at
ion
has bee
n
com
par
ed
t
o
that usi
ng capacit
or
bank.
In a
dd
it
io
n,
the PS
O
al
gori
thm
p
erf
orm
ance h
as
al
so
been com
par
e
d wit
h
t
he im
ple
m
entat
io
n of A
rtific
ia
l B
ee Colo
ny (A
BC
)
Al
gorithm
[8].
4.1.
IEE
E 30 Bus
Sy
s
tem
Dat
a
The
perf
or
m
ance
of
the
PS
O
al
gorithm
has
been
te
ste
d
us
i
ng
the
30
-
bus
syst
e
m
IEEE
s
ta
nd
a
rd
data
as
f
ollow
s:
B
us
N
u
m
ber
:
30,
Slac
k
bus:
Bu
s
no#1,
Ge
ne
r
at
or
:
Bu
s
no
#
2,
5,
8,
11,
a
nd
13,
T
otal
de
m
and
:
201.4
3
M
W
and
137.8
0
MVAR.
T
he
PS
O
al
gorithm
will
determ
ine
the
best
locat
ion
an
d
siz
in
g
of
the
reacti
ve
power
require
d
i
n
th
e
syst
e
m
by
pe
rfor
m
ing
the
l
oa
d
fl
ow
analy
s
is
for
eac
h
it
er
at
ion
.
The
re
ar
e
fou
r
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
Elec
&
C
om
p
En
g
IS
S
N: 20
88
-
8708
Op
ti
miz
atio
n o
f t
he
T
hyristor
Con
tr
olled P
hase
Shif
ti
ng
Tr
an
sf
ormer
Usi
ng P
SO Alg
or
i
thm
(
H
adi
Su
y
ono
)
5477
(4)
cases
of
t
he
syst
em
that
will
be
pe
rfo
rm
ed
to
sho
w
the
perform
a
nce
of
the
PS
O
al
go
rithm
a
nd
the
i
m
ple
m
ented
of the
co
m
pen
sa
tor de
vices i.e.:
-
Ca
se#1
:
with
out any i
nj
e
ct
io
n of com
pen
sat
ion
,
-
Ca
se#2
:
with i
nj
ect
io
n o
f
c
a
pa
ci
tor bank c
om
pen
sat
ion
-
Ca
se#3
:
with i
nj
ect
io
n TC
PS
T
-
TCSC
c
om
pen
sat
io
n
-
Ca
se#4
:
with
inj
ect
io
n
S
VC
com
pen
sat
ion
by
us
in
g
a
nother
opti
m
iz
a
tio
n
m
et
ho
d
i.e
.
Ar
ti
fici
al
Be
e
Colo
ny (ABC
)
A
lg
ori
thm
[
8].
Fo
r
Ca
se
#2
an
d
#3,
the
l
oad
f
low
a
naly
ses
ha
ve
bee
n
pe
rfo
rm
ed
after
the
determ
inati
on
of
op
ti
m
u
m
locat
ion
a
nd
c
apacit
y
of
reac
ti
ve
power
c
om
pen
sat
ion
re
qu
i
red
in
t
he
s
yst
e
m
us
ing
th
e
PSO
al
go
rith
m
.
In
add
it
io
n,
t
he P
SO
Algorit
hm
is al
so
c
om
par
ed wit
h ABC
a
lgorit
hm
as g
iv
en
in
Case#
4.
4.2.
Results
of
C
ase
#1:
w
ith
out
any in
jecti
on
of
co
m
pens
at
i
on
In
t
his
a
naly
sis,
the
30
-
bus
IEEE
syst
em
has
bee
n
te
s
te
d
un
der
the
co
nd
it
io
n
without
any
com
pen
sat
ing
dev
ic
e.
Ba
se
d
on
the
loa
d
f
low
analy
sis,
the
powe
r
flo
w
as
well
as
po
wer
los
ses
on
each
br
a
nc
h,
an
d
th
e
vo
lt
age
on
each
sys
te
m
b
us
co
uld
be
de
te
rm
ined.
Ne
wton
Ra
phs
on
al
go
rithm
has
bee
n
adopted
to
s
ol
ve
the
loa
d
flo
w
pro
blem
base
d
on
t
he
fo
ll
owin
g
pa
ram
et
ers:
base
powe
r
=
10
0
MVA,
accuracy
=
0.00001,
an
d
m
axim
u
m
it
erati
on
num
ber
=
20.
The
res
ults
of
load
fl
ow
an
al
ysi
s
fo
r
this
case
i
s
sh
ow
n
in
Ta
ble 2
.
Ba
sed
on
Tabl
e
2,
t
otal
act
ive
an
d
reacti
ve
powe
r
ge
ne
rated
wer
e
a
rou
nd
205.4
89
M
W
a
nd
118.4
01
MVAR
res
pecti
vely
.
In
ad
diti
on,
the
total
ac
ti
ve
an
d
reacti
ve
power
losse
s
in
the
syst
em
wer
e
ap
pro
xi
m
at
ely
4.061
M
W
an
d
-
19.
399
MV
AR.
T
her
e
we
re
thre
e
buses
exp
e
rienci
ng
unde
r
vo
lt
age
pro
blem
,
being
lowe
r
than
t
he
al
lowa
ble
m
ini
m
u
m
vo
lt
a
ge,
i.e.
0.
95
p.u.
The
bu
ses
with
volt
age
le
vel
beyo
nd
the
li
m
i
ts
occu
r
re
d
on
bus
#
18, b
us#19,
and
bu
s
#20. T
he
pe
rce
nt
age of
the act
i
ve
po
wer
l
os
se
s is about
2.02% wit
h
re
sp
ect
to
the
act
ive pow
e
r
l
oad.
Table
2.
L
oa
d flo
w
re
su
lt
s Ca
se#
1
Bu
s#
Vo
ltag
e
Load
Gen
eration
|
V
|
(
p
u
)
P (
M
W
)
Q
(M
V
AR)
P (
M
W
)
Q
(M
V
AR)
1
1
0
0
0
2
4
.81
9
-
1
.74
2
2
1
-
0
.33
4
2
1
.7
1
2
.7
6
0
.97
3
0
.37
1
3
0
.98
3
-
1
.35
3
2
.4
1
.2
0
0
4
0
.97
9
-
1
.59
7
7
.6
1
.6
0
0
5
0
.98
3
-
1
.76
7
0
0
0
0
6
0
.97
1
-
2
.05
0
0
0
0
7
0
.96
7
-
2
.49
4
2
2
.8
1
0
.9
0
0
8
0
.95
8
-
2
.53
1
30
30
0
0
9
0
.96
3
-
2
.53
1
0
0
0
0
10
0
.96
-
2
.78
9
5
.9
2
0
0
11
0
.96
3
-
2
.53
1
0
0
0
0
12
0
.97
5
-
1
.34
6
1
1
.2
7
.5
0
0
13
1
1
.7
0
0
37
1
8
.85
5
14
0
.96
2
-
2
.05
5
6
.2
1
.6
0
0
15
0
.96
2
-
1
.89
8
8
.2
2
.5
0
0
16
0
.96
-
2
.26
3
3
.5
1
.8
0
0
17
0
.95
4
-
2
.88
2
9
5
.8
0
0
18
0
.91
4
-
2
.13
3
3
.2
0
.9
0
0
19
0
.88
9
-
2
.02
7
9
.5
34
0
0
20
0
.90
5
-
2
.33
2
.2
0
.7
0
0
21
0
.97
1
-
2
.87
7
1
9
.66
9
1
1
.2
0
0
22
0
.98
-
2
.70
8
0
0
3
1
.59
3
6
.95
4
23
1
-
1
.60
3
3
.2
1
.6
2
2
.2
2
0
.46
3
24
0
.97
5
-
2
.75
2
15
6
.7
0
0
25
0
.98
4
-
2
.01
5
1
0
0
0
26
0
.96
6
-
2
.46
4
3
.5
2
.3
0
0
27
1
-
1
.15
4
0
0
2
8
.91
1
3
.5
28
0
.97
3
-
2
.12
2
0
0
0
0
29
0
.97
6
-
2
.80
8
3
.65
9
0
.9
0
0
30
0
.96
4
-
3
.80
3
12
1
.9
0
0
Total
2
0
1
.428
1
3
7
.8
2
0
5
.489
1
1
8
.401
Total Los
ses
4
.06
1
MW
-
1
9
.39
9
MVAR
% o
f
L
o
ss
es
2
.02
%
MW
-
1
6
.4%
MVAR
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8708
In
t J
Elec
&
C
om
p
En
g,
V
ol.
8
, N
o.
6
,
Dece
m
ber
2
01
8
:
5472
-
5483
5478
4.3.
Results
of
C
ase
#2:
w
ith
inje
ction
of c
apac
itor ba
nk
c
om
pensatio
n
IEEE
sta
nd
a
r
d
syst
e
m
has
be
en
te
ste
d
for
t
he
c
onditi
on
w
it
h
the
placem
ent
of
ca
pacit
or
ba
nk.
T
he
nu
m
ber
of
ca
pa
ci
tor
banks
re
qu
i
red
in
t
he
s
yst
e
m
was
3
locat
ions
with
capaci
ty
value
s
bet
ween
0
up
to
50
MVAR.
T
he
optim
u
m
locat
i
on
a
nd
capaci
t
y
of
capa
ci
tor
b
an
k
us
ed
a
re
sh
ow
n
in
Ta
bl
e
3.
F
ro
m
the
ta
ble
it
can
be
see
n
t
hat
the
res
ulted
locat
io
n
an
d
capaci
ty
of
c
apacit
or
ba
nk
after
opti
m
iz
ation
us
in
g
the
PS
O
al
gorithm
were
12.
5433
M
V
AR
(
0.2
502
p.
u.)
locat
e
d
at
bu
s
#17,
25.
5432
MV
AR
(0.
5105
p.u.)
l
oc
at
ed
at
bu
s
#7
, a
nd
28.
2801 MV
AR
(
0.566
4 p.u.
)
lo
cat
ed
at
bu
s
#3
1.
Table
3.
Ca
pac
it
or
bank o
ptim
iz
at
ion
r
es
ults f
or
Cas
e#
2 us
ing
t
he
P
SO al
gorithm
Co
m
p
en
satio
n
Bu
s No
#
L
o
catio
n
Ratin
g
(
p
.u.)
Ratin
g
(
MVAR
)
Cap
acito
r
Ban
k
17
0
.25
0
2
1
2
.54
3
3
Cap
acito
r
Ban
k
7
0
.51
0
5
2
5
.54
3
2
Cap
acito
r
Ban
k
31
0
.56
6
4
2
8
.28
0
1
Table
4
show
s
the
si
m
ulatio
n
res
ult
of
the
syst
e
m
after
t
he
optim
u
m
place
m
ent
of
the
capaci
tor
banks
with
t
he
m
ini
m
u
m
power
l
os
ses
.
It
c
an
be
see
n
that
the
total
po
we
r
ge
ne
rated
we
re
ar
ound
213.83
M
W
for
act
ive po
w
er and
14
9.91
MVAR fo
r
rea
ct
ive p
owe
r.
T
he
total
acti
ve
and
reacti
ve power
lo
sses fo
r C
ase#
2
wer
e
9.9
01
M
W
an
d 16.00
9 M
VA
R re
sp
ect
ively
. Th
e
re is n
o v
oltage
vio
l
at
ion
for
t
he
C
ase#
2
since al
l
of
bus
vo
lt
age
val
ues
wer
e
i
n
the
r
ang
e
of
0.9
5
p.u.
t
o
1.05
p.u
.
The
volt
age
prof
il
e
f
or
eac
h
bus
is
de
pic
te
d
in
Figure 8. Th
e
vo
lt
age le
vel of buses which e
xp
e
rience
d
un
der
vo
lt
age c
onditi
on in
Ca
se
#
1
h
a
s b
ee
n
ri
sing
to
m
eet
the all
owable v
oltage
level.
Table
4.
L
oa
d flo
w
re
su
lt
s
for
Case#
2
Bu
s#
Vo
ltag
e
Load
Gen
eration
|
V
|
(
p
u
)
P (
M
W
)
Q (
MVAR)
P (
M
W
)
Q (
MVAR)
1
1
0
0
0
2
3
.11
2
-
1
0
.15
6
2
1
-
0
.28
8
2
1
.7
1
2
.7
6
0
.97
6
.64
1
3
0
.99
8
-
1
.52
2
.4
1
.2
0
0
4
0
.99
7
-
1
.81
3
7
.6
1
.6
0
0
5
0
.99
1
-
1
.79
6
0
0
0
0
6
0
.98
7
-
2
.22
4
0
0
0
0
7
0
.98
-
2
.60
2
2
2
.8
1
0
.9
0
0
8
0
.97
4
-
2
.68
30
30
0
0
9
0
.99
7
-
2
.74
3
0
0
0
0
10
0
.98
9
-
3
.01
8
5
.9
2
0
0
11
0
.99
7
-
2
.74
3
0
0
0
0
12
0
.98
9
-
1
.37
3
1
1
.2
7
.5
0
0
13
1
1
.62
8
0
0
37
8
.64
5
14
0
.97
9
-
2
.07
7
6
.2
1
.6
0
0
15
0
.98
2
-
2
.01
5
8
.2
2
.5
0
0
16
0
.98
1
-
2
.40
1
3
.5
1
.8
0
0
17
0
.98
1
-
3
.05
9
9
5
.8
0
0
18
0
.96
9
-
3
.08
3
.2
0
.9
0
0
19
0
.96
5
-
3
.50
3
9
.5
34
0
0
20
0
.97
-
3
.45
2
.2
0
.7
0
0
21
0
.99
4
-
2
.94
4
1
9
.66
9
1
1
.2
0
0
22
1
-
2
.73
0
0
3
1
.59
2
6
.99
8
23
1
-
1
.13
4
3
.2
1
.6
2
2
.2
6
.70
3
24
0
.98
5
-
2
.54
8
15
6
.7
0
0
25
0
.98
8
-
1
.87
1
0
0
0
26
0
.97
-
2
.31
5
3
.5
2
.3
0
0
27
1
-
1
.05
1
0
0
2
8
.91
8
.48
8
28
0
.98
8
-
2
.23
6
0
0
0
0
29
0
.97
6
-
2
.70
5
3
.65
9
0
.9
0
0
30
0
.96
4
-
3
.7
12
1
.9
0
0
Total
2
0
1
.428
1
3
7
.8
2
0
3
.782
4
7
.31
9
Total Los
ses
2
.35
4
MW
-
2
4
.11
4
MVAR
% o
f
L
o
ss
es
1
.17
%
-
1
7
.5%
The
process
i
n
achievi
ng
t
he
m
ini
m
u
m
po
w
er
losse
s
us
i
ng
the
PS
O
al
gor
it
h
m
is
sh
own
in
Fig
ur
e
7.
The
m
ini
m
u
m
power
lo
ss
on
each
it
erati
on
as
the
ob
j
ec
ti
ve
functi
on
has
bee
n
rec
orde
d.
It
is
onl
y
after
reachi
ng
the
c
onve
rg
e
nce
cri
te
ria
that
the
PSO
al
go
rithm
ste
ps
co
uld
be
end
e
d.
T
he
m
axi
m
u
m
i
te
rati
on
s
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
Elec
&
C
om
p
En
g
IS
S
N: 20
88
-
8708
Op
ti
miz
atio
n o
f t
he
T
hyristor
Con
tr
olled P
hase
Shif
ti
ng
Tr
an
sf
ormer
Usi
ng P
SO Alg
or
i
thm
(
H
adi
Su
y
ono
)
5479
perform
ed
for
the
te
st
wer
e
20
it
erati
ons.
B
ased
on
t
he
fi
gure
,
it
al
so
s
howed
t
hat
the
m
ini
m
u
m
act
ive
powe
r
losses ca
n be
r
eached
on t
he 5
th
it
erati
on w
it
h
the
v
al
ue of
2.354 M
W.
Figure
7. The
c
onve
rg
e
nce
c
ri
te
ria for
Ca
se
#2
4.4.
Result
of
Case
#3:
w
ith
injec
t
ion TCSC
-
TC
PST co
mpens
at
i
on
In
this
par
t,
th
e
sta
ndar
d
IE
EE
30
-
bus
syst
e
m
has
bee
n
te
ste
d
in
a
co
nd
it
io
n
with
T
CSC
-
TCP
S
T
bein
g
i
m
ple
m
e
nted
in the s
yst
e
m
. Based
on
the r
es
ults, the o
ptim
u
m
locat
i
on
a
nd
siz
e o
f
t
he
TCSC
-
TCP
ST is
are
show
n
in
Table
5.
The
optim
u
m
place
of
TCSC
was
on
the
li
ne#15
wh
ic
h
was
co
nnect
ed
to
bus
#27
a
nd
bu
s
#29
wit
h
a
rati
ng
of
-
0,5
535
X
line
an
d
li
ne
#31
w
hich
was
co
nn
ect
e
d
t
o
bu
s
#27
a
nd
bu
s#
30
with
the
r
at
ing
of
-
0,5
343
X
li
ne
.
In
a
dd
it
ion
,
the
TCPST
ha
s
al
so
bee
n
im
plem
ented
in
the
li
ne#2
6
w
hich
was
c
onnec
te
d
to
bu
s
#10 a
nd bu
s#
20
with
the i
nj
ect
e
d phase
-
ang
le
of
-
2.6
839°
.
The
sim
ulati
o
n
res
ults
of
t
he
syst
em
after
the
placem
ent
of
TC
SC
and
TC
PST
f
or
the
m
os
t
m
ini
m
u
m
po
w
er
loss
is
s
how
n
in
Ta
ble
6.
It
can
be
seen
t
ha
t
the
total
power
ge
ner
at
e
d
by
the
ge
ne
rator
was
equ
al
to
203.6
02
M
W
an
d
40.
891
M
V
AR
for
act
ive
po
w
er
a
nd
reacti
ve
powe
r
res
pecti
vely
.
The
tota
l
act
ive
and
reacti
ve
powe
r
l
os
ses
for
Ca
se
#3
we
re
2.1
74
M
W
a
nd
-
25.04
1
M
VA
R
res
p
ect
ively
.
T
her
e
w
as
no
vo
lt
age
vi
olati
on
f
or
t
he
Ca
s
e#3
since
t
he
volt
age
of
al
l
buses
wer
e
i
n
th
e
range
of
0.9
5
p.u
.
–
1.0
5
p.u.
Th
e
per
ce
ntage
of t
he powe
r
los
se
s is abo
ut 1.07
% w
it
h res
pect
to
the
acti
ve p
ow
e
r
l
oad.
The
proce
ss
in
achievin
g
the
m
ini
m
u
m
po
w
er
losses
f
or
C
ase#
3
with
TCSC
-
TCPS
T
co
m
pen
sat
ion
us
in
g
t
he
P
SO
al
gorithm
is
giv
en
in
Fig
ur
e
8.
T
he
m
ini
m
um
active
powe
r
los
ses
c
ould
be
reache
d
on
t
he
14
th
it
erati
on
with t
he value
of
2.1
74 M
W.
Figure
8. The
c
onve
rg
e
nce c
ri
te
ria for
Ca
se
#3
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8708
In
t J
Elec
&
C
om
p
En
g,
V
ol.
8
, N
o.
6
,
Dece
m
ber
2
01
8
:
5472
-
5483
5480
Table
5.
TC
SC & TCP
ST
opti
m
iz
at
ion
r
es
ults usi
ng the
PS
O
al
go
rithm
f
or
Case
#3
Co
m
p
en
satio
n
Locatio
n
(L
in
e)
Fro
m
Bu
s
To Bu
s
Ratin
g
TCSC
15
27
29
-
0
,55
3
5
X
lin
e
TCSC
31
27
30
-
0
,53
4
3
X
lin
e
TCPST
26
10
20
-
2
,68
3
9
°
Table
6.
L
oa
d flo
w
re
su
lt
s
for
Case#
3
Bu
s#
Vo
ltag
e
Load
Gen
eration
|
V
|
(
p
u
)
P (
M
W
)
Q (
MVAR)
P (
M
W
)
Q (
MVAR)
1
1
0
0
0
2
2
.93
2
-
8
.16
2
1
-
0
.28
4
2
1
.7
1
2
.7
6
0
.97
5
.87
6
3
0
.99
5
-
1
.46
7
2
.4
1
.2
0
0
4
0
.99
3
-
1
.74
6
7
.6
1
.6
0
0
5
0
.99
3
-
1
.81
0
0
0
0
6
0
.99
1
-
2
.26
9
0
0
0
0
7
0
.98
3
-
2
.63
3
2
2
.8
1
0
.9
0
0
8
0
.98
8
-
2
.88
7
30
30
0
0
9
0
.99
-
2
.75
3
0
0
0
0
10
0
.98
9
-
3
.00
9
5
.9
2
0
0
11
0
.99
-
2
.75
3
0
0
0
0
12
0
.99
3
-
1
.39
3
1
1
.2
7
.5
0
0
13
1
1
.59
7
0
0
37
5
.97
8
14
0
.99
3
-
2
.44
5
6
.2
1
.6
0
0
15
0
.98
9
-
2
.10
9
8
.2
2
.5
0
0
16
0
.98
3
-
2
.39
8
3
.5
1
.8
0
0
17
0
.98
2
-
3
.05
4
9
5
.8
0
0
18
0
.98
3
-
3
.36
6
3
.2
0
.9
0
0
19
0
.98
3
-
3
.90
4
9
.5
34
0
0
20
0
.98
3
-
3
.73
9
2
.2
0
.7
0
0
21
0
.99
4
-
2
.93
1
9
.66
9
1
1
.2
0
0
22
1
-
2
.71
4
0
0
3
1
.59
2
6
.71
2
23
1
-
1
.06
8
3
.2
1
.6
2
2
.2
3
.30
2
24
0
.98
5
-
2
.52
4
15
6
.7
0
0
25
0
.98
8
-
1
.88
4
1
0
0
0
26
0
.97
-
2
.32
9
3
.5
2
.3
0
0
27
1
-
1
.08
8
0
0
2
8
.91
7
.18
3
28
0
.99
3
-
2
.30
3
0
0
0
0
29
0
.97
6
-
2
.74
3
3
.65
9
0
.9
0
0
30
0
.96
4
-
3
.73
8
12
1
.9
0
0
Total
2
0
1
.428
1
3
7
.8
2
0
3
.602
4
0
.89
1
Total Los
ses
2
.17
4
MW
-
2
5
.04
1
MVAR
% o
f
L
o
ss
es
1
.07
%
-
1
8
.2%
4.5. Resul
t of
Ca
se
#4:
wi
th
i
nj
ecti
on
SVC
using Ar
tifici
al
Bee C
olo
n
y (
ABC
) Alg
orit
hm [8]
To
s
how
t
he
pe
rfor
m
ance
of
the
PS
O
al
gorithm
,
the
com
par
iso
n
with
Art
ific
ia
l
Be
e
Colon
y
(
ABC)
Algorithm
[8
]
resu
lt
has
be
en
m
ade.
The
sam
e
si
m
ula
ti
on
us
in
g
IEE
E
30
-
bus
syst
em
as
a
base
-
case data
hav
e
been
m
ade
and
com
par
ed
in
te
r
m
s
of
vo
lt
age
pro
file
and
the
best
act
ive
power
loss
re
ached.
Ba
sed
on
th
e
ABC
al
gorith
m
resu
lt
sh
ow
s
that
the
num
ber
of
S
VCs
r
equ
i
red
i
n
the
syst
e
m
was
two
(
2)
l
ocati
ons
with
capaci
ty
v
al
ues
36.996 M
VAR
at
bus#5 a
nd
36.971 M
VAR
at b
us
#1
9 re
sp
ect
ively
.
The
sim
ulati
on
resu
lt
s
of
the
syst
e
m
after
the
placem
ent
of
SV
C
f
or
t
he
m
os
t
m
ini
m
u
m
power
l
os
s
is
sh
ow
n
in
Ta
ble
7.
It
can
be
seen
that
the
t
otal
powe
r
ge
ne
rated
by
the
ge
ner
at
or
was
e
qu
al
to
204.2
1
M
W
and
48
.
40
MV
AR
f
or
act
ive
powe
r
an
d
rea
ct
ive
powe
r.
T
he
total
act
ive
and
reacti
ve
powe
r
los
ses
ob
ta
ined
for
this
case
w
ere
2.792
7
M
W
a
nd
-
15.
2076
M
VA
R
resp
ect
ively
.
T
her
e
was
no
volt
age
vio
la
ti
on
in
this
case
since
the
vo
lt
age
of
al
l
bu
s
es
we
re
in
t
he
acce
pta
ble
r
ang
e
.
T
he
pe
rc
entage
of
th
e
powe
r
losse
s
is
about
1.37% wit
h
re
s
pect to t
he
act
i
ve powe
r
loa
d.
Table
7.
L
oa
d flo
w
re
su
lt
s
for
Case#
4: w
it
h i
nj
ect
io
n SVC
us
in
g ABC
A
l
gorithm
[
8]
Bu
s#
Vo
ltag
e
Load
Gen
eration
|
V
|
(
p
u
)
P (
M
W
)
Q (
MVAR)
P (
M
W
)
Q (
MVAR)
1
1
0
0
0
.00
2
3
.54
-
5
.64
2
1
-
0
.36
9
2
1
.7
1
2
.70
6
0
.97
1
.60
3
0
.98
8
3
-
1
.53
5
2
.4
1
.20
0
.00
0
.00
4
0
.98
6
-
1
.78
6
7
.6
1
.60
0
.00
0
.00
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
Elec
&
C
om
p
En
g
IS
S
N: 20
88
-
8708
Op
ti
miz
atio
n o
f t
he
T
hyristor
Con
tr
olled P
hase
Shif
ti
ng
Tr
an
sf
ormer
Usi
ng P
SO Alg
or
i
thm
(
H
adi
Su
y
ono
)
5481
Table
7.
L
oa
d flo
w
re
su
lt
s
for
Case#
4: w
it
h i
nj
ect
io
n SVC
us
in
g ABC
A
l
gorithm
[
8]
Bu
s#
Vo
ltag
e
Load
Gen
eration
|
V
|
(
p
u
)
P (
M
W
)
Q (
MVAR)
P (
M
W
)
Q (
MVAR)
5
1
.02
2
3
-
2
.47
2
0
0
.00
0
.00
0
.00
6
0
.98
1
5
-
2
.24
6
0
0
.00
0
.00
0
.00
7
0
.98
8
5
-
2
.84
6
2
2
.8
1
0
.90
0
.00
0
.00
8
0
.96
9
4
-
2
.70
9
30
3
0
.00
0
.00
0
.00
9
0
.97
9
-
2
.82
5
0
0
.00
0
.00
0
.00
10
0
.97
7
6
-
3
.12
9
5
.9
2
.00
0
.00
0
.00
11
0
.97
9
-
2
.82
5
0
0
.00
0
.00
0
.00
12
0
.98
6
-
1
.41
5
1
1
.2
7
.50
0
.00
0
.00
13
1
1
.59
6
6
0
0
.00
3
7
.00
1
0
.95
14
0
.97
7
5
-
2
.14
6
.2
1
.60
0
.00
0
.00
15
0
.98
1
5
-
2
.10
6
8
.2
2
.50
0
.00
0
.00
16
0
.97
4
5
-
2
.47
2
3
.5
1
.80
0
.00
0
.00
17
0
.97
0
8
-
3
.18
1
9
5
.80
0
.00
0
.00
18
0
.97
3
3
-
3
.42
6
3
.2
0
.90
0
.00
0
.00
19
0
.97
2
7
-
3
.99
9
.5
3
4
.00
0
.00
0
.00
20
0
.97
2
7
-
3
.83
4
2
.2
0
.70
0
.00
0
.00
21
0
.97
4
6
-
3
.50
7
1
9
.66
9
1
1
.20
0
.00
0
.00
22
1
-
2
.07
2
0
0
.00
3
1
.59
2
4
.64
23
1
-
0
.96
2
3
.2
1
.60
2
2
.20
6
.94
24
0
.98
4
8
-
2
.15
9
15
6
.70
0
.00
0
.00
25
0
.98
8
-
1
.64
8
1
0
.00
0
.00
0
.00
26
0
.97
-
2
.1
3
.5
2
.30
0
.00
0
.00
27
1
-
0
.92
8
0
0
.00
2
8
.91
9
.92
28
0
.98
3
1
-
2
.29
1
0
0
.00
0
.00
0
.00
29
0
.97
6
2
-
2
.53
1
3
.65
9
0
.90
0
.00
0
.00
30
0
.96
3
7
-
3
.53
8
12
1
.90
0
.00
0
.00
Total
2
0
1
.428
1
3
7
.80
2
0
4
.21
4
8
.40
Total Los
ses
2
.79
2
7
MW
-
1
5
.20
7
6
MVAR
% o
f
L
o
ss
es
1
.37
%
-
3
1
.42
%
4.6. C
ompari
s
on
re
sults
betw
een cases
The
res
ults
of
syst
e
m
si
m
ulatio
n
on
IEEE
30
-
bus
syst
em
with
fou
r
case
s
ha
ve
bee
n
c
om
par
ed
i
n
te
rm
s
of
vo
lt
a
ge
pr
ofi
le
and
t
he
best
act
ive
powe
r
loss
rea
ched
f
or
each
case
by
us
in
g
the
PS
O
al
gorithm
and
ABC
al
gorith
m
[8
]
.
Figure
8
sho
ws
the
volt
age
pro
file
s
com
par
ison.
The
w
orst
volt
age
pro
file
ha
s
been
exp
e
rience
d
in
Ca
se#1
w
he
r
e
the
avail
abili
ty
of
the
reacti
ve
power
w
as
ver
y
lim
it
e
d
de
pendin
g
on
the
gen
e
rati
ng
un
it
. T
her
e a
re t
hr
e
e buses
we
re
be
low
t
he
al
lo
w
able m
ini
m
u
m
vo
lt
age
of
0.9
5 p.u.
Howe
ver,
the
s
upply
of
the
r
eact
ive
powe
r
dep
e
nded
on
the
outp
ut
of
th
e
act
ive
power
loading
f
or
each
unit
.
O
n
the
oth
e
r
ha
nd,
the
vo
lt
age
pr
ofi
le
s
ha
ve
bee
n
im
pr
ov
e
d
i
n
Ca
se#2
a
nd
Ca
se#
3
by
usi
ng
PSO
al
gorithm
and
Ca
se#4
by
usi
ng
ABC
al
gori
thm
,
since
the
reacti
ve
po
wer
so
urces
ha
ve
been
im
ple
m
e
nted
t
o
su
pp
or
t
the
defi
ci
ency
of
the
reacti
ve
powe
r
.
All
of
the
bus
es
vo
lt
age
was
above
0.9
5
p.u.,
si
nce
the
re
act
ive
powe
r
com
pensat
ion
s
re
quire
d
in
the
syst
e
m
wer
e
sat
isfie
d
us
i
ng
ca
pac
it
or
ba
nk
f
or
C
ase#
2,
TCSC
-
TCPST
for
Ca
se
#
3, a
nd S
VC
for
Ca
s
e#4. T
he
Ca
se
#3 sho
wed a
be
tt
er volta
ge pr
of
il
e c
om
par
ed
to
the
o
t
her ca
ses.
Figure
8. V
oltage
prof
il
e c
omparis
on for ea
c
h
case
Evaluation Warning : The document was created with Spire.PDF for Python.