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Science
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.
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Feb
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20
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p
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I
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icit
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d
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m
an
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co
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f
u
lf
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m
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r
eq
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s
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m
w
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tr
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m
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s
[
1
-
3
].
C
o
n
s
tr
u
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f
d
is
tr
ib
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p
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.
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s
to
m
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s
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m
p
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m
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t
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d
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h
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m
b
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an
d
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ca
tio
n
o
f
s
ec
tio
n
alize
r
s
[
11
-
13]
.
T
h
e
r
elo
ca
tio
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o
f
s
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tio
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al
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ca
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b
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s
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p
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p
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b
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m
to
b
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s
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lv
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u
s
i
n
g
ar
ti
f
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in
tel
li
g
en
ce
m
e
th
o
d
s
[
1
4
,
1
5
]
.
I
n
o
r
d
er
to
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m
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o
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
17
,
No
.
2
,
Feb
r
u
ar
y
20
20
:
8
7
7
-
8
8
5
878
r
eliab
ilit
y
in
d
ice
s
o
f
th
e
d
is
t
r
ib
u
tio
n
n
et
w
o
r
k
s
co
n
s
id
er
ed
in
th
is
p
ap
er
,
t
w
o
ar
tif
icial
in
telli
g
en
ce
-
b
ased
m
et
h
o
d
s
h
av
e
b
ee
n
e
x
p
lo
r
ed
,
w
h
ich
w
er
e
th
e
An
t
C
o
lo
n
y
Op
ti
m
izatio
n
(
AC
O)
an
d
Si
m
u
lated
An
n
ea
li
n
g
(
SA
)
m
et
h
o
d
s
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
T
h
e
ad
o
p
ted
m
eth
o
d
to
ac
h
ie
v
e
t
h
e
r
esear
ch
p
u
r
p
o
s
e
w
as
b
ased
o
n
th
e
s
i
m
u
latio
n
o
f
t
h
e
p
r
o
p
o
s
ed
o
p
tim
izatio
n
al
g
o
r
ith
m
s
u
s
i
n
g
th
e
r
ea
l
d
ata
o
f
th
e
o
b
j
e
ct
u
n
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er
co
n
s
id
er
atio
n
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y
tak
in
g
in
to
ac
co
u
n
t
s
o
m
e
s
ce
n
ar
io
s
.
2
.
1
.
Required
Da
t
a
T
h
e
r
eq
u
ir
ed
d
ata
in
clu
d
e
t
h
e
s
in
g
le
-
li
n
e
d
ia
g
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m
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h
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b
s
tatio
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to
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t
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n
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jo
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ee
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er
w
a
s
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n
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ted
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t
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len
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th
e
lo
ad
in
g
d
ata
o
f
t
h
e
p
o
w
er
tr
an
s
f
o
r
m
er
,
s
ec
tio
n
al
izer
s
,
an
d
th
e
p
o
w
er
ca
p
ac
it
y
o
f
th
e
co
n
n
ec
ted
d
is
tr
ib
u
ted
g
en
er
ati
o
n
s
.
2
.
2
.
Ca
lcula
t
io
n o
f
t
he
E
x
is
t
ing
G
rid R
el
ia
bil
it
y
I
n
dices
T
h
e
ca
lcu
latio
n
o
f
r
eliab
ilit
y
in
d
ices
i
n
cl
u
d
es
t
h
e
f
r
eq
u
e
n
c
y
a
n
d
d
u
r
atio
n
o
f
i
n
ter
r
u
p
tio
n
s
at
ea
ch
lo
ad
p
o
in
t
o
f
th
e
P
u
j
o
n
f
ee
d
er
s
y
s
te
m
.
T
h
e
o
v
er
all
S
A
I
FI
an
d
SA
I
DI
v
al
u
es
ar
e
o
b
tain
ed
b
y
s
u
m
m
i
n
g
al
l
th
e
r
eliab
ilit
y
i
n
d
ices v
a
lu
e
s
at
ea
ch
lo
ad
p
o
in
t (
b
u
s
)
.
T
h
e
r
eliab
ilit
y
i
n
d
ices o
f
S
A
I
DI
an
d
SA
I
FI
f
o
r
ea
ch
eq
u
ip
m
en
t c
an
b
e
ca
lcu
lated
u
s
i
n
g
(
1
)
an
d
(
2
).
∑
∑
(
1
)
∑
∑
∑
∑
(
2
)
Usi
n
g
(
1
)
an
d
(
2
)
,
th
e
C
A
I
DI
ca
n
b
e
o
b
tain
ed
u
s
i
n
g
(
3
)
.
(
3
)
2
.
3
.
Ca
lcula
t
io
n o
f
Relia
bil
it
y
I
nd
ices
w
it
h
Co
nn
ec
t
ed
Dis
t
ri
bu
t
ed
G
e
nera
t
io
ns
T
h
e
ca
lcu
latio
n
p
r
o
ce
s
s
o
f
th
e
r
eliab
ilit
y
in
d
ices
a
f
ter
th
e
i
n
tr
o
d
u
ctio
n
o
f
d
is
tr
ib
u
ted
g
e
n
e
r
ato
r
s
in
to
th
e
s
y
s
te
m
f
o
llo
w
s
t
h
e
s
i
m
ila
r
p
r
o
ce
d
u
r
e
o
f
th
at
f
o
r
th
e
e
x
is
ti
n
g
co
n
d
itio
n
s
,
e
x
ce
p
t
th
a
t
th
r
ee
s
ce
n
ar
io
s
h
ad
b
ee
n
co
n
s
id
er
ed
.
T
h
e
f
ir
s
t
s
ce
n
ar
io
w
as
th
e
ad
d
itio
n
o
f
w
i
n
d
tu
r
b
in
e
in
to
th
e
g
r
id
,
t
h
e
s
e
co
n
d
ca
s
e
w
a
s
t
h
e
co
n
n
ec
tio
n
o
f
m
icr
o
h
y
d
r
o
p
o
w
er
p
la
n
t
to
th
e
g
r
id
,
w
h
er
ea
s
in
t
h
e
t
h
ir
d
s
ce
n
ar
io
b
o
th
th
e
w
in
d
tu
r
b
i
n
e
a
n
d
m
icr
o
h
y
d
r
o
p
o
w
er
p
lan
t
s
w
er
e
co
n
n
ec
ted
to
th
e
g
r
id
.
2
.
4
.
Relo
ca
t
io
n o
f
Sect
io
na
lizer
s
Af
t
er
t
he
Co
nn
ec
t
io
n
o
f
Dis
t
ribute
d
G
ener
a
t
io
ns
T
h
e
atte
m
p
ts
to
o
p
ti
m
ize
t
h
e
p
lac
e
m
en
t
an
d
d
i
f
f
er
en
t
n
u
m
b
er
s
o
f
s
ec
tio
n
alize
r
s
as
w
ell
as
t
h
e
ca
lcu
latio
n
o
f
t
h
e
r
elate
d
r
eliab
ilit
y
i
n
d
ices
w
er
e
to
p
er
f
o
r
m
an
d
co
m
p
ar
e
u
s
i
n
g
t
h
e
AC
O
a
n
d
S
A
m
e
th
o
d
s
.
2
.
5
.
Ana
ly
s
is
o
f
Relia
bil
it
y
I
nd
e
x
us
ing
Ant
Co
lo
ny
O
pti
m
iza
t
io
n (
ACO
)
M
et
ho
d
T
h
e
an
al
y
s
i
s
u
s
in
g
t
h
e
AC
O
m
et
h
o
d
s
tar
ts
w
ith
t
h
e
d
eter
m
i
n
atio
n
o
f
t
h
e
A
C
O
p
ar
a
m
eter
s
.
T
h
e
ch
an
g
e
i
n
t
h
e
r
eliab
il
it
y
i
n
d
ex
a
s
w
el
l a
s
th
e
s
ec
tio
n
aliz
er
p
lace
m
en
t
is
i
n
f
l
u
e
n
ce
d
b
y
th
e
u
s
ed
p
ar
a
m
e
ter
s
o
f
th
e
AC
O
m
eth
o
d
.
T
h
e
in
itia
l p
ar
am
eter
s
o
f
A
C
O
to
b
e
u
s
e
d
ar
e
g
iv
en
i
n
T
ab
le
1
.
T
h
e
co
n
v
er
g
e
n
ce
is
to
b
e
ac
h
i
ev
ed
b
ef
o
r
e
th
e
m
a
x
i
m
u
m
ite
r
atio
n
n
u
m
b
er
i
s
r
ea
ch
ed
,
w
h
i
ch
is
1
0
0
.
Hig
h
er
th
e
iter
atio
n
n
u
m
b
er
,
lo
n
g
er
t
h
e
co
m
p
u
ta
tio
n
p
r
o
ce
s
s
to
tak
e.
T
h
e
alp
h
a
v
a
lu
e
c
o
n
tr
o
ls
th
e
s
ize
o
f
p
h
er
o
m
o
n
e.
B
ig
g
er
t
h
e
alp
h
a
v
alu
e,
m
o
r
e
d
i
f
f
icu
l
t
t
h
e
o
p
ti
m
u
m
p
o
i
n
t
to
r
ea
c
h
.
T
h
e
an
ts
n
u
m
b
er
p
ar
a
m
e
ter
r
ep
r
esen
ts
ce
r
tai
n
co
m
b
in
atio
n
o
f
s
ec
tio
n
alize
r
s
p
o
s
itio
n
at
ea
ch
b
u
s
.
E
ac
h
a
n
t
p
as
s
i
n
g
t
h
r
o
u
g
h
ea
c
h
s
ec
to
r
r
ep
r
esen
ts
t
h
e
p
o
s
itio
n
o
f
s
ec
tio
n
alize
r
s
p
lace
m
e
n
t
a
t
ea
c
h
b
u
s
.
Hi
g
h
n
u
m
b
er
o
f
an
t
s
u
s
ed
in
d
icate
s
h
i
g
h
n
u
m
b
er
o
f
b
est
p
ath
ch
o
ice
s
,
as
ea
c
h
an
t
w
il
l
tr
y
to
f
i
n
d
th
e
b
es
t
p
at
h
d
u
r
i
n
g
co
m
p
u
ta
tio
n
p
r
o
ce
s
s
[
10
]
.
T
h
e
n
u
m
b
er
o
f
a
n
ts
to
b
e
u
s
ed
is
4
0
,
to
cr
ea
te
th
e
g
o
o
d
r
an
d
o
m
izin
g
co
n
d
itio
n
.
2
.
6
.
Ana
ly
s
is
o
f
Relia
bil
it
y
I
nd
e
x
us
ing
S
i
m
ula
t
ed
An
nea
lin
g
(
SA)
M
e
t
ho
d
T
h
e
ch
an
g
e
in
t
h
e
r
eliab
ilit
y
in
d
e
x
as
w
ell
as
t
h
e
s
ec
tio
n
alize
r
p
lace
m
en
t
d
ep
en
d
s
o
n
t
h
e
u
s
ed
p
ar
am
eter
s
o
f
t
h
e
S
A
m
et
h
o
d
.
T
h
e
S
A
p
ar
a
m
eter
s
u
s
ed
a
r
e
g
iv
e
n
i
n
T
ab
le
2
.
T
h
e
fin
a
l
s
to
p
temp
era
tu
r
e
r
ep
r
esen
ts
th
e
f
in
a
l
te
m
p
er
at
u
r
e
to
r
ea
ch
d
u
r
in
g
t
h
e
an
n
ea
li
n
g
p
r
o
ce
s
s
.
T
h
e
min
va
lu
e
o
f
fu
n
ctio
n
d
escr
ib
es
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
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n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
E
n
h
a
n
ce
me
n
t o
f th
e
p
o
w
er sys
tem
d
is
tr
ib
u
tio
n
r
elia
b
ilit
y
u
s
i
n
g
a
n
t
co
lo
n
y
o
p
ti
miz
a
tio
n
…
(
Ha
d
i S
u
yo
n
o
)
879
th
e
m
i
n
i
m
u
m
v
al
u
e
a
s
t
h
e
t
ar
g
eted
s
o
lu
tio
n
r
ep
r
ese
n
ti
n
g
th
e
ac
h
ie
v
e
m
en
t
o
f
t
h
e
o
p
ti
m
u
m
f
i
tn
e
s
s
v
al
u
e,
g
iv
in
g
t
h
e
m
i
n
i
m
u
m
v
al
u
es
o
f
S
A
I
DI
an
d
S
A
I
FI.
T
h
e
co
o
lin
g
fa
cto
r
co
r
r
esp
o
n
d
s
to
th
e
r
ate
o
f
te
m
p
er
atu
r
e
d
ec
r
ea
s
e,
an
d
h
as
b
ee
n
s
et
at
0
.
9
5
t
o
p
r
o
d
u
ce
s
lo
w
co
o
lin
g
p
r
o
ce
s
s
an
d
h
i
g
h
n
u
m
b
er
o
f
iter
atio
n
s
f
o
r
co
n
v
er
g
e
n
ce
.
T
h
e
f
it
n
es
s
f
u
n
ct
io
n
u
s
ed
d
u
r
i
n
g
th
e
o
p
ti
m
izati
o
n
p
r
o
ce
s
s
is
g
i
v
e
n
in
(
4
)
[
1
6
-
2
4
]
.
(
4
)
T
ab
le
1
.
P
ar
am
eter
s
u
s
ed
in
O
p
ti
m
izatio
n
u
s
in
g
AC
O
Me
th
o
d
P
a
r
a
me
t
e
r
s
V
a
l
u
e
M
a
x
i
m
u
m
i
t
e
r
a
t
i
o
n
n
u
m
b
e
r
1
0
0
T
h
e
a
n
t
n
u
m
b
e
r
A
l
p
h
a
1
T
ab
le
2
.
P
ar
am
eter
s
u
s
ed
in
O
p
ti
m
izatio
n
u
s
in
g
SA
Me
th
o
d
P
a
r
a
me
t
e
r
s
V
a
l
u
e
F
i
n
a
l
st
o
p
t
e
mp
e
r
a
t
u
r
e
M
i
n
v
a
l
u
e
o
f
f
u
n
c
t
i
o
n
M
a
x
n
u
mb
e
r
o
f
r
e
j
e
c
t
i
o
n
s
1
0
0
M
a
x
n
u
mb
e
r
o
f
r
u
n
s
3
0
0
M
a
x
n
u
mb
e
r
o
f
a
c
c
e
p
t
10
B
o
l
t
z
man
n
c
o
n
st
a
n
t
1
(
d
e
f
a
u
l
t
)
C
o
o
l
i
n
g
f
a
c
t
o
r
0
.
9
5
3.
RE
SU
L
T
S
A
ND
AN
AL
Y
SI
S
T
h
e
d
ata
u
s
ed
in
ca
lcu
lat
io
n
a
n
d
s
i
m
u
la
tio
n
,
as
w
ell
a
s
th
e
r
esu
lt
s
o
f
s
i
m
u
latio
n
f
o
r
v
ar
io
u
s
s
ce
n
ar
io
s
ar
e
g
iv
e
n
as
f
o
llo
w
s
.
3
.
1
.
Da
t
a
o
f
t
he
P
ujo
n F
ee
der
at
Seng
k
a
lin
g
Su
bs
t
a
t
io
n
T
h
e
s
y
s
te
m
co
n
s
id
er
ed
in
t
h
i
s
p
ap
er
is
th
e
P
u
j
o
n
f
ee
d
er
o
f
Sen
g
k
ali
n
g
s
u
b
s
tatio
n
,
lo
ca
t
ed
in
E
a
s
t
J
av
a
p
r
o
v
in
ce
o
f
I
n
d
o
n
es
ia.
T
h
e
Sen
g
k
alin
g
s
u
b
s
tatio
n
i
s
s
u
p
p
lied
f
r
o
m
a
n
o
th
er
Keb
o
n
a
g
u
n
g
s
u
b
s
tatio
n
a
n
d
o
p
er
atin
g
at
t
h
e
r
ec
eiv
i
n
g
v
o
lt
ag
e
o
f
1
5
0
k
V.
T
h
e
P
u
j
o
n
f
ee
d
er
is
o
p
er
atin
g
at
a
m
ed
iu
m
v
o
ltag
e
o
f
2
0
k
V
a
n
d
is
s
u
p
p
lied
u
s
i
n
g
t
h
e
T
r
an
s
f
o
r
m
er
T
h
r
ee
at
t
h
e
Se
n
g
k
ali
n
g
s
u
b
s
ta
tio
n
.
T
h
e
P
u
j
o
n
f
ee
d
e
r
h
as
8
s
ec
tio
n
alize
r
s
lo
ca
ted
o
n
b
u
s
2
,
b
u
s
8
,
b
u
s
1
6
,
b
u
s
4
0
,
b
u
s
4
5
,
b
u
s
6
9
,
b
u
s
7
2
,
an
d
b
u
s
1
0
2
.
T
h
e
ca
lcu
latio
n
o
f
r
eliab
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ased
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1
9
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)
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ap
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licab
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th
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g
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d
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s
ia
[
13
]
,
ar
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w
n
in
T
ab
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3
.
T
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3
.
Data
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5
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1
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8
5
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5
[
2
5
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
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Feb
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ased
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ased
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5
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I
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1
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2
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9
8
6
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3
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2
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s
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r
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r
S
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FI
an
d
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1
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y
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t
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s
talled
to
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w
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FI
an
d
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DI
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at
P
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3
.
4
.
Ca
lcula
t
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n
R
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lt
s
o
f
t
he
Relia
bil
it
y
I
nd
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s
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it
h
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nn
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t
ed
Dis
t
ribute
d
G
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a
t
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n
s
T
h
e
ca
lcu
latio
n
o
f
th
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s
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r
r
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s
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r
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g
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d
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1
7
w
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t
o
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tr
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s
f
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4
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3
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.
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.
T
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lcu
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T
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7
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7
.
T
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
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-
4752
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n
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ch
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u
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est a)
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d
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w
it
h
r
h
o
0
.
1
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2502
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
17
,
No
.
2
,
Feb
r
u
ar
y
20
20
:
8
7
7
-
8
8
5
882
3
.
7
.
Resul
t
s
o
f
Relia
bil
it
y
I
n
dex
us
ing
Si
m
ula
t
ed
An
nea
lin
g
(
SA)
M
et
ho
d
B
ased
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n
th
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S
A
p
ar
a
m
eter
s
g
iv
e
n
i
n
T
ab
le
2
,
th
e
p
r
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s
s
o
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r
m
(
en
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r
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)
[
26
]
,
w
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d
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-
3
,
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ted
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d
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est r
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.
T
ab
le
10
.
T
h
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est R
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T
ab
le
13
.
T
h
e
C
o
m
p
ar
is
o
n
R
e
s
u
lt
s
o
f
AC
O
an
d
SA
Me
th
o
d
s
o
n
th
e
C
o
n
d
itio
n
C
a
s
e
o
f
Gr
id
-
W
in
d
T
u
r
b
in
e
-
Mic
r
o
H
y
d
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o
P
lan
t
S
i
mu
l
a
t
e
d
A
n
n
e
a
l
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n
g
(
S
A
)
me
t
h
o
d
A
n
t
C
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l
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y
O
p
t
i
mi
z
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t
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o
n
(
A
C
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)
me
t
h
o
d
T
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l
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I
F
I
(
i
n
t
e
r
r
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p
t
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n
/
y
e
a
r
)
S
A
I
D
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(
h
o
u
r
s/
y
e
a
r
)
C
A
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D
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(
h
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r
s/
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r
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B
e
st
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A
I
F
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(
i
n
t
e
r
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p
t
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n
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r
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B
e
st
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D
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(
h
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r
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6
9
1
On
t
h
e
s
ce
n
ar
io
o
f
g
r
id
-
m
icr
o
h
y
d
r
o
p
lan
t,
t
h
e
AC
O
m
et
h
o
d
r
esu
lted
i
n
th
e
in
d
ice
s
o
f
r
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s
p
ec
tiv
el
y
4
.
0
1
9
4
in
ter
r
u
p
tio
n
s
/
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ea
r
,
1
2
1
0
0
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h
o
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d
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0
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h
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s
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w
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s
in
g
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S
A
m
eth
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th
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in
d
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4
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ter
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p
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h
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,
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d
3
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7
2
4
h
o
u
r
s
/
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ea
r
,
r
esp
ec
tiv
el
y
.
T
h
e
r
elate
d
r
eliab
ilit
y
in
d
ice
s
o
n
t
h
e
s
ce
n
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r
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w
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d
t
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r
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m
icr
o
h
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m
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ter
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h
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1
h
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r
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y
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b
s
er
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g
th
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co
m
p
u
tat
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ev
o
lu
tio
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cu
r
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it c
a
n
b
e
k
n
o
w
n
th
at
t
h
e
b
etter
r
esu
l
ts
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n
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m
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h
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d
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b
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n
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d
ices
a
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r
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s
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m
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lts
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f
b
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s
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ca
tio
n
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n
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c
h
co
m
p
u
tatio
n
tr
ial.
Ho
w
e
v
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,
an
o
th
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r
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m
ar
k
co
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ce
r
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n
g
co
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p
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tatio
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t
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m
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s
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also
b
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co
n
s
id
er
ed
.
T
h
e
A
C
O
m
et
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d
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m
p
le
m
en
t
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m
u
c
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lo
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A
s
an
ex
a
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p
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in
o
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r
tain
tr
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e
AC
O
co
m
p
u
ta
tio
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last
ed
±
1
7
3
s
ec
o
n
d
s
,
w
h
e
r
ea
s
th
e
S
A
m
et
h
o
d
n
ee
d
ed
j
u
s
t ±
1
3
s
ec
o
n
d
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
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4752
I
n
d
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J
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g
&
C
o
m
p
Sci,
Vo
l.
17
,
No
.
2
,
Feb
r
u
ar
y
20
20
:
8
7
7
-
8
8
5
884
4.
CO
NCLU
SI
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v
id
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at
w
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p
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s
tated
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o
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u
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ch
ap
ter
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lti
m
atel
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lts
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Dis
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ch
ap
ter
,
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co
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p
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tib
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Mo
r
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ca
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to
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ased
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t
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at
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telli
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is
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er
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k
e
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lar
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m
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o
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alize
r
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w
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a
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co
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b
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ti
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in
tell
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ased
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et
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d
s
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.
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NO
WL
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M
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R
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Ser
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A
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Facu
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e
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o
f
w
h
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ar
e
p
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b
lis
h
ed
in
th
is
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d
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P
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R
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Gr
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f
th
is
r
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t
.
RE
F
E
R
E
NC
E
S
[1
]
K.
Je
n
n
e
tt
,
e
t
a
l.
,
"
An
a
lys
is
o
f
t
h
e
sy
mp
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ti
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trip
p
in
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p
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two
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Distrib
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n
e
ra
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in
P
ro
c
.
2
0
1
1
I
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te
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a
ti
o
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Co
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A
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P
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S
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l.
1
,
p
p
.
3
8
4
-
3
8
9
,
2
0
1
1
.
[2
]
H.
S
u
y
o
n
o
,
e
t
a
l.
,
"
P
o
w
e
r
s
y
ste
m
o
p
ti
m
iza
ti
o
n
o
f
S
tatic
V
A
R
C
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m
p
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sa
to
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u
sin
g
No
v
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l
G
lo
b
a
l
Ha
r
m
o
n
y
S
e
a
rc
h
M
e
th
o
d
,
"
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
El
e
c
tro
n
ic
En
g
i
n
e
e
rin
g
&
T
e
lec
o
mm
u
n
ica
t
io
n
s
(
IJ
EE
ET
)
,
v
o
l.
8
(
1
)
,
p
p
.
2
6
-
3
2
,
2
0
1
9
.
[3
]
K.
M
a
,
e
t
a
l.
,
"
En
e
rg
y
m
a
n
a
g
e
m
e
n
t
c
o
n
sid
e
ri
n
g
u
n
k
n
o
w
n
d
y
n
a
m
ic
s
b
a
se
d
o
n
Ex
trem
u
m
S
e
e
k
i
n
g
Co
n
tr
o
l
a
nd
P
a
rti
c
le S
w
a
rm
Op
ti
m
iza
ti
o
n
,
"
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
C
o
n
tr
o
l
S
y
ste
ms
T
e
c
h
n
o
l
o
g
y
(
Ea
rly
Acc
e
ss
)
,
2
0
1
9
.
[4
]
W
.
Ch
a
e
,
e
t
a
l.
,
"
Op
ti
ma
l
in
ter
c
o
n
n
e
c
ti
o
n
d
e
v
ice
fo
r
d
istrib
u
te
d
e
n
e
rg
y
re
so
u
rc
e
s
o
f
c
u
sto
me
r
,"
in
P
r
o
c
e
e
d
in
g
s
o
f
2
0
1
2
3
rd
I
EE
E
I
n
ter
n
a
ti
o
n
a
l
S
y
m
p
o
siu
m
o
n
P
o
w
e
r
El
e
c
tro
n
ic
s
f
o
r
Distrib
u
ted
G
e
n
e
ra
ti
o
n
S
y
ste
m
s
(P
EDG
),
p
p
.
8
7
8
-
8
8
2
,
2
0
1
2
.
[5
]
W
.
L
.
M
in
g
a
n
d
L
.
Ju
n
,
"
S
tu
d
y
o
n
lo
ss
a
ll
o
c
a
ti
o
n
o
f
p
o
we
r
d
istrib
u
ti
o
n
n
e
tw
o
rk
wit
h
d
istrib
u
ted
g
e
n
e
ra
ti
o
n
,"
i
n
P
r
o
c
e
e
d
in
g
s
o
f
T
h
e
2
n
d
In
ter
n
a
ti
o
n
a
l
S
y
m
p
o
siu
m
o
n
P
o
w
e
r
El
e
c
tro
n
ics
f
o
r
Distrib
u
ted
G
e
n
e
ra
ti
o
n
S
y
ste
m
s,
p
p
.
6
7
8
-
6
8
0
,
2
0
1
0
.
[6
]
M
.
N.
Hid
a
y
a
t
a
n
d
F
.
L
i,
"
I
m
p
a
c
t
o
f
Distrib
u
ted
G
e
n
e
ra
ti
o
n
tec
h
n
o
l
o
g
ies
o
n
g
e
n
e
ra
ti
o
n
c
u
r
tailm
e
n
t,
"
in
2
0
1
3
IEE
E
Po
we
r
&
En
e
rg
y
S
o
c
iety
Ge
n
e
ra
l
M
e
e
ti
n
g
,
p
p
.
1
-
5
,
2
0
1
3
.
[7
]
Z.
J
un
-
f
a
n
g
,
e
t
a
l.
,
"
Res
e
a
rc
h
o
n
d
istrib
u
t
e
d
g
e
n
e
ra
ti
o
n
so
u
rc
e
p
l
a
c
e
me
n
t
,"
in
P
r
o
c
e
e
d
in
g
s
o
f
2
0
0
9
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
S
u
sta
in
a
b
le
P
o
w
e
r
G
e
n
e
ra
ti
o
n
a
n
d
S
u
p
p
ly
,
p
p
.
1
-
4
,
2
0
0
9
.
[8
]
W
.
Jia
n
a
n
d
C.
Do
n
g
y
in
g
,
"
Distr
ib
u
te
d
c
o
n
t
ro
l
o
f
p
o
we
r
g
e
n
e
ra
ti
o
n
sy
ste
m
,"
in
P
ro
c
e
e
d
i
n
g
s
o
f
2
0
1
2
In
ter
n
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
Co
m
p
u
ter Distri
b
u
ted
Co
n
tro
l
a
n
d
In
telli
g
e
n
t
En
v
iro
n
m
e
n
tal
M
o
n
it
o
rin
g
,
p
p
.
2
5
3
-
2
5
6
,
2
0
1
2
.
[9
]
G
.
Ch
e
n
,
e
t
a
l.
,
"
Di
strib
u
ted
o
p
ti
m
a
l
a
c
ti
v
e
p
o
w
e
r
c
o
n
tro
l
o
f
m
u
lt
ip
le
g
e
n
e
ra
ti
o
n
s
y
ste
m
s,"
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
I
n
d
u
stria
l
El
e
c
tro
n
ics
,
v
o
l
.
6
2
(
11
),
p
p
.
7
0
7
9
-
7
0
9
0
,
2
0
1
5
.
[1
0
]
K.I.
Je
n
n
e
tt
,
e
t
a
l.
,
"
In
v
e
stig
a
ti
o
n
o
f
th
e
s
y
m
p
a
th
e
ti
c
tri
p
p
in
g
p
r
o
b
lem
in
p
o
w
e
r
s
y
ste
m
s
w
it
h
larg
e
p
e
n
e
tratio
n
s
o
f
d
istr
ib
u
ted
g
e
n
e
ra
ti
o
n
,
"
IET
Ge
n
e
ra
ti
o
n
,
T
r
a
n
sm
issio
n
a
n
d
Distrib
u
ti
o
n
v
o
l
.
9
(
4
),
p
p
.
3
7
9
-
3
8
5
,
2
0
1
5
.
[1
1
]
M
.
L
w
in
,
e
t
a
l.
,
"
P
r
o
tec
ti
v
e
d
e
v
ice
a
n
d
sw
it
c
h
a
ll
o
c
a
ti
o
n
f
o
r
re
li
a
b
il
it
y
o
p
ti
m
iza
ti
o
n
w
it
h
d
istri
b
u
t
e
d
g
e
n
e
ra
to
rs,"
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
S
u
sta
i
n
a
b
l
e
En
e
rg
y
,
v
o
l.
1
0
(
1
)
,
p
p
.
4
4
9
-
4
5
8
,
2
0
1
9
.
[1
2
]
H.
G
h
o
re
ish
i,
"
Op
ti
ma
l
p
l
a
c
e
me
n
t
o
f
t
ie
p
o
in
ts
a
n
d
se
c
ti
o
n
a
li
ze
rs
i
n
ra
d
ia
l
d
istri
b
u
ti
o
n
n
e
tw
o
rk
in
p
re
se
n
c
e
o
f
DG
s
c
o
n
sid
e
rin
g
l
o
a
d
sig
n
if
ic
a
n
c
e
,"
in
P
ro
c
e
e
d
in
g
s o
f
2
0
1
3
S
m
a
rt
G
rid
Co
n
f
e
re
n
c
e
(S
G
C),
p
p
.
1
6
0
-
1
6
5
,
2
0
1
3
.
[1
3
]
P
T
.
P
L
N
(In
d
o
n
e
sia
n
Na
ti
o
n
a
l
El
e
c
tri
c
it
y
Co
m
p
a
n
y
).
S
P
L
N
5
9
:
R
e
li
a
b
il
it
y
o
f
2
0
k
V
a
n
d
6
k
V
Distri
b
u
ti
o
n
S
y
ste
m
.
Ja
k
a
rta:
M
in
istry
o
f
M
in
e
s an
d
E
n
e
rg
y
,
1
9
8
5
.
[1
4
]
M
.
K.M
.
Zam
a
n
i,
e
t
a
l.
,
"
Op
ti
m
a
l
S
V
C
a
ll
o
c
a
ti
o
n
v
ia
sy
m
b
io
ti
c
o
rg
a
n
ism
s
se
a
r
c
h
f
o
r
v
o
lt
a
g
e
se
c
u
rit
y
im
p
ro
v
e
m
e
n
t,
"
T
E
L
KO
M
NIK
A
(T
e
le
c
o
m
m
u
n
ica
ti
o
n
,
Co
m
p
u
ti
n
g
,
El
e
c
tro
n
ics
a
n
d
Co
n
tro
l)
,
v
o
l.
17(
3
)
,
p
p
.
1
2
6
7
-
1
2
7
4
,
2
0
1
9
.
[1
5
]
H.
S
u
y
o
n
o
,
e
t
a
l
.
,
"
Op
ti
m
iza
ti
o
n
o
f
th
e
th
y
risto
r
c
o
n
tro
ll
e
d
p
h
a
se
sh
if
ti
n
g
tran
sf
o
r
m
e
r
u
sin
g
P
S
O
a
lg
o
rit
h
m
,
"
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
E
lec
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
8
(
6
)
,
p
p
.
5
4
7
2
-
5
4
8
3
,
2
0
1
8
.
[1
6
]
F
.
M
.
A
lh
a
d
d
a
d
a
n
d
M
.
El
-
Ha
w
a
ry
,
"
Op
ti
ma
l
Fi
lt
e
r
Pl
a
c
e
me
n
t
a
n
d
S
izin
g
Us
in
g
An
t
C
o
lo
n
y
Op
ti
miza
ti
o
n
i
n
El
e
c
trica
l
Distrib
u
ti
o
n
S
y
ste
m
,
"
in
P
r
o
c
e
e
d
in
g
2
0
1
4
IEE
E
El
e
c
tri
c
a
l
P
o
w
e
r
a
n
d
En
e
rg
y
Co
n
f
e
r
e
n
c
e
,
p
p
.
1
2
8
-
1
3
3
,
2
0
1
4
.
[1
7
]
M
.
G
e
n
,
e
t
a
l.
,
“
Ne
tw
o
rk
M
o
d
e
ls
a
n
d
O
p
ti
m
iza
ti
o
n
:
M
u
l
ti
o
b
jec
t
iv
e
Ge
n
e
ti
c
A
l
g
o
rit
h
m
A
p
p
ro
a
c
h
”
.
Ne
w
Yo
rk
:
S
p
rin
g
e
r
-
Ver
la
g
,
2
0
0
8
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
E
n
h
a
n
ce
me
n
t o
f th
e
p
o
w
er sys
tem
d
is
tr
ib
u
tio
n
r
elia
b
ilit
y
u
s
i
n
g
a
n
t
co
lo
n
y
o
p
ti
miz
a
tio
n
…
(
Ha
d
i S
u
yo
n
o
)
885
[1
8
]
R.
Ja
n
g
ra
a
n
d
R.
Ra
m
e
sh
Ka
it
,
"
An
a
lys
is
a
n
d
c
o
mp
a
riso
n
a
m
o
n
g
An
t
S
y
ste
m;
An
t
C
o
lo
n
y
S
y
ste
m
a
n
d
M
a
x
-
M
in
An
t
S
y
ste
m
wit
h
d
if
fer
e
n
t
p
a
ra
me
ter
s
se
tt
in
g
,"
in
P
ro
c
e
e
d
i
n
g
s
o
f
2
0
1
7
3
rd
In
ter
n
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
Co
m
p
u
tatio
n
a
l
In
telli
g
e
n
c
e
&
Co
m
m
u
n
ica
ti
o
n
T
e
c
h
n
o
l
o
g
y
(CIC
T
),
p
p
.
1
-
4
,
2
0
1
7
.
[1
9
]
G
.
P
i
n
g
,
e
t
a
l.
,
"
Ad
a
p
ti
v
e
a
n
t
c
o
l
o
n
y
o
p
ti
miz
a
ti
o
n
a
lg
o
rit
h
m
,"
in
P
ro
c
e
e
d
in
g
s
o
f
2
0
1
4
In
ter
n
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
M
e
c
h
a
tro
n
ics
a
n
d
Co
n
tr
o
l
(ICM
C
),
p
p
.
9
5
-
9
8
,
2
0
1
4
.
[2
0
]
R.
A
.
Zein
El
d
in
.
,
"
An
im
p
ro
v
e
d
si
mu
la
ted
a
n
n
e
a
li
n
g
a
p
p
ro
a
c
h
f
o
r
so
lvin
g
th
e
c
o
n
stra
in
e
d
o
p
ti
mi
za
t
io
n
p
ro
b
lem
s
,"
in
P
ro
c
e
e
d
i
n
g
s
o
f
2
0
1
2
8
th
In
tern
a
t
io
n
a
l
C
o
n
f
e
re
n
c
e
o
n
In
f
o
rm
a
ti
c
s
a
n
d
S
y
st
e
m
s
(INFOS
),
p
p
.
BIO
-
27
-
BIO
-
3
1
,
2
0
1
2
.
[2
1
]
Z.
S
h
a
n
,
e
t
a
l.
,
"
Rea
c
ti
v
e
p
o
we
r
o
p
t
imiza
ti
o
n
o
f
d
istri
b
u
ti
o
n
n
e
two
rk
b
a
se
d
o
n
GA
wit
h
simu
la
ted
a
n
n
e
a
l
in
g
se
lec
ti
o
n
,"
in
P
r
o
c
e
e
d
in
g
s
o
f
2
0
1
1
6
th
I
n
tern
a
ti
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
C
o
m
p
u
ter
S
c
ien
c
e
&
Ed
u
c
a
ti
o
n
(ICCS
E),
p
p
.
1
0
5
4
-
1
0
5
7
,
2
0
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