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Lin
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co
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c
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5
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m
e
d
ev
elo
p
m
en
t
i
n
h
ig
h
i
m
p
ed
a
n
ce
f
au
lt
d
etec
tio
n
,
u
s
i
n
g
m
at
h
e
m
atica
l
m
o
d
el
a
n
d
p
o
w
er
lin
e
co
m
m
u
n
icatio
n
ap
p
r
o
ac
h
f
o
r
im
p
r
o
v
ed
n
et
w
o
r
k
s
s
a
f
et
y
[
8
]
.
Nev
er
th
ele
s
s
,
t
h
e
h
i
g
h
co
m
p
u
tatio
n
al
r
ig
o
u
r
o
f
th
ese
ap
p
r
o
ac
h
es
n
ec
es
s
itated
an
i
m
p
r
o
v
ed
s
o
f
t
co
m
p
u
tatio
n
al
in
te
llig
e
n
t
(
S
C
I
)
ap
p
r
o
ac
h
es
f
o
r
n
et
w
o
r
k
p
r
o
tectio
n
an
al
y
s
es
w
it
h
u
s
in
g
ad
v
an
ce
d
d
i
g
ital
s
ig
n
a
l
p
r
o
ce
s
s
i
n
g
(
DSP
)
in
co
m
b
in
at
io
n
w
i
th
S
u
p
p
o
r
t
Vec
to
r
Ma
ch
in
e
(
SVM)
alg
o
r
ith
m
f
o
r
ea
s
e
o
f
co
m
p
u
ta
tio
n
a
n
d
ac
cu
r
ac
y
.
T
h
e
cr
o
s
s
-
co
u
n
tr
y
ea
r
t
h
f
au
l
t
id
en
ti
f
icati
o
n
o
n
d
i
f
f
er
en
t
T
L
p
h
ases
i
n
s
a
m
e
cir
cu
it
u
s
in
g
o
n
e
en
d
s
i
g
n
al
s
tatis
t
ical
d
ev
i
atio
n
d
ata
f
o
r
t
h
e
tr
ai
n
in
g
o
f
an
ar
ti
f
icial
n
e
u
r
o
n
et
w
o
r
k
(
A
NN)
d
etec
tio
n
m
o
d
el
[
9
]
.
I
n
ad
d
itio
n
,
DSP
an
d
d
escr
ete
w
av
e
let
tr
an
s
f
o
r
m
(
DW
T
)
an
al
y
s
i
s
o
f
f
au
lt
s
i
g
n
als
w
av
e
f
o
r
m
s
r
ec
o
r
d
s
at
m
o
n
ito
r
in
g
lo
ca
tio
n
o
f
a
m
u
lti
-
b
u
s
m
es
h
ed
n
et
w
o
r
k
f
o
r
u
s
e
f
u
l
f
ea
t
u
r
e
in
f
o
r
m
atio
n
g
ath
er
i
n
g
ad
o
p
ted
to
d
etec
t
an
d
class
if
y
f
a
u
lts
[
1
0
]
.
P
r
o
t
ec
tio
n
f
au
lt
an
a
l
y
s
is
s
ch
e
m
e
o
n
a
s
er
ies
an
d
s
h
u
n
t
co
m
p
e
n
s
ated
T
L
o
n
th
i
s
n
et
w
o
r
k
to
p
o
lo
g
y
u
s
i
n
g
h
al
f
-
c
y
c
le
p
o
s
t
-
f
a
u
lt
c
u
r
r
en
t
s
i
g
n
al
f
o
r
ANN
tr
ain
i
n
g
[
1
1
-
1
2]
.
Oth
er
h
y
b
r
id
n
et
w
o
r
k
to
p
o
lo
g
y
p
r
o
tectio
n
s
ch
e
m
e
ap
p
r
o
ac
h
f
o
r
f
a
u
lt
id
en
ti
f
ica
tio
n
,
class
i
f
icatio
n
,
an
d
lo
ca
tio
n
i
n
co
m
b
i
n
ed
o
v
er
h
ea
d
T
L
an
d
u
n
d
er
g
r
o
u
n
d
ca
b
les
n
et
w
o
r
k
to
p
o
lo
g
y
u
s
i
n
g
h
y
b
r
id
A
N
N
-
Fu
zz
y
lo
g
ic
[
1
3
]
.
T
h
e
r
o
b
u
s
tn
es
s
co
u
ld
n
o
t
b
e
g
u
a
r
an
teed
d
u
e
to
f
e
w
n
u
m
b
er
s
o
f
f
a
u
lt
s
s
ce
n
ar
io
s
i
m
u
lated
in
t
h
ese
r
esear
ch
w
o
r
k
.
T
h
ese
r
ev
ie
w
ed
liter
at
u
r
es
h
a
v
e
n
o
t
p
r
ese
n
ted
m
u
c
h
w
o
r
k
s
i
n
th
e
n
e
w
f
r
o
n
tier
o
f
R
GE
S
in
te
g
r
atio
n
o
n
T
L
p
r
o
tectio
n
s
ch
e
m
e
d
e
v
elo
p
m
e
n
t
as
o
n
e
ch
alle
n
g
e
an
d
li
m
ited
to
f
e
w
s
ce
n
er
io
s
s
tu
d
ies a
s
m
o
ti
v
ati
n
g
f
ac
to
r
s
f
o
r
th
i
s
r
esear
ch
.
T
h
ese
n
ec
ess
itated
th
e
n
ee
d
f
o
r
th
e
d
esig
n
o
f
a
h
i
g
h
-
s
p
ee
d
,
lo
w
co
s
t
an
d
r
eliab
le
u
n
i
t
p
r
o
tectio
n
s
ch
e
m
e
m
o
d
el
d
e
v
elo
p
m
e
n
t
f
o
r
an
i
n
te
g
r
ated
W
FG
-
T
L
p
r
o
tectio
n
s
c
h
e
m
e
w
it
h
d
etail
co
m
p
ar
ativ
e
ass
es
s
m
en
t
s
t
u
d
y
o
f
Di
s
cr
ete
W
av
elet
Mu
ltire
s
o
lu
tio
n
An
al
y
s
i
s
(
DW
MR
A
)
o
f
o
n
e
-
c
y
cle
d
u
r
in
g
-
f
a
u
lts
s
ig
n
al
s
(
v
o
ltag
e
a
n
d
cu
r
r
en
t)
s
ig
n
at
u
r
es
f
r
o
m
t
w
o
T
L
n
et
w
o
r
k
to
p
o
lo
g
ies
w
i
th
a
n
d
w
it
h
o
u
t
W
F
G
in
te
g
r
atio
n
a
s
ca
s
e
s
tu
d
y
.
T
h
e
ar
ticle
o
r
g
an
ized
w
ith
t
h
e
in
tr
o
d
u
ctio
n
s
ec
tio
n
ill
u
s
t
r
atin
g
th
e
ca
p
ar
ativ
e
ad
v
an
ta
g
es
o
f
th
e
R
GE
S
a
g
ain
s
t
t
h
e
tr
ad
itio
n
a
ll
y
ex
is
ti
n
g
en
er
g
y
g
en
er
atio
n
s
o
u
r
ce
s
w
i
th
r
esp
ec
t
to
c
o
s
t,
en
v
ir
o
n
m
e
n
tal
ass
es
s
m
en
t
s
e
f
f
ec
ts
a
n
d
n
eg
at
i
v
e
i
m
p
ac
ts
o
n
e
x
is
t
in
g
p
r
o
tect
io
n
s
s
ch
e
m
e
e
f
f
ec
ti
v
en
e
s
s
.
M
eth
o
d
o
lo
g
y
s
ec
tio
n
d
iv
u
l
g
es
t
h
e
p
r
o
p
o
s
ed
s
o
f
t
co
m
p
u
tat
io
n
al
ap
p
r
o
ac
h
w
it
h
t
h
e
ap
p
licatio
n
o
f
DW
MR
A
.
T
h
i
s
is
f
o
llo
w
ed
b
y
th
e
r
esu
lt a
n
d
d
is
cu
s
s
io
n
s
ec
tio
n
a
n
d
f
i
n
all
y
,
th
e
i
m
p
licatio
n
o
f
t
h
e
r
esu
l
t e
x
p
r
ess
ed
i
n
th
e
C
o
n
clu
s
io
n
s
ec
tio
n
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
Th
e
C
I
ap
p
r
o
ac
h
f
o
r
d
ev
elo
p
in
g
an
i
m
p
r
o
v
e
p
r
o
tectio
n
c
la
s
s
i
f
ier
m
o
d
el
th
at
co
u
ld
b
e
a
d
o
p
ted
f
o
r
f
au
lt
t
y
p
es
id
en
ti
f
icat
io
n
an
d
class
if
icia
tio
n
in
T
L
p
r
o
t
ec
tio
n
r
ela
y
.
T
h
is
w
ill
h
elp
in
p
r
ev
en
t
i
n
g
an
d
eli
m
i
n
at
i
n
g
f
a
u
lt
s
as f
a
s
t a
s
p
o
s
s
ib
le
w
it
h
h
i
g
h
p
r
ec
is
io
n
,
s
el
ec
tiv
it
y
,
an
d
r
eliab
ilit
y
2
.
1
.
P
ro
po
s
e
Unit
P
ro
t
ec
t
io
n Cla
s
s
if
ier
M
o
del
T
h
is
r
esear
ch
p
r
o
p
o
s
ed
a
Ma
tlab
Si
m
u
li
n
k
m
o
d
el
o
f
a
t
w
o
-
e
n
d
p
o
w
er
g
e
n
er
atio
n
s
o
u
r
ce
s
o
f
1
3
2
k
V,
5
0
Hz,
2
0
0
k
m
T
L
w
it
h
i
n
te
g
r
ated
9
MW
R
GE
S
-
W
FG
h
a
v
i
n
g
s
i
x
u
n
it
s
o
f
1
.
5
MW
o
n
th
e
co
m
m
o
n
s
y
s
te
m
b
u
s
o
f
Fi
g
u
r
e
1
(
a)
.
Sim
u
latio
n
s
s
ce
n
ar
io
s
o
f
1
1
f
a
u
lts
t
y
p
e
s
(
A
G,
B
G,
C
G,
A
B
G,
B
C
G,
AC
G,
A
B
C
G,
A
B
,
B
C
,
A
C
,
A
B
C
)
w
h
er
e
ex
ec
u
t
ed
ac
r
o
s
s
th
e
en
tire
tr
an
s
m
is
s
i
o
n
li
n
es
a
t
s
e
lecte
d
f
a
u
lt
lo
ca
t
io
n
s
(
5
,
2
5
,
4
5
,
6
5
,
8
5
,
1
0
5
,
1
2
5
,
1
6
5
,
an
d
1
8
5
k
m
)
,
an
d
f
a
u
lt
i
n
ce
p
tio
n
an
g
els
(
0
,
an
d
9
0
0
)
.
T
h
e
s
a
m
p
li
n
g
f
r
eq
u
en
c
y
o
f
5
0
k
Hz
ad
o
p
ted
f
o
r
o
n
e
en
d
s
o
u
r
ce
f
a
u
lt
s
i
g
n
a
l
ex
tr
ac
tio
n
o
f
v
o
lta
g
e
an
d
cu
r
r
en
ts
to
eli
m
i
n
ate
aliasin
g
ef
f
ec
t.
Fi
g
u
r
e
2
(
b
)
d
is
p
lay
ed
t
h
e
ex
tr
ac
ted
f
au
lt
s
i
g
n
al
s
a
m
p
les
f
r
o
m
p
h
a
s
e
A
s
i
n
g
le
l
in
e
-
to
-
g
r
o
u
n
d
(
S
L
G)
f
a
u
lt
at
5
k
m
b
ef
o
r
e
p
r
ep
r
o
ce
s
s
in
g
.
200
KM
,
135
kV
,
50
H
z
H
V
T
L
SO
U
R
CE
1
SO
U
R
CE
2
9
MW
,
W
FG
(
a)
(
b
)
Fig
u
r
e
1
.
(
a)
I
n
teg
r
ated
W
FG
-
R
GE
S o
n
HVT
L
(
b
)
E
x
tr
ac
ted
f
au
l
t v
o
lta
g
e
an
d
cu
r
r
e
n
t si
g
n
als
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
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2
5
0
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I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
12
,
No
.
1
,
Octo
b
er
2
0
1
8
:
2
4
6
–
253
248
T
h
e
s
ig
n
al
is
p
r
ep
r
o
ce
s
s
ed
b
y
p
ass
in
g
t
h
e
m
t
h
r
o
u
g
h
t
w
o
s
e
t
ca
s
ca
d
ed
b
an
d
s
f
il
ter
s
.
T
h
e
d
is
p
la
y
ed
MR
A
f
i
lter
ar
ch
itect
u
r
e
o
f
Fi
g
u
r
e
2
is
m
ad
e
u
p
o
f
lo
w
p
ass
f
ilter
h
(
k
)
(
L
P
F)
an
d
h
ig
h
p
ass
f
ilter
s
g
(
k
)
(
HP
F)
f
o
r
s
ig
n
al
d
ec
o
m
p
o
s
itio
n
u
s
in
g
DW
MR
A
o
f
e
x
tr
ac
tes
o
n
e
-
c
y
cle
n
o
i
s
y
f
au
lt
tr
an
s
ien
t
s
i
g
n
als
o
f
v
o
lta
g
e
an
d
cu
r
r
en
t
s
i
g
n
at
u
r
es
f
r
o
m
t
w
o
p
r
o
p
o
s
e
n
et
w
o
r
k
s
to
p
o
lo
g
ies
(
w
it
h
,
a
n
d
w
it
h
o
u
t
in
teg
r
ated
R
GE
S
-
W
FG)
.
T
h
e
L
P
F
is
r
ea
li
s
ed
b
y
th
e
s
ca
li
n
g
f
u
n
ctio
n
(
ɸ)
o
f
E
q
u
e
tio
n
1
,
t
h
e
HP
F
is
ac
t
u
alize
d
w
it
h
t
h
e
ap
p
licatio
n
o
f
th
e
m
o
th
er
w
a
v
elet
f
u
n
ctio
n
(
Ψ
)
o
f
E
q
u
atio
n
2
.
(
)
=
2
(
)
(
2
-
)
n
k
h
n
k
n
(
1
)
(
)
=
2
(
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Fig
u
r
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h
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DWM
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jj
n
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3.
RE
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CA
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g
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3
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1
.
G
ro
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2
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(
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Fig
u
r
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3
.
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s
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w
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(
b
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w
ith
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FG i
n
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Fig
u
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4
.
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r
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t
s
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(
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w
ith
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b
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5
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T
h
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th
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p
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Gr
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d
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A
B
C
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f
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6
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Evaluation Warning : The document was created with Spire.PDF for Python.
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4752
F
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xtra
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ted
Tr
a
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s
mis
s
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Lin
e
To
p
o
lo
g
y
(
Osa
ji E
mma
n
u
el
)
253
RE
F
E
R
E
NC
E
S
[
1]
P
a
li
w
a
l
P
,
P
a
t
id
a
r
N
P
,
Ne
m
a
R
K.
"
P
lan
n
i
n
g
o
f
g
rid
in
teg
ra
ted
d
istri
b
u
ted
g
e
n
e
ra
to
rs:
A
re
v
ie
w
o
f
tec
h
n
o
l
o
g
y
,
o
b
jec
ti
v
e
s an
d
tec
h
n
iq
u
e
s
"
.
Ren
e
w
S
u
st
a
in
En
e
rg
y
Rev
.
2
0
1
4
;
4
0
(1
):5
5
7
–
7
0
.
[2
]
Esm
a
e
il
ian
A
,
P
o
p
o
v
ic
T
,
Ke
z
u
n
o
v
ic
M
.
"
T
ra
n
sm
is
sio
n
li
n
e
re
la
y
m
is
-
o
p
e
ra
ti
o
n
d
e
tec
ti
o
n
b
a
se
d
o
n
ti
m
e
-
s
y
n
c
h
ro
n
ize
d
f
ield
d
a
ta
"
.
El
e
c
tr
Po
we
r S
y
st R
e
s
.
2
0
1
5
;
1
2
5
:1
7
4
–
8
3
.
[3
]
P
a
ss
e
y
R,
S
p
o
o
n
e
r
T
,
M
a
c
G
il
l
I,
W
a
tt
M
,
S
y
n
g
e
ll
a
k
is
K.
"
T
h
e
p
o
ten
ti
a
l
im
p
a
c
ts
o
f
g
rid
-
c
o
n
n
e
c
ted
d
istri
b
u
ted
g
e
n
e
ra
ti
o
n
a
n
d
h
o
w
to
a
d
d
re
ss
th
e
m
:
A
re
v
ie
w
o
f
te
c
h
n
ica
l
a
n
d
n
o
n
-
tec
h
n
ica
l
f
a
c
to
rs
"
.
En
e
rg
y
Po
li
c
y
.
2
0
1
1
;
3
9
(
1
0
):
6
2
8
0
–
9
0
.
[4
]
d
o
s
S
a
n
to
s
A
,
Ba
rro
s
M
T
C
De
,
Co
rre
ia
P
F
.
"
T
ra
n
sm
is
sio
n
li
n
e
p
ro
tec
ti
o
n
sy
ste
m
s
w
it
h
a
id
e
d
c
o
m
m
u
n
ica
ti
o
n
c
h
a
n
n
e
ls
—
P
a
rt
II:
C
o
m
p
a
ra
ti
v
e
p
e
rf
o
r
m
a
n
c
e
a
n
a
l
y
sis
"
.
El
e
c
tr
Po
we
r S
y
st R
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s
2
0
1
5
;
1
2
7
:3
3
9
–
4
6
.
[5
]
Ha
jj
a
r
A
a
.
"
A
h
ig
h
sp
e
e
d
n
o
n
c
o
m
m
u
n
ica
ti
o
n
p
r
o
tec
ti
o
n
sc
h
e
m
e
f
o
r
p
o
w
e
r
tran
sm
is
sio
n
li
n
e
s
b
a
se
d
o
n
w
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v
e
let
tran
sf
o
r
m
"
.
El
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c
tr
Po
we
r S
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s
.
2
0
1
3
;
9
6
:1
9
4
–
2
0
0
.
[6
]
Ne
y
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st
a
n
a
k
i
M
K,
Ra
n
jb
a
r
a
M
.
"
A
n
A
d
a
p
ti
v
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P
M
U
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se
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ti
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c
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m
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o
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T
ra
n
s
m
issio
n
L
in
e
s
"
.
IEE
E
T
ra
n
s
S
ma
rt Gri
d
.
2
0
1
5
;
6
(3
):
1
5
5
0
–
9.
[7
]
T
z
u
-
Ch
iao
L
,
P
ei
-
Yin
L
,
C
h
ih
-
W
e
n
L
.
"
A
n
A
l
g
o
rit
h
m
f
o
r
Lo
c
a
ti
n
g
F
a
u
lt
s
in
T
h
re
e
-
T
e
r
m
in
a
l
M
u
lt
ise
c
ti
o
n
No
n
h
o
m
o
g
e
n
e
o
u
s
T
ra
n
s
m
issio
n
L
in
e
s
Us
in
g
S
y
n
c
h
ro
p
h
a
so
r
M
e
a
su
re
m
e
n
ts
"
.
S
ma
rt
Gr
id
,
IEE
E
T
r
a
n
s
.
2
0
1
4
;
5
(1
):
3
8
–
5
0
.
[8
]
Ba
ti
sta
OE,
F
lau
z
in
o
RA
,
De
A
r
a
u
jo
M
A
,
De
M
o
ra
e
s
LA
,
D
a
S
il
v
a
IN.
"
M
e
th
o
d
o
l
o
g
y
f
o
r
in
f
o
rm
a
ti
o
n
e
x
trac
ti
o
n
f
ro
m
o
sc
il
lo
g
ra
m
s
a
n
d
it
s
a
p
p
l
ica
ti
o
n
f
o
r
h
ig
h
-
im
p
e
d
a
n
c
e
f
a
u
l
ts
a
n
a
l
y
sis
"
.
In
t
J
El
e
c
tr
Po
we
r
En
e
rg
y
S
y
st
.
2
0
1
6
;
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6
:
2
3
–
3
4
.
[9
]
S
w
e
tap
a
d
m
a
A
,
Ya
d
a
v
A
.
"
A
ll
sh
u
n
t
f
a
u
lt
l
o
c
a
ti
o
n
i
n
c
lu
d
in
g
c
ro
ss
-
c
o
u
n
try
a
n
d
e
v
o
lv
in
g
f
a
u
lt
s
in
tran
sm
issio
n
li
n
e
s
w
it
h
o
u
t
f
a
u
lt
ty
p
e
c
las
si
f
ica
ti
o
n
"
.
El
e
c
tr
Po
we
r S
y
st R
e
s
.
2
0
1
5
;
1
2
3
:
1
–
1
2
.
[1
0
]
J.
L
á
z
a
ro
a
,
J.F
.
M
iñ
a
m
b
re
sb
M
A
Z
b
,
A
.
"
S
e
lec
ti
v
e
e
sti
m
a
ti
o
n
o
f
h
a
r
m
o
n
ic
c
o
m
p
o
n
e
n
ts
in
n
o
isy
e
lec
tri
c
a
l
si
g
n
a
ls
f
o
r
p
ro
tec
ti
v
e
re
la
y
in
g
p
u
rp
o
se
s
"
.
In
t
J
El
e
c
tr
P
o
we
r E
n
e
rg
y
S
y
st
.
2
0
1
4
;5
6
(1
):
1
4
0
–
6
.
[1
1
]
V
y
a
s
B,
Da
s
B,
M
a
h
e
sh
w
a
ri
RP
.
"
A
n
i
m
p
ro
v
e
d
sc
h
e
m
e
f
o
r
id
e
n
ti
f
y
in
g
f
a
u
lt
z
o
n
e
in
a
se
ries
c
o
m
p
e
n
sa
ted
tran
sm
issio
n
li
n
e
u
sin
g
u
n
d
e
c
im
a
ted
w
a
v
e
let
tran
s
f
o
rm
a
n
d
Ch
e
b
y
sh
e
v
Ne
u
ra
l
Ne
t
w
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rk
"
.
In
t
J
E
lec
tr
Po
we
r
En
e
rg
y
S
y
st
.
2
0
1
4
;6
3
:7
6
0
–
8.
[1
2
]
Eri
sti
H.
"
F
a
u
lt
d
iag
n
o
sis
sy
ste
m
f
o
r
se
ries
c
o
m
p
e
n
sa
ted
tran
sm
issi
o
n
l
in
e
b
a
se
d
o
n
w
a
v
e
let
tran
s
f
o
rm
a
n
d
a
d
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p
ti
v
e
n
e
u
ro
-
f
u
z
z
y
in
fe
re
n
c
e
s
y
ste
m
"
.
M
e
a
su
re
me
n
t
.
2
0
1
3
;4
6
(1
)
:3
9
3
–
4
0
1
.
[1
3
]
L
iv
a
n
i
H,
E
v
re
n
o
so
g
lu
CY.
"
A
M
a
c
h
in
e
L
e
a
rn
in
g
a
n
d
W
a
v
e
let
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Ba
se
d
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a
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lt
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ti
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M
e
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o
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f
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Hy
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rid
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ra
n
s
m
issio
n
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s
"
.
S
ma
rt Grid
,
IEE
E
T
r
a
n
s
.
2
0
1
4
;5
(
1
):5
1
–
9.
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