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UCT
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ltil
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i
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a
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to
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w
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f
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d
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s
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s
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r
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w
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etc.
T
h
e
H
b
r
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in
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ter
p
r
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s
l
y
p
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ce
s
a
n
o
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tp
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t
v
o
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f
V
dc
,
0
,
-
V
dc
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h
is
b
asi
c
H
b
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g
e
s
w
itc
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in
g
tech
n
iq
u
e
is
e
x
te
n
d
ed
to
o
th
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cir
c
u
it
s
t
h
at
ca
n
g
e
n
er
ate
ad
d
ed
o
u
tp
u
t
v
o
ltag
e
le
v
els.
T
h
i
s
m
u
ltil
e
v
el
o
u
tp
u
t
v
o
lta
g
e
g
iv
e
s
a
s
tair
ca
s
e
w
a
v
ef
o
r
m
w
h
ich
is
s
i
m
i
lar
to
s
i
n
u
s
o
id
al
w
a
v
e
f
o
r
m
t
h
u
s
r
ed
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ci
n
g
th
e
h
ar
m
o
n
ic
co
n
te
n
t
i
n
th
e
o
u
tp
u
t.
T
h
er
e
ar
e
d
if
f
er
en
t
t
y
p
e
o
f
m
u
ltil
e
v
el
in
v
er
ter
to
p
o
lo
g
ies
l
ik
e
n
e
u
tr
al
p
o
in
t
cla
m
p
ed
,
f
l
y
i
n
g
ca
p
ac
ito
r
an
d
ca
s
ca
d
ed
in
v
er
ter
o
u
t
o
f
w
h
ich
t
h
e
ca
s
ca
d
ed
m
u
l
t
ilev
el
i
n
v
er
ter
h
a
s
g
ain
ed
a
lo
t
o
f
p
o
p
u
lar
it
y
d
u
e
to
its
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m
p
r
o
v
ed
q
u
alit
y
a
n
d
c
o
n
n
ec
tio
n
o
f
in
d
ep
en
d
e
n
t
d
.
c
s
o
u
r
ce
s
(
S
DC
S)
to
ea
ch
o
f
th
e
m
o
d
u
le
s
o
as
to
attain
h
ig
h
p
o
w
er
le
v
e
l
at
th
e
o
u
tp
u
t.
[1
]
-
[
2
]
T
h
e
c
ascad
ed
m
u
lti
lev
el
in
v
er
ter
(
C
ML
I
)
is
v
er
y
e
f
f
ici
en
t
in
m
in
i
m
izin
g
T
HD
an
d
g
iv
e
s
b
etter
q
u
alit
y
o
f
p
o
w
er
.
I
t
is
an
i
m
p
o
r
tan
t
to
p
o
lo
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y
as
it
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s
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o
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m
p
lei
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i
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g
t
h
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o
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tp
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t
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r
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C
.
s
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u
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te
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s
.
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e
u
tili
t
y
o
f
a
m
u
lt
ilev
el
i
n
v
er
ter
(
M
L
I
)
.
[3
]
I
t
h
as
a
m
o
d
u
lar
s
tr
u
ct
u
r
e
w
it
h
s
i
m
p
le
s
w
itc
h
i
n
g
m
et
h
o
d
an
d
o
cc
u
p
ies
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les
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er
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ac
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B
y
co
n
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ti
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g
ad
eq
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ate
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m
b
er
o
f
H
-
b
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i
n
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s
ca
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alo
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w
it
h
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h
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e,
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n
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y
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in
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tp
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t
v
o
ltag
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w
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f
o
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m
ca
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e
o
b
ta
in
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.
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ac
h
H
B
r
id
g
e
o
p
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ates
w
it
h
a
d
if
f
er
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t
s
w
i
tch
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n
g
s
c
h
e
m
e
w
h
ic
h
is
u
s
ed
f
o
r
h
ar
m
o
n
ic
co
n
tr
o
l.
I
f
th
e
n
u
m
b
er
o
f
H
-
b
r
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e
g
iv
e
n
b
y
‘
s
’
th
e
n
th
e
n
o
lev
el
o
f
o
u
tp
u
t
v
o
ltag
e
o
b
tain
ed
p
er
p
h
ase
in
C
M
L
I
is
2
s
+1
.
E
ac
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H
B
r
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p
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ates a
t a
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if
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ela
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air
ca
s
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w
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v
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f
o
r
m
o
f
th
e
o
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tp
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t
p
h
a
s
e
v
o
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e
w
h
er
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th
e
o
u
tp
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t
v
o
lta
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is
th
e
s
u
m
o
f
all
v
o
ltag
e
g
en
er
ated
b
y
H
B
r
id
g
e.
[
4
]
-
[5
]
T
h
e
o
u
tp
u
t
p
h
ase
an
d
li
n
e
v
o
ltag
e
o
b
tain
ed
an
d
th
e
efficien
c
y
o
f
DC
to
A
C
co
n
v
er
s
io
n
d
ep
en
d
s
o
n
th
e
T
HD.
No
r
m
a
ll
y
t
h
e
o
u
tp
u
t
v
o
lta
g
e
w
a
v
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f
o
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m
o
f
a
s
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n
g
le
p
h
a
s
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in
v
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ter
co
n
tai
n
s
3
3
.
5
p
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ce
n
t o
f
th
ir
d
h
ar
m
o
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ics,
2
0
p
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f
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f
t
h
h
ar
m
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a
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d
1
4
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5
p
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h
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ar
m
o
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ic
s
ap
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m
a
tel
y
.
A
s
th
e
o
u
tp
u
t
v
o
lta
g
e
i
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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&
Dr
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s
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I
SS
N:
2
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8
8
-
8
694
S
elec
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Ha
r
mo
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limin
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f a
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lev
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Leve
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ter Usi
n
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W
h
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le…
(
S
r
ika
n
ta
K
u
ma
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Da
s
h
)
1945
C
M
L
I
is
o
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b
y
t
h
e
s
y
n
t
h
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s
o
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m
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n
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D.
C
.
So
u
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t
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ab
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a.
c.
v
alu
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h
en
ce
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t
is
e
s
s
e
n
tial
to
m
i
n
i
m
ize
t
h
e
h
ar
m
o
n
ics
a
n
d
to
k
ee
p
th
e
to
tal
h
ar
m
o
n
ic
d
is
to
r
tio
n
(
T
HD)
w
ith
in
t
h
e
s
p
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i
f
ied
li
m
i
ts
p
r
escr
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ed
b
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I
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tan
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s
.
[6
]
T
h
is
p
ap
er
is
o
r
g
an
ized
as
f
o
llo
w
s
.
I
n
s
ec
tio
n
I
I
th
e
SHE
an
d
m
ath
e
m
at
ical
eq
u
atio
n
s
o
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SHE
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e
g
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v
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n
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y
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e
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n
tr
o
d
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cti
o
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s
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I
I
.
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n
s
ec
tio
n
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V
W
OA
i
s
ap
p
lied
in
h
ar
m
o
n
ic
el
i
m
in
ati
o
n
p
r
o
b
le
m
to
f
i
n
d
o
u
t
b
est
s
w
itc
h
i
n
g
a
n
g
les
is
p
r
esen
ted
a
lo
n
g
w
it
h
t
h
e
r
esu
lt
s
an
d
d
is
cu
s
s
io
n
f
o
r
an
1
1
-
lev
el
in
v
er
ter
.
T
h
is
in
cl
u
d
es
t
h
e
ca
lcu
latio
n
o
f
T
HD,
an
d
th
e
elim
i
n
atio
n
o
f
t
h
e
5
th
,
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th
,
1
1
th
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1
3
th
h
ar
m
o
n
ics at
v
ar
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s
m
o
d
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la
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n
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ex
i
s
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en
f
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llo
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ed
b
y
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n
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u
s
io
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s
ec
tio
n
V.
Fig
u
r
e
1
.
C
o
n
f
ig
u
r
atio
n
o
f
C
ML
I
Fig
u
r
e
2
.
P
u
ls
e
w
id
th
i
f
C
M
L
I
2.
SH
E
E
Q
UA
T
I
O
N
S F
O
R
A
CASCAD
E
M
UL
T
I
L
E
VE
L
I
NVE
RT
E
R
I
n
SHE
-
P
W
M
tech
n
iq
u
e
t
h
e
s
w
itc
h
i
n
g
a
n
g
le
s
ar
e
g
e
n
er
ated
to
ca
n
ce
l
a
s
et
o
f
l
o
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er
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d
er
h
ar
m
o
n
ics
at
f
u
n
d
a
m
e
n
tal
f
r
eq
u
en
c
y
[7
].
Fi
g
u
r
e
1
s
h
o
w
s
co
n
f
i
g
u
r
atio
n
o
f
C
M
L
I
.
T
h
e
o
u
tp
u
t
v
o
ltag
e
w
a
v
e
f
o
r
m
o
b
tain
ed
i
n
a
C
M
L
I
is
a
s
tair
ca
s
e
w
av
e
f
o
r
m
as
s
h
o
w
n
i
n
Fi
g
u
r
e
2.
As
p
er
t
h
e
Fo
u
r
ier
s
er
ies
o
f
s
tair
ca
s
e
w
a
v
ef
o
r
m
th
e
e
v
en
h
ar
m
o
n
ics
ar
e
les
s
p
r
o
b
lem
at
ic
w
it
h
r
esp
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t
to
th
e
o
d
d
h
ar
m
o
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ic
s
.
Hen
ce
t
h
e
h
ar
m
o
n
ics
t
h
o
s
e
ar
e
to
b
e
elim
i
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ated
ar
e3
,
5
,
7
.
.
.
,
u
p
to
k
-
1
h
ar
m
o
n
ics
.
Fo
r
th
e
el
i
m
in
at
io
n
o
f
k
-
1
h
ar
m
o
n
ic
s
,
k
n
u
m
b
er
o
f
s
w
i
tch
i
n
g
a
n
g
le
s
ar
e
to
b
e
g
en
er
ated
.
[8
]
-
[9
]
I
n
b
alan
ce
d
t
h
r
ee
-
p
h
ase,
th
e
th
ir
d
h
ar
m
o
n
ic
s
i
s
n
eg
l
ig
ib
le
i
n
li
n
e
v
o
lta
g
e
w
h
e
r
ea
s
p
r
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t
in
-
p
h
a
s
e
v
o
lta
g
e
an
d
th
er
ef
o
r
e
it
is
p
o
s
s
ib
le
to
r
ej
ec
t
5
th
,
7
th
,
1
1
th
,
etc
f
r
o
m
t
h
e
lin
e
v
o
ltag
e
w
a
v
e
f
o
r
m
at
a
lo
w
s
w
itc
h
i
n
g
f
r
eq
u
en
c
y
[
1
0
]
.
T
h
e
o
u
tp
u
t
v
o
lta
g
e
w
a
v
e
f
o
r
m
is
g
iv
e
n
by
(
)
=
{
∑
4V
dc
n
π
(
cos
(
n
α
k
)
si
n
n
w
t
)
∞
=
1
,
3
,
5
…
}
(
1
)
W
h
er
e
n
is
th
e
h
ar
m
o
n
ic
n
u
m
b
er
an
d
c
o
n
s
tr
ain
t
s
o
f
0
≤
1
≤
2
≤
3
≤
4
≤
5
≤
2
.
T
h
e
o
b
j
ec
tiv
e
o
f
th
is
p
ap
er
is
to
ca
lcu
late
t
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ti
m
u
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witch
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les
1
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2
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3
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4
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5
f
o
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1
1
lev
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ter
h
a
v
in
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eq
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v
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ag
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s
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ce
s
i.e
.
V
1
=
V
2
=
V
3
=
V
4
=
V
5
=
V
5
=
c
os
1
+
c
os
2
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c
os
3
+
c
os
4
+
c
os
5
0
=
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os
5
1
+
c
os
5
2
+
c
os
5
3
+
c
os5
4
+
c
os5
5
0
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os
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1
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c
os
7
2
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c
os
7
3
+
c
os7
4
+
c
os7
5
(
2
)
0
=
c
os
11
1
+
c
os
11
2
+
c
os
11
3
+
c
os1
1
4
+
c
os1
1
5
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
:
2
0
8
8
-
8
694
I
n
t J
P
o
w
E
lec
&
Dr
i
S
y
s
t
,
Vo
l.
9
,
No
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4
,
Dec
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b
er
2
0
1
8
:
1944
–
1
9
5
1
1946
0
=
c
os
13
1
+
c
os
13
2
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c
os
13
3
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c
os1
3
4
+
c
os1
3
5
Her
e
Mo
d
u
latio
n
in
d
e
x
(
M
a
)
=
th
e
r
atio
o
f
th
e
1
st
h
ar
m
o
n
ic
co
m
p
o
n
en
t o
f
v
o
lta
g
e
to
th
e
m
a
x
i
m
u
m
at
tain
ab
le
v
o
ltag
e.
I
f
t
h
e
m
ax
i
m
u
m
1
st
h
a
r
m
o
n
ic
o
r
f
u
n
d
a
m
en
tal
v
o
lta
g
e
is
V
1
an
d
th
e
d
.
c
v
o
ltag
e
i
s
eq
u
al
to
V
dc
.
[
1
1
]
M
a
=
V
1
π
4K
V
dc
=
co
s
1
+
co
s
2
+
co
s
3
+
co
s
4
+
co
s
5
(
3
)
Ag
ai
n
,
th
e
e
x
p
r
ess
io
n
o
f
T
HD
=
√
(
∑
v
k
2
∞
k
v
1
2
)
w
h
er
e
k
=
3
,
5
,
7
,
1
1
…
(
4
)
An
d
v
1
i
s
th
e
f
u
n
d
a
m
en
ta
l c
o
m
p
o
n
en
t o
f
v
o
lta
g
e
a
n
d
k
is
t
h
e
h
ar
m
o
n
ic
n
u
m
b
er
.
2
.
1
.
P
r
o
ble
m
Fo
r
m
u
la
t
io
n o
f
Select
iv
e
H
a
r
m
o
nic El
i
m
ina
t
io
n
Usi
ng
WO
A
T
h
e
o
b
j
ec
tiv
e
f
u
n
ctio
n
is
g
i
v
en
b
elo
w
[
1
2
]
.
Fo
r
elim
i
n
atio
n
o
f
h
ar
m
o
n
ics,
ea
ch
ter
m
o
f
th
e
f
u
n
ctio
n
(
α
)
s
h
o
u
ld
b
e
eq
u
al
to
ze
r
o
w
h
er
e
α
th
e
s
w
itc
h
i
n
g
a
n
g
les
.
(
α
)
=
(
∑
cos
(
α
)
5
=
1
−
5
)
2
+
(
4
5
∑
cos
(
5
α
)
5
=
1
)
2
+
(
4
7
∑
cos
(
7α
)
5
=
1
)
2
+
(
4
11
∑
cos
(
11
α
)
5
=
1
)
2
+
(
4
13
∑
cos
(
13
α
)
5
=
1
)
2
W
ith
a
co
n
s
tr
ai
n
ts
0
≤
α
≤
2
(
5
)
3.
WH
AL
E
O
P
T
I
M
I
Z
A
T
I
O
N
AL
G
O
RI
T
H
M
(
W
O
A)
W
h
ale
o
p
ti
m
izat
io
n
al
g
o
r
ith
m
i
s
a
n
e
w
m
eta
h
eu
r
i
s
tic
o
p
ti
m
izatio
n
al
g
o
r
ith
m
b
ased
o
n
th
e
h
u
n
ti
n
g
ac
tiv
itie
s
o
f
h
u
m
p
b
ac
k
w
h
ale
s
.
[
1
3
]
.
T
h
e
h
u
m
p
b
ac
k
w
h
ale
s
ar
e
v
er
y
b
r
ain
y
m
a
m
m
als
t
h
at
lik
e
to
h
u
n
t
k
r
il
l
o
r
s
m
al
l
f
is
h
es
n
ea
r
er
to
s
u
r
f
ac
e
o
f
th
e
s
ea
.
T
h
e
y
m
o
v
e
i
n
a
9
s
h
ap
ed
p
ath
f
o
r
m
i
n
g
a
u
n
iq
u
e
b
u
b
b
le
to
d
ec
eiv
e
th
e
s
m
al
l
f
is
h
es.T
h
is
m
et
h
o
d
is
q
u
i
te
u
n
iq
u
e
in
h
u
m
p
b
ac
k
w
h
ales.
T
h
e
m
at
h
e
m
a
tical
m
o
d
el
o
f
W
O
A
i
s
d
iv
id
ed
in
to
th
r
ee
p
ar
ts
en
cir
cl
in
g
o
f
p
r
e
y
f
o
llo
w
ed
b
y
b
u
b
b
l
e
n
et
h
u
n
tin
g
m
et
h
o
d
an
d
Sear
ch
th
e
p
r
e
y
.
3
.
1
.
E
ncircling
P
r
e
y
W
O
A
tec
h
n
iq
u
e
co
n
s
id
er
s
t
h
ep
r
esen
t
b
est
ca
n
d
id
ate
s
o
lu
t
io
n
is
clo
s
e
to
f
i
n
est
r
esu
lts
.
T
h
e
lead
er
a
m
o
n
g
t
h
e
h
u
m
p
b
ac
k
w
h
ale
is
d
e
f
i
n
ed
f
ir
s
t
a
n
d
o
th
er
h
u
m
p
b
ac
k
w
h
ales
f
o
llo
w
t
h
e
lead
er
i
n
h
u
n
ti
n
g
.
T
h
e
m
at
h
e
m
at
ical
eq
u
atio
n
o
f
ab
o
v
e
b
eh
a
v
io
u
r
is
g
i
v
en
b
y
⃗
⃗
⃗
=
|
C
⃗
.
X
⃗
⃗
⃗
∗
(
)
−
(
)
⃗
⃗
⃗
⃗
⃗
⃗
⃗
⃗
|
(
6
)
X
⃗
⃗
⃗
(
+
1
)
=
X
⃗
⃗
⃗
∗
(
)
−
⋅
⃗
⃗
(
7
)
=
2
.
−
⃗
⃗
⃗
⃗
(
8
)
=
2
.
(
9
)
W
h
er
e‘
t
’
d
esig
n
ate
s
th
e
p
r
ese
n
t
iter
atio
n
∗
⃗
⃗
⃗
⃗
is
th
e
lo
ca
tio
n
o
f
th
e
r
esu
lt
atta
in
ed
w
h
ich
i
s
u
p
d
ated
af
ter
e
v
er
y
r
ei
ter
atio
n
f
o
r
g
e
t
tin
g
i
m
p
r
o
v
ed
o
u
tco
m
es.
E
q
u
atio
n
(
6
)
g
i
v
es
th
e
ab
s
o
lu
te
v
al
u
e,
‘
a
’
s
h
r
i
n
k
s
lin
ea
r
l
y
f
r
o
m
2
to
0
an
d
‘
r
’
i
s
a
r
an
d
o
m
v
ec
to
r
b
et
w
ee
n
0
an
d
1
.
3
.
2
.
B
ub
ble
Net
At
t
a
ck
ing
M
et
ho
d
T
h
is
m
et
h
o
d
is
th
e
e
x
p
lo
itatio
n
s
ta
g
e
an
d
t
h
e
m
at
h
e
m
atica
l
m
o
d
el
o
f
th
i
s
m
e
th
o
d
is
as
f
o
ll
o
w
s
a.
Sh
r
i
n
k
i
n
g
E
n
cir
cli
n
g
M
eth
o
d
T
h
is
p
er
f
o
r
m
an
ce
is
atta
in
ed
b
y
s
h
r
in
k
i
n
g
t
h
e
v
al
u
e
o
f
‘
a’
in
E
q
u
atio
n
(
8
)
.
T
h
e
f
u
n
ctio
n
r
an
g
e
o
f
‘
A’
is
b
y
‘
a
’
.
A
w
ill
m
o
v
e
al
s
o
d
ec
r
ea
s
ed
f
r
o
m
(
X,
Y)
to
(
X*
Y
*
)
f
o
r
0
≤
A
≤
1
.
b.
Sp
ir
al
u
p
d
atin
g
p
o
s
itio
n
I
n
h
u
n
ti
n
g
,
h
u
m
p
b
ac
k
w
h
ale
s
s
w
i
m
ar
o
u
n
d
th
e
p
r
e
y
in
s
h
r
in
k
in
g
cir
cle
an
d
alo
n
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I
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:
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694
I
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t J
P
o
w
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lec
&
Dr
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S
y
s
t
,
Vo
l.
9
,
No
.
4
,
Dec
em
b
er
2
0
1
8
:
1944
–
1
9
5
1
1948
I
f
P
<
0
.
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f
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>
=
1
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n
p
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t
b
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f
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r
=
i
t
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r
+
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4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
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O
NS
Me
tah
e
u
r
is
tic
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izatio
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r
ith
m
p
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e
s
s
e
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tial
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o
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in
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t
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u
m
s
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r
eq
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ir
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f
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m
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ic
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.
As
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h
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m
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ter
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h
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tiv
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E
q
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5
also
in
cr
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m
a
k
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r
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.
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g
o
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ith
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T
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ith
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a
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ith
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Fig
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a
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le
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ase
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t
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p
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ase
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n
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at
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.
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o
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5
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6
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RE
F
E
R
E
NC
E
S
[1
]
J.
Ro
d
ríg
u
e
z
,
S
.
M
e
m
b
e
r,
J.
L
a
i,
a
n
d
S
.
M
e
m
b
e
r,
“
M
u
lt
il
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v
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l
In
v
e
rters
:
A
S
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rv
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o
f
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o
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ies
,
Co
n
tr
o
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,
a
n
d
A
p
p
li
c
a
ti
o
n
s,” v
o
l.
4
9
,
n
o
.
4
,
p
p
.
7
2
4
–
7
3
8
,
2
0
0
2
.
[2
]
M
.
M
a
li
n
o
w
sk
i
e
t
a
l.
,
“
A
S
u
rv
e
y
o
n
Ca
sc
a
d
e
d
M
u
lt
i
lev
e
l
In
v
e
rters
,
”
v
o
l.
5
7
,
n
o
.
7
,
p
p
.
2
1
9
7
–
2
2
0
6
,
2
0
1
0
.
[3
]
W
.
A
.
Ha
li
m
,
T
.
No
o
r,
A
.
T
e
n
g
k
u
,
K.
A
p
p
las
a
m
y
,
a
n
d
A
.
Jid
in
,
“
S
e
lec
ti
v
e
Ha
r
m
o
n
ic
El
im
in
a
ti
o
n
Ba
se
d
o
n
Ne
w
to
n
-
ra
p
h
s
o
n
M
e
th
o
d
f
o
r
Ca
sc
a
d
e
d
H
-
b
ri
d
g
e
M
u
lt
i
lev
e
l
In
v
e
rter,” v
o
l.
8
,
n
o
.
3
,
p
p
.
1
1
93
–
1
2
0
2
,
2
0
1
7
.
[4
]
N.
P
ra
b
a
h
a
ra
n
a
n
d
K
.
P
a
lan
isa
m
y
,
“
A
c
o
m
p
re
h
e
n
siv
e
re
v
ie
w
o
n
re
d
u
c
e
d
sw
it
c
h
m
u
lt
il
e
v
e
l
in
v
e
rter
to
p
o
lo
g
ies
,
m
o
d
u
latio
n
tec
h
n
i
q
u
e
s
a
n
d
a
p
p
li
c
a
ti
o
n
s,”
Ren
e
w.
S
u
st
a
in
.
E
n
e
rg
y
Rev
.
,
v
o
l.
7
6
,
n
o
.
Ja
n
u
a
ry
2
0
1
6
,
p
p
.
1
2
4
8
–
1
2
8
2
,
2
0
1
7
.
[5
]
T
.
P
o
rs
e
lv
i,
K.
De
e
p
a
,
a
n
d
R.
M
u
th
u
,
“
F
P
G
A
B
a
se
d
S
e
lec
ti
v
e
Ha
r
m
o
n
ic
El
im
in
a
ti
o
n
T
e
c
h
n
iq
u
e
f
o
r
M
u
lt
il
e
v
e
l
In
v
e
rter,” v
o
l.
9
,
n
o
.
1
,
p
p
.
1
6
6
–
1
7
3
,
2
0
1
8
.
[6
]
D.
Co
m
m
it
tee
,
I.
P
o
w
e
r,
a
n
d
E.
S
o
c
iety
,
“
IEE
E
Re
c
o
m
m
e
n
d
e
d
P
ra
c
ti
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e
a
n
d
Re
q
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irem
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n
ts
f
o
r
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r
m
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ic
Co
n
tro
l
in
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lec
tri
c
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o
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r
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ste
m
s IE
EE
P
o
w
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r
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n
d
En
e
rg
y
S
o
c
iet
y
,
”
v
o
l.
2
0
1
4
,
2
0
1
4
.
[7
]
H.
T
a
g
h
iza
d
e
h
a
n
d
M
.
T
.
Ha
g
h
,
“
Ha
rm
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im
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ti
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sc
a
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u
lt
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l
In
v
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rters
w
it
h
No
n
e
q
u
a
l
DC
S
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rc
e
s Us
in
g
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rti
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le S
w
a
r
m
Op
ti
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iza
ti
o
n
,
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v
o
l.
5
7
,
n
o
.
1
1
,
p
p
.
3
6
7
8
–
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6
8
4
,
2
0
1
0
.
[8
]
R.
T
a
leb
,
M
.
H
e
lai
m
i,
D.
B
e
n
y
o
u
c
e
f
,
a
n
d
Z.
Bo
u
d
jem
a
,
“
Ge
n
e
ti
c
A
l
g
o
rit
h
m
A
p
p
li
c
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ti
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n
in
A
s
y
m
m
e
tri
c
a
l
9
-
Lev
e
l
In
v
e
rter,” v
o
l.
7
,
n
o
.
2
,
2
0
1
6
.
[9
]
R.
P
.
A
g
u
il
e
ra
e
t
a
l.
,
“
S
e
lec
ti
v
e
Ha
r
m
o
n
ic
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im
in
a
ti
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n
M
o
d
e
l
P
re
d
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c
ti
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Co
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tro
l
f
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r
M
u
lt
il
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v
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l
P
o
w
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r
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n
v
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rters
,
”
IEE
E
T
ra
n
s.
P
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we
r E
lec
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.
,
v
o
l
.
3
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,
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o
.
3
,
p
p
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2
4
1
6
–
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4
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6
,
2
0
1
7
.
[1
0
]
S
.
M
.
In
v
e
rter,
M
.
A
h
m
e
d
,
A
.
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h
e
ir,
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.
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n
d
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.
M
e
m
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e
r,
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m
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p
lem
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tatio
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r
m
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ic E
li
m
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o
l.
5
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.
4
,
p
p
.
1
7
0
0
–
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7
0
9
,
2
0
1
7
.
[1
1
]
J.
Ku
m
a
r,
B.
Da
s,
a
n
d
P
.
A
g
a
r
wa
l,
“
S
e
lec
ti
v
e
h
a
rm
o
n
ic
e
li
m
in
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ti
o
n
tec
h
n
i
q
u
e
f
o
r
a
m
u
lt
il
e
v
e
l
in
v
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rter,”
Fi
ft
e
e
n
t
h
Na
tl
.
P
o
we
r S
y
st.
C
o
n
f.
,
n
o
.
De
c
e
m
b
e
r,
p
p
.
6
0
8
–
6
1
3
,
2
0
0
8
.
[1
2
]
P
.
Q.
Dz
u
n
g
,
N.
T
.
T
ien
,
N.
D.
T
u
y
e
n
,
a
n
d
H
.
L
e
e
,
“
S
e
lec
ti
v
e
Ha
r
m
o
n
ic
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im
in
a
ti
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n
f
o
r
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sc
a
d
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d
M
u
lt
i
lev
e
l
In
v
e
rters
Us
in
g
G
r
e
y
W
o
lf
Op
ti
m
ize
r
A
l
g
o
rit
h
m
,
”
p
p
.
2
7
7
6
–
2
7
8
1
,
2
0
1
5
.
[1
3
]
S
.
M
irj
a
li
l
i
a
n
d
A
.
L
e
w
i
s,
“
A
d
v
a
n
c
e
s
in
En
g
in
e
e
rin
g
S
o
f
twa
re
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h
e
W
h
a
le
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ti
m
iza
ti
o
n
A
lg
o
rit
h
m
,
”
Ad
v
.
En
g
.
S
o
ft
w
.
,
v
o
l.
9
5
,
p
p
.
5
1
–
6
7
,
2
0
1
6
.
[1
4
]
I.
J.
El
e
c
tr
o
n
,
C.
A
e
ü
,
B.
Na
y
a
k
,
B.
M
isra
,
a
n
d
T
.
R.
Ch
o
u
d
h
u
ry
,
“
M
e
ta
-
h
e
u
risti
c
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
s
f
o
r
d
e
sig
n
o
f
g
a
in
c
o
n
stra
in
e
d
sta
te v
a
riab
le f
i
lt
e
r,
”
In
t.
J
.
E
lec
tro
n
.
Co
mm
u
n
.
,
v
o
l.
9
3
,
n
o
.
F
e
b
r
u
a
ry
,
p
p
.
7
–
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8
,
2
0
1
8
.
[1
5
]
S
.
S
u
d
h
a
,
T
.
T
h
a
k
u
r,
a
n
d
J.
K
u
m
a
r,
“
Ha
r
m
o
n
ic
e
li
m
in
a
ti
o
n
o
f
a
p
h
o
t
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v
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ic
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a
se
d
c
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sc
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-
b
rid
g
e
m
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lt
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v
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l
in
v
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rter
u
sin
g
P
S
O
(
p
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rti
c
le
sw
a
r
m
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p
ti
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iza
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n
)
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c
ti
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o
to
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e
rg
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,
v
o
l.
1
0
7
,
p
p
.
3
3
5
–
3
4
6
,
2
0
1
6
.
[1
6
]
P
.
P
.
B
isw
a
s,
N.
H.
Aw
a
d
,
a
n
d
P
.
N.
S
u
g
a
n
t
h
a
n
,
“
M
i
n
im
izin
g
T
H
D
o
f
M
u
lt
il
e
v
e
l
In
v
e
rters
w
it
h
Op
ti
m
a
l
V
a
lu
e
s
o
f
DC V
o
lt
a
g
e
s an
d
S
w
it
c
h
in
g
A
n
g
les
u
sin
g
L
S
HA
DE
-
Ep
S
in
a
lg
o
rit
h
m
,
”
n
o
.
Ju
n
e
,
2
0
1
7
.
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