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e
d
in
[
1
9
]
u
tili
zin
g
g
en
et
ic
al
g
o
r
ith
m
(
G
A
)
to
co
n
tr
o
l
t
h
e
p
h
o
to
v
o
ltaic
s
y
s
te
m
p
er
f
o
r
m
an
ce
esp
ec
iall
y
t
h
e
o
u
tp
u
t
v
o
lta
g
e.
Yet
,
h
ar
m
o
n
y
s
ea
r
c
h
(
HS)
o
p
ti
m
iz
atio
n
alg
o
r
it
h
m
h
as
n
o
t
b
ee
n
ap
p
lied
in
th
e
in
v
er
ter
ap
p
licatio
n
s
to
tu
n
e
t
h
e
P
I
co
ef
f
ici
e
n
t
s
.
I
n
th
is
r
esear
c
h
,
th
e
P
I
c
o
n
tr
o
ller
b
ased
HS
alg
o
r
ith
m
is
u
tili
ze
d
to
en
h
a
n
ce
th
e
p
er
f
o
r
m
an
ce
o
f
th
e
v
o
lta
g
e
s
o
u
r
ce
in
v
er
ter
.
T
h
e
in
v
er
ter
p
r
o
to
ty
p
e
an
d
th
e
co
n
tr
o
l
alg
o
r
it
h
m
ar
e
m
o
d
eled
u
s
i
n
g
t
h
e
en
v
ir
o
n
m
e
n
t
o
f
M
A
T
L
A
B
(
Si
m
u
li
n
k
/
C
o
d
e)
.
A
f
ter
th
at,
th
e
co
n
tr
o
l
alg
o
r
ith
m
o
f
t
h
e
in
v
er
ter
p
r
o
to
ty
p
e
is
ex
p
er
i
m
e
n
tall
y
i
m
p
le
m
e
n
ted
in
t
h
e
eZ
d
s
p
F2
8
3
3
5
b
o
ar
d
to
v
alid
ate
th
e
e
f
f
ec
t
iv
e
n
es
s
o
f
th
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
u
n
d
er
d
if
f
er
en
t lo
ad
co
n
d
itio
n
s.
2.
DE
SCR
I
P
T
I
O
N
O
F
VO
L
T
AG
E
SO
URC
E
I
NV
E
R
T
E
R
Fig
u
r
e
1
d
escr
ib
es
th
e
v
o
lta
g
e
s
o
u
r
ce
i
n
v
er
ter
co
n
s
id
er
e
d
in
th
is
r
esear
c
h
,
w
h
ich
i
n
c
lu
d
es
b
o
th
p
o
w
er
an
d
co
n
tr
o
l
s
tag
es.
T
h
e
p
o
w
er
s
ta
g
e
co
n
s
is
t
s
o
f
a
DC
v
o
lta
g
e
s
o
u
r
ce
,
f
u
ll
b
r
id
g
e
co
n
f
i
g
u
r
atio
n
w
it
h
I
GB
T
s
s
w
i
tch
e
s
f
o
llo
w
e
d
b
y
an
ap
p
r
o
p
r
iate
L
C
f
ilter
cir
cu
it
w
h
ich
f
i
lter
s
o
u
t
t
h
e
f
r
eq
u
en
c
y
s
w
itc
h
i
n
g
o
f
th
e
b
r
id
g
e
cir
cu
i
t
as
w
ell
a
s
i
m
p
r
o
v
e
t
h
e
v
o
lta
g
e
w
a
v
ef
o
r
m
lin
k
ed
to
th
e
lo
ad
s
,
an
d
t
wo
r
esis
tiv
e
lo
ad
s
.
T
h
e
co
n
tr
o
l stag
e
co
n
s
i
s
ts
o
f
DSP
b
o
ar
d
,
p
r
o
p
o
s
ed
co
n
tr
o
ller
,
an
d
b
ip
o
lar
SP
W
M
m
et
h
o
d
.
T
h
e
o
u
tp
u
t
v
o
ltag
e
o
f
th
e
i
n
v
er
ter
(
)
ca
n
b
e
s
en
s
ed
at
th
e
ter
m
i
n
al
o
f
t
w
o
d
if
f
er
en
t
lo
ad
s
(
)
b
y
u
s
in
g
a
v
o
ltag
e
f
ee
d
b
ac
k
s
e
n
s
o
r
an
d
it c
an
b
e
r
ep
r
esen
ted
as;
(
1
)
W
h
er
e
is
th
e
p
ea
k
v
o
ltag
e
an
d
is
th
e
f
u
n
d
a
m
en
ta
l
f
r
eq
u
en
c
y
o
f
t
h
e
i
n
v
er
ter
o
u
tp
u
t.
Ho
w
e
v
er
,
th
e
g
en
er
ated
er
r
o
r
b
et
w
ee
n
th
e
r
ef
er
en
ce
a
n
d
th
e
m
ea
s
u
r
ed
v
o
ltag
es
a
s
s
h
o
w
n
in
eq
u
atio
n
(
2
)
is
th
e
n
s
e
n
t
to
t
h
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
w
h
ich
in
clu
d
es
t
h
e
h
ar
m
o
n
y
s
ea
r
ch
al
g
o
r
ith
m
b
ased
P
I
ap
p
r
o
ac
h
.
Nex
t,
a
co
m
p
ar
i
s
o
n
b
et
w
ee
n
an
d
is
d
o
n
e
to
d
er
iv
e
th
e
in
v
er
ter
b
y
g
e
n
er
atin
g
an
d
s
ig
n
al
s
in
o
r
d
er
to
o
b
tain
th
e
d
esire
d
o
u
tp
u
t.
A
ll
t
h
ese
s
tep
s
ar
e
i
m
p
le
m
en
ted
u
s
i
n
g
th
e
T
MS3
2
0
F2
8
3
3
5
b
o
a
r
d
.
T
h
e
m
ea
n
ab
s
o
lu
te
er
r
o
r
(
MA
E
)
is
ap
p
lied
an
o
p
ti
m
izatio
n
p
r
o
b
lem
as
i
n
eq
u
ati
o
n
(
3
)
to
m
i
n
i
m
ize
th
e
o
u
tp
u
t
er
r
o
r
o
f
th
e
v
o
ltag
e
so
u
r
ce
in
v
er
ter
[
2
0
]
.
(
2
)
∑
|
|
(
3
)
R
1
R
2
Ki
K
p
+
----
s
V
r
e
f
r
m
s
e
10
K
H
z
PI
HS
_
A
l
gor
i
th
m
Kp
Ki
V
l
oa
d r
m
s
S
1
S
2
S
1
S
1
S
2
S
2
V
dc
L
f
C
f
I
L
I
R
1
I
R
2
+
-
Cont
rol
S
t
a
ge
(
T
M
S
320
F
28335
)
P
ow
e
r S
t
a
ge
I
L
oa
d
I
C
+
-
+
-
-
+
V
i
nv
+
-
V
c
ont
r
ol
V
c
a
r
r
i
e
r
-
+
S
P
W
M
+
S
i
ne
Fig
u
r
e
1
.
Vo
ltag
e
s
o
u
r
ce
i
n
v
er
ter
w
it
h
p
r
o
p
o
s
ed
co
n
tr
o
ller
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
PEDS
I
SS
N:
2
0
8
8
-
8
694
A
n
E
fficien
t Co
n
tr
o
l I
mp
leme
n
ta
tio
n
fo
r
I
n
ve
r
ter B
a
s
ed
Ha
r
mo
n
y
S
ea
r
ch
A
l
g
o
r
ith
m
(
Mu
s
h
ta
q
N
a
jeeb
)
281
3.
H
S IM
P
L
E
M
E
NT
AT
I
O
N
T
O
F
I
ND
P
I
P
ARAM
E
T
E
R
S
Har
m
o
n
y
s
ea
r
c
h
(
HS)
is
a
w
el
l
-
k
n
o
w
n
m
eta
-
h
e
u
r
is
tic
o
p
ti
m
i
za
tio
n
alg
o
r
it
h
m
in
s
p
ir
ed
b
y
t
h
e
m
o
d
er
n
n
atu
r
al
p
h
en
o
m
en
a,
w
h
ic
h
w
a
s
p
r
o
p
o
s
ed
b
y
[
2
1
]
,
[
2
2
]
.
I
n
th
is
r
esear
ch
an
o
p
ti
m
u
m
P
I
v
o
lt
ag
e
co
n
tr
o
ller
u
s
in
g
HS
al
g
o
r
ith
m
to
o
p
ti
m
ize
an
d
co
ef
f
icie
n
t
s
is
p
r
o
p
o
s
ed
to
co
n
tr
o
l
th
e
o
u
tp
u
t
v
o
lta
g
e
d
r
o
p
an
d
k
ee
p
t
h
e
s
y
s
te
m
is
at
a
d
esire
d
p
er
f
o
r
m
an
ce
w
it
h
a
f
a
s
t
d
y
n
a
m
ic
r
esp
o
n
s
e.
T
h
e
HS
alg
o
r
it
h
m
h
as
b
ee
n
w
id
el
y
u
tili
ze
d
in
d
i
f
f
er
e
n
t
s
tu
d
ie
s
to
s
o
lv
e
a
lo
t
o
f
o
p
ti
m
izatio
n
p
r
o
b
lem
s
r
elate
d
to
th
e
ap
p
licatio
n
s
o
f
en
g
in
ee
r
i
n
g
f
elid
s
s
u
c
h
as
d
es
ig
n
o
f
s
teel
s
tr
u
ct
u
r
e,
h
ea
t
ex
c
h
a
n
g
er
d
esi
g
n
,
r
o
b
o
tics
,
telec
o
m
m
u
n
ica
tio
n
s
,
a
n
d
s
o
o
n
[
2
3
]
b
u
t
it
h
as
n
o
t
b
ee
n
u
s
ed
to
s
o
l
v
e
t
h
e
v
o
ltag
e
co
n
tr
o
l
p
r
o
b
le
m
s
f
o
r
th
e
i
n
v
er
ter
ap
p
licatio
n
s
u
n
d
er
d
i
f
f
er
en
t
lo
ad
co
n
d
itio
n
s
.
I
n
b
r
ief
,
t
h
e
o
p
tim
izatio
n
p
r
o
ce
s
s
f
o
r
th
e
p
r
o
p
o
s
ed
co
n
tr
o
l
alg
o
r
ith
m
i
s
d
escr
ib
ed
in
th
e
p
s
eu
d
o
co
d
e
b
elo
w
;
Co
ntr
o
l f
lo
w
o
f
P
I
ba
s
ed
H
a
r
m
o
ny
Sea
rc
h Alg
o
rit
h
m
:
p
s
eu
d
o
co
d
e
Sta
rt
pro
g
ra
m
:
Def
in
itio
n
o
f
;
Def
in
itio
n
o
f
HM
S,
H
MCR
,
P
AR
,
an
d
Ma
x
I
;
Def
in
itio
n
th
e
u
p
p
er
an
d
lo
w
er
b
o
u
n
d
ar
ies o
f
t
h
e
d
ec
is
io
n
p
ar
a
m
eter
s
(
,
)
;
Har
m
o
n
y
m
e
m
o
r
y
(
H
M)
in
itializat
io
n
;
,
if
s
ati
s
f
ied
,
if
s
ati
s
f
ied
,
if
s
ati
s
f
ied
C
h
o
o
s
e
a
d
ec
is
io
n
p
ar
a
m
eter
f
r
o
m
t
h
e
HM
;
;
,
if
s
ati
s
f
ied
A
d
j
u
s
t th
e
d
ec
is
io
n
p
ar
a
m
eter
b
y
;
);
C
h
o
o
s
e
a
n
e
w
r
an
d
o
m
d
ec
i
s
io
n
p
ar
a
m
eter
b
y
;
;
A
cc
ep
t th
e
n
e
w
s
o
lu
tio
n
v
ec
to
r
an
d
r
ep
lace
d
b
y
t
h
e
o
ld
o
n
e,
th
en
ad
d
ed
it to
th
e
HM
;
R
etu
r
n
b
ac
k
th
e
b
est
s
o
lu
tio
n
f
o
u
n
d
(
,
)
;
4.
I
M
P
L
E
M
E
NT
AT
I
O
N
CO
N
T
RO
L
A
L
G
O
RI
T
H
M
USI
NG
e
Z
d
s
p F
2
8
3
3
5
I
n
r
ec
en
t
d
ec
ad
es,
T
ex
as
I
n
s
tr
u
m
en
t
s
u
c
h
as
th
e
C
2
0
0
0
f
a
m
il
y
o
f
e
Z
d
s
p
T
MS3
2
0
F
2
8
3
3
x
is
b
ec
o
m
i
n
g
v
er
y
e
s
s
e
n
tial
b
o
ar
d
f
o
r
th
e
h
i
g
h
s
w
itc
h
i
n
g
al
g
o
r
ith
m
s
i
n
d
if
f
er
en
t
co
n
tr
o
l
ap
p
licatio
n
s
f
o
r
v
o
ltag
e
s
o
u
r
ce
in
v
er
ter
s
[
2
4
]
.
I
n
th
is
r
esear
ch
,
th
e
Har
v
ar
d
ar
ch
itec
tu
r
e
o
f
eZ
d
s
p
T
MS3
2
0
F2
8
3
3
5
b
o
a
r
d
is
u
s
ed
d
u
e
to
its
f
ea
t
u
r
es
as
co
m
p
ar
ed
w
it
h
t
h
e
p
r
ev
io
u
s
m
o
d
els
li
k
e
T
MS3
2
0
F2
8
1
2
b
o
ar
d
.
I
n
th
is
al
g
o
r
ith
m
,
t
h
e
f
ee
d
b
ac
k
v
o
lta
g
e
is
in
i
tiall
y
m
ea
s
u
r
ed
u
s
i
n
g
a
v
o
ltag
e
s
e
n
s
o
r
w
h
ic
h
ca
lled
L
E
M
L
V2
5
-
P
(
7
1
6
0
2
9
)
.
T
h
is
s
en
s
o
r
d
ec
r
ea
s
es
th
e
v
a
lu
e
o
f
th
e
m
ea
s
u
r
ed
v
o
lta
g
e
to
e
Z
d
s
p
F2
8
3
3
5
b
o
ar
d
’
s
r
an
g
e
w
h
ic
h
is
f
r
o
m
0
to
3
v
o
lt
an
d
th
en
f
ed
to
th
e
an
alo
g
d
ig
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as f
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ex
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ac
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ig
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r
e
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m
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tp
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t
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v
e
f
o
r
m
s
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u
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u
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5
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x
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u
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6
s
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h
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ased
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ith
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u
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6
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alu
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n
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Fig
u
r
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7
a
s
h
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r
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e
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Fi
g
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r
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7
b
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ased
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n
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ec
r
ea
s
in
g
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ad
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e
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e
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ea
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ed
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h
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o
r
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er
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e
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at
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r
o
m
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g
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r
e
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e
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e
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f
.
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g
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8
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is
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n
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ch
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HS)
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ce
c
h
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n
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SO
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o
r
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m
b
ased
P
I
(
P
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SO)
.
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ith
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a
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u
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lik
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u
m
b
er
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s
,
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ize,
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im
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ased
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n
Fig
u
r
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8
,
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e
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ad
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I
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Fig
u
r
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7
a
.
Si
m
u
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o
u
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t
w
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f
o
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m
s
w
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th
s
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Fig
u
r
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7
b
.
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x
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im
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n
tal
o
u
tp
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t
w
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v
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m
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s
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ad
ch
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u
r
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8
.
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n
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m
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s
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ased
o
n
HS
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I
an
d
P
SO
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PI
Fu
r
t
h
er
m
o
r
e,
b
ased
o
n
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s
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tical
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atio
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a
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ilco
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est
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s
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cted
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h
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-
v
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e
eq
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al
to
0
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0
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to
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y
w
h
e
th
er
t
h
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o
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r
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y
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s
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g
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S
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P
I
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P
I
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SO a
l
g
o
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ith
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s
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ig
n
i
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ica
n
t.
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ased
o
n
th
e
g
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ated
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ep
o
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e
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atio
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e
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-
v
alu
e
f
o
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I
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er
s
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s
P
I
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SO
is
less
t
h
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0
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0
5
(
p
-
v
alu
e
<0
.
0
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)
.
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h
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ate
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at
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ted
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s
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e
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y
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I
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n
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SO
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ased
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g
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
PEDS
I
SS
N:
2
0
8
8
-
8
694
A
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E
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n
tr
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l I
mp
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n
ta
tio
n
fo
r
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ve
r
ter B
a
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Ha
r
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m
(
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s
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s
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f
o
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th
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d
ev
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as c
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m
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0
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0
1
6
o
f
th
e
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SO
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P
I
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n
tr
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Fig
u
r
e
9
.
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o
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lo
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is
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ased
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PI
7.
CO
NCLU
SI
O
N
I
n
th
i
s
r
esear
ch
,
a
P
I
co
n
tr
o
lle
r
f
o
r
v
o
ltag
e
s
o
u
r
ce
in
v
er
ter
b
ase
d
o
n
h
ar
m
o
n
y
s
ea
r
c
h
(
HS)
alg
o
r
ith
m
h
as
b
ee
n
d
e
v
elo
p
ed
an
d
i
m
p
l
e
m
en
ted
.
T
h
e
p
r
o
ce
d
u
r
e
o
f
tr
ial
an
d
er
r
o
r
in
f
i
n
d
i
n
g
P
I
p
ar
a
m
eter
s
h
as
b
ee
n
av
o
id
ed
b
y
u
s
i
n
g
HS
a
lg
o
r
it
h
m
.
T
h
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
h
as
b
ee
n
m
o
d
eled
u
s
i
n
g
Ma
tla
b
en
v
ir
o
n
m
e
n
t
a
n
d
lin
k
ed
b
y
th
e
p
r
o
to
t
y
p
e
i
n
v
er
t
er
u
s
i
n
g
e
Z
d
s
p
T
MS3
2
0
F2
8
3
3
5
co
n
tr
o
l
u
n
it.
T
h
e
m
ea
n
ab
s
o
lu
te
er
r
o
r
(
MA
E
)
v
alu
e
o
f
t
h
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
PI
-
HS
is
0
.
0
0
0
3
4
as
c
o
m
p
ar
ed
to
0
.
0
0
1
6
o
f
th
e
PI
-
P
SO
alg
o
r
ith
m
.
E
x
p
er
i
m
e
n
tal
r
esu
lts
h
a
s
b
ee
n
d
o
n
e
u
n
d
er
d
if
f
er
en
t
lo
ad
s
to
v
al
id
ate
th
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
.
T
h
e
r
esu
lts
s
h
o
w
ed
t
h
at
t
h
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
o
f
f
er
s
a
n
e
f
f
icie
n
t
r
e
s
p
o
n
s
e
i
n
ter
m
s
o
f
o
u
tp
u
t
v
o
ltag
e
a
n
d
cu
r
r
en
t
w
a
v
e
f
o
r
m
s
.
Me
a
n
w
h
ile,
th
er
e
is
n
o
n
e
g
ati
v
e
ef
f
ec
t
s
o
r
o
v
er
s
h
o
o
t in
th
e
o
u
tp
u
t
w
a
v
e
f
o
r
m
s
.
RE
F
E
R
E
NC
E
S
[1
]
I
.
Co
lak
,
e
t
a
l
.
,
“
Re
v
iew
o
f
m
u
lt
il
e
v
e
l
v
o
lt
a
g
e
so
u
rc
e
in
v
e
rter
to
p
o
l
o
g
ies
a
n
d
c
o
n
tro
l
sc
h
e
m
e
s,”
En
e
rg
y
Co
n
v
e
rs
io
n
a
n
d
M
a
n
a
g
e
me
n
t
,
v
o
l
/i
ss
u
e
:
52
(
2
)
,
p
p
.
1
1
1
4
–
1
1
2
8
,
2
0
1
1
.
[2
]
A
.
M
.
Hu
m
a
d
a
,
e
t
a
l.
,
“
A
Ne
w
M
e
th
o
d
o
f
P
V
Re
c
o
n
f
ig
u
ra
ti
o
n
u
n
d
e
r
P
a
rt
ial
S
h
a
d
o
w
Co
n
d
it
io
n
s
b
a
se
d
o
n
DC/
DC
Ce
n
tral
Co
n
v
e
rter,”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Ren
e
w
a
b
le E
n
e
rg
y
Re
so
u
rc
e
s
,
v
o
l.
4
,
p
p
.
4
9
-
5
3
,
2
0
1
4
.
[3
]
M
u
sh
taq
N.,
e
t
a
l.
,
“
S
im
u
latio
n
o
f
Re
g
u
late
d
P
o
w
e
r
S
u
p
p
ly
f
o
r
S
o
lar
P
h
o
to
-
V
o
lt
a
ic
M
o
d
e
l,
”
I
n
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
E
n
g
i
n
e
e
rin
g
S
c
e
in
c
e
&
Res
e
a
c
h
T
e
c
h
n
o
l
o
g
y
,
v
o
l
/i
ss
u
e
:
2
(
12
)
,
p
p
.
3
6
0
7
-
3
6
1
3
,
2
0
1
3
.
[4
]
A
.
B
e
n
slim
a
n
e
,
e
t
a
l.
,
“
A
n
Ex
p
e
r
im
e
n
tal
S
tu
d
y
o
f
th
e
Un
b
a
lan
c
e
Co
m
p
e
n
sa
ti
o
n
b
y
V
o
lt
a
g
e
S
o
u
rc
e
In
v
e
rter
Ba
se
d
S
TAT
COM,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
Po
we
r
El
e
c
tro
n
ics
a
n
d
Dr
ive
S
y
ste
m
(
I
J
PE
DS
),
v
o
l
/i
ss
u
e
:
7
(
1
)
,
p
p
.
4
5
-
55
,
2
0
1
6
.
[5
]
S
.
Ojh
a
,
e
t
a
l
.
,
“
Clo
se
L
o
o
p
V
/
F
Co
n
tr
o
l
o
f
V
o
lt
a
g
e
S
o
u
rc
e
In
v
e
rter
u
sin
g
S
in
u
so
i
d
a
l
P
W
M
,
T
h
ird
Ha
rm
o
n
ic
In
jec
ti
o
n
P
W
M
a
n
d
S
p
a
c
e
V
e
c
to
r
P
W
M
M
e
th
o
d
f
o
r
In
d
u
c
ti
o
n
M
o
t
o
r,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Po
w
e
r
El
e
c
tro
n
ics
a
n
d
Dr
ive
S
y
ste
m (
IJ
PE
DS
)
,
v
o
l
/i
ss
u
e
:
7
(
1
)
,
p
p
.
2
1
7
-
2
2
4
,
2
0
1
6
.
[6
]
A
li
M
.
,
et
a
l.
,
“
A
Re
v
ie
w
o
n
P
h
o
to
v
o
lt
a
ic
A
rra
y
Be
h
a
v
io
r,
Co
n
f
ig
u
ra
ti
o
n
S
trate
g
ies
a
n
d
M
o
d
e
ls
u
n
d
e
r
M
ism
a
tch
Co
n
d
it
io
n
s,”
AR
PN
J
o
u
r
n
a
l
o
f
En
g
in
e
e
rin
g
a
n
d
Ap
p
li
e
d
S
c
ien
c
e
s
,
v
o
l
/i
ss
u
e
:
11
(
7
)
,
p
p
.
4
8
9
6
-
4
9
0
3
,
2
0
1
6
.
[7
]
R.
Orte
g
a
,
et
a
l.
,
“
Co
n
tro
l
tec
h
n
i
q
u
e
s
f
o
r
re
d
u
c
ti
o
n
o
f
th
e
to
tal
h
a
rm
o
n
ic
d
isto
rti
o
n
in
v
o
lt
a
g
e
a
p
p
l
ied
to
a
sin
g
le
-
p
h
a
se
in
v
e
rter
w
it
h
n
o
n
li
n
e
a
r
lo
a
d
s:
Re
v
ie
w
,
”
Ren
e
wa
b
le
a
n
d
S
u
sta
i
n
a
b
le
En
e
rg
y
Rev
iews
,
v
o
l
/i
ss
u
e
:
16
(
3
)
,
p
p
.
1
7
5
4
–
1
7
6
1
,
2
0
1
2
.
[8
]
J.
S
e
lv
a
ra
j,
et
a
l.
,
“
M
u
lt
i
le
v
e
l
In
v
e
rter
f
o
r
G
rid
-
Co
n
n
e
c
ted
P
V
S
y
ste
m
E
m
p
lo
y
in
g
Dig
it
a
l
P
I
Co
n
tro
ll
e
r,
”
IE
EE
T
ra
n
sa
c
ti
o
n
s
o
n
In
d
u
stri
a
l
El
e
c
tr
o
n
ics
,
v
o
l
/
issu
e
:
56
(
1
)
,
p
p
.
1
4
9
–
1
5
8
,
2
0
0
9
.
[9
]
P.
S
a
n
c
h
is,
et
a
l.
,
“
Bo
o
st
DC
-
AC
In
v
e
rter:
A
Ne
w
Co
n
tro
l
S
trate
g
y
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
P
o
we
r
El
e
c
tro
n
ics
,
v
o
l.
2
0
,
p
p
.
3
4
3
–
3
5
3
,
2
0
0
5
.
[1
0
]
A
.
M
a
h
m
o
o
d
,
e
t
a
l.
,
“
Re
c
o
n
f
ig
u
ra
ti
o
n
M
e
t
h
o
d
Ba
se
d
o
n
DC
-
DC
Ce
n
tral
Co
n
v
e
rter
w
it
h
in
Dif
fe
re
n
t
M
ism
a
tch
Co
n
d
it
io
n
s
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
En
g
in
e
e
rin
g
S
c
e
in
c
e
&
Res
e
a
c
h
T
e
c
h
n
o
lo
g
y
,
v
o
l
/i
ss
u
e
:
2
(1
2
)
,
p
p
.
3
6
3
4
-
3
6
3
9
,
2
0
1
3
.
[1
1
]
A
li
M
.
,
et
a
l.
,
“
P
h
o
t
o
v
o
lt
a
ic
G
r
id
-
Co
n
n
e
c
ted
M
o
d
e
li
n
g
a
n
d
Ch
a
ra
c
teriz
a
ti
o
n
Ba
se
d
o
n
Ex
p
e
ri
m
e
n
tal
Re
su
lt
s,”
PL
OS
ONE
,
v
o
l
/i
ss
u
e
:
11
(
4
)
,
p
p
.
1
-
1
3
,
2
0
1
6
.
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0
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8
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8
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1
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Ma
r
ch
2
0
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7
:
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7
9
–
289
288
[1
2
]
M
.
M
o
n
f
a
re
d
,
et
a
l.
,
“
A
n
a
l
y
sis,
De
sig
n
,
a
n
d
Ex
p
e
rim
e
n
tal
V
e
rif
ic
a
ti
o
n
o
f
a
S
y
n
c
h
ro
n
o
u
s
Re
f
e
re
n
c
e
F
ra
m
e
V
o
lt
a
g
e
Co
n
tr
o
l
f
o
r
S
in
g
le
-
P
h
a
se
In
v
e
rter
s,”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
In
d
u
str
ia
l
El
e
c
tro
n
ics
,
v
o
l
/i
ss
u
e
:
61
(
1
)
,
p
p
.
2
5
8
–
2
6
9
,
2
0
1
4
.
[1
3
]
B
.
A
.
S
u
h
a
s,
e
t
a
l
.
,
“
V
a
rio
u
s
Co
n
tro
l
S
c
h
e
me
s
fo
r
V
o
lt
a
g
e
S
o
u
rc
e
In
v
e
rte
r
in
PV
g
ri
d
i
n
ter
fa
c
e
d
sy
ste
m,”
2
0
1
5
In
tern
a
ti
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
E
n
e
rg
y
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y
ste
m
s an
d
A
p
p
li
c
a
ti
o
n
s
,
p
p
.
4
4
1
-
4
4
5
,
2
0
1
5
.
[1
4
]
A
.
M
u
th
u
ra
m
a
li
n
g
a
m
,
et
a
l.
,
“
P
e
rf
o
rm
a
n
c
e
e
v
a
lu
a
ti
o
n
o
f
a
n
F
P
GA
c
o
n
tro
ll
e
d
so
f
t
s
w
it
c
h
e
d
in
v
e
rter,”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Po
we
r E
lec
tro
n
i
c
s
,
v
o
l.
2
1
,
p
p
.
9
2
3
–
9
3
2
,
2
0
0
6
.
[1
5
]
M
.
S
re
e
d
e
v
i,
et
a
l.
,
“
F
u
z
z
y
P
I
c
o
n
tr
o
ll
e
r
b
a
se
d
g
ri
d
-
c
o
n
n
e
c
ted
P
V
sy
ste
m
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
S
o
f
t
Co
mp
u
t
in
g
,
v
o
l
/
issu
e
:
6
(
1
)
,
p
p
.
1
1
–
1
5
,
2
0
1
1
.
[1
6
]
Z.
A
.
G
h
a
n
i,
et
a
l.
,
“
S
im
u
latio
n
m
o
d
e
l
li
n
k
e
d
P
V
in
v
e
rter
im
p
lem
e
n
tatio
n
u
ti
li
z
i
n
g
d
S
P
A
CE
DS
1
1
0
4
c
o
n
tr
o
ll
e
r,
”
En
e
rg
y
a
n
d
Bu
il
d
i
n
g
s
,
v
o
l.
5
7
,
p
p
.
6
5
–
7
3
,
2
0
1
3
.
[1
7
]
A
.
H
m
id
e
t,
et
a
l.
,
“
De
v
e
lo
p
m
e
n
t,
im
p
lem
e
n
tatio
n
a
n
d
e
x
p
e
rime
n
tatio
n
o
n
a
d
S
P
A
CE
DS1
1
0
4
o
f
a
d
irec
t
v
o
lt
a
g
e
c
o
n
tro
l
sc
h
e
m
e
,
”
J
o
u
rn
a
l
o
f
P
o
we
r E
lec
tro
n
ics
,
v
o
l
/i
ss
u
e
:
10
(
5
)
,
p
p
.
4
6
8
–
4
7
6
,
2
0
1
0
.
[1
8
]
M.
A
.
Ha
n
n
a
n
,
et
a
l
.
,
“
A
n
En
h
a
n
c
e
d
In
v
e
rter
Co
n
tro
ll
e
r
f
o
r
P
V
A
p
p
li
c
a
ti
o
n
s
Us
in
g
t
h
e
d
S
P
A
CE
P
latf
o
rm
,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
P
h
o
to
e
n
e
rg
y
,
v
o
l.
2
0
1
0
,
p
p
.
1
-
1
0
,
2
0
1
0
.
[1
9
]
N
.
G
h
a
d
i
m
i,
“
P
I
Co
n
tro
l
ler
De
sig
n
f
o
r
P
h
o
to
v
o
l
taic
S
y
ste
m
s
i
n
Isla
n
d
i
n
g
M
o
d
e
Op
e
ra
ti
o
n
,
”
W
o
rld
Ap
p
li
e
d
S
c
ien
c
e
s Jo
u
rn
a
l
,
v
o
l
/i
ss
u
e
:
15
(
3
)
,
p
p
.
3
2
6
-
3
3
0
,
2
0
1
1
.
[2
0
]
A
.
H
.
M
u
tl
a
g
,
e
t
a
l
.
,
“
A
Na
tu
re
-
In
sp
ired
Op
ti
m
iza
ti
o
n
-
Ba
se
d
Op
ti
m
u
m
F
u
z
z
y
L
o
g
ic
P
h
o
to
v
o
lt
a
ic
In
v
e
rter
Co
n
tr
o
ll
e
r
Util
izi
n
g
a
n
e
Zd
s
p
F
2
8
3
3
5
Bo
a
rd
,
”
En
e
rg
ies
,
v
o
l
/i
ss
u
e
:
9
(
1
2
0
)
,
p
p
.
1
-
3
2
,
2
0
1
6
.
[2
1
]
Z.
W
.
G
e
e
n
,
e
t
a
l.
,
“
A
Ne
w
He
u
r
isti
c
Op
ti
m
iza
ti
o
n
A
lg
o
rit
h
m
:
Ha
rm
o
n
y
S
e
a
rc
h
,
”
S
imu
la
ti
o
n
,
v
o
l
/i
ss
u
e
:
76
(
2
)
,
p
p
.
60
-
6
9
,
2
0
0
1
.
[2
2
]
E
.
T
.
Ya
ss
e
n
,
e
t
a
l
.,
“
Ha
rm
o
n
y
S
e
a
rc
h
A
l
g
o
rit
h
m
f
o
r
V
e
h
icle
Ro
u
ti
n
g
P
ro
b
lem
w
it
h
T
i
m
e
W
in
d
o
w
s,
”
J
o
u
rn
a
l
o
f
Ap
p
li
e
d
S
c
ie
n
c
e
s
,
v
o
l
/i
ss
u
e
:
13
(
4
)
,
p
p
.
6
3
3
-
6
3
8
,
2
0
1
3
.
[2
3
]
D.
M
a
n
jarre
s,
e
t
a
l.
,
“
A
su
rv
e
y
o
n
a
p
p
li
c
a
ti
o
n
s
o
f
th
e
h
a
rm
o
n
y
se
a
rc
h
a
lg
o
rit
h
m
,
”
En
g
in
e
e
rin
g
Ap
p
li
c
a
ti
o
n
s
o
f
Arti
fi
c
ia
l
I
n
telli
g
e
n
c
e
,
v
o
l.
2
6
,
p
p
.
1
8
1
8
–
1
8
3
1
,
2
0
1
3
.
[2
4
]
M.
S.
Ba
k
a
r,
e
t
a
l
.
,
“
Ex
p
e
rim
e
n
tal
S
tu
d
y
o
f
S
BP
W
M
f
o
r
Z
-
S
o
u
rc
e
In
v
e
rter
F
iv
e
P
h
a
se
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Po
we
r E
lec
tro
n
ics
a
n
d
Dr
ive
S
y
ste
m (
IJ
PE
DS
)
,
v
o
l
/i
ss
u
e
:
6
(
1
)
,
p
p
.
4
5
-
5
5
,
2
0
1
5
.
B
I
O
G
RAP
H
I
E
S
O
F
AUTH
O
RS
M
u
sh
ta
q
Na
j
e
e
b
w
a
s
b
o
rn
i
n
1
9
8
2
.
He
is
re
c
e
iv
e
d
h
is
Ba
c
h
e
lo
r
d
e
g
re
e
in
Co
n
tro
l
En
g
i
n
e
e
rin
g
(2
0
0
4
)
f
ro
m
Un
iv
e
r
sit
y
o
f
Tec
h
n
o
l
o
g
y
,
B
a
g
h
d
a
d
,
Ira
q
.
He
a
lso
h
a
s
g
o
t
h
is
M
a
ste
r
d
e
g
re
e
in
e
lec
tri
c
a
l
e
n
g
in
e
e
rin
g
(2
0
1
2
)
f
ro
m
Un
iv
e
rsit
y
T
e
n
a
g
a
Na
sio
n
a
l
(UN
IT
EN),
S
e
lan
g
o
r,
M
a
la
y
si
a
.
He
is
c
u
rre
n
tl
y
a
P
h
D
c
a
n
d
id
a
te
a
t
Un
iv
e
rsiti
M
a
la
y
sia
P
a
h
a
n
g
(UMP
)
.
F
ro
m
2
0
0
5
to
2
0
0
9
,
h
e
w
o
rk
e
d
a
s
lab
o
ra
to
ry
a
ss
istan
t
a
n
d
tu
to
r
a
t
Un
iv
e
rsity
o
f
A
n
b
a
r,
e
lec
tri
c
a
l
e
n
g
in
e
e
rin
g
d
e
p
a
rtm
e
n
t,
Ra
m
a
d
i
,
Ira
q
.
L
a
ter
in
2
0
1
2
,
h
e
w
o
rk
e
d
a
s
a
lec
tu
re
r
a
n
d
th
e
c
o
o
rd
in
a
to
r
o
f
th
e
sa
m
e
d
e
p
a
rtm
e
n
t.
His
re
se
a
rc
h
in
tere
st
s
a
re
r
e
n
e
w
a
b
le
e
n
e
r
g
y
r
e
so
u
rc
e
s
,
c
o
n
tro
l
o
f
p
o
w
e
r
e
lec
tro
n
ics
d
e
v
ice
s
,
m
icro
g
rid
s
s
y
ste
m
s,
a
n
d
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
s.
He
is
a
m
e
m
b
e
r
o
f
Ira
q
i
En
g
in
e
e
rs
Un
io
n
sin
c
e
2
0
0
5
.
Dr
.
H
a
m
d
a
n
Da
n
iy
a
l
(M
'
0
7
)
re
c
e
iv
e
d
th
e
B.
E.
d
e
g
re
e
in
e
lec
tri
c
a
l
&
e
le
c
tro
n
ics
(2
0
0
2
)
f
ro
m
Un
iv
e
rsiti
T
e
k
n
o
lo
g
i
M
a
lay
sia
,
t
h
e
M
.
E.
d
e
g
re
e
in
m
e
c
h
a
tro
n
ics
(2
0
0
4
)
f
ro
m
Ko
lej
Un
iv
e
rsiti
T
e
k
n
o
lo
g
i
T
u
n
Hu
ss
e
in
On
n
a
n
d
th
e
P
h
.
D.
d
e
g
re
e
(2
0
1
1
)
f
ro
m
T
h
e
Un
iv
e
rsit
y
o
f
W
e
ste
rn
A
u
stra
li
a
.
In
2
0
0
2
,
h
e
w
o
rk
e
d
a
s
a
n
E
E
e
n
g
in
e
e
r
a
t
S
m
a
rt
In
d
.
,
a
sw
it
c
h
e
d
m
o
d
e
p
o
w
e
r
su
p
p
ly
m
a
n
u
f
a
c
tu
rin
g
c
o
m
p
a
n
y
.
L
a
ter
in
2
0
0
3
,
h
e
jo
in
e
d
Un
iv
e
rsiti
M
a
lay
sia
P
a
h
a
n
g
(f
o
rm
e
rl
y
k
n
o
w
n
a
s
KU
KT
EM
)
a
s
a
lec
tu
re
r.
Af
te
r
f
in
ish
e
d
h
is
P
h
.
D.
b
y
in
v
e
stig
a
t
in
g
d
ig
it
a
l
c
u
rre
n
t
c
o
n
tr
o
l
f
o
r
p
o
w
e
r
e
lec
tro
n
ics
,
h
e
b
e
c
a
m
e
o
n
e
o
f
th
e
k
e
y
p
e
rso
n
in
S
u
sta
i
n
a
b
l
e
En
e
rg
y
&
P
o
w
e
r
El
e
c
tro
n
ics
Re
se
a
rc
h
(S
u
P
ER)
Cl
u
ste
r,
UM
P
.
His
re
se
a
rc
h
in
tere
st
in
c
lu
d
e
sw
it
c
h
in
g
stra
teg
y
,
n
o
n
li
n
e
a
r
c
o
n
tro
l
a
n
d
d
ig
it
a
l
c
o
n
tro
l
i
n
p
o
w
e
r
e
lec
tro
n
ics
a
p
p
li
c
a
ti
o
n
s
su
c
h
a
s
re
n
e
w
a
b
le
e
n
e
rg
y
,
e
lec
tri
c
v
e
h
icle
,
b
a
tt
e
r
y
m
a
n
a
g
e
m
e
n
t,
p
o
w
e
r
q
u
a
li
t
y
a
n
d
a
c
ti
v
e
p
o
we
r
f
il
ters
.
Dr.
Ha
m
d
a
n
Da
n
i
y
a
l
is
a
m
e
m
b
e
r
o
f
IEE
E
P
o
w
e
r
El
e
c
tro
n
ics
S
o
c
iety
(P
EL
S
)
a
n
d
I
EE
E
In
d
u
strial
El
e
c
tro
n
ics
S
o
c
iety
(IE
S
).
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