I
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o
ne
s
ia
n J
o
urna
l o
f
E
lect
rica
l En
g
ineering
a
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Co
m
pu
t
er
Science
Vo
l.
3
6
,
No
.
2
,
N
o
v
em
b
e
r
20
24
,
p
p
.
7
4
9
~
7
5
9
I
SS
N:
2
502
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7
52
,
DOI
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0
.
1
1
5
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1
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cs
.v
3
6
.
i
2
.
pp
749
-
7
5
9
749
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ttp
:
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cs
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An impro
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Tu
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icle
I
nfo
AB
S
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RAC
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A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Feb
1
,
2
0
2
4
R
ev
is
ed
J
u
n
1
1
,
2
0
2
4
Acc
ep
ted
A
ug
14
,
2
0
2
4
Th
e
fu
tu
re
p
o
we
r
o
f
p
h
o
to
v
o
lt
a
ic
sy
ste
m
s
(P
VS)
is
g
a
in
in
g
sig
n
ifi
c
a
n
t
a
tt
e
n
ti
o
n
d
u
e
to
it
s
risin
g
p
o
ten
ti
a
l.
T
h
is
h
a
s
re
su
lt
e
d
i
n
a
su
b
sta
n
ti
a
l
a
m
o
u
n
t
o
f
re
se
a
rc
h
e
m
p
h
a
siz
in
g
th
e
imp
o
rtan
c
e
o
f
o
p
ti
m
izin
g
t
h
e
P
VS
e
fficie
n
c
y
.
Ho
we
v
e
r,
th
e
id
e
n
ti
fica
ti
o
n
o
f
P
V
c
e
ll
m
o
d
e
l
p
a
ra
m
e
ters
r
e
m
a
in
s
a
c
h
a
ll
e
n
g
i
n
g
tas
k
,
m
a
in
ly
d
u
e
t
o
th
e
c
h
a
ra
c
teristics
o
f
P
V
c
e
ll
s
a
n
d
th
e
ir
d
e
p
e
n
d
e
n
c
e
o
n
v
a
r
y
in
g
m
e
teo
ro
l
o
g
ica
l
c
o
n
d
it
i
o
n
s.
In
th
is
wo
r
k
,
we
p
re
se
n
t
a
n
o
v
e
l
m
e
th
o
d
o
l
o
g
y
b
a
se
d
o
n
a
n
imp
r
o
v
e
d
n
e
w
m
u
lt
i
o
b
jec
ti
v
e
p
a
rti
c
le
sw
a
rm
o
p
ti
m
iza
ti
o
n
(NMOP
S
O
)
a
lg
o
rit
h
m
fo
r
t
h
e
P
V
c
e
ll
p
a
ra
m
e
ters
id
e
n
ti
fica
ti
o
n
.
Th
e
m
a
in
g
o
a
l
is
to
m
in
imiz
e
t
h
e
ro
o
t
m
e
a
n
sq
u
a
re
e
rro
r
(RM
S
E)
a
n
d
to
c
a
lcu
late
th
e
se
ries
re
sista
n
c
e
(Rs)
b
y
m
e
a
n
s
o
f
it
s
n
o
n
-
li
n
e
a
r
e
q
u
a
ti
o
n
fo
rm
.
Th
e
a
p
p
li
e
d
a
l
g
o
r
it
h
m
u
se
s
a
n
e
v
o
lv
in
g
a
n
d
a
d
a
p
ti
v
e
se
a
rc
h
stra
teg
y
to
e
n
h
a
n
c
e
b
o
t
h
sp
e
e
d
o
f
c
o
n
v
e
rg
e
n
c
e
fo
r
th
e
p
a
ra
m
e
ter
id
e
n
ti
fica
ti
o
n
p
r
o
c
e
ss
p
re
c
isio
n
.
Th
r
o
u
g
h
e
x
ten
si
v
e
sim
u
lat
io
n
s,
we
d
e
m
o
n
stra
te
th
a
t
p
r
o
p
o
se
d
a
p
p
ro
a
c
h
o
u
t
p
e
rfo
rm
s
c
u
rre
n
t
m
e
th
o
d
s
in
term
s
o
f
a
c
c
u
ra
c
y
,
p
re
c
isio
n
,
a
n
d
P
V p
a
ra
m
e
ters
e
x
trac
ti
o
n
.
K
ey
w
o
r
d
s
:
NM
OPSO
Par
am
eter
id
en
tific
atio
n
Ph
o
to
v
o
ltaic
ce
lls
Sin
g
le
d
io
d
e
m
o
d
el
So
lar
en
er
g
y
s
y
s
tem
s
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Ali M
an
s
o
u
r
i
L
ab
o
r
ato
r
y
o
f
T
ec
h
n
o
lo
g
y
,
E
n
er
g
y
,
a
n
d
I
n
n
o
v
ativ
e
Ma
ter
ials
,
Facu
lty
o
f
Scien
ce
s
o
f
Gaf
s
a
Un
iv
er
s
ity
o
f
Gaf
s
a
Gaf
s
a,
T
u
n
is
ia
E
m
ail: a
li.m
an
s
o
u
r
i@
is
etg
f
.
r
n
u
.
tn
1.
I
NT
RO
D
UCT
I
O
N
Ov
er
s
ev
er
al
d
ec
ad
es,
th
e
ex
ten
s
iv
e
u
s
e
o
f
f
o
s
s
il
f
u
els
h
as
r
esu
lted
in
co
n
s
id
er
ab
le
en
v
i
r
o
n
m
en
tal
p
o
llu
tio
n
[
1
]
.
T
o
r
e
d
u
ce
en
v
ir
o
n
m
en
tal
p
o
llu
tio
n
,
th
e
in
teg
r
atio
n
o
f
r
e
n
ewa
b
le
en
er
g
y
s
o
u
r
ce
s
is
p
o
is
ed
to
p
lay
a
p
iv
o
tal
r
o
le
in
t
h
e
f
u
tu
r
e.
Am
o
n
g
th
ese
s
o
u
r
ce
s
,
s
o
lar
en
er
g
y
is
a
n
ticip
ated
to
g
ai
n
wid
ely
p
o
p
u
lar
d
u
e
to
its
ea
s
e
o
f
in
s
tallatio
n
,
ze
r
o
em
is
s
io
n
s
,
s
u
s
tain
ab
ilit
y
,
an
d
ec
o
n
o
m
ic
v
iab
ilit
y
[
2
]
.
So
lar
p
o
wer
s
tan
d
s
o
u
t
as
o
n
e
o
f
th
e
m
o
s
t
ab
u
n
d
a
n
t
an
d
ac
ce
s
s
ib
le
f
o
r
m
s
o
f
clea
n
en
er
g
y
[
3
]
,
as
it
ca
n
b
e
c
o
n
n
ec
te
d
in
d
iv
er
s
e
lo
ca
tio
n
s
s
u
ch
as
r
o
o
f
to
p
s
,
s
tr
ee
ts
,
m
o
u
n
tain
s
,
p
r
a
ir
ies,
a
n
d
o
th
er
ar
ea
s
with
v
is
ib
le
s
u
n
lig
h
t
[
4
]
-
[
6
]
.
I
t
is
an
in
teg
r
al
co
m
p
o
n
e
n
t
o
f
r
e
n
ewa
b
le
en
er
g
y
s
o
u
r
ce
s
f
o
r
el
ec
tr
icity
g
en
er
atio
n
,
alo
n
g
s
id
e
g
r
ee
n
en
e
r
g
ies
lik
e
h
y
d
r
o
p
o
wer
,
g
e
o
th
er
m
al,
an
d
win
d
p
o
wer
.
Fu
r
th
er
m
o
r
e,
s
o
lar
en
er
g
y
o
wn
s
a
n
o
tab
le
ad
v
an
ta
g
e
as
it
is
n
o
n
-
ex
p
lo
itativ
e
a
n
d
e
n
v
ir
o
n
m
en
t
ally
f
r
ien
d
l
y
,
co
n
tr
ib
u
tin
g
to
a
m
o
r
e
s
u
s
tain
ab
le
an
d
ec
o
-
c
o
n
s
cio
u
s
f
u
t
u
r
e
[
3
]
,
[
6
]
,
[
7
]
.
W
h
ile
p
r
ev
io
u
s
s
tu
d
ies
h
av
e
e
x
ten
s
iv
ely
ex
p
lo
r
ed
th
e
a
d
v
an
tag
es
an
d
p
o
ten
tial
o
f
s
o
lar
en
er
g
y
as
a
r
en
ewa
b
le
en
e
r
g
y
s
o
u
r
ce
,
th
er
e
s
till
ex
is
t
n
o
tab
le
g
ap
s
in
o
u
r
u
n
d
er
s
tan
d
in
g
an
d
ap
p
licatio
n
o
f
t
h
is
tech
n
o
lo
g
y
.
T
h
e
ef
f
icien
c
y
an
d
p
er
f
o
r
m
a
n
ce
o
f
p
h
o
to
v
o
ltaic
(
PV
)
s
y
s
tem
s
ar
e
s
ig
n
if
ican
tly
d
ep
e
n
d
en
t
o
n
th
e
p
r
ec
is
e
esti
m
atio
n
o
f
PV
ce
ll
p
ar
am
eter
s
[
8
]
.
I
n
th
e
f
ield
o
f
PV
m
o
d
u
le
s
,
th
e
p
a
r
am
ete
r
s
esti
m
atio
n
o
f
PV
ce
lls
is
a
ch
allen
g
e
task
d
u
e
to
its
d
if
f
icu
lt
b
eh
av
i
o
r
an
d
th
e
n
u
m
er
o
u
s
o
f
i
n
v
o
lv
e
d
v
ar
iab
les.
T
h
is
task
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
6
,
No
.
2
,
No
v
em
b
er
20
24
:
7
4
9
-
7
5
9
750
r
eq
u
ir
es
p
r
ec
is
e
m
ea
s
u
r
e
m
en
ts
to
co
n
s
id
er
d
if
f
er
en
t
f
ac
t
o
r
s
s
u
ch
as
n
o
n
-
lin
ea
r
ity
an
d
v
ar
iab
ilit
y
am
o
n
g
p
ar
am
eter
s
.
Fu
r
th
er
m
o
r
e,
o
p
tim
izin
g
en
er
g
y
co
n
v
e
r
s
io
n
ef
f
icien
cy
with
in
PV
s
y
s
tem
s
is
b
ased
o
n
ac
cu
r
ate
p
ar
am
eter
esti
m
atio
n
.
T
h
u
s
,
a
cc
u
r
ate
p
ar
a
m
eter
esti
m
atio
n
is
p
iv
o
tal
f
o
r
en
s
u
r
in
g
th
e
o
p
tim
al
p
er
f
o
r
m
an
ce
an
d
s
u
s
tain
ab
ilit
y
o
f
p
h
o
to
v
o
lt
aic
s
y
s
tem
s
(
PVS
)
in
h
ar
n
e
s
s
i
n
g
s
o
lar
p
o
wer
.
R
esear
ch
er
s
ar
e
co
n
tin
u
ally
s
tr
iv
in
g
to
en
h
an
ce
th
e
ac
cu
r
ac
y
o
f
th
eir
m
o
d
els.
T
h
i
s
in
v
o
lv
es
im
p
r
o
v
in
g
t
h
e
m
at
h
em
atica
l
f
r
am
ewo
r
k
s
u
s
ed
to
d
escr
ib
e
P
V
m
o
d
u
les.
A
c
r
u
cial
asp
ec
t
o
f
th
is
s
ea
r
c
h
is
th
e
ev
alu
atio
n
o
f
PV
p
ar
am
eter
s
.
So
m
e
s
tu
d
i
es
ap
p
ly
m
ath
e
m
atica
l
tech
n
iq
u
es,
w
h
ile
o
t
h
er
s
u
s
e
n
u
m
er
ical
an
aly
s
es
to
s
o
lv
e
co
m
p
lex
an
d
n
o
n
-
lin
ea
r
eq
u
atio
n
s
.
No
tab
ly
,
th
e
in
teg
r
atio
n
o
f
m
etah
e
u
r
is
tic
m
eth
o
d
s
o
f
f
er
s
ef
f
icien
t
s
o
lu
tio
n
s
co
m
p
ar
ed
to
tr
ad
itio
n
al
ap
p
r
o
ac
h
es,
f
u
r
th
er
en
h
an
cin
g
th
e
m
o
d
eli
n
g
ac
cu
r
ac
y
o
f
PV
s
y
s
tem
s
.
Hu
s
s
ein
[
9
]
,
s
u
g
g
ested
an
iter
ativ
e
tech
n
iq
u
e
b
ased
o
n
th
e
New
to
n
–
R
ap
h
s
o
n
m
eth
o
d
to
ex
tr
ac
t
th
e
s
in
g
le
-
d
io
d
e
p
a
r
am
eter
s
.
T
h
e
f
u
n
d
a
m
en
tal
id
ea
o
f
th
is
m
eth
o
d
is
to
estab
lis
h
f
o
u
r
e
q
u
a
tio
n
s
b
ased
o
n
th
e
r
em
ar
k
ab
le
p
o
in
ts
as
f
u
n
ctio
n
s
o
f
th
e
f
iv
e
p
ar
am
eter
s
.
A
cl
o
s
ed
-
f
o
r
m
ex
p
r
ess
io
n
is
th
en
d
er
iv
ed
to
ca
lcu
late
th
e
v
alu
e
o
f
(
R
s
)
wh
ile
in
cr
em
en
tin
g
th
e
id
ea
lity
f
ac
to
r
’
s
v
alu
e.
T
h
e
ap
p
r
o
ac
h
u
s
ed
in
[
9
]
s
tan
d
s
o
u
t
f
o
r
its
im
p
r
o
v
e
d
co
m
p
u
tatio
n
al
r
esu
lts
,
r
ep
r
esen
tin
g
a
s
ig
n
if
ican
t
im
p
r
o
v
em
e
n
t
in
p
r
ec
is
io
n
co
m
p
ar
ed
to
ex
is
tin
g
liter
atu
r
e.
Nd
eg
wa
et
a
l.
[
1
0
]
,
a
p
r
ec
is
e
an
d
ef
f
icien
t
a
n
aly
tical
m
eth
o
d
was
in
tr
o
d
u
ce
d
f
o
r
p
ar
am
eter
p
r
ed
ictio
n
.
T
h
is
m
eth
o
d
,
b
as
ed
o
n
d
ata
p
r
o
v
id
ed
b
y
th
e
m
an
u
f
ac
tu
r
er
,
aim
s
to
s
im
p
li
f
y
th
e
ca
lcu
latio
n
tech
n
iq
u
e
f
o
r
ev
alu
atin
g
th
e
i
d
ea
lity
f
ac
to
r
.
T
h
e
u
s
e
o
f
p
ar
t
icle
s
war
m
o
p
tim
izatio
n
(
PS
O
)
in
[
1
1
]
le
d
to
th
e
ac
h
iev
em
en
t
o
f
r
em
ar
k
a
b
ly
lo
w
r
o
o
t
m
ea
n
s
q
u
a
r
e
er
r
o
r
(
R
MSE
)
v
alu
es
in
p
ar
am
eter
ex
tr
ac
tio
n
with
m
in
im
u
m
co
m
p
u
tatio
n
tim
e.
T
h
is
p
er
f
o
r
m
an
ce
s
ig
n
if
ica
n
t
ly
s
u
r
p
ass
ed
co
m
p
etin
g
m
eth
o
d
o
l
o
g
ies
an
d
co
m
p
u
tatio
n
al
alg
o
r
it
h
m
s
.
T
h
e
f
in
d
in
g
s
s
h
o
ws
th
e
s
u
b
s
tan
tial
p
o
ten
tial
o
f
PS
O
in
d
eter
m
in
in
g
s
o
lar
ce
ll
p
ar
am
eter
s
.
Saad
ao
u
i
et
a
l.
[
1
2
]
,
a
n
in
n
o
v
ativ
e
m
et
h
o
d
b
ased
o
n
th
e
m
u
ltip
le
lear
n
in
g
J
AYA
alg
o
r
ith
m
is
p
r
esen
t
ed
f
o
r
e
x
tr
ac
tin
g
th
e
p
ar
am
eter
s
f
r
o
m
PV
m
o
d
els.
T
h
is
ap
p
r
o
ac
h
in
teg
r
ates
ad
ap
tiv
e
weig
h
tin
g
to
ac
ce
ler
ate
th
e
ex
p
lo
r
atio
n
o
f
p
o
ten
tial
s
ea
r
ch
s
p
ac
es
an
d
im
p
r
o
v
i
n
g
th
e
ef
f
icien
c
y
o
f
p
ar
am
eter
ex
tr
ac
tio
n
tech
n
iq
u
es.
W
an
g
[
1
3
]
,
s
u
g
g
ested
th
e
u
s
e
o
f
th
e
E
PS
O
alg
o
r
ith
m
to
m
in
im
ize
th
e
m
ea
n
s
q
u
ar
ed
er
r
o
r
b
etwe
en
m
ea
s
u
r
ed
an
d
esti
m
ated
d
ata.
L
id
ai
g
h
b
i
et
a
l.
[
1
4
]
ap
p
lied
a
h
y
b
r
id
an
al
y
tical/iter
ativ
e
m
eth
o
d
,
with
th
e
g
o
al
o
f
m
in
im
izin
g
d
is
p
ar
ities
b
etwe
en
ca
lcu
lated
an
d
ex
p
er
im
en
tal
d
ata,
r
esu
ltin
g
in
r
em
ar
k
a
b
le
ac
cu
r
ac
y
th
at
o
u
tp
er
f
o
r
m
e
d
o
th
er
tech
n
iq
u
es.
T
h
e
im
p
r
o
v
e
d
f
ir
ef
ly
alg
o
r
ith
m
(
I
FA)
was
ap
p
lied
in
[
1
5
]
to
p
r
o
f
icien
tly
ex
tr
ac
t
t
h
e
u
n
id
e
n
tifie
d
p
ar
a
m
eter
s
o
f
PV
s
o
lar
ce
lls
,
p
r
ec
is
ely
a
d
ju
s
tin
g
th
e
g
lo
b
al
m
ax
im
u
m
p
o
wer
p
o
in
t
(
GM
PP
)
in
PV
p
an
els.
T
h
is
m
eth
o
d
o
lo
g
y
i
n
tr
o
d
u
ce
d
a
n
o
v
el
ap
p
r
o
ac
h
to
o
p
tim
ize
e
n
er
g
y
p
r
o
d
u
ctio
n
with
in
PVS
.
C
h
o
u
lli
et
a
l.
[
1
6
]
,
a
n
o
v
el
h
y
b
r
i
d
an
aly
tical/iter
ativ
e
m
eth
o
d
o
l
o
g
y
was
ap
p
lied
to
ex
tr
ac
t
p
ar
am
ete
r
s
o
f
th
e
s
in
g
le
d
io
d
e
m
o
d
el
(
SDM)
.
T
h
i
s
tech
n
iq
u
e
is
b
ased
o
n
th
e
L
am
b
er
t
f
u
n
ct
io
n
to
r
eso
lv
e
th
e
n
o
n
lin
ea
r
eq
u
ati
o
n
f
o
r
(
R
s
)
.
I
t
lead
s
to
a
s
i
g
n
if
ican
tly
im
p
r
o
v
ed
R
MSE
co
m
p
ar
ed
to
o
th
e
r
m
eth
o
d
s
.
T
h
e
p
r
im
ar
y
aim
is
to
m
in
im
ize
th
e
a
v
er
ag
e
e
r
r
o
r
b
etwe
en
s
im
u
lated
an
d
e
x
p
er
i
m
en
tal
cu
r
r
e
n
ts
.
L
o
n
g
et
a
l.
[
1
7
]
,
u
s
ed
a
h
y
b
r
id
alg
o
r
ith
m
,
n
am
ely
th
e
g
r
ey
wo
lf
o
p
tim
izer
an
d
cu
c
k
o
o
s
ea
r
ch
(
GW
OC
S),
to
ad
d
r
ess
v
ar
io
u
s
o
p
tim
izatio
n
ch
allen
g
es
ass
o
ciate
d
with
p
ar
am
ete
r
ex
tr
ac
tio
n
in
f
o
u
r
d
is
tin
ct
PV
s
o
lar
ce
ll
m
o
d
els.
T
h
is
h
y
b
r
id
m
et
h
o
d
n
o
t
o
n
ly
aim
e
d
to
elev
ate
th
e
o
v
er
all
o
p
tim
izatio
n
s
tan
d
ar
d
s
b
u
t
also
s
p
ec
if
ically
d
ev
elo
p
ed
th
e
GW
OC
S
to
tack
le
g
lo
b
al
o
p
tim
izatio
n
p
r
o
b
lem
s
an
d
ex
tr
a
ct
p
ar
am
eter
s
f
r
o
m
s
ev
er
al
s
o
lar
PV c
ell
m
o
d
els u
n
d
er
d
if
f
e
r
en
t o
p
e
r
atin
g
co
n
d
itio
n
s
,
wh
ile
attem
p
tin
g
to
s
o
lv
e
th
e
(
R
s
)
eq
u
atio
n
.
Sh
a
r
m
a
an
d
T
r
ip
at
h
i
[
1
8
]
,
c
o
m
p
ar
ed
t
o
tr
ad
itio
n
al
m
eth
o
d
s
,
m
etah
eu
r
is
tic
tech
n
iq
u
es
h
av
e
d
em
o
n
s
tr
ated
s
u
p
er
io
r
p
er
f
o
r
m
an
ce
.
Du
e
to
th
eir
ea
s
e
o
f
im
p
lem
en
tatio
n
an
d
ef
f
icien
c
y
,
th
ese
m
eth
o
d
s
a
r
e
s
u
itab
le
f
o
r
s
o
lv
in
g
n
o
n
-
lin
ea
r
o
p
tim
izatio
n
p
r
o
b
lem
s
as (
R
s
)
eq
u
atio
n
.
Ou
r
p
r
o
p
o
s
ed
m
eth
o
d
,
b
ased
o
n
n
ew
m
u
lti
o
b
jectiv
e
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
N
MO
PS
O
)
alg
o
r
ith
m
,
in
t
r
o
d
u
ce
d
in
2
0
2
2
[
1
9
]
,
r
ep
r
esen
ts
a
n
o
v
el
ap
p
r
o
ac
h
th
at
h
as
d
e
m
o
n
s
tr
ated
r
e
m
ar
k
ab
le
r
esu
lts
in
th
e
d
o
m
ain
o
f
elec
tr
ic
m
o
to
r
s
p
ar
am
eter
s
o
p
tim
izatio
n
.
T
h
is
alg
o
r
ith
m
s
tan
d
s
o
u
t
f
o
r
its
ab
ilit
y
to
ef
f
icien
tly
s
o
lv
e
n
o
n
-
lin
ea
r
eq
u
atio
n
s
w
ith
in
m
in
im
al
co
m
p
u
tatio
n
tim
e.
No
tab
ly
,
its
ap
p
licatio
n
h
as
s
u
r
p
ass
ed
th
e
p
er
f
o
r
m
an
ce
o
f
co
n
v
en
tio
n
al
PS
O
an
d
v
ar
io
u
s
en
h
a
n
ce
d
P
SO
v
ar
ian
ts
.
T
h
e
p
r
esen
t
s
tu
d
y
in
v
esti
g
ated
th
e
id
en
tific
atio
n
o
f
th
e
PV
ce
ll
p
ar
am
eter
s
b
y
m
ea
n
s
o
f
th
e
NM
OPSO
alg
o
r
ith
m
.
T
o
ac
h
iev
e
th
is
g
o
al,
a
n
o
p
tim
izatio
n
p
r
o
ce
s
s
,
in
v
o
lv
i
n
g
two
o
b
jectiv
e
f
u
n
ctio
n
s
,
is
ap
p
lied
.
T
h
e
f
ir
s
t
o
b
jectiv
e
f
u
n
ctio
n
aim
s
to
m
in
im
ize
th
e
R
MSE
,
wh
ile
th
e
s
ec
o
n
d
ca
lc
u
lates
th
e
s
er
ies
r
esis
tan
ce
(
R
s
)
b
y
u
s
in
g
its
n
o
n
-
lin
ea
r
eq
u
atio
n
f
o
r
m
.
T
h
is
tech
n
iq
u
e
is
b
ased
o
n
an
ad
ap
tiv
e
an
d
s
ca
lab
le
s
ea
r
ch
s
tr
ateg
y
.
T
o
ev
alu
ate
th
e
ef
f
ec
tiv
e
n
ess
o
f
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
,
d
ee
p
s
im
u
latio
n
s
,
an
d
co
m
p
ar
is
o
n
s
with
s
tate
o
f
ar
t
tech
n
iq
u
es
h
av
e
b
ee
n
co
n
d
u
cted
.
T
h
e
r
e
m
ain
d
er
o
f
th
is
p
ap
er
i
s
s
tr
u
ctu
r
ed
as
f
o
llo
ws:
t
h
e
P
V
ce
ll
m
o
d
ellin
g
b
ased
o
n
SDM
is
d
escr
ib
ed
in
s
ec
tio
n
2
.
I
n
s
ec
tio
n
3
,
we
d
ef
in
e
th
e
o
p
tim
izatio
n
p
r
o
b
lem
a
n
d
in
tr
o
d
u
ce
th
e
u
s
ed
alg
o
r
ith
m
.
T
h
e
o
p
tim
izatio
n
r
esu
lts
an
d
th
e
d
i
s
cu
s
s
io
n
ar
e
p
r
esen
ted
in
s
ec
ti
o
n
4
.
Fin
ally
,
we
f
in
is
h
b
y
a
c
o
n
clu
s
io
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
A
n
imp
r
o
ve
d
P
S
O
-
b
a
s
ed
a
p
p
r
o
a
ch
fo
r
th
e
p
h
o
t
o
vo
lta
ic
ce
ll
p
a
r
a
mete
r
s
…
(
Ma
r
ia
A
ma
id
i
)
751
2.
P
V
CE
L
L
M
O
D
E
L
L
I
NG
:
S
I
NG
L
E
DIOD
E
M
O
D
E
L
T
h
e
u
s
e
o
f
th
e
SDM
s
h
o
ws
a
g
o
o
d
ac
cu
r
ac
y
in
m
o
d
ell
in
g
elec
tr
ical
f
ea
tu
r
es
o
f
d
if
f
er
en
t
PV
ce
ll/mo
d
u
les
v
ar
ian
ts
u
n
d
er
v
ar
io
u
s
en
v
ir
o
n
m
en
tal
co
n
d
itio
n
s
.
As
s
h
o
wn
in
Fig
u
r
e
1
,
th
is
m
o
d
el
co
n
s
is
ts
o
f
a
p
ar
allel
ar
r
an
g
em
e
n
t
o
f
a
d
io
d
e
an
d
a
co
n
s
tan
t
cu
r
r
en
t
s
o
u
r
ce
o
f
en
er
g
y
.
W
h
en
ex
p
o
s
ed
to
s
u
n
lig
h
t,
th
e
PV
ce
ll p
r
o
d
u
ce
s
a
lig
h
t c
u
r
r
en
t.
T
h
is
cu
r
r
en
t is d
eter
m
in
e
d
b
y
a
p
p
ly
in
g
th
e
Kir
ch
h
o
f
f
’
s
law.
=
ℎ
−
−
ℎ
(
1
)
W
h
er
e:
=
0
[
(
+
)
−
1
]
(
2
)
ℎ
=
+
ℎ
(
3
)
Fig
u
r
e
1
.
E
q
u
iv
alen
t c
ir
c
u
it o
f
SDM
C
o
n
s
eq
u
en
tly
,
we
ca
n
m
o
d
if
y
(
1
)
as:
=
ℎ
−
0
[
(
+
)
−
1
]
−
+
ℎ
(
4
)
w
h
er
e
(
I
0
)
,
(
I
ph
)
,
(
n
)
,
(
R
sh
)
an
d
(
R
s
)
r
ep
r
esen
t:
t
h
e
s
atu
r
atio
n
cu
r
r
en
t
o
f
th
e
d
io
d
e,
th
e
p
h
o
t
o
-
g
en
er
ated
cu
r
r
en
t
,
th
e
d
io
d
e
i
d
ea
lity
f
ac
to
r
,
th
e
s
h
u
n
t,
a
n
d
R
s
.
T
h
e
o
u
tp
u
t v
o
ltag
e,
(
V
t
)
,
is
ex
p
r
ess
ed
as
(
5
)
:
V
t
=
q
(
5
)
(
T
)
is
th
e
PV m
o
d
u
le
tem
p
e
r
at
u
r
e
in
Kelv
in
,
with
=
1
.
602
∗
10
−
19
an
d
=
1
.
3806
∗
10
−
23
/
2
.
1
.
P
V
ce
ll pa
r
a
m
et
er
s
identif
ica
t
io
n m
e
t
ho
ds
2
.
1
.
1
.
P
ho
t
o
curr
ent
(
I
ph
)
B
ased
o
n
m
an
u
f
ac
tu
r
er
’
s
s
p
ec
if
icatio
n
s
r
eg
ar
d
in
g
th
e
s
h
o
r
t
cir
cu
it
co
n
d
itio
n
at
s
tan
d
ar
d
test
co
n
d
itio
n
s
(
STC),
th
e
ca
lcu
lat
io
n
o
f
th
e
lig
h
t
-
g
en
e
r
ated
c
u
r
r
en
t
(
I
ph
)
is
p
er
f
o
r
m
ed
.
T
h
e
o
b
t
ain
ed
ex
p
r
ess
io
n
is
ca
lcu
lated
b
y
u
s
in
g
th
e
s
h
o
r
t c
ir
cu
it c
o
n
d
itio
n
s
(
V
=
0
; I
=
I
sc
)
in
(
4
)
.
=
ℎ
−
0
[
(
)
−
1
]
−
ℎ
(
6
)
Sin
ce
th
e
v
alu
e
o
f
(
R
s
)
is
ex
ce
p
tio
n
ally
lo
w
[
1
4
]
,
th
e
f
o
llo
win
g
ex
p
r
ess
io
n
is
d
er
i
v
ed
:
ℎ
=
+
ℎ
ℎ
(
7
)
2
.
1
.
2
.
Dio
de
s
a
t
ura
t
io
n c
urre
nt
(I
0
)
T
h
e
ex
p
r
ess
io
n
is
d
er
iv
ed
b
y
s
u
b
s
titu
tin
g
th
e
o
p
en
cir
c
u
it c
o
n
d
itio
n
s
(
I
=0
; V
=V
oc
)
i
n
(
4
)
.
0
=
ℎ
−
ℎ
(
)
−
1
(
8
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
6
,
No
.
2
,
No
v
em
b
er
20
24
:
7
4
9
-
7
5
9
752
2
.
1
.
3
.
P
a
ra
llel
r
esis
t
a
nce
(
R
sh
)
I
n
th
is
s
tu
d
y
,
we
a
p
p
ly
th
e
(
R
sh
)
in
(
9
)
,
o
r
i
g
in
ally
g
iv
e
n
b
y
[
1
2
]
:
R
sh
=
V
OC
(
ex
p
(
V
mp
+
I
mp
R
s
n
V
t
)
−
ex
p
(
I
sc
R
s
n
V
t
)
)
−
V
mp
(
ex
p
(
V
oc
n
V
t
)
)
−
ex
p
(
I
sc
R
s
n
V
t
)
I
mp
(
ex
p
(
V
oc
n
V
t
)
)
−
ex
p
(
I
sc
R
s
n
V
t
)
)
−
I
sc
(
ex
p
(
V
oc
n
V
t
)
)
−
ex
p
(
V
mp
+
I
mp
R
s
n
V
t
)
−
R
s
(
9
)
2
.
1
.
4
.
T
he
s
er
ies
re
s
is
t
a
nce
(
R
s
)
T
o
ca
lcu
late
th
e
R
s
in
th
e
SDM
o
f
a
s
o
lar
p
a
n
el,
th
e
(
1
0
)
ca
n
b
e
u
s
ed
[
1
4
]
:
e
xp
(
(
+
)
−
)
=
(
2
−
)
+
(
−
)
(
−
)
−
(
−
)
(
1
0
)
2
.
1
.
5
.
Dio
de
idea
lity
f
a
c
t
o
r
(
n)
I
n
p
r
ac
tice,
th
e
id
ea
lity
f
ac
to
r
(
n
)
ca
n
b
e
e
x
p
r
ess
ed
as
a
f
u
n
ctio
n
o
f
th
e
ce
ll
v
o
ltag
e,
an
d
i
t
d
ep
en
d
s
o
n
tem
p
er
atu
r
e,
ce
ll
’
s
PV
m
o
d
u
le
n
u
m
b
er
,
an
d
v
o
ltag
e
v
ar
iatio
n
s
.
I
n
t
h
is
s
tu
d
y
,
a
n
o
v
el
iter
ativ
e
m
eth
o
d
is
in
tr
o
d
u
ce
d
to
ca
lc
u
late
th
e
id
e
ality
f
ac
to
r
(
n
)
,
b
ased
o
n
th
e
r
esu
lts
s
h
o
wn
in
[
1
4
]
.
T
h
is
ap
p
r
o
ac
h
e
n
h
an
ce
s
th
e
r
eliab
ilit
y
o
f
ca
lcu
latin
g
t
h
is
p
ar
am
eter
.
I
t is ex
p
r
ess
ed
b
y
(
1
1
)
.
=
0
+
0
.
01
(
1
1
)
C
h
eg
aa
r
et
a
l.
[
2
0
]
,
it
was
d
e
m
o
n
s
tr
ated
th
at
th
e
id
ea
lity
f
a
cto
r
is
co
n
tin
g
en
t
o
n
th
e
in
ten
s
ity
o
f
t
h
e
ir
r
ad
iatio
n
,
in
c
r
ea
s
in
g
lin
ea
r
ly
with
r
ad
iatio
n
lev
els ab
o
v
e
3
5
0
W
/m
2
.
T
h
er
ef
o
r
e,
we
ca
n
m
o
d
if
y
th
e
(
1
1
)
b
y
:
=
0
+
0
.
01
+
/
(
1
2
)
w
h
er
e
(
n
0
)
is
th
e
id
ea
lity
f
ac
t
o
r
in
itial
v
alu
e,
(
k
)
is
a
co
ef
f
icien
t
r
ep
r
esen
tin
g
t
h
e
in
f
lu
e
n
ce
o
f
s
o
lar
ir
r
ad
ia
n
ce
o
n
(
n
)
,
(
G
)
is
th
e
s
o
lar
i
r
r
ad
i
an
ce
.
T
h
is
r
elatio
n
s
h
ip
s
u
g
g
e
s
ts
th
at
th
e
id
ea
lity
f
ac
to
r
(
n
)
ca
n
s
lig
h
tly
ch
an
g
e
with
v
ar
iatio
n
s
in
s
o
lar
ir
r
ad
ian
ce
an
d
tem
p
er
atu
r
e.
Alth
o
u
g
h
th
ese
in
f
lu
en
ce
s
ar
e
r
ela
tiv
ely
s
m
all,
th
ey
co
n
tr
ib
u
te
to
ac
h
iev
in
g
m
o
r
e
a
cc
u
r
ate
r
esu
lts
.
3.
M
UL
T
I
-
O
B
J
E
C
T
I
V
E
O
P
T
I
M
I
Z
AT
I
O
N
P
RO
CE
SS
Sto
ch
asti
c
o
p
tim
izatio
n
alg
o
r
ith
m
s
p
lay
a
k
ey
r
o
le
in
s
o
lv
in
g
co
m
p
lex
PV
ce
ll
p
r
o
b
le
m
s
.
I
n
th
is
s
ec
tio
n
,
th
e
o
p
tim
izatio
n
p
r
o
b
lem
is
d
ef
in
ed
b
y
in
tr
o
d
u
c
in
g
d
ec
is
io
n
v
ar
ia
b
les
an
d
s
p
ec
if
y
in
g
t
h
e
two
o
b
jectiv
e
f
u
n
ctio
n
s
.
T
h
e
d
e
cisi
o
n
v
ar
iab
les
ar
e
d
e
r
iv
e
d
f
r
o
m
th
e
p
ar
am
eter
s
o
f
th
e
SDM
cir
cu
it.
Su
b
s
eq
u
en
tly
,
two
o
b
jectiv
e
f
u
n
ctio
n
s
ar
e
id
en
tifie
d
:
th
e
f
ir
s
t
aim
ed
to
s
o
lv
e
th
e
n
o
n
lin
ea
r
eq
u
atio
n
f
o
r
th
e
R
s
,
wh
ile
th
e
s
ec
o
n
d
aim
e
d
to
m
in
im
ize
th
e
(
R
MSE
)
.
T
o
co
n
d
u
ct
s
im
u
latio
n
s
,
we
i
m
p
lem
en
ted
th
e
NM
OPSO
a
lg
o
r
ith
m
u
s
in
g
“
E
clip
s
e
”
s
o
f
twar
e
an
d
J
AVA
p
r
o
g
r
am
m
in
g
lan
g
u
a
g
e.
W
e
ex
tr
ac
ted
th
e
p
ar
a
m
eter
s
o
b
tain
ed
f
r
o
m
th
e
NM
O
PS
O
alg
o
r
ith
m
an
d
ap
p
lied
th
em
to
th
e
cir
cu
it
o
f
th
e
SDM
u
s
in
g
MA
T
L
AB
/S
im
u
lin
k
.
T
h
is
s
tep
was
cr
u
cial
in
v
alid
atin
g
th
e
r
esu
lts
o
b
tain
ed
f
r
o
m
th
e
o
p
ti
m
izatio
n
p
r
o
ce
s
s
.
3
.
1
.
Dec
is
io
n v
a
ria
bles
T
h
e
d
ec
is
io
n
v
ar
iab
les
o
f
th
is
o
p
tim
izatio
n
p
r
o
b
lem
ar
e
th
e
f
iv
e
p
ar
am
eter
s
(
R
s
)
,
(
R
sh
)
,
(
I
0
)
,
(
I
ph
)
,
an
d
(
n
)
.
T
a
b
le
1
p
r
o
v
i
d
es th
e
v
ar
ia
tio
n
r
an
g
es f
o
r
ea
c
h
p
ar
am
ete
r
o
f
ea
ch
ce
ll.
T
ab
le
1
.
Dec
is
io
n
v
a
r
iab
les
B
P
5
1
7
0
S
S
TM
6
4
0
/
3
6
P
h
o
t
o
w
a
t
t
-
P
W
P
2
0
1
R
TC
F
r
P
V
M
7
5
2
G
a
A
s
S
TM
6
1
2
0
/
3
6
R
s
(
Ω
)
[
0
,
1
]
[
0
,
1
]
[
0
,
1
]
[
0
,
1
]
[
0
,
1
]
[
0
,
1
]
R
sh
(
Ω
)
[
1
0
0
,
4
0
0
]
[
1
0
0
,
6
0
0
]
[
3
0
0
,
8
0
0
]
[
0
,
1
0
0
]
[
3
0
0
,
8
0
0
]
[
1
0
0
,
4
0
0
]
I
0
(
A
)
[
0
,
1
]
[
0
,
1
]
[
0
,
1
]
[
0
,
1
]
[
0
,
1
]
[
0
,
1
]
I
ph
(A)
[
0
,
1
0
]
[
0
,
1
0
]
[
0
,
1
0
]
[
0
,
5
]
[
0
,
1
]
[
0
,
1
0
]
N
[
1
,
2
]
[
1
,
2
]
[
1
,
2
]
[
1
,
2
]
[
1
,
2
]
[
1
,
2
]
3
.
2
.
O
bje
c
t
iv
e
f
un
ct
io
ns
As
p
r
ev
io
u
s
ly
m
en
tio
n
ed
,
o
u
r
s
tu
d
y
f
o
c
u
s
es
o
n
two
o
b
jecti
v
e
f
u
n
ctio
n
s
:
th
e
f
ir
s
t
aim
s
to
m
in
im
ize
th
e
R
MSE
f
o
r
ea
ch
PV
ce
l
l,
wh
ile
th
e
s
ec
o
n
d
aim
s
to
ca
lc
u
late
th
e
R
s
.
T
h
e
eq
u
atio
n
d
et
er
m
in
in
g
th
e
R
s
is
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
A
n
imp
r
o
ve
d
P
S
O
-
b
a
s
ed
a
p
p
r
o
a
ch
fo
r
th
e
p
h
o
t
o
vo
lta
ic
ce
ll
p
a
r
a
mete
r
s
…
(
Ma
r
ia
A
ma
id
i
)
753
n
o
n
lin
ea
r
.
Var
i
o
u
s
m
eth
o
d
s
h
av
e
b
ee
n
ex
p
lo
r
ed
i
n
th
e
liter
a
tu
r
e
to
ap
p
r
o
x
im
ate
(
R
s
)
,
in
clu
d
in
g
th
e
u
tili
za
tio
n
o
f
th
e
L
am
b
er
t
f
u
n
ctio
n
as
r
ef
er
en
ce
d
in
[
1
6
]
.
I
n
o
u
r
wo
r
k
,
we
ap
p
ly
th
e
NM
OPSO
alg
o
r
ith
m
.
T
h
e
ex
p
r
ess
io
n
f
o
r
th
e
f
ir
s
t o
b
jectiv
e
f
u
n
ctio
n
is
as f
o
llo
ws:
1
=
(
)
(
1
3
)
t
h
e
R
MSE
is
g
iv
en
b
y
:
=
1
√
∑
(
−
)
2
=
1
(
1
4
)
(
I
measured
)
an
d
(
I
cal
)
ar
e
th
e
m
ea
s
u
r
ed
an
d
esti
m
ated
c
u
r
r
en
ts
.
T
h
e
eq
u
atio
n
r
e
p
r
esen
tin
g
th
e
R
s
h
as
a
n
o
n
-
lin
ea
r
f
o
r
m
.
T
h
er
ef
o
r
e,
to
f
in
d
R
s
,
it
is
n
ec
ess
ar
y
to
s
im
p
lify
its
ex
p
r
ess
io
n
at
f
ir
s
t.
B
ased
o
n
(
1
0
)
,
we
ca
n
d
er
iv
e
th
e
f
o
llo
win
g
e
x
p
r
ess
io
n
:
=
(
ln
(
(
2
−
)
+
(
−
)
(
−
)
−
(
−
)
)
−
(
−
)
)
(1
5)
e
ith
er
:
(
ln
(
(
2
−
)
+
(
−
)
(
−
)
−
(
−
)
)
−
(
−
)
)
=
1
(
1
6
)
f
o
r
s
im
p
lify
in
g
ca
lcu
latio
n
,
we
ass
u
m
e
two
au
x
iliar
y
v
ar
iab
les
(
A
)
an
d
(
B
)
th
at
r
esp
e
ctiv
ely
r
ep
r
esen
t
th
e
n
u
m
er
ato
r
an
d
th
e
d
en
o
m
i
n
ato
r
o
f
(
1
6
)
.
T
h
e
o
p
tim
izatio
n
alg
o
r
ith
m
aim
s
to
id
en
tify
o
p
tim
al
v
alu
es
o
f
R
s
,
en
s
u
r
in
g
th
at
th
e
r
atio
(
A/B
)
ap
p
r
o
x
im
ates
a
v
alu
e
clo
s
e
to
1
.
T
h
er
ef
o
r
e,
th
e
s
ec
o
n
d
o
b
jectiv
e
f
u
n
ctio
n
ca
n
b
e
ex
p
r
ess
ed
as
(
1
7
)
.
2
=
(
1
−
A
/
B
)
(
1
7
)
3
.
3
.
Used o
ptim
iza
t
io
n a
lg
o
r
it
hm
T
h
e
in
v
esti
g
ated
m
et
h
o
d
u
s
es
a
r
ec
en
tly
d
e
v
elo
p
e
d
alg
o
r
ith
m
k
n
o
w
n
as
NM
OPSO
[
1
9
]
.
T
h
is
s
to
ch
asti
c
alg
o
r
ith
m
en
co
m
p
ass
es
a
r
an
d
o
m
ized
p
r
o
ce
s
s
f
o
r
g
en
er
atin
g
p
o
in
ts
with
in
th
e
s
ea
r
ch
s
p
ac
e,
co
u
p
led
with
a
h
e
u
r
is
tic
f
ac
ilit
atin
g
co
n
v
er
g
en
ce
.
I
n
t
h
is
ap
p
r
o
ac
h
,
p
ar
ticles
ar
e
r
e
p
r
esen
ted
as
v
ec
to
r
s
n
av
ig
atin
g
th
r
o
u
g
h
a
D
-
d
im
e
n
s
io
n
al
s
ea
r
ch
s
p
ac
e
with
th
e
o
b
jectiv
e
o
f
alig
n
i
n
g
th
em
s
elv
es
with
an
o
p
tim
al
s
o
lu
tio
n
.
E
ac
h
p
ar
ticle
is
d
es
cr
ib
ed
b
y
b
o
th
a
p
o
s
itio
n
(
x
id
)
a
n
d
a
v
elo
city
(
v
id
)
.
All
p
ar
ticle
s
in
th
e
s
war
m
ca
n
co
m
m
u
n
icate
,
estab
lis
h
in
g
a
g
lo
b
al
n
eig
h
b
o
r
h
o
o
d
o
f
i
n
f
o
r
m
an
ts
.
Ad
d
itio
n
ally
,
ea
ch
p
a
r
ticle
m
ain
tain
s
a
m
em
o
r
y
th
at
s
to
r
es
th
e
b
est
-
v
is
ited
p
o
s
itio
n
(
p
id
)
k
n
o
wn
as
th
e
“in
d
iv
id
u
al
lead
e
r
”,
an
d
t
h
e
o
p
tim
al
p
o
s
itio
n
ac
h
iev
ed
with
in
its
n
eig
h
b
o
r
h
o
o
d
b
ased
o
n
Par
eto
d
o
m
in
a
n
ce
(
p
g
)
k
n
o
wn
as
th
e
“g
lo
b
al
l
ea
d
er
”.
I
n
d
ee
d
,
t
h
e
in
co
r
p
o
r
atio
n
o
f
th
e
g
lo
b
al
n
eig
h
b
o
r
h
o
o
d
tech
n
iq
u
e
n
o
t
o
n
ly
im
p
r
o
v
es
e
x
p
lo
r
atio
n
o
f
th
e
s
ea
r
ch
s
p
ac
e
b
u
t
als
o
f
ac
ilit
ates m
o
r
e
in
tellig
en
t m
o
v
em
en
t o
f
p
ar
ticles,
aid
in
g
in
th
e
d
is
co
v
er
y
o
f
o
p
tim
al
s
o
lu
tio
n
s
.
C
er
tain
ly
,
th
e
co
llab
o
r
ativ
e
tea
m
b
e
h
av
io
r
d
e
m
o
n
s
tr
ates
g
r
ea
ter
i
n
s
ig
h
t
co
m
p
ar
e
d
to
th
at
o
f
an
in
d
iv
id
u
al
p
ar
ticle,
en
ab
lin
g
a
m
o
r
e
s
o
p
h
is
ticated
ap
p
r
o
ac
h
t
o
th
e
o
p
tim
izatio
n
p
r
o
ce
s
s
.
T
o
av
o
id
g
ettin
g
tr
ap
p
ed
in
lo
ca
l
o
p
tim
a,
th
e
NM
PS
O
alg
o
r
ith
m
m
o
n
it
o
r
s
th
e
p
o
s
itio
n
o
f
an
ex
tr
a
p
ar
ticle
k
n
o
wn
as
th
e
“
co
n
tem
p
o
r
ar
y
lead
er
”
(
n
id
)
.
T
h
is
p
o
s
itio
n
is
co
n
s
tan
tly
u
p
d
ated
b
y
esti
m
atin
g
two
r
a
n
d
o
m
p
a
r
ticles
in
th
e
s
wa
r
m
ac
co
r
d
in
g
to
t
h
eir
cr
o
wd
in
g
d
is
tan
ce
.
T
h
e
s
o
lu
t
io
n
th
at
is
s
im
u
ltan
eo
u
s
ly
n
o
n
-
d
o
m
in
ated
an
d
less
cr
o
w
d
ed
b
etwe
en
th
ese
p
ar
ticles is
d
esig
n
ated
as th
e
n
ew
co
n
tem
p
o
r
an
eo
u
s
p
ar
ticle.
Du
r
in
g
its
m
o
v
em
en
t,
th
e
p
a
r
ticle
h
as
m
u
ltip
le
ch
o
ices:
it
c
an
co
n
tin
u
e
a
lo
n
g
its
cu
r
r
en
t
p
ath
(
with
its
cu
r
r
en
t
v
elo
city
v
id
)
,
r
et
u
r
n
to
its
p
r
ev
io
u
s
ly
id
en
tifie
d
b
e
s
t
p
o
s
itio
n
(
p
id
)
,
tr
ail
th
e
b
est
p
o
s
itio
n
id
en
tifie
d
b
y
its
n
eig
h
b
o
r
h
o
o
d
(
p
g
)
,
o
r
ad
v
an
ce
to
war
d
s
th
e
p
o
s
itio
n
o
f
th
e
c
o
n
tem
p
o
r
an
e
o
u
s
p
ar
ticle
(
n
id
)
.
T
h
e
co
m
p
u
tat
io
n
o
f
th
e
m
o
v
em
en
t
an
d
th
e
v
elo
city
o
f
p
a
r
ticles
is
d
eter
m
in
ed
b
y
m
ea
n
s
o
f
th
ese
f
o
u
r
ten
d
en
cies
an
d
co
n
s
id
er
in
g
a
s
p
ec
if
ic
p
r
o
b
ab
ilit
y
.
T
h
e
m
o
v
em
e
n
t o
f
p
ar
ticles is
ca
lcu
lated
u
s
in
g
(
1
8
)
.
(
+
1
)
=
{
(
)
(
)
+
1
1
(
−
)
+
2
2
(
−
)
(
)
≥
(
)
(
)
+
1
1
(
−
)
+
2
2
(
−
)
(
)
<
+
3
3
(
−
)
(
1
8
)
(
ω
d
)
is
th
e
in
er
tia
f
ac
t
o
r
(
ω
d
∈
[
ω
min,
ω
max
]
)
,
(
c
1
)
,
(
c
2
)
,
a
n
d
(
c
3
)
ar
e
th
e
lear
n
in
g
f
ac
to
r
s
,
an
d
(
r
1
)
,
(
r
2
)
,
a
n
d
(
r
3
)
ar
e
a
r
an
d
o
m
n
u
m
b
er
s
b
elo
n
g
in
g
t
o
[
0
.
1
]
,
d
ete
r
m
in
ed
f
o
llo
win
g
a
p
r
o
b
a
b
ilis
tic
d
is
tr
ib
u
tio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
6
,
No
.
2
,
No
v
em
b
er
20
24
:
7
4
9
-
7
5
9
754
T
h
e
in
er
tia
f
ac
t
o
r
an
d
th
e
lea
r
n
in
g
f
ac
t
o
r
s
ar
e
em
p
lo
y
ed
to
g
o
v
er
n
th
e
p
ar
ticle
’
s
m
o
tio
n
,
s
tr
ik
in
g
a
b
alan
ce
b
etwe
en
ex
p
lo
itatio
n
an
d
e
x
p
lo
r
atio
n
with
in
t
h
e
s
ea
r
ch
s
p
ac
e.
I
n
th
is
alg
o
r
i
th
m
,
an
e
v
o
lu
tio
n
ar
y
s
tr
ateg
y
u
s
ed
to
ad
ju
s
t
th
e
v
al
u
es
o
f
th
ese
f
ac
t
o
r
s
.
I
n
d
ee
d
,
t
h
is
ap
p
r
o
ac
h
in
teg
r
ates
th
e
ad
ap
tiv
e
in
er
tia
f
ac
to
r
tech
n
iq
u
e
a
n
d
g
iv
es
h
eig
h
ten
ed
im
p
o
r
tan
ce
to
th
e
in
tellig
e
n
ce
o
f
in
d
iv
id
u
al
p
a
r
ticles
f
r
o
m
th
e
in
itial
s
tag
es.
As
th
e
p
r
o
ce
s
s
u
n
f
o
ld
s
,
NM
OPSO
th
en
h
ig
h
lig
h
ts
th
e
co
llectiv
e
in
tellig
en
ce
o
f
th
e
en
tire
s
war
m
in
later
s
tag
es.
T
h
ese
f
ac
to
r
s
ar
e
ex
p
r
e
s
s
ed
as f
o
llo
ws:
(
)
=
{
(
)
>
−
(
−
)
×
(
(
)
−
)
(
−
)
(
)
≤
(
1
9
)
1
=
0
.
5
+
2
×
c
os
(
×
(
−
1
)
2
×
(
−
1
)
)
(
2
0
)
2
=
0
.
5
+
2
×
s
in
(
×
(
−
1
)
2
×
(
−
1
)
)
(
2
1
)
3
=
1
(
2
2
)
wh
er
e
(
x
min
)
is
th
e
m
in
im
u
m
v
alu
e
o
f
(
x
id
)
,
(
x
mean
)
is
th
e
m
ea
n
v
alu
e
o
f
(
x
id
)
,
a
n
d
T
is
th
e
m
ax
im
u
m
n
u
m
b
e
r
o
f
g
en
er
atio
n
s
.
Fin
ally
,
th
is
alg
o
r
ith
m
u
s
es
th
e
m
u
tatio
n
m
ec
h
a
n
is
m
o
n
two
th
ir
d
s
o
f
th
e
p
ar
ticles
an
d
in
c
o
r
p
o
r
ates
th
e
cr
o
wd
in
g
d
is
tan
ce
to
en
h
an
ce
th
e
d
iv
er
s
ity
o
f
s
o
lu
tio
n
s
.
Ad
d
itio
n
ally
,
it
u
tili
ze
s
an
ex
ter
n
al
ar
ch
iv
e
to
s
to
r
e
th
e
o
p
tim
al
s
o
lu
tio
n
s
.
T
h
e
p
s
eu
d
o
co
d
e
f
o
r
th
e
NM
OPSO a
lg
o
r
ith
m
is
p
r
o
v
id
ed
in
alg
o
r
ith
m
1
.
Alg
o
r
ith
m
1
.
Ps
eu
d
o
co
d
e
o
f
N
MO
PS
O
1
-
Initialize the positions of the particles in the swarm
2
-
Evaluate the particles
3
-
Initialize the individual and the glob
al leaders
4
-
Compute the crowding distance for the global leaders
5
-
Initialize the contemporary leaders
7
-
Repeat
8
-
For each particle do
9
-
Choose the global leader.
10
-
Update the velocity and position
11
-
Mutate particle based on a
specified probability
12
-
Evaluate the particle
13
-
Update the individual leader.
14
-
End for
15
-
Update the global and contemporary leaders of particles.
16
-
Send global leaders to the external archive.
17
-
Compute the crowding distance for global leade
rs
18
-
Until (maximum number of generations is reached)
19
-
Return the external archive
4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
o
ev
alu
ate
th
e
ac
cu
r
ac
y
o
f
o
u
r
p
r
o
p
o
s
ed
m
eth
o
d
an
d
q
u
an
tify
th
e
v
ar
ian
ce
b
etwe
en
t
h
e
o
b
tain
ed
r
esu
lts
an
d
m
ea
s
u
r
em
en
ts
,
we
ap
p
ly
th
e
R
MSE
cr
iter
io
n
.
T
h
is
cr
iter
io
n
is
d
eter
m
in
e
d
f
o
r
v
ar
io
u
s
s
o
lar
ce
ll
co
n
f
ig
u
r
atio
n
s
,
in
clu
d
in
g
:
−
T
h
e
B
P
5
1
7
0
S
PV
m
o
d
u
le
u
s
es
7
2
m
o
n
o
cr
y
s
tallin
e
s
ilic
o
n
ce
lls
co
n
n
ec
ted
in
s
er
ies,
o
p
er
atin
g
at
a
tem
p
er
atu
r
e
o
f
2
5
°C
with
an
ir
r
ad
iatio
n
o
f
1
,
0
0
0
W
/m
2
.
−
T
h
e
Ph
o
t
o
wat
t
-
PW
P
2
0
1
Po
l
y
cr
y
s
tallin
e
s
o
lar
m
o
d
u
les
co
n
s
is
t
o
f
3
6
ce
lls
c
o
n
n
ec
ted
in
s
er
ies,
o
p
er
atin
g
at
a
tem
p
er
atu
r
e
o
f
4
5
°C
u
n
d
e
r
an
ir
r
a
d
iatio
n
o
f
1
,
0
0
0
W
/m
2
.
−
T
h
e
STM
6
4
0
/3
6
a
n
d
STM
6
1
2
0
/3
6
,
b
o
th
w
o
r
k
in
g
at
STC
at
a
tem
p
er
atu
r
e
o
f
2
5
°C
with
a
n
ir
r
a
d
iatio
n
o
f
1
,
0
0
0
W
/m
2
.
−
T
h
e
PVM
7
5
2
GaA
s
th
in
f
ilm
ce
ll,
wh
ich
o
p
er
ates
at
STC
co
n
d
itio
n
s
,
2
5
°C
tem
p
er
atu
r
e,
a
n
d
1
,
0
0
0
W
/m
2
ir
r
ad
iatio
n
.
−
T
h
e
R
T
C
Fra
n
ce
s
ilico
n
s
o
lar
ce
ll,
f
ea
tu
r
in
g
a
5
7
m
m
d
ia
m
eter
,
o
p
er
ates
at
3
3
°C
tem
p
er
atu
r
e
with
an
ir
r
ad
iatio
n
o
f
1
,
0
0
0
W
/m
2
.
T
h
e
d
iv
e
r
s
e
co
n
f
i
g
u
r
atio
n
s
u
s
ed
f
o
r
ev
alu
ati
n
g
th
e
ac
cu
r
ac
y
o
f
o
u
r
m
eth
o
d
ac
r
o
s
s
a
b
r
o
ad
s
p
ec
tr
u
m
o
f
s
o
lar
ce
ll
ty
p
es
a
n
d
en
v
ir
o
n
m
en
tal
c
o
n
d
itio
n
s
.
Mo
r
e
o
v
er
,
ac
cu
r
ately
p
r
e
d
ictin
g
t
h
e
I
-
V
cu
r
v
es
o
f
co
m
m
er
cial
PV
m
o
d
u
les
is
cr
u
cial
to
v
alid
ate
th
e
ac
c
u
r
ac
y
o
f
th
e
alg
o
r
ith
m
u
s
ed
as
a
to
o
l
f
o
r
ch
ar
ac
ter
izin
g
th
e
p
er
f
o
r
m
a
n
ce
o
f
th
ese
m
o
d
u
les.
T
h
e
an
al
y
ze
d
PV
ce
lls
ar
e
d
ef
in
e
d
with
elec
tr
ical
c
h
ar
ac
ter
is
tics
wh
ich
ar
e:
th
e
n
u
m
b
e
r
o
f
ce
lls
in
s
er
ies
(
N
s
)
,
th
e
m
ax
im
u
m
p
o
wer
cu
r
r
en
t
(
I
mp
)
,
th
e
m
ax
im
u
m
p
o
wer
v
o
ltag
e
(
V
mp
)
,
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
A
n
imp
r
o
ve
d
P
S
O
-
b
a
s
ed
a
p
p
r
o
a
ch
fo
r
th
e
p
h
o
t
o
vo
lta
ic
ce
ll
p
a
r
a
mete
r
s
…
(
Ma
r
ia
A
ma
id
i
)
755
th
e
s
h
o
r
t
-
cir
cu
it
cu
r
r
en
t
(
I
sc
)
,
an
d
th
e
o
p
en
-
cir
cu
it
v
o
lt
ag
e
(
V
oc
)
.
T
h
ese
elec
tr
ical
ch
ar
ac
ter
is
tics
ar
e
s
u
m
m
ar
ized
in
T
ab
le
2
.
T
a
b
le
3
p
r
esen
ts
th
e
r
esu
lts
o
f
th
e
f
i
v
e
p
ar
a
m
eter
s
f
r
o
m
th
e
ap
p
lie
d
NM
OPSO
b
ased
tech
n
iq
u
e
f
o
r
th
e
test
ed
s
ix
PV
ce
lls
/m
o
d
u
les.
B
ased
o
n
th
ese
r
esu
lts
,
we
ca
n
n
o
tice
a
g
o
o
d
ag
r
ee
m
e
n
t
b
etwe
en
th
e
e
x
p
er
im
e
n
tal
an
d
th
e
ca
lcu
lated
d
ata,
p
r
o
v
in
g
t
h
e
ca
p
ab
ilit
y
o
f
o
u
r
ap
p
r
o
ac
h
in
d
eter
m
in
i
n
g
t
h
e
p
ar
am
eter
s
o
f
t
h
e
SDM.
T
ab
le
2
.
E
lectr
ical
ch
a
r
ac
ter
is
tics
o
f
th
e
an
aly
ze
d
PV c
ells
El
e
c
t
r
i
c
a
l
f
e
a
t
u
r
e
B
P
5
1
7
0
S
S
TM
6
4
0
/
3
6
P
h
o
t
o
w
a
t
t
P
W
P
2
0
1
R
T
C
F
r
a
n
c
e
P
V
M
7
5
2
G
a
A
s
S
TM
6
1
2
0
/
3
6
V
mp
(V)
36
1
6
.
9
8
1
2
.
6
4
9
0
.
4
5
0
7
0
.
8
0
5
3
1
4
.
9
3
I
mp
(A)
4
.
7
2
1
.
5
0
.
9
1
2
0
0
.
6
8
9
4
0
.
0
9
3
7
6
.
8
3
V
oc
(V)
4
4
.
2
2
1
.
0
2
1
6
.
7
7
8
0
.
5
7
2
8
0
.
9
9
2
6
1
9
.
2
1
I
sc
(A)
5
1
.
6
6
3
1
.
0
3
0
0
.
7
6
0
3
0
.
0
9
9
8
7
.
4
8
N
s
72
36
36
1
1
36
T
ab
le
3
.
O
p
tim
izatio
n
r
esu
lts
B
P
5
1
7
0
S
S
TM
6
4
0
/
3
6
P
h
o
t
o
w
a
t
t
-
P
W
P
2
0
1
R
TC
F
r
a
n
c
e
P
V
M
7
5
2
G
a
A
s
S
TM
6
1
2
0
/
3
6
R
s
(
Ω
)
0
.
0
7
0
3
7
7
8
0
.
3
3
1
1
8
6
5
1
.
1
9
1
1
2
8
9
6
2
3
0
.
4
1
7
1
6
2
6
3
4
0
.
8
1
1
2
8
9
6
4
1
0
.
1
7
8
1
9
3
4
7
4
4
R
sh
(
Ω
)
3
1
0
.
8
7
9
3
4
5
6
1
.
5
0
3
2
3
7
4
6
.
4
8
0
1
4
6
5
4
7
.
1
4
7
4
6
8
5
7
1
4
.
8
8
3
7
0
9
6
3
3
2
.
9
3
7
2
0
4
6
I
0
(
A
)
1
.
8
3
5
0
8
1
0
9
E
-
9
3
.
7
4
9
7
1
1
4
E
-
6
1
.
3
1
8
8
2
7
5
1
E
-
9
1
.
0
6
1
2
0
1
7
1
E
-
7
4
.
5
7
4
8
1
4
7
0
6
E
-
6
3
.
3
6
8
8
5
7
8
E
-
6
I
ph
(A)
4
.
5
8
4
0
2
1
8
2
8
6
6
.
0
1
1
0
5
7
3
6
5
.
7
7
0
3
7
5
5
9
9
0
.
9
0
0
4
7
2
7
7
0
.
0
8
6
0
9
4
1
4
3
3
6
.
0
1
1
0
5
7
3
6
6
N
1
.
3
2
5
5
3
4
8
1
.
3
1
5
1
5
9
4
1
.
1
9
1
1
2
8
9
6
2
3
1
.
6
3
2
6
3
5
9
4
1
.
2
0
9
8
6
2
7
1
1
.
2
6
8
3
5
2
7
6
1
Acc
o
r
d
in
g
to
th
e
o
b
tain
ed
r
es
u
lts
,
we
ca
n
also
n
o
tice,
th
at
th
e
er
r
o
r
b
etwe
en
th
e
m
ea
s
u
r
ed
cu
r
r
en
t
an
d
th
e
ca
lcu
lated
o
n
e
is
n
ea
r
ly
n
eg
lig
ib
le,
wh
ich
s
h
o
ws
th
e
ac
cu
r
ac
y
o
f
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
.
T
h
e
o
p
tim
izatio
n
o
u
tco
m
es
ac
h
iev
ed
b
y
t
h
e
NM
OPSO
alg
o
r
ith
m
f
o
r
m
i
n
im
izin
g
R
MSE
ar
e
co
n
tr
asted
with
alter
n
ativ
e
m
eth
o
d
s
,
ea
ch
r
e
f
er
en
ce
d
ac
co
r
d
in
g
ly
.
T
h
e
r
esu
lts
f
o
r
th
e
f
o
u
r
s
o
lar
ce
l
ls
ar
e
p
r
esen
ted
in
T
ab
les 4
to
6.
Fo
r
th
e
PVM
7
5
2
GaA
s
lis
ted
in
T
ab
le
4
,
th
e
NM
OPSO
alg
o
r
ith
m
e
x
h
ib
its
ex
ce
p
tio
n
al
ac
cu
r
ac
y
,
g
iv
es
a
s
ig
n
if
ican
tly
lo
wer
R
MSE
(
0
.
9
1
5
1
0
-
3
)
co
m
p
ar
e
d
to
alter
n
ativ
e
m
o
d
els.
Similar
co
n
clu
s
io
n
s
ar
e
n
o
ticed
f
o
r
th
e
STM
6
-
4
0
/3
6
c
ell,
wh
er
e
NM
OP
SO
s
u
r
p
ass
e
s
o
th
er
m
o
d
els
with
a
lo
wer
R
MSE
(
1
.
0
1
9
1
0
-
3
)
co
m
p
ar
ed
to
o
th
er
alg
o
r
ith
m
s
.
Fu
r
th
er
m
o
r
e,
f
o
r
th
e
Po
ly
cr
y
s
ta
llin
e
Ph
o
to
watt
-
PW
P
2
0
1
r
esu
lts
illu
s
tr
ated
in
T
ab
le
5
,
NM
OPSO
m
ain
tai
n
s
its
r
em
ar
k
ab
le
ac
cu
r
ac
y
with
a
m
in
im
al
R
M
SE
o
f
(
0
.
2
1
2
1
0
-
3
)
.
T
h
is
p
er
f
o
r
m
an
ce
n
o
tab
ly
ex
ce
ed
s
th
e
R
MSE
o
b
tain
ed
with
o
th
er
tec
h
n
iq
u
es,
co
n
f
ir
m
in
g
th
e
NM
OPSO
’
s
ef
f
ec
tiv
en
ess
in
esti
m
at
in
g
th
e
ch
ar
ac
ter
is
tics
o
f
th
is
p
o
ly
c
r
y
s
tallin
e
s
o
lar
m
o
d
u
le.
Fo
r
t
h
e
s
o
lar
ce
ll
-
R
T
C
Fra
n
ce
,
NM
OPSO
d
em
o
n
s
tr
ates
its
s
u
p
er
io
r
ity
b
y
ac
h
iev
i
n
g
an
im
p
r
ess
iv
ely
lo
w
R
MSE
o
f
(
0
.
1
4
1
0
-
3
)
.
No
tab
ly
,
NM
OPSO
o
u
tp
er
f
o
r
m
s
alter
n
ativ
e
m
eth
o
d
s
s
u
ch
as
en
h
an
ce
d
lead
e
r
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
E
L
PS
O)
,
co
n
v
e
n
tio
n
al
p
ar
ti
cle
s
war
m
o
p
tim
izatio
n
(
C
PS
O)
,
b
ac
k
tr
ac
k
i
n
g
s
ea
r
ch
alg
o
r
ith
m
(
B
SA)
,
an
d
ar
tific
ial
b
ee
co
lo
n
y
(
AB
C
)
.
T
ab
le
7
p
r
esen
t
th
e
v
alu
es
o
f
th
e
s
ec
o
n
d
o
b
jectiv
e
f
u
n
ctio
n
,
all
o
f
wh
ich
co
n
v
er
g
e
to
n
ea
r
ly
ze
r
o
.
T
h
is
co
n
v
e
r
g
en
ce
v
alid
ates
th
e
ac
cu
r
ac
y
o
f
th
e
R
s
o
b
tain
ed
,
v
al
id
atin
g
th
e
e
f
f
icac
y
o
f
NM
OPSO in
s
o
lv
in
g
th
e
n
o
n
-
lin
ea
r
eq
u
atio
n
.
T
ab
le
4
.
C
alcu
lated
R
MSE
f
o
r
PVM
7
5
2
GaA
s
an
d
STM
6
-
4
0
/3
6
ce
lls
M
o
d
e
l
R
M
S
E
P
V
M
7
5
2
G
a
A
s
R
M
S
E
S
T
M
6
-
4
0
/
3
6
N
M
O
P
S
O
Li
d
a
i
g
h
b
i
e
t
a
l
.
[
1
4
]
ELPS
O
C
P
S
O
B
S
A
A
B
C
0
.
9
1
5
.
1
0
-
3
1
.
8
6
5
.
1
0
-
3
2
5
.
4
0
.
1
0
-
3
2
5
.
4
0
.
1
0
-
3
2
.
1
4
.
1
0
-
3
2
.
0
4
.
1
0
-
3
1
.
0
1
9
.
1
0
-
3
1
.
9
0
3
.
1
0
-
3
2
.
1
8
.
1
0
-
3
2
.
1
8
.
1
0
-
3
3
.
6
2
.
1
0
-
3
2
.
3
9
.
1
0
-
3
T
ab
le
5
.
C
alcu
lated
R
MSE
f
o
r
p
o
ly
cr
y
s
tallin
e
p
h
o
to
watt
-
PW
P 2
0
1
M
o
d
e
l
R
M
S
E
P
h
o
t
o
w
a
t
t
-
P
W
P
2
0
1
N
M
O
P
S
O
K
a
r
e
e
m
a
n
d
S
a
r
a
v
a
n
a
n
[
2
1
]
C
u
b
a
s
e
t
a
l
.
[
2
2
]
P
h
a
n
g
e
t
a
l.
[
2
3
]
Li
d
a
i
g
h
b
i
e
t
a
l
.
[
1
4
]
0
.
2
1
2
.
1
0
-
3
6
.
5
4
.
1
0
-
3
2
.
9
4
.
1
0
-
3
3
.
5
4
9
.
1
0
-
3
2
.
1
6
4
.
1
0
-
3
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
6
,
No
.
2
,
No
v
em
b
er
20
24
:
7
4
9
-
7
5
9
756
T
ab
le
6
.
C
alcu
lated
R
MSE
f
o
r
s
o
lar
ce
ll
-
R
T
C
Fra
n
ce
M
o
d
e
l
R
M
S
E
s
o
l
a
r
c
e
l
l
-
R
TC
F
r
a
n
c
e
N
M
O
P
S
O
Li
d
a
i
g
h
b
i
e
t
a
l
.
[
1
4
]
P
e
n
g
e
t
a
l
.
[
2
4
]
Lo
u
z
a
z
n
i
e
t
a
l
.
[
2
5
]
To
l
e
d
o
et
al
.
[
2
6
]
I
sh
i
b
a
s
h
i
e
t
a
l
.
[
2
7
]
A
k
b
a
b
a
a
n
d
A
l
a
t
t
a
w
i
[
2
8
]
D
a
s
[
2
9
]
Lu
n
e
t
a
l
.
[
3
0
]
P
i
n
d
a
d
o
a
n
d
C
u
b
a
s
[
3
1
]
O
u
l
c
a
i
d
e
t
a
l
.
[
3
2
]
B
S
A
[
3
3
]
A
B
C
[
3
3
]
G
W
O
C
S
[
1
7
]
M
P
S
O
[
3
4
]
H
C
LPS
O
[
3
5
]
0
.
1
4
.
1
0
-
3
0
.
8
8
6
.
1
0
-
3
3
.
5
4
.
1
0
-
3
5
.
8
0
.
1
0
-
3
0
.
7
7
7
.
1
0
-
3
8
.
0
8
0
1
0
-
3
2
3
.
6
0
.
1
0
-
3
3
1
.
7
4
.
1
0
-
3
1
4
.
0
1
.
1
0
-
3
7
.
6
3
.
1
0
-
3
3
1
.
9
9
.
1
0
-
3
1
.
4
4
.
1
0
-
3
0
.
8
8
.
1
0
-
3
0
.
9
8
.
1
0
-
3
7
.
3
3
0
.
1
0
-
3
1
.
1
2
.
1
0
-
3
T
ab
le
7
.
R
esu
lts
o
f
th
e
s
ec
o
n
d
o
b
jectiv
e
f
u
n
ctio
n
B
P
5
1
7
0
S
S
TM
6
4
0
/
3
6
P
h
o
t
o
w
a
t
t
-
P
W
P
2
0
1
R
TC
F
r
a
n
c
e
P
V
M
7
5
2
G
a
A
s
S
TM
6
1
2
0
/
3
6
f
2
0
.
0
0
0
1
0
1
0
.
0
0
0
0
9
8
0
.
0
0
0
3
2
0
.
0
0
0
1
1
0
.
0
0
0
0
2
0
.
0
0
0
0
1
C
o
n
ce
r
n
in
g
th
e
co
m
p
u
tatio
n
a
l
tim
e
o
f
s
ev
er
al
s
war
m
o
p
ti
m
izatio
n
alg
o
r
ith
m
s
,
we
ca
lcu
lated
th
e
av
er
ag
e
tim
e
o
f
t
h
e
NM
OPSO
alg
o
r
ith
m
.
W
e
ex
ec
u
ted
th
e
a
lg
o
r
ith
m
ten
tim
es
f
o
r
ea
ch
ce
ll,
an
d
we
e
v
alu
ate
th
e
av
er
ag
e
p
er
f
o
r
m
an
ce
.
T
h
e
r
esu
lts
ar
e
p
r
esen
ted
in
T
ab
le
8
.
Am
o
n
g
all
th
e
s
tu
d
ied
alg
o
r
ith
m
s
,
NM
OPSO
ex
h
ib
its
th
e
s
h
o
r
test
ex
ec
u
tio
n
tim
e,
h
ig
h
lig
h
t
in
g
its
r
ap
id
c
o
n
v
er
g
e
n
ce
.
T
h
e
co
m
p
ar
is
o
n
am
o
n
g
d
i
v
er
s
e
alg
o
r
ith
m
s
ap
p
lied
to
s
p
ec
if
ic
ce
ll
ty
p
es,
in
clu
d
in
g
PVM
7
5
2
GaA
s
,
STM
6
-
4
0
/3
6
,
Ph
o
to
watt
-
PW
P
2
0
1
,
an
d
s
o
lar
ce
ll
-
R
T
C
Fra
n
ce
,
s
h
o
ws
th
at
th
e
p
r
o
p
o
s
ed
m
eth
o
d
in
th
is
s
tu
d
y
ten
d
ed
th
e
m
in
im
u
m
R
MSE
v
alu
es
.
T
o
d
em
o
n
s
tr
ate
th
e
p
r
ec
is
io
n
o
f
th
e
p
r
o
p
o
s
ed
a
lg
o
r
ith
m
,
ex
ten
s
iv
e
s
im
u
latio
n
s
wer
e
ca
r
r
ie
d
o
u
t
u
s
in
g
MA
T
L
AB
.
Fig
u
r
e
2
s
er
v
es
as
an
ex
am
p
le
u
s
in
g
th
e
STM
6
4
0
/3
6
PV
ce
ll/mo
d
u
le.
Af
ter
ex
tr
ac
tin
g
th
e
p
ar
am
eter
s
v
alu
es
f
r
o
m
t
h
e
NM
OPSO
alg
o
r
ith
m
,
we
ap
p
lied
t
h
em
with
in
o
u
r
Simu
lin
k
m
o
d
el.
T
h
e
o
b
ta
in
ed
s
im
u
latio
n
r
esu
lts
ar
e
p
r
esen
ted
in
Fig
u
r
es
3
to
6
.
T
h
ese
f
ig
u
r
es
illu
s
tr
ate
th
e
I
(
V)
cu
r
v
es e
x
tr
ac
ted
f
r
o
m
th
e
m
o
d
u
le
d
atash
ee
ts
u
n
d
e
r
STC
.
T
ab
le
8
.
R
u
n
tim
e
N
M
O
P
S
O
EPS
O
[
1
3
]
I
P
S
O
[
1
3
]
PSO
[
1
3
]
DE
[
1
3
]
A
B
C
[
1
3
]
R
u
n
t
i
m
e
(
s
e
c
o
n
d
)
3
.
2
9
9
3
.
8
9
9
0
4
.
7
6
8
4
.
4
8
4
9
.
3
1
8
1
1
.
1
2
Fig
u
r
e
2
.
Simu
latio
n
o
f
STM
6
4
0
/3
6
PV
ce
ll/mo
d
u
le
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
A
n
imp
r
o
ve
d
P
S
O
-
b
a
s
ed
a
p
p
r
o
a
ch
fo
r
th
e
p
h
o
t
o
vo
lta
ic
ce
ll
p
a
r
a
mete
r
s
…
(
Ma
r
ia
A
ma
id
i
)
757
T
h
e
r
ed
p
o
in
ts
o
n
th
e
g
r
ap
h
s
r
ep
r
esen
t
th
e
ex
p
er
im
en
tal
I
(
V)
d
ata
c
o
llected
d
ir
ec
tly
f
r
o
m
t
h
e
d
atash
ee
t.
T
h
e
co
n
tin
u
o
u
s
b
lu
e
lin
e,
o
n
th
e
o
t
h
er
h
a
n
d
,
r
e
p
r
esen
ts
th
e
s
im
u
lated
cu
r
v
es
g
en
er
ated
u
s
in
g
th
e
p
ar
am
eter
s
ex
tr
a
cted
th
r
o
u
g
h
th
e
p
r
o
p
o
s
ed
m
eth
o
d
.
Fro
m
th
ese
f
i
g
u
r
es,
we
ca
n
cle
ar
ly
n
o
tice
th
at
th
e
s
im
u
lated
an
d
e
x
p
er
im
e
n
tal
I
(
V)
ch
ar
ac
ter
is
tics
ar
e
p
r
ac
ti
ca
lly
id
en
tical.
T
h
ese
f
ig
u
r
es
also
s
h
o
w
a
h
i
g
h
d
eg
r
ee
o
f
ag
r
ee
m
e
n
t
b
etwe
e
n
ex
p
er
im
en
tal
a
n
d
ca
lcu
late
d
d
ata,
v
alid
atin
g
th
e
ef
f
icac
y
o
f
th
e
p
r
o
p
o
s
ed
m
eth
o
d
.
T
h
is
an
aly
s
is
in
clu
d
es
th
e
ev
alu
atio
n
o
f
d
iv
er
s
e
alg
o
r
ith
m
s
f
o
r
d
if
f
er
en
t
ce
ll
m
o
d
els,
in
clu
d
in
g
an
ex
ten
s
iv
e
v
ar
iety
o
f
m
eth
o
d
s
,
s
u
ch
as
an
aly
tical,
n
u
m
er
ical,
an
d
m
etah
eu
r
is
tic
tech
n
iq
u
es.
Ou
r
s
tu
d
y
s
u
b
m
it
an
ev
alu
ati
o
n
,
co
m
p
a
r
in
g
th
e
NM
OPSO
-
b
ased
ap
p
r
o
ac
h
a
g
ain
s
t
a
s
p
ec
tr
u
m
o
f
a
n
aly
tic
al
m
eth
o
d
s
in
[
1
4
]
,
[
24
]
-
[
2
6
]
,
ex
p
licit
m
o
d
els
[
2
8
]
-
[
3
1
]
,
a
n
d
s
ig
n
if
ican
t
m
eta
h
eu
r
is
tic
s
tr
ateg
ies
s
u
ch
as
t
h
e
GW
O
in
[
3
2
]
.
B
y
co
m
p
ar
in
g
th
e
r
esu
lts
o
f
R
MSE
v
alu
es
f
o
r
alg
o
r
ith
m
s
lik
e
E
L
PS
O,
C
PS
O,
B
S
A,
an
d
AB
C
[
3
3
]
,
th
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
tu
r
n
s
to
b
e
th
e
b
est.
Fig
u
r
e
3
.
C
u
r
v
e
I
-
V
r
elate
d
PW
P2
0
1
(
T
=4
5
°
C
,
1
,
0
0
0
W
/m
2
)
Fig
u
r
e
4
.
C
u
r
v
e
I
-
V
r
elate
d
to
PVM
7
5
2
GaA
s
(
T
=2
5
°
C
,
G=
1
,
0
0
0
W
/m
2
)
Fig
u
r
e
5
.
C
u
r
v
e
STM
6
4
0
/3
6
T
=2
5
°
C
,
G=
1
,
0
0
0
W
/m
2
Fig
u
r
e
6
.
c
u
r
v
e
I
-
V
cu
r
v
es r
el
ated
to
R
T
C
(
T
=3
3
°
C
,
G=
1
,
0
0
0
W
/m
2
)
Fu
r
th
er
m
o
r
e
,
NM
OPSO
-
b
ase
d
alg
o
r
ith
m
o
u
t
p
er
f
o
r
m
ed
o
t
h
er
tech
n
iq
u
es
n
o
t
o
n
ly
in
ac
cu
r
ac
y
b
u
t
also
in
ex
ec
u
tio
n
tim
e.
I
ts
ab
ilit
y
to
co
n
v
er
g
e
f
aster
m
a
k
e
s
it
an
ap
p
ea
lin
g
a
n
d
r
eliab
le
to
o
l
f
o
r
r
ap
id
an
d
d
ep
en
d
a
b
le
p
ar
am
ete
r
ex
tr
ac
ti
o
n
in
th
e
PV
d
o
m
ain
.
Ov
er
al
l,
th
e
co
m
p
r
e
h
en
s
iv
e
an
aly
s
is
u
n
d
er
s
co
r
es
th
e
r
o
b
u
s
tn
ess
an
d
ef
f
ec
tiv
en
ess
o
f
NM
OPSO,
p
r
esen
tin
g
it
as
a
h
ig
h
ly
ac
cu
r
ate
m
eth
o
d
f
o
r
c
h
ar
ac
ter
izin
g
an
d
e
v
alu
atin
g
th
ese
s
p
ec
if
ic
t
y
p
es
o
f
ce
lls
with
in
th
e
f
ield
o
f
s
o
lar
e
n
er
g
y
r
esear
ch
.
T
h
is
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
n
o
t
o
n
ly
im
p
r
o
v
es
th
e
ac
cu
r
ac
y
an
d
ef
f
icien
cy
o
f
p
ar
am
eter
s
ex
tr
ac
tio
n
b
u
t
als
o
estab
lis
h
es
a
n
o
v
el
en
h
an
ce
PS
O
in
th
e
o
p
tim
izatio
n
o
f
PV
ce
ll
p
ar
am
eter
s
.
W
h
ile
o
u
r
s
tu
d
y
estab
lis
h
es
th
e
ap
p
licatio
n
o
f
th
e
NM
O
PS
O
as
a
s
u
p
er
io
r
o
p
tim
izatio
n
s
tr
ateg
y
,
f
u
tu
r
e
r
esear
ch
ca
n
d
el
v
e
in
t
o
its
a
p
p
licab
ilit
y
in
d
y
n
am
ic
en
v
ir
o
n
m
en
tal
co
n
d
itio
n
s
,
s
ca
lab
il
ity
to
lar
g
er
s
o
lar
en
er
g
y
s
y
s
tem
s
,
an
d
in
teg
r
atio
n
with
em
er
g
in
g
tech
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.
5.
CO
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SI
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ly
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ased
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tial
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p
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m
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im
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R
MS
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wh
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is
ely
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s
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T
h
e
p
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p
o
s
ed
alg
o
r
ith
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in
teg
r
ates
an
ev
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lu
tio
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s
ea
r
ch
s
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ateg
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,
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h
an
cin
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b
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v
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en
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th
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p
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n
o
f
p
ar
am
eter
id
en
tific
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p
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o
ce
s
s
es.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
6
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No
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2
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b
er
20
24
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R
ec
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g
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est
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at
th
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p
r
ec
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io
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in
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ar
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m
eter
ex
tr
ac
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s
ig
n
if
ican
tly
im
p
ac
ts
th
e
p
er
f
o
r
m
an
ce
o
f
PV
ce
lls
.
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r
f
in
d
in
g
s
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cl
u
s
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ith
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r
ac
y
in
p
ar
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eter
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d
m
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im
al
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MSE
v
alu
es.
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h
r
o
u
g
h
e
x
ten
s
iv
e
s
im
u
latio
n
s
,
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u
r
m
eth
o
d
s
ig
n
if
ican
tly
o
u
tp
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f
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r
m
e
d
ex
is
tin
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p
r
o
ac
h
es.
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-
b
ased
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p
tim
izatio
n
tech
n
iq
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e
d
em
o
n
s
tr
ated
s
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p
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r
ac
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n
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en
t
b
etwe
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d
ex
p
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en
tal
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ata.
T
h
is
h
ei
g
h
ten
ed
ac
cu
r
ac
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is
cr
u
cial
f
o
r
p
r
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is
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m
o
d
elin
g
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d
p
r
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PV
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ll
b
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av
io
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.
Fu
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th
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m
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p
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also
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R
s
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itical
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ar
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eter
im
p
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.
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d
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d
,
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e
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e
s
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lts
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p
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ates
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RE
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NC
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[
1
]
G
.
D
.
Th
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,
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K
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.
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.
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P
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)
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6
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N
.
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,
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.
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b
r
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.
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F
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8
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A
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