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O
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ti
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a
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ra
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g
e
n
e
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m
s
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ize
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s
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tro
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two
rk
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d
it
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n
a
ll
y
,
a
p
re
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ise
siz
in
g
m
e
th
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d
o
l
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g
y
b
a
se
d
o
n
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lar
irrad
i
a
n
c
e
d
a
ta
wa
s
imp
lem
e
n
ted
to
e
n
su
re
th
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sy
ste
m
is
n
e
it
h
e
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o
v
e
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d
n
o
r
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d
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d
.
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e
sy
ste
m
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s
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e
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s
tes
ted
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n
d
v
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li
d
a
ted
u
si
n
g
M
ATLAB/S
imu
li
n
k
sim
u
lati
o
n
s
,
wh
ich
d
e
m
o
n
stra
ted
su
p
e
rio
r
p
re
d
ictiv
e
a
c
c
u
ra
c
y
,
fa
ste
r
c
o
n
v
e
rg
e
n
c
e
,
a
n
d
o
p
t
imiz
e
d
e
n
e
rg
y
c
a
p
tu
re
.
T
h
is
c
o
m
b
i
n
e
d
a
p
p
ro
a
c
h
o
f
i
n
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M
P
P
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n
d
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c
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u
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te
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in
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p
re
se
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ts
a
h
ig
h
l
y
e
ffe
c
ti
v
e
so
lu
ti
o
n
fo
r
imp
ro
v
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g
th
e
e
ffic
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c
y
a
n
d
re
li
a
b
i
li
ty
o
f
sta
n
d
-
a
l
o
n
e
so
lar
e
n
e
rg
y
sy
ste
m
s u
n
d
e
r
v
a
ry
i
n
g
e
n
v
iro
n
m
e
n
tal
c
o
n
d
it
io
n
s
.
K
ey
w
o
r
d
s
:
Ar
tific
ial
n
eu
r
al
n
etwo
r
k
B
atter
y
s
to
r
ag
e
Dee
p
lear
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in
g
Gen
etic
alg
o
r
ith
m
s
Ma
x
im
u
m
p
o
wer
p
o
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n
t tr
ac
k
in
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Ph
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to
v
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ltaic
Stan
d
-
alo
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s
y
s
tem
T
h
is i
s
a
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a
c
c
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ss
a
rticle
u
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d
e
r th
e
CC B
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SA
li
c
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se
.
C
o
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r
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s
p
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ing
A
uth
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r
:
Mo
u
f
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Saad
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E
lectr
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an
d
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in
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a
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y
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L
AB
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)
,
Facu
lty
o
f
E
lectr
ical
E
n
g
i
n
ee
r
in
g
Un
iv
er
s
ity
o
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T
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b
ess
a
T
eb
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a
1
2
0
0
0
,
Alg
er
ia
E
m
ail:
s
aa
d
im
o
u
f
id
a8
@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
s
h
if
t
to
s
u
s
tain
ab
le
en
e
r
g
y
s
o
lu
tio
n
s
in
c
r
ea
s
in
g
ly
h
i
g
h
lig
h
ts
s
tan
d
-
alo
n
e
p
h
o
t
o
v
o
lt
aic
(
PV)
s
y
s
tem
s
as
p
r
o
m
is
in
g
alter
n
ativ
es
to
tr
ad
itio
n
al
p
o
wer
s
o
u
r
ce
s
.
T
h
ese
s
y
s
tem
s
g
en
er
ate
elec
tr
icity
f
r
o
m
s
u
n
lig
h
t,
an
in
ex
h
au
s
tib
le
s
o
u
r
ce
th
at
em
its
n
o
g
r
ee
n
h
o
u
s
e
g
ases
,
m
ak
in
g
th
em
cr
u
cial
t
o
r
en
ewa
b
le
en
er
g
y
tr
an
s
itio
n
s
,
esp
ec
ially
in
r
em
o
te
ar
ea
s
o
u
ts
id
e
co
n
v
e
n
tio
n
al
g
r
id
r
ea
ch
.
Fo
r
s
elf
-
s
u
f
f
icien
c
y
,
ef
f
icien
t
b
atter
y
s
to
r
ag
e
an
d
ac
cu
r
ate
s
izin
g
o
f
co
m
p
o
n
en
ts
,
lik
e
s
o
lar
p
an
els
an
d
b
atter
ies,
ar
e
v
ital
f
o
r
co
n
tin
u
o
u
s
,
co
s
t
-
ef
f
ec
tiv
e
p
o
wer
s
u
p
p
ly
[
1
]
–
[
3
]
.
Sizin
g
o
p
tim
izatio
n
d
eter
m
in
es
th
e
b
est
PV
co
n
f
ig
u
r
atio
n
to
m
ee
t
en
er
g
y
n
ee
d
s
with
o
u
t
waste
[
4
]
.
Var
io
u
s
m
eth
o
d
s
ar
e
u
s
ed
f
o
r
th
is
p
u
r
p
o
s
e,
ea
c
h
with
s
p
ec
if
ic
ad
v
an
tag
es
an
d
lim
itatio
n
s
[
5
]
.
On
e
c
o
m
m
o
n
ap
p
r
o
ac
h
,
th
e
'
m
o
n
th
ly
a
v
er
a
g
e
s
o
lar
r
ad
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n
'
m
eth
o
d
,
l
ev
er
ag
es
h
is
to
r
ical
s
o
lar
d
ata
to
b
alan
ce
en
e
r
g
y
g
en
er
atio
n
a
n
d
s
to
r
ag
e
ef
f
ec
tiv
ely
in
r
eg
io
n
s
with
s
tab
le
w
ea
th
er
[
6
]
.
Yet,
it
m
ay
b
e
less
ac
cu
r
ate
in
ar
ea
s
with
h
ig
h
s
o
lar
v
ar
iab
ilit
y
[
7
]
.
T
h
e
'
p
ea
k
s
u
n
h
o
u
r
s
'
m
eth
o
d
s
im
p
lifie
s
s
iz
in
g
b
y
u
s
in
g
p
ea
k
s
u
n
lig
h
t
h
o
u
r
s
,
b
u
t
its
s
im
p
licity
ca
n
r
ed
u
ce
ac
cu
r
ac
y
[
8
]
.
Mo
r
e
ad
v
a
n
ce
d
m
eth
o
d
s
,
lik
e
'
h
y
b
r
id
s
im
u
latio
n
-
o
p
tim
izatio
n
,
'
co
m
b
in
e
s
im
u
latio
n
with
o
p
ti
m
izatio
n
alg
o
r
ith
m
s
to
ad
ap
t
to
s
p
ec
if
ic
co
n
d
itio
n
s
,
th
o
u
g
h
th
ey
r
eq
u
ir
e
h
i
g
h
co
m
p
u
tatio
n
al
r
eso
u
r
ce
s
[
9
]
,
[
10
]
.
AI
-
b
ased
ap
p
r
o
ac
h
es,
in
c
lu
d
in
g
m
ac
h
i
n
e
lear
n
in
g
an
d
n
eu
r
al
n
etwo
r
k
s
,
ar
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
Op
timiz
a
tio
n
a
n
d
d
imen
s
io
n
i
n
g
o
f sta
n
d
-
a
lo
n
e
s
ystems
:
en
h
a
n
cin
g
MPP
T e
fficien
cy
…
(
M
o
u
fid
a
S
a
a
d
i
)
309
em
er
g
in
g
f
o
r
PV
s
izin
g
,
y
ield
in
g
ac
cu
r
ate
p
r
ed
ictio
n
s
wh
en
q
u
ality
d
ata
is
av
ailab
le
[1
1
]
,
[
1
2
]
.
Op
tim
izatio
n
s
tr
ateg
ies
f
u
r
th
er
en
h
an
ce
P
V
s
y
s
tem
p
er
f
o
r
m
a
n
ce
,
in
cl
u
d
in
g
s
tr
ateg
ic
p
a
n
el
p
lace
m
e
n
t,
ef
f
ec
tiv
e
b
atter
y
m
an
ag
em
en
t,
an
d
m
ax
im
u
m
p
o
wer
p
o
in
t
tr
ac
k
in
g
(
MPPT)
f
o
r
o
p
tim
al
en
er
g
y
co
n
v
er
s
i
o
n
u
n
d
er
ch
an
g
in
g
en
v
ir
o
n
m
en
tal
co
n
d
itio
n
s
[1
3
]
–
[1
5
]
.
MPPT
s
ig
n
if
ican
tly
b
o
o
s
ts
en
er
g
y
y
ield
s
in
r
e
g
io
n
s
with
v
ar
iab
l
e
wea
th
er
,
wh
ile
ad
v
a
n
ce
d
te
ch
n
iq
u
es
lik
e
a
r
tific
ial
n
eu
r
al
n
etwo
r
k
s
(
ANN)
an
d
d
e
ep
lear
n
in
g
g
en
eti
c
alg
o
r
ith
m
s
(
DL
GA)
r
ef
in
e
o
p
t
im
izatio
n
,
im
p
r
o
v
i
n
g
en
er
g
y
m
an
ag
em
en
t
ac
cu
r
ac
y
an
d
ad
ap
tab
ilit
y
in
d
iv
er
s
e
en
v
ir
o
n
m
en
ts
[1
6
]
–
[1
9
]
.
T
h
e
s
tr
u
ctu
r
e
o
f
t
h
e
p
a
p
er
i
s
m
eth
o
d
ically
o
r
g
an
ize
d
to
f
ac
ilit
ate
u
n
d
er
s
tan
d
in
g
th
e
p
r
o
ce
s
s
o
f
p
r
ec
is
e
s
izin
g
an
d
o
p
tim
izatio
n
o
f
s
tan
d
-
alo
n
e
PV
s
y
s
tem
s
.
Sectio
n
2
d
is
cu
s
s
es
th
e
m
o
d
elin
g
an
d
s
izin
g
m
eth
o
d
o
l
o
g
ies
f
o
r
t
h
ese
s
y
s
tem
s
.
Sectio
n
3
r
ev
iews
r
ec
en
t
ad
v
an
ce
m
e
n
ts
in
in
tellig
en
t
MPPT
tech
n
iq
u
es.
Sectio
n
4
f
o
cu
s
es
o
n
th
e
ap
p
li
ca
tio
n
o
f
ANN
an
d
DL
GA
in
o
p
tim
izin
g
MPPT,
wh
ile
s
ec
tio
n
5
p
r
esen
ts
an
d
an
aly
ze
s
th
e
r
esear
ch
f
in
d
i
n
g
s
.
Fin
ally
,
s
ec
tio
n
6
s
u
m
m
ar
izes
th
e
s
tu
d
y
'
s
k
ey
in
s
ig
h
ts
an
d
c
o
n
clu
s
io
n
s
,
h
ig
h
lig
h
tin
g
th
e
p
o
ten
tial f
o
r
f
u
tu
r
e
r
esear
ch
an
d
d
ev
elo
p
m
e
n
t.
2.
M
O
DE
L
I
NG
AN
D
SI
Z
I
NG
ST
AND
-
A
L
O
N
E
SYS
T
E
M
T
h
e
co
m
p
o
n
e
n
ts
o
f
a
ty
p
ical
is
o
lated
s
y
s
tem
p
o
wer
ed
b
y
s
o
lar
en
e
r
g
y
,
s
u
p
p
lem
e
n
ted
wi
th
b
atter
y
s
to
r
ag
e,
ar
e
m
o
d
eled
m
ath
em
atica
lly
.
T
h
is
s
y
s
tem
is
r
ep
r
esen
ted
as
a
s
tan
d
-
al
o
n
e
c
o
n
f
ig
u
r
atio
n
in
Fig
u
r
e
1
.
T
o
ac
h
iev
e
e
n
er
g
y
s
elf
-
s
u
f
f
ici
en
cy
,
th
e
f
in
al
s
y
s
tem
co
n
f
i
g
u
r
atio
n
co
n
s
is
ts
o
f
th
e
f
o
llo
win
g
elem
en
ts
:
-
A
1
.
2
k
W
s
o
lar
p
o
wer
u
n
it,
c
o
m
p
r
is
in
g
1
6
PV
p
an
els,
c
o
n
n
ec
ted
to
a
DC
-
DC
co
n
v
e
r
ter
an
d
in
ter
f
ac
ed
with
th
e
d
ir
ec
t c
u
r
r
en
t (
DC
)
b
u
s
.
-
T
wo
b
atter
ies,
ea
ch
with
a
c
ap
ac
ity
o
f
1
0
0
Ah
an
d
a
v
o
l
tag
e
o
f
1
2
V,
i
n
teg
r
ated
i
n
to
th
e
s
y
s
tem
v
ia
a
b
id
ir
ec
tio
n
al
DC
-
DC
co
n
v
er
ter
.
B
o
th
b
atter
ies
s
h
ar
e
th
e
s
am
e
co
n
n
ec
tio
n
p
o
in
t
an
d
ar
e
co
n
n
ec
ted
to
th
e
DC
b
u
s
th
r
o
u
g
h
b
o
th
alter
n
atin
g
cu
r
r
en
t (
AC
)
/DC
an
d
D
C
-
DC
co
n
v
er
ter
s
.
Fig
u
r
e
1
.
Sy
s
tem
co
m
p
o
n
e
n
ts
an
d
d
escr
ip
tio
n
I
n
th
is
s
ec
tio
n
,
we
d
elv
e
in
to
a
d
etailed
ex
p
lo
r
atio
n
o
f
a
p
o
wer
s
y
s
tem
,
f
o
cu
s
in
g
o
n
th
e
i
n
tr
icac
ies
o
f
m
o
d
elin
g
its
v
ar
i
o
u
s
co
m
p
o
n
e
n
ts
.
T
h
e
eq
u
ilib
r
i
u
m
o
f
p
o
wer
with
in
th
e
DC
b
u
s
ca
n
b
e
f
o
r
m
u
lated
as
(
1
)
.
(
)
=
(
(
)
±
(
)
)
(
1
)
I
n
th
is
eq
u
atio
n
,
(
)
an
d
(
)
r
ep
r
e
s
en
t
th
e
p
o
wer
o
u
tp
u
ts
f
r
o
m
th
e
PV
ar
r
ay
an
d
t
h
e
b
atter
y
b
an
k
,
r
esp
ec
tiv
ely
.
T
h
e
co
n
s
tan
ts
,
d
en
o
te
th
e
ef
f
icien
cies o
f
th
e
DC
/D
C
an
d
DC
/A
C
p
o
wer
co
n
v
er
ter
s
.
Fo
r
th
e
p
u
r
p
o
s
e
o
f
th
is
an
aly
s
is
,
t
h
ese
ef
f
icien
cies
ar
e
ass
u
m
ed
to
b
e
co
n
s
tan
t,
with
=
0
.
95
an
d
=
0
.
9
.
T
h
e
s
ig
n
co
n
v
en
tio
n
f
o
r
P
b
(
t
)
d
esig
n
ates
it
as
n
eg
ativ
e
wh
en
th
e
b
atter
y
is
ch
a
r
g
in
g
an
d
p
o
s
itiv
e
wh
en
d
is
ch
ar
g
in
g
.
Ho
wev
er
,
it
is
ess
en
tial
to
n
o
te
th
at
p
o
wer
b
alan
ce
is
c
o
n
s
tr
ain
ed
b
y
c
er
tain
p
h
y
s
ical
an
d
o
p
er
atio
n
al
lim
itatio
n
s
.
0
≤
(
)
≤
(
t)
≤
(
)
≤
(
2
)
W
h
er
e
r
ep
r
esen
ts
th
e
av
aila
b
le
p
o
wer
g
en
e
r
atio
n
f
r
o
m
t
h
e
PV
ar
r
ay
an
d
r
ef
er
to
th
e
m
in
im
u
m
an
d
m
ax
im
u
m
b
atte
r
y
b
an
k
p
o
wer
,
r
esp
ec
tiv
ely
[
20
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
9
2
I
n
t J Ap
p
l Po
wer
E
n
g
,
Vo
l.
1
4
,
No
.
2
,
J
u
n
e
20
2
5
:
3
08
-
3
18
310
2
.
1
.
P
ho
t
o
v
o
lt
a
ic
a
rr
a
y
T
h
e
p
o
wer
tr
an
s
m
is
s
io
n
to
th
e
g
en
er
ato
r
s
h
af
t
in
a
PV
s
y
s
tem
r
ef
er
s
to
t
h
e
co
n
v
er
s
io
n
o
f
in
cid
e
n
t
s
o
lar
r
ad
iatio
n
i
n
to
elec
tr
ical
p
o
wer
.
T
h
is
co
n
v
e
r
s
io
n
p
r
o
ce
s
s
is
ac
co
m
p
lis
h
ed
th
r
o
u
g
h
t
h
e
o
p
er
atio
n
o
f
th
e
PV p
an
els
[2
1
]
.
T
h
e
p
o
wer
tr
a
n
s
m
itted
to
th
e
g
en
er
ato
r
s
h
af
t
,
r
ep
r
esen
ted
b
y
(
3
)
,
is
a
f
u
n
cti
o
n
o
f
th
e
a
v
ailab
le
s
o
lar
r
ad
iatio
n
,
th
e
ef
f
icien
cy
o
f
th
e
PV
p
an
els,
s
u
r
f
ac
e
ar
ea
o
f
th
e
PV
p
an
els,
th
e
tem
p
er
atu
r
e
co
ef
f
icien
t f
o
r
th
e
PV p
an
els.
T
h
is
eq
u
atio
n
q
u
an
tifie
s
th
e
p
o
wer
o
u
tp
u
t
o
f
th
e
PV
s
y
s
tem
,
p
r
o
v
id
in
g
v
al
u
ab
le
in
s
ig
h
ts
in
to
its
ca
p
ac
ity
to
g
e
n
er
ate
elec
tr
ical
en
er
g
y
f
r
o
m
s
u
n
lig
h
t
.
(
)
=
.
(
)
.
.
(
1
+
.
(
(
)
−
)
)
(
3
)
W
h
er
e
r
ef
er
en
ce
tem
p
er
atu
r
e
is
tem
p
er
atu
r
e
as
a
f
u
n
ctio
n
o
f
tim
e
an
d
is
th
e
s
o
lar
r
ad
iatio
n
as
a
f
u
n
ctio
n
o
f
tim
e.
T
h
e
av
e
r
ag
e
p
o
wer
o
f
o
v
er
th
e
s
p
ec
if
ied
tim
e
p
er
io
d
ca
n
b
e
ca
lcu
lated
u
s
in
g
(
4
)
.
=
1
∫
0
.
(
)
.
.
(
1
+
.
(
(
)
−
)
)
.
(
4
)
2
.
2
.
St
o
ra
g
e
o
f
ener
g
y
L
ea
d
-
ac
id
b
atter
ies
u
s
ed
in
PV
-
w
in
d
s
y
s
tem
s
f
u
n
ctio
n
u
n
d
er
d
ef
i
n
ed
co
n
d
itio
n
s
.
I
n
t
h
e
t
y
p
i
c
al
o
p
e
r
a
t
i
o
n
a
l
s
t
a
t
e
,
i
t
i
s
d
i
f
f
i
c
u
l
t
t
o
a
n
t
i
c
i
p
at
e
w
h
et
h
e
r
e
n
e
r
g
y
wi
l
l
b
e
d
r
a
w
n
f
r
o
m
o
r
s
u
p
p
l
i
e
d
to
t
h
e
b
a
t
t
e
r
y
[2
2
]
.
E
ac
h
b
atter
y
with
in
th
e
en
e
r
g
y
s
to
r
ag
e
s
y
s
tem
is
d
ep
icted
as
an
eq
u
iv
alen
t
cir
cu
it,
c
o
m
p
r
is
in
g
a
v
o
ltag
e
s
o
u
r
ce
(
r
ep
r
esen
tin
g
o
p
e
n
cir
cu
it
v
o
ltag
e,
)
in
s
er
ies
with
a
n
in
ter
n
al
r
esis
tan
ce
(
R
_
in
t)
[2
3
]
.
As
a
r
esu
lt,
th
e
ter
m
in
al
v
o
lta
g
e
o
f
t
h
e
b
at
ter
y
is
estab
lis
h
ed
b
y
(
5
)
.
=
−
(
5
)
I
n
th
is
m
o
d
el,
b
o
t
h
an
d
ar
e
d
ep
e
n
d
en
t
o
n
th
e
b
atter
y
'
s
s
tate
o
f
ch
ar
g
e
(
)
,
w
h
ich
in
d
icate
s
th
e
r
em
ain
i
n
g
ca
p
ac
i
ty
av
ailab
le
f
o
r
d
is
ch
ar
g
e.
T
h
i
s
co
r
r
elatio
n
is
r
ep
r
esen
ted
as
d
ata
v
ec
t
o
r
s
,
with
th
eir
v
alu
es
d
eter
m
in
ed
th
r
o
u
g
h
in
ter
p
o
latio
n
with
in
th
e
r
e
s
p
ec
tiv
e
v
ec
to
r
b
ased
o
n
th
e
cu
r
r
en
t
.
T
h
is
ac
co
m
m
o
d
ates
th
e
n
o
n
lin
ea
r
in
ter
d
ep
en
d
e
n
cies
b
etwe
en
an
d
.
T
h
e
s
tate
o
f
ch
ar
g
e
ca
n
b
e
ex
p
r
ess
ed
as
(
6
)
.
=
∗
,
−
∗
,
∗
,
100
[
%
]
(
6
)
W
h
er
e
∗
,
r
ep
r
esen
ts
th
e
n
u
m
b
er
o
f
am
p
er
e
-
h
o
u
r
s
alr
ea
d
y
u
tili
ze
d
an
d
∗
,
s
ig
n
if
ies
th
e
m
ax
im
u
m
ca
p
ac
ity
,
m
ea
s
u
r
ed
in
am
p
e
r
e
-
h
o
u
r
s
.
T
h
is
ca
n
b
e
co
m
p
u
te
d
a
s
(
7
)
.
∗
,
=
∫
3600
0
[
ℎ
]
(
7
)
W
h
er
e
d
en
o
tes
th
e
ch
a
r
g
e/d
is
ch
ar
g
e
b
atter
y
C
o
u
l
o
m
b
ic
e
f
f
i
cien
cy
,
wh
ich
is
0
.
9
7
5
i
n
th
is
ca
s
e.
s
ig
n
if
ies
th
e
b
atter
y
cu
r
r
en
t
in
am
p
er
e
s
,
with
>
0
in
d
icatin
g
d
is
ch
a
r
g
e
a
n
d
<
0
in
d
icatin
g
c
h
ar
g
in
g
.
T
h
e
i
n
itial
is
d
eter
m
in
ed
b
y
a
n
o
n
ze
r
o
i
n
itial
v
alu
e
o
f
∗
,
.
T
o
en
s
u
r
e
o
p
t
im
al
p
er
f
o
r
m
an
ce
an
d
b
atter
y
lo
n
g
ev
ity
,
m
u
s
t b
e
m
ain
tain
ed
with
in
s
p
ec
if
ic
lim
its
,
d
ef
in
ed
as
≤
≤
.
T
h
e
b
atter
y
cu
r
r
e
n
t
is
s
u
b
jec
t
to
co
n
s
tr
ain
ts
,
an
d
th
ese
li
m
its
ar
e
co
n
tin
g
e
n
t
o
n
an
d
,
as
d
escr
ib
ed
b
y
(
8
)
.
=
{
(
−
)
ℎ
(
−
)
ℎ
(
8
)
an
d
r
ep
r
esen
t
th
e
m
in
im
u
m
an
d
m
a
x
im
u
m
p
e
r
m
is
s
ib
le
b
atter
y
b
an
k
v
o
ltag
es,
r
esp
ec
tiv
ely
.
Fu
r
th
er
m
o
r
e
,
is
in
d
ir
ec
tly
in
f
l
u
en
ce
d
b
y
th
r
o
u
g
h
th
e
p
r
ev
i
o
u
s
ly
m
en
tio
n
ed
n
o
n
lin
ea
r
r
elatio
n
s
h
ip
s
.
Ad
d
itio
n
ally
,
a
m
ec
h
an
is
m
is
in
p
lace
to
lim
it
th
e
b
atter
y
b
an
k
cu
r
r
en
t,
en
s
u
r
in
g
ze
r
o
c
u
r
r
en
t
wh
en
r
ea
ch
es its
m
ax
im
u
m
o
r
m
in
i
m
u
m
v
alu
e
[2
4
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
Op
timiz
a
tio
n
a
n
d
d
imen
s
io
n
i
n
g
o
f sta
n
d
-
a
lo
n
e
s
ystems
:
en
h
a
n
cin
g
MPP
T e
fficien
cy
…
(
M
o
u
fid
a
S
a
a
d
i
)
311
3.
SI
Z
I
NG
S
T
AND
-
A
L
O
NE
S
YST
E
M
B
AS
E
D
O
N
M
O
N
T
H
L
Y
AVE
RAG
E
M
E
T
H
O
D
T
h
e
ef
f
ec
tiv
e
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d
d
ep
e
n
d
ab
le
f
u
n
ctio
n
in
g
o
f
a
s
tan
d
-
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p
h
o
to
v
o
ltaic/b
atter
y
s
y
s
tem
r
eli
es
h
ea
v
ily
o
n
ac
cu
r
ate
s
izin
g
.
Sizin
g
t
h
is
s
y
s
tem
u
tili
zin
g
m
o
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th
ly
av
er
ag
e
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ata
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estab
lis
h
in
g
th
e
s
u
itab
le
ca
p
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ities
f
o
r
th
e
PV
p
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els
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d
en
er
g
y
s
to
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ag
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elem
en
ts
,
wh
ich
ar
e
cr
u
cial
in
p
r
o
f
icie
n
tly
f
u
lf
illi
n
g
th
e
lo
a
d
d
em
an
d
s
(
r
e
f
er
to
T
ab
le
1
)
.
T
h
e
g
en
er
al
lo
a
d
,
PV
,
an
d
en
er
g
y
p
r
o
d
u
ce
d
ar
e
g
i
v
en
b
y
(
9
)
an
d
(
1
0
)
.
=
(
9
)
=
(
1
0
)
W
ith
:
=
−
[
1
−
(
−
−
)
]
(
1
1
)
T
h
r
o
u
g
h
r
ig
o
r
o
u
s
co
m
p
u
tatio
n
s
o
f
m
o
n
th
ly
en
e
r
g
y
y
ield
f
o
r
ea
ch
g
en
er
ato
r
an
d
co
r
r
esp
o
n
d
in
g
lo
ad
d
em
an
d
,
d
is
tin
ct
s
u
r
f
ac
e
ar
ea
s
f
o
r
p
h
o
to
v
o
ltaic
p
an
els
ar
e
d
is
ce
r
n
ed
.
T
h
ese
q
u
an
tific
atio
n
s
ar
e
d
ed
u
ce
d
u
s
in
g
th
e
f
o
r
m
u
latio
n
s
p
r
esen
ted
f
o
r
PV,
as e
lu
cid
ated
in
[2
5
]
.
=
ma
x
(
,
,
)
(
1
2
)
T
h
e
Mo
n
tn
e
y
en
er
g
ies p
r
o
d
u
c
ed
b
y
PV
ar
e
g
iv
en
i
n
(
1
3
)
.
{
,
=
(
∑
12
=
1
)
/
12
,
=
(
∑
12
=
1
)
/
12
(
1
3
)
H
er
e,
E
lm
ea
n
r
e
p
r
esen
ts
th
e
e
n
er
g
y
r
eq
u
ir
e
d
to
m
ee
t
t
h
e
lo
a
d
d
em
an
d
.
I
t
is
ca
lcu
lated
as
t
h
e
av
er
ag
e
en
er
g
y
n
ee
d
ed
to
s
atis
f
y
t
h
e
s
y
s
tem
'
s
lo
ad
d
em
a
n
d
u
n
d
er
v
ar
io
u
s
c
o
n
f
ig
u
r
atio
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s
o
f
win
d
t
u
r
b
in
e
s
an
d
p
h
o
t
o
v
o
ltaic
p
an
els.
r
ep
r
esen
ts
t
h
e
p
r
o
p
o
r
tio
n
o
f
th
e
lo
a
d
s
u
p
p
lied
b
y
t
h
e
PV
s
o
u
r
ce
.
C
o
n
s
eq
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en
tly
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we
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th
e
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o
llo
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r
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lt
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x
p
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ess
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in
(
1
4
)
.
=
(
,
,
)
(
1
4
)
T
h
e
s
u
b
s
eq
u
en
t e
q
u
atio
n
s
esta
b
lis
h
th
e
q
u
an
titi
es o
f
PV p
a
n
els r
eq
u
ir
ed
,
as e
x
p
r
ess
ed
in
(
1
5
)
.
,
=
,
(
1
5
)
T
h
e
m
ea
n
e
n
er
g
y
co
n
s
u
m
p
tio
n
is
ex
p
r
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as
(
1
6
)
.
−
=
,
,
(
1
6
)
T
ab
le
1
.
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h
e
s
etu
p
an
d
p
ar
a
m
eter
s
o
f
th
e
PV a
n
d
win
d
en
er
g
y
s
y
s
tem
s
M
o
n
t
h
(
K
W
h
/
m)
T
(
°
C)
(
K
W
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/
m
2
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(
K
W
h
)
Jan
u
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8
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5
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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312
T
h
e
s
izin
g
p
ar
a
m
eter
s
f
o
r
th
e
h
y
b
r
i
d
s
y
s
tem
ar
e
d
eter
m
i
n
ed
b
ased
o
n
th
e
p
r
e
v
io
u
s
ly
o
u
tlin
ed
r
elatio
n
s
h
ip
s
.
T
ab
le
2
p
r
o
v
id
e
s
a
b
r
ea
k
d
o
wn
o
f
th
e
m
o
n
t
h
ly
en
er
g
y
p
r
o
d
u
ctio
n
f
r
o
m
th
e
s
o
lar
s
y
s
tem
.
I
t
ca
n
b
e
n
o
ted
th
at
t
h
e
av
er
a
g
e
p
h
o
to
v
o
ltaic
en
er
g
y
o
u
tp
u
t
is
ap
p
r
o
x
im
ately
1
3
.
4
2
k
W
h
/m
2
.
Giv
en
th
at
th
e
av
er
a
g
e
lo
ad
en
e
r
g
y
d
em
an
d
is
3
3
8
.
5
k
W
h
,
an
d
co
n
s
id
er
i
n
g
th
at
th
e
s
y
s
tem
in
q
u
esti
o
n
is
a
s
tan
d
-
alo
n
e
PV
s
y
s
tem
,
o
n
ly
th
e
c
o
n
f
ig
u
r
atio
n
o
f
4
0
p
an
els co
m
es c
lo
s
est to
m
ee
tin
g
th
e
r
eq
u
ir
ed
l
o
ad
en
e
r
g
y
o
f
5
2
3
.
4
7
k
W
h
.
B
atter
y
ca
p
ac
ity
is
ca
lcu
lated
u
s
in
g
th
e
an
n
u
al
m
o
n
th
ly
av
e
r
ag
e
m
eth
o
d
with
th
e
d
ay
o
f
au
to
n
o
m
y
,
as e
x
p
r
ess
ed
in
(
1
7
)
.
=
.
,
.
.
.
(
1
7
)
W
h
er
e
,
m
o
n
th
ly
lo
ad
co
n
s
u
m
ed
(
k
W
h
/d
)
an
d
th
e
n
u
m
b
e
r
o
f
d
ay
s
o
f
th
e
m
o
n
th
th
at
p
r
e
s
en
ts
th
e
m
ax
im
u
m
lo
a
d
(
3
1
d
ay
s
)
,
PD
P
s
tan
d
s
f
o
r
p
er
ce
n
tag
e
d
ep
th
o
f
d
is
ch
ar
g
e
.
T
h
e
ef
f
icien
c
y
o
f
th
e
b
atter
y
.
T
h
e
n
u
m
b
er
o
f
b
atter
ies u
s
ed
i
s
ca
lcu
lated
b
y
(
1
8
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.
=
[
−
]
(
1
8
)
W
h
er
e
−
r
ep
r
esen
ts
th
e
s
elec
ted
b
atter
y
ca
p
ac
ity
.
T
o
s
u
m
m
a
r
ize,
th
e
to
tal
m
ax
im
u
m
p
o
w
er
o
u
tp
u
t
o
f
th
e
p
h
o
to
v
o
ltaic
p
an
els
is
d
eter
m
in
ed
as
Pp
v
=
40
×
80
=
3
,
6
0
0
k
W
.
Mo
r
eo
v
er
,
th
e
s
y
s
tem
u
tili
ze
s
3
b
atter
ies
with
s
p
ec
if
icatio
n
s
o
f
(
1
2
V,
1
0
0
Ah
)
.
T
ab
le
2
.
T
h
e
n
u
m
b
er
o
f
win
d
tu
r
b
in
es a
n
d
p
an
els wa
s
d
eter
m
in
ed
th
r
o
u
g
h
(m
2
)
,
f
i
n
a
l
(m
2
)
El
me
a
n
(
K
w
h
)
0
0
0
0
0
0
.
1
4
.
2
8
7
4
.
5
2
2
6
0
.
6
8
0
.
2
7
.
5
12
7
.
7
5
2
1
0
4
.
0
3
0
.
3
7
.
7
6
12
7
.
7
5
2
1
0
4
.
0
3
0
.
4
8
.
4
0
13
8
.
3
9
1
1
2
.
5
9
0
.
5
8
.
6
4
13
8
.
3
9
8
1
1
2
.
7
0
0
.
6
1
0
.
0
4
16
1
0
.
3
3
6
1
9
8
.
7
0
0
.
7
1
1
.
1
7
17
1
0
.
9
8
1
4
7
.
3
5
0
.
8
1
4
.
1
2
23
1
4
.
8
5
8
1
9
9
.
2
8
0
.
9
1
9
.
8
3
31
2
0
.
0
2
2
6
8
.
6
6
1
2
6
.
3
8
40
2
6
.
4
8
3
4
5
.
3
6
4.
AP
P
L
I
CA
T
I
O
N
O
F
H
YB
RI
D
I
NT
E
L
L
I
G
E
N
T
M
P
P
T
(
DL
G
A)
T
h
e
ap
p
licatio
n
o
f
ANN
in
m
ax
im
u
m
p
o
wer
p
o
in
t
(
MPP
)
T
r
ac
k
in
g
is
p
ar
ticu
lar
ly
ess
en
tial
d
u
e
to
s
o
lar
en
er
g
y
'
s
in
h
er
en
tly
v
ar
ia
b
le
n
atu
r
e,
wh
ich
is
af
f
ec
ted
b
y
a
r
an
g
e
o
f
e
n
v
ir
o
n
m
en
tal
co
n
d
itio
n
s
,
in
clu
d
in
g
th
e
in
ten
s
ity
o
f
s
u
n
lig
h
t,
tem
p
er
atu
r
e,
an
d
s
h
ad
o
w
im
p
ac
ts
.
ANN
f
u
n
ctio
n
s
s
im
ilar
ly
to
th
e
h
u
m
an
b
r
ain
b
y
lear
n
in
g
a
n
d
r
etain
in
g
i
n
f
o
r
m
atio
n
an
d
in
s
ig
h
ts
th
r
o
u
g
h
a
n
etwo
r
k
o
f
in
ter
co
n
n
ec
ted
lin
k
s
k
n
o
wn
as
weig
h
ts
.
Fo
r
p
r
ec
is
e
id
en
tific
atio
n
o
f
th
e
MPP,
th
ese
we
ig
h
ts
as
s
o
ciate
d
with
th
e
n
eu
r
o
n
s
m
u
s
t
b
e
m
eticu
lo
u
s
ly
ca
lcu
lated
v
ia
an
ex
ten
s
iv
e
t
r
ain
in
g
p
r
o
ce
s
s
.
On
ce
th
is
tr
ain
in
g
is
co
m
p
lete,
th
e
AN
N
ca
n
s
er
v
e
as
an
esti
m
ato
r
f
o
r
th
e
MPP,
p
r
o
v
id
in
g
th
e
r
ef
er
e
n
ce
v
alu
e
(
m
ax
i
m
u
m
p
o
wer
v
o
ltag
e
(
VM
P
)
or
m
ax
im
u
m
p
o
wer
cu
r
r
en
t
(
I
MP
)
)
to
th
e
MPPT
co
n
tr
o
ller
[2
6
]
.
T
h
e
tr
ain
in
g
o
f
an
ANN
in
v
o
l
v
es
a
s
y
s
tem
atic
ad
ju
s
tm
en
t
o
f
weig
h
ts
an
d
b
iases
,
o
f
ten
u
ti
lizin
g
th
e
s
ig
m
o
id
ac
tiv
atio
n
f
u
n
ctio
n
.
I
n
itially
,
weig
h
ts
an
d
b
iases
ar
e
r
an
d
o
m
ly
ass
ig
n
ed
to
s
et
th
e
s
tar
tin
g
p
o
in
t
f
o
r
th
e
lear
n
in
g
p
r
o
ce
s
s
.
Du
r
in
g
f
o
r
war
d
p
r
o
p
ag
atio
n
,
in
p
u
ts
p
ass
th
r
o
u
g
h
th
e
n
etwo
r
k
,
with
ea
ch
n
eu
r
o
n
ca
lcu
latin
g
a
weig
h
ted
s
u
m
an
d
ad
d
in
g
a
b
ias,
s
u
b
s
eq
u
en
t
ly
p
ass
ed
th
r
o
u
g
h
a
n
ac
tiv
atio
n
f
u
n
ctio
n
lik
e
a
s
ig
m
o
id
.
T
h
e
s
ig
m
o
id
f
u
n
ctio
n
,
m
ap
p
in
g
v
alu
es
b
etwe
en
0
an
d
1
,
is
f
av
o
r
ed
f
o
r
its
ab
ilit
y
to
co
n
v
er
t n
u
m
b
e
r
s
in
to
p
r
o
b
ab
ilit
ies
an
d
h
an
d
le
n
o
n
-
lin
ea
r
d
ata
r
elatio
n
s
h
ip
s
.
Fo
llo
win
g
th
is
,
th
e
b
ac
k
p
r
o
p
ag
atio
n
p
h
ase
b
eg
in
s
,
wh
er
e
th
e
n
etwo
r
k
'
s
o
u
tp
u
t
er
r
o
r
is
ca
lcu
lated
a
n
d
p
r
o
p
a
g
at
ed
b
ac
k
war
d
,
ad
j
u
s
tin
g
weig
h
ts
an
d
b
iases
.
T
h
is
ad
ju
s
tm
en
t
is
b
ased
o
n
th
e
er
r
o
r
'
s
p
ar
tial
d
er
iv
ativ
es
co
n
ce
r
n
in
g
ea
ch
weig
h
t
an
d
b
ias,
g
u
id
ed
b
y
a
lea
r
n
in
g
r
ate
p
ar
am
eter
.
T
h
is
cy
cle
o
f
f
o
r
war
d
p
r
o
p
ag
atio
n
,
b
ac
k
p
r
o
p
ag
atio
n
,
a
n
d
weig
h
t
an
d
b
ias
a
d
ju
s
tm
en
ts
r
ep
ea
ts
o
v
er
m
u
ltip
le
iter
atio
n
s
,
g
r
ad
u
ally
r
ef
in
in
g
th
e
n
etwo
r
k
to
m
in
im
ize
p
r
ed
ictio
n
er
r
o
r
s
.
T
h
e
tr
ain
in
g
p
r
o
ce
s
s
also
in
clu
d
es
ev
alu
atin
g
an
d
ad
ju
s
tin
g
th
e
m
o
d
el
with
a
v
a
lid
atio
n
s
et
to
p
r
ev
en
t
o
v
er
f
itt
in
g
o
r
u
n
d
er
f
itti
n
g
,
en
s
u
r
in
g
th
e
ANN
ef
f
ec
tiv
ely
g
en
er
alize
s
to
n
ew
d
ata.
I
n
A
NNs,
an
in
cr
ea
s
e
in
th
e
n
u
m
b
er
o
f
h
id
d
e
n
lay
er
s
ca
n
lead
to
en
h
a
n
ce
d
tr
ac
k
in
g
ef
f
icien
cy
an
d
im
p
r
o
v
ed
p
er
f
o
r
m
an
ce
in
ad
a
p
tin
g
to
p
o
wer
f
lu
ctu
atio
n
s
in
th
e
ar
r
ay
,
th
o
u
g
h
it m
ay
also
r
esu
lt in
s
lo
wer
tr
ac
k
in
g
s
p
ee
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
Op
timiz
a
tio
n
a
n
d
d
imen
s
io
n
i
n
g
o
f sta
n
d
-
a
lo
n
e
s
ystems
:
en
h
a
n
cin
g
MPP
T e
fficien
cy
…
(
M
o
u
fid
a
S
a
a
d
i
)
313
T
h
e
in
teg
r
atio
n
GA
with
DL
f
o
r
th
e
o
p
tim
izatio
n
o
f
ANN
a
r
ch
itectu
r
es
h
as
b
ee
n
a
f
o
cu
s
o
f
v
ar
i
o
u
s
r
esear
ch
er
s
.
T
h
is
ap
p
r
o
ac
h
ai
m
s
to
en
h
an
ce
th
e
p
er
f
o
r
m
an
ce
o
f
m
u
lti
-
lay
er
p
er
ce
p
tr
o
n
n
etwo
r
k
s
.
Giv
en
th
e
co
m
p
u
tatio
n
al
co
m
p
lex
ity
a
n
d
ex
ten
d
e
d
tr
ai
n
in
g
d
u
r
atio
n
in
h
er
en
t
i
n
DL
ev
o
lu
tio
n
ar
y
alg
o
r
ith
m
s
lik
e
GA
ar
e
em
p
lo
y
ed
t
o
o
p
tim
ize
n
etwo
r
k
p
er
f
o
r
m
an
ce
.
GA
is
p
ar
ticu
lar
ly
n
o
ted
f
o
r
its
r
o
b
u
s
t
o
p
tim
izatio
n
ca
p
ab
ilit
ies.
T
h
is
m
eth
o
d
ef
f
ec
tiv
el
y
r
e
d
u
ce
s
co
m
p
u
tatio
n
al
co
m
p
lex
ity
an
d
in
cr
ea
s
es
o
v
e
r
all
s
y
s
tem
f
lex
ib
ilit
y
th
r
o
u
g
h
p
ar
am
eter
tu
n
i
n
g
,
th
e
r
eb
y
a
u
g
m
en
tin
g
th
e
p
er
f
o
r
m
an
ce
o
f
D
L
.
I
n
th
is
s
ch
em
e,
DL
is
u
tili
ze
d
to
d
eter
m
i
n
e
th
e
o
p
tim
al
d
u
ty
cy
cle
v
alu
e,
e
n
s
u
r
in
g
m
ax
im
u
m
p
o
wer
ex
tr
ac
ti
o
n
.
T
h
e
n
eu
r
al
n
etwo
r
k
u
n
d
er
g
o
es tr
ain
in
g
with
a
d
ataset,
wh
ich
is
th
en
o
p
tim
iz
ed
u
s
in
g
GA
f
o
r
im
p
r
o
v
ed
ef
f
ic
ien
cy
.
T
h
e
s
tep
s
in
v
o
lv
e
d
in
im
p
lem
en
tin
g
th
e
g
en
etic
alg
o
r
ith
m
ar
e
o
u
tlin
ed
as f
o
llo
ws:
-
Step
I
:
A
s
s
es
s
th
e
f
itn
ess
f
u
n
ctio
n
an
d
p
in
p
o
in
t th
e
d
esig
n
p
a
r
am
eter
s
.
-
Step
I
I
:
Gen
er
ate
a
p
o
p
u
latio
n
,
r
ep
r
esen
tin
g
p
o
ten
tial so
lu
tio
n
s
to
th
e
p
r
o
b
lem
.
-
Step
I
I
I
:
E
v
alu
ate
t
h
is
p
o
p
u
lati
o
n
u
s
in
g
a
n
o
b
jectiv
e
f
u
n
ctio
n
.
-
Step
I
V:
F
r
o
m
th
e
p
o
p
u
latio
n
,
s
elec
t
two
p
ar
en
ts
b
ased
o
n
t
h
eir
f
itn
ess
lev
els.
Hig
h
er
f
itn
ess
in
cr
ea
s
es
th
e
lik
elih
o
o
d
o
f
s
elec
tio
n
.
-
Step
V:
C
r
ea
te
a
n
ew
p
o
p
u
latio
n
b
y
r
ep
e
ated
ly
ex
e
cu
tin
g
s
el
ec
tio
n
,
cr
o
s
s
o
v
er
,
an
d
m
u
tatio
n
u
n
til
th
e
n
ew
p
o
p
u
latio
n
is
co
m
p
lete.
-
Step
VI
:
F
o
r
m
a
n
ew
g
e
n
er
ati
o
n
an
d
r
etu
r
n
to
s
tep
I
I
I
.
-
Step
VI
I
:
I
f
th
e
en
d
c
o
n
d
itio
n
(
m
in
im
izatio
n
o
f
m
ea
n
s
q
u
ar
ed
er
r
o
r
(
MSE
)
)
is
m
et,
co
n
cl
u
d
e
th
e
p
r
o
ce
s
s
an
d
id
en
tif
y
th
e
b
est s
o
lu
tio
n
as th
e
tar
g
et
(
s
ee
F
ig
u
r
e
2
)
.
Fig
u
r
e
2
.
B
lo
ck
d
iag
r
am
t
r
ain
i
n
g
MPPT
u
s
in
g
DL
GA
Fig
u
r
e
3
illu
s
tr
ates
th
e
tr
ain
in
g
d
y
n
am
ics
o
f
d
if
f
er
en
t
AN
N
ar
ch
itectu
r
es
:
ANN
with
1
0
n
eu
r
o
n
s
,
ANN
with
1
0
0
n
eu
r
o
n
s
,
d
ee
p
lear
n
in
g
(
DL
)
,
an
d
DL
GA
,
r
ep
r
esen
ted
as
Fig
u
r
es
3
(
a
)
-
3
(
d
)
,
r
esp
ec
tiv
ely
.
Am
o
n
g
th
ese,
DL
GA
(
Fig
u
r
e
3
(
d
)
)
s
h
o
ws
th
e
b
est
p
er
f
o
r
m
an
ce
,
with
r
a
p
id
c
o
n
v
e
r
g
e
n
ce
an
d
lo
w
m
ea
n
s
q
u
ar
ed
e
r
r
o
r
(
MSE
)
ac
r
o
s
s
tr
ain
in
g
,
v
alid
atio
n
,
an
d
test
p
h
ases
,
in
d
icatin
g
a
h
ig
h
ly
g
e
n
er
aliza
b
le
m
o
d
el.
Fig
u
r
e
3
(
a
)
s
h
o
ws
in
itial
im
p
r
o
v
em
en
t b
u
t
r
ea
c
h
es
a
p
latea
u
,
wh
ile
Fig
u
r
e
3
(
b
)
ex
h
ib
its
o
v
er
f
itti
n
g
,
as
s
ee
n
in
th
e
r
is
e
o
f
v
alid
atio
n
er
r
o
r
af
t
er
in
itial
p
r
o
g
r
ess
.
Fig
u
r
e
3
(
c
)
,
lik
e
Fig
u
r
e
3
(
a)
,
f
its
th
e
d
ata
d
ec
en
tly
b
u
t
s
h
o
ws
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
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8
7
9
2
I
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p
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n
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,
Vo
l.
1
4
,
No
.
2
,
J
u
n
e
20
2
5
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3
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3
18
314
a
s
lig
h
t
d
iv
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en
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etwe
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tr
ain
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g
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d
v
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r
s
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u
g
g
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n
g
p
o
s
s
ib
le
o
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er
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itti
n
g
.
Ov
er
all,
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p
r
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v
es
to
b
e
th
e
m
o
s
t
r
o
b
u
s
t,
m
ak
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g
it
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tim
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ch
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o
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ld
ap
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n
s
d
u
e
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its
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u
p
er
io
r
ac
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r
ac
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n
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g
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er
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n
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T
ab
le
3
p
r
o
v
id
es
a
d
etailed
co
m
p
a
r
is
o
n
o
f
th
e
ar
ch
itect
u
r
es
b
ased
o
n
k
ey
m
etr
ics
lik
e
ep
o
ch
r
an
g
e
(
0
to
1
0
0
0
)
,
tr
ain
i
n
g
tim
e,
o
v
er
all
p
er
f
o
r
m
an
ce
,
an
d
g
r
ad
ien
t
b
eh
av
i
o
r
.
T
h
ese
m
etr
ics
o
f
f
er
in
s
ig
h
ts
in
to
th
e
ef
f
icien
cy
an
d
ef
f
ec
tiv
e
n
ess
o
f
ea
ch
m
o
d
el,
with
th
e
g
r
ad
ien
t
tar
g
et
s
et
at
1e
-
1
6
,
r
ef
lectin
g
a
h
ig
h
p
r
ec
is
io
n
in
th
e
lear
n
in
g
p
r
o
ce
s
s
.
T
ab
le
3
.
C
o
m
p
a
r
is
o
n
b
etwe
en
p
er
f
o
r
m
an
ce
s
o
f
d
if
f
er
e
n
t a
r
ch
itectu
r
e
o
f
ANN
A
N
N
a
r
c
h
i
t
e
c
t
u
r
e
N
u
mb
e
r
o
f
e
p
o
c
h
s
El
a
p
se
d
t
i
m
e
(
s)
P
e
r
f
o
r
ma
n
c
e
G
r
a
d
i
e
n
t
A
N
N
1
0
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1
0
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0
00
:
0
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:
0
4
1
.
4
4
e
-
14
9
.
4
5
e
-
14
A
N
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1
0
0
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1
0
0
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00
:
0
0
:
0
8
1
.
3
3
e
-
14
7
.
3
2
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-
11
DL
1
0
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00
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0
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5
4
.
0
9
e
-
12
9
.
6
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e
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9
D
L
G
A
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4
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7
3
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4
7
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-
32
5
.
1
6
e
-
17
(
a)
(
b
)
(
c)
(
d
)
Fig
u
r
e
3
.
T
h
e
d
y
n
am
ic
tr
ain
in
g
o
f
v
ar
io
u
s
ANN
ar
ch
itectu
r
e
s
:
(
a)
ANN
with
1
0
n
eu
r
o
n
s
,
(
b
)
ANN
with
1
0
0
n
eu
r
o
n
s
,
(
c
)
d
ee
p
lear
n
in
g
(
DL
)
,
an
d
(
d
)
DL
GA
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
Op
timiz
a
tio
n
a
n
d
d
imen
s
io
n
i
n
g
o
f sta
n
d
-
a
lo
n
e
s
ystems
:
en
h
a
n
cin
g
MPP
T e
fficien
cy
…
(
M
o
u
fid
a
S
a
a
d
i
)
315
5.
DIS
CU
SS
I
O
N
O
F
R
E
SU
L
T
S
Set w
ith
in
th
e
s
p
ec
if
ic
en
v
ir
o
n
m
en
tal
co
n
d
itio
n
s
o
f
Neg
r
in
e,
W
ilay
a
o
f
T
eb
ess
a
in
Alg
er
ia,
th
e
s
tu
d
y
u
tili
ze
s
h
is
to
r
ical
atm
o
s
p
h
er
ic
d
ata
f
r
o
m
2
0
1
2
,
in
cl
u
d
in
g
v
ar
iab
les
lik
e
am
b
ien
t
tem
p
er
atu
r
e
a
n
d
s
o
la
r
in
s
o
latio
n
,
to
ac
cu
r
ately
s
ize
an
d
o
p
tim
ize
th
e
s
y
s
tem
as
s
h
o
wn
i
n
F
ig
u
r
e
4
.
T
h
e
s
y
s
tem
,
co
m
p
r
is
in
g
PV
p
an
els
an
d
b
atter
y
s
to
r
a
g
e,
was
s
im
u
lated
in
MA
T
L
AB
/
Simu
lin
k
u
s
in
g
l
o
ca
lized
d
at
a
an
d
lo
a
d
p
r
o
f
iles
,
s
h
o
wca
s
in
g
th
e
ef
f
ec
tiv
e
n
ess
o
f
ANN
-
o
p
tim
ized
MPPT
i
n
im
p
r
o
v
in
g
p
o
wer
g
en
er
atio
n
to
m
ee
t
v
a
r
y
in
g
en
er
g
y
d
em
a
n
d
s
.
T
h
e
s
tu
d
y
p
r
o
v
id
es
v
alu
ab
le
in
s
ig
h
ts
in
to
th
e
d
ep
lo
y
m
e
n
t
o
f
ef
f
icien
t
s
o
lar
en
er
g
y
s
y
s
tem
s
in
ar
id
an
d
s
em
i
-
ar
id
r
e
g
io
n
s
.
Fig
u
r
e
5
p
r
esen
ts
th
e
p
o
wer
g
en
er
ated
b
y
th
e
PV
an
d
w
in
d
tu
r
b
in
e
is
d
e
p
icted
alo
n
g
s
id
e
th
e
lo
ad
p
r
o
f
ile.
T
h
is
f
i
g
u
r
e
h
elp
s
v
is
u
alize
h
o
w
t
h
e
c
o
m
b
in
e
d
e
n
er
g
y
p
r
o
d
u
ctio
n
f
r
o
m
th
ese
r
en
e
wab
le
s
o
u
r
ce
s
alig
n
s
with
th
e
d
em
an
d
r
eq
u
ir
em
en
t
s
.
B
y
co
m
p
ar
in
g
th
ese
cu
r
v
e
s
,
o
n
e
ca
n
ass
ess
wh
eth
er
th
e
g
en
er
ated
p
o
wer
m
ee
ts
,
ex
ce
ed
s
,
o
r
f
alls
s
h
o
r
t o
f
th
e
lo
a
d
at
v
ar
i
o
u
s
p
o
in
ts
in
tim
e.
Fig
u
r
e
4
.
His
to
r
ical
d
ata
am
b
ien
t
tem
p
er
atu
r
e
an
d
s
o
lar
in
s
o
latio
n
in
o
n
e
y
ea
r
Fig
u
r
e
5
.
Po
wer
l
o
ad
p
r
o
f
ile
c
h
o
s
en
Fig
u
r
e
6
p
r
esen
ts
a
co
m
p
ar
ati
v
e
an
aly
s
is
o
f
two
MPPT
m
e
th
o
d
s
:
DL
GA
an
d
p
er
tu
r
b
an
d
o
b
s
er
v
e
(
P&
O
)
,
ap
p
lied
to
a
s
tan
d
-
a
lo
n
e
PV
s
y
s
tem
,
f
o
c
u
s
in
g
o
n
DC
b
u
s
v
o
ltag
e
.
Ov
er
1
2
h
o
u
r
s
,
th
e
DL
GA
co
n
s
is
ten
tly
m
ain
tain
s
a
h
ig
h
er
an
d
m
o
r
e
s
tab
le
v
o
ltag
e
t
h
an
P&
O.
W
h
ile
P&
O
s
h
o
ws
a
s
tep
-
lik
e
in
cr
ea
s
e
d
u
r
in
g
its
in
itial
r
am
p
-
u
p
,
in
d
icatin
g
its
iter
ativ
e
ap
p
r
o
ac
h
,
DL
GA
d
em
o
n
s
tr
ates
a
s
m
o
o
th
er
an
d
q
u
ic
k
er
co
n
v
er
g
en
ce
to
th
e
m
a
x
im
u
m
p
o
wer
p
o
in
t.
T
h
is
is
lik
ely
d
u
e
to
DL
GA'
s
p
r
ed
ictiv
e
ca
p
a
b
ilit
ies,
wh
ich
u
s
e
h
is
to
r
ical
d
ata
f
o
r
m
o
r
e
p
r
ec
i
s
e
co
n
tr
o
l.
T
h
e
zo
o
m
e
d
-
in
v
iew
r
ev
ea
ls
th
at
DL
GA
h
as
m
in
im
al
r
ip
p
le
an
d
tig
h
ter
v
o
ltag
e
r
eg
u
latio
n
,
s
u
g
g
esti
n
g
b
etter
h
an
d
lin
g
o
f
v
a
r
iab
le
en
v
ir
o
n
m
en
tal
co
n
d
itio
n
s
,
wh
ile
P&
O
s
h
o
ws
m
o
r
e
p
r
o
n
o
u
n
ce
d
v
o
ltag
e
f
lu
c
tu
atio
n
s
,
in
d
icatin
g
less
s
tab
ilit
y
.
DL
GA'
s
s
tab
ilit
y
r
ed
u
ce
s
p
o
wer
o
s
cillatio
n
s
,
en
h
an
cin
g
s
y
s
tem
ef
f
icien
cy
a
n
d
m
in
im
izin
g
wea
r
o
n
co
m
p
o
n
en
ts
.
Fig
u
r
e
7
c
o
m
p
ar
es
t
h
e
p
er
f
o
r
m
an
ce
o
f
f
o
u
r
MPPT
tech
n
iq
u
es
:
DL
GA,
DL
,
ANN,
an
d
P&
O
,
o
v
er
1
2
h
o
u
r
s
in
a
PV
s
y
s
tem
.
DL
GA,
ANN,
an
d
DL
d
em
o
n
s
tr
ate
a
s
wif
t
an
d
s
tab
le
r
is
e
to
p
ea
k
p
o
wer
,
with
DL
GA
s
h
o
win
g
s
u
p
er
io
r
s
tab
ilit
y
a
n
d
m
in
im
al
f
lu
ct
u
atio
n
s
.
As
s
o
lar
ir
r
ad
ian
ce
ch
a
n
g
es,
DL
GA
ad
ap
ts
well,
m
ain
tain
in
g
n
ea
r
-
o
p
tim
al
p
o
w
er
ar
o
u
n
d
8
8
0
W
,
wh
ile
P&
O
ex
p
er
ien
ce
s
a
lar
g
er
d
ip
to
7
8
0
W
.
Du
r
in
g
p
ea
k
m
id
d
ay
ir
r
a
d
ian
ce
,
DL
GA
s
u
s
tain
s
ar
o
u
n
d
1
5
5
0
W
,
o
u
t
p
e
r
f
o
r
m
in
g
P&
O,
wh
ich
f
lu
ctu
ates
n
ea
r
1
5
0
0
W
.
ANN
an
d
DL
m
atch
DL
GA
a
t
1
3
5
0
W
b
u
t
s
h
o
w
a
le
s
s
d
y
n
am
ic
r
esp
o
n
s
e
to
ir
r
ad
ian
ce
ch
an
g
es.
As
s
u
n
lig
h
t
wan
es,
DL
GA
m
ain
tain
s
th
e
h
ig
h
est
o
u
tp
u
t
(
8
5
0
W
)
,
wh
ile
P&
O
d
ec
lin
es
m
o
r
e
er
r
atic
ally
,
an
d
ANN/DL
d
r
o
p
m
o
r
e
s
h
ar
p
ly
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
9
2
I
n
t J Ap
p
l Po
wer
E
n
g
,
Vo
l.
1
4
,
No
.
2
,
J
u
n
e
20
2
5
:
3
08
-
3
18
316
Fig
u
r
e
8
,
d
e
p
ictin
g
b
atter
y
p
o
wer
o
u
tp
u
t
,
s
h
o
ws
th
at
DL
GA
s
tab
ilizes
q
u
ick
ly
,
m
ain
tain
in
g
co
n
s
is
ten
t
p
o
wer
with
m
in
im
al
f
lu
ctu
atio
n
,
in
d
icatin
g
e
f
f
icien
t
b
atter
y
m
an
ag
em
e
n
t.
I
n
co
n
tr
ast,
P&
O
ex
h
ib
its
m
o
r
e
p
r
o
n
o
u
n
ce
d
f
l
u
ctu
atio
n
s
,
s
u
g
g
esti
n
g
less
ef
f
icien
t
b
atter
y
ch
ar
g
e
r
e
g
u
lat
io
n
.
As
th
e
s
y
s
tem
tr
an
s
itio
n
s
to
d
is
ch
ar
g
in
g
,
DL
GA
h
an
d
les th
e
s
h
if
t sm
o
o
th
ly
,
wh
ile
ANN
an
d
DL
m
ir
r
o
r
ea
ch
o
th
er
clo
s
ely
in
p
er
f
o
r
m
an
ce
.
Ov
er
all,
DL
GA
s
tan
d
s
o
u
t
f
o
r
its
r
o
b
u
s
tn
ess
an
d
ad
a
p
tab
ilit
y
,
e
n
s
u
r
in
g
m
ax
i
m
u
m
b
atter
y
ef
f
icien
cy
an
d
s
y
s
tem
en
er
g
y
av
ailab
ilit
y
th
r
o
u
g
h
o
u
t th
e
d
a
y
.
Fig
u
r
e
6
.
Pro
f
ile
o
f
v
o
ltag
e
D
C
b
u
s
in
1
2
h
o
u
r
s
Fig
u
r
e
7
.
P
r
o
f
ile
o
f
a
PV p
o
w
er
in
th
e
1
2
h
o
u
r
s
Fig
u
r
e
8
.
Pro
f
ile
o
f
a
b
atter
y
p
o
wer
in
th
e
1
2
h
o
u
r
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
Op
timiz
a
tio
n
a
n
d
d
imen
s
io
n
i
n
g
o
f sta
n
d
-
a
lo
n
e
s
ystems
:
en
h
a
n
cin
g
MPP
T e
fficien
cy
…
(
M
o
u
fid
a
S
a
a
d
i
)
317
6.
CO
NCLU
SI
O
N
T
h
is
s
tu
d
y
in
v
esti
g
ated
th
e
o
p
tim
izatio
n
o
f
a
s
tan
d
-
alo
n
e
s
o
lar
p
o
wer
s
y
s
tem
b
y
im
p
r
o
v
in
g
MPPT
alg
o
r
ith
m
s
u
s
in
g
ANN
an
d
g
e
n
etic
alg
o
r
ith
m
s
(
GA)
,
s
p
ec
if
i
ca
lly
th
e
DL
GA
ap
p
r
o
ac
h
.
T
h
e
r
esu
lts
,
b
ased
o
n
s
im
u
latio
n
s
u
s
in
g
atm
o
s
p
h
er
ic
d
ata
f
r
o
m
Neg
r
in
e,
Alg
er
i
a,
s
h
o
wed
th
at
th
e
DL
GA
m
eth
o
d
o
u
t
p
er
f
o
r
m
s
tr
ad
itio
n
al
tech
n
i
q
u
es
lik
e
P
&
O
in
m
ain
tain
i
n
g
h
ig
h
er
,
m
o
r
e
s
tab
le
v
o
ltag
es,
lead
in
g
to
im
p
r
o
v
e
d
en
e
r
g
y
ca
p
tu
r
e.
T
h
e
DL
GA
also
d
e
m
o
n
s
tr
ated
s
u
p
er
i
o
r
p
e
r
f
o
r
m
an
c
e
in
m
an
a
g
in
g
b
atter
y
ch
ar
g
i
n
g
an
d
d
is
ch
ar
g
i
n
g
cy
cles,
en
h
an
cin
g
b
atter
y
ef
f
i
cien
cy
an
d
life
s
p
an
.
Ad
d
itio
n
ally
,
th
e
ANN
m
o
d
els
s
h
o
wed
ef
f
ec
tiv
e
p
o
wer
m
an
ag
em
en
t,
a
n
d
m
ea
n
s
q
u
a
r
ed
er
r
o
r
an
aly
s
is
co
n
f
ir
m
ed
ex
ce
llen
t
g
en
er
aliza
tio
n
ca
p
a
b
ilit
ies
in
th
e
ANN
tr
ain
in
g
p
r
o
ce
s
s
.
Ov
er
all,
th
is
r
esear
ch
h
ig
h
lig
h
ts
th
e
p
o
te
n
tial
o
f
in
tellig
en
t
MPPT
m
eth
o
d
s
to
o
p
tim
ize
s
o
lar
en
er
g
y
s
y
s
tem
s
,
o
f
f
er
i
n
g
m
o
r
e
r
eliab
le
an
d
ef
f
icien
t
s
o
lu
t
io
n
s
f
o
r
r
eg
i
o
n
s
with
h
ig
h
s
o
lar
p
o
ten
tial.
T
h
e
m
eth
o
d
o
l
o
g
ies p
r
esen
ted
ca
n
s
er
v
e
as a
b
en
c
h
m
ar
k
f
o
r
f
u
tu
r
e
r
en
ewa
b
le
en
e
r
g
y
o
p
tim
izatio
n
ef
f
o
r
ts
.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
N
o
f
u
n
d
in
g
in
v
o
lv
e
d
.
AUTHO
R
CO
NT
RI
B
UT
I
O
NS ST
A
T
E
M
E
N
T
T
h
is
jo
u
r
n
al
u
s
es
th
e
C
o
n
t
r
ib
u
to
r
R
o
les
T
a
x
o
n
o
m
y
(
C
R
ed
iT)
to
r
ec
o
g
n
ize
in
d
iv
i
d
u
al
au
th
o
r
co
n
tr
ib
u
tio
n
s
,
r
ed
u
ce
au
th
o
r
s
h
ip
d
is
p
u
tes,
an
d
f
ac
ilit
ate
co
llab
o
r
atio
n
.
Na
m
e
o
f
Aut
ho
r
C
M
So
Va
Fo
I
R
D
O
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