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[
1
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.
T
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[
4
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
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1328
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2
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er
t
h
a
n
t
h
e
n
e
u
r
al
n
et
w
o
r
k
co
n
tr
o
ller
a
n
d
ca
n
g
iv
e
m
o
r
e
p
o
w
er
t
h
a
n
o
t
h
er
d
if
f
er
e
n
t
m
eth
o
d
s
f
o
u
n
d
in
lite
r
atu
r
e
[
1
9
]
.
D'
So
u
za
et
al.
i
m
p
le
m
en
t
ed
v
ar
iab
le
s
ize
p
er
tu
r
b
atio
n
s
u
s
i
n
g
f
u
zz
y
lo
g
ic
an
d
n
o
n
-
s
w
i
tch
in
g
zo
n
e
s
ch
e
m
es
t
o
i
m
p
r
o
v
e
tr
a
n
s
ie
n
t
an
d
s
tead
y
-
s
tate
r
esp
o
n
s
es
[
20
]
.
Ho
w
e
v
er
,
th
e
p
er
f
o
r
m
a
n
ce
o
f
t
h
ier
d
ev
elo
p
e
d
alg
o
r
ith
m
s
w
as
n
o
t te
s
ted
p
ar
tial s
h
ad
i
n
g
co
n
d
it
io
n
.
I
t
is
th
e
o
b
j
ec
tiv
e
o
f
th
i
s
s
t
u
d
y
to
d
ev
elo
p
a
r
o
b
u
s
t
ef
f
ici
en
t
MP
P
T
alg
o
r
ith
m
t
h
at
o
v
e
r
co
m
e
s
t
h
e
p
r
o
b
lem
s
w
i
th
p
r
ev
io
u
s
co
n
v
en
tio
n
al
m
et
h
o
d
s
u
n
d
er
s
u
d
d
en
ch
a
n
g
es
a
n
d
p
ar
tial
s
h
ad
i
n
g
co
n
d
itio
n
s
.
T
h
e
m
ai
n
cr
eter
ia
f
o
r
th
e
d
esire
d
alg
o
r
ith
m
ar
e
ar
e;
h
i
g
h
er
ef
f
ic
ien
c
y
,
f
aster
co
n
v
er
g
e
n
ce
an
d
lo
w
er
o
s
cilla
tio
n
ab
o
u
t
th
e
g
lo
b
al
MP
P
u
n
d
er
s
ev
er
e
w
ea
t
h
er
co
n
d
itio
n
s
.
T
h
e
m
ain
id
ea
o
f
th
e
d
ev
e
lo
p
ed
a
lg
o
r
ith
m
is
u
s
i
n
g
a
h
y
b
r
id
co
m
b
in
atio
n
b
et
w
ee
n
th
e
f
u
zz
y
lo
g
ic
co
n
tr
o
ller
(
FLC)
an
d
th
e
co
n
v
e
n
tio
n
al
P
er
tu
r
b
-
an
d
-
Ob
s
er
v
e
(
P
&
O)
m
et
h
o
d
.
I
t
u
s
es
F
L
C
a
lg
o
r
ith
m
to
b
r
in
g
s
y
s
te
m
n
ea
r
th
e
MP
P
.
T
h
en
,
th
e
P
&
O
al
g
o
r
ith
m
w
it
h
a
s
m
al
l
s
tep
s
ize
is
u
s
ed
to
f
in
d
ac
cu
r
atel
y
an
d
ef
f
icie
n
tl
y
t
h
e
MP
P
.
B
y
r
ap
id
ly
b
r
in
g
s
th
e
s
y
s
te
m
to
th
e
v
ici
n
it
y
o
f
th
e
MP
P
an
d
P
&
O
alg
o
r
ith
m
w
it
h
s
m
all
s
tep
s
ize
ca
n
b
e
u
s
ed
f
o
r
h
i
g
h
er
ac
cu
r
ac
y
an
d
lo
w
er
o
s
cillatio
n
s
.
MA
T
L
A
B
/S
i
m
u
li
n
k
m
o
d
els c
o
n
s
is
tin
g
o
f
t
h
e
p
h
o
to
v
o
ltaic
s
y
s
te
m
,
b
o
o
s
t c
o
n
v
er
ter
an
d
co
n
tr
o
ller
s
ar
e
b
u
ilt to
in
v
e
s
ti
g
at
e
t
h
e
p
er
f
o
r
m
a
n
ce
o
f
th
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
.
2.
P
V
M
O
DE
L
I
N
G
AN
D
CH
A
RACT
E
RI
ST
I
CS
Detiale
d
d
escr
ip
tio
n
o
f
t
h
e
c
h
ar
ac
ter
is
tic
o
f
P
V
ce
ll
i
s
f
o
u
n
d
in
[
2
]
.
T
y
p
icall
y
,
th
e
g
e
n
er
at
ed
v
o
ltag
e
f
r
o
m
o
n
e
ce
ll
v
ar
ies
f
r
o
m
0
.
5
t
o
0
.
8
V
d
ep
en
d
in
g
o
n
th
e
m
an
u
f
ac
tu
r
i
n
g
tec
h
n
o
lo
g
y
.
T
o
b
o
o
s
t
th
i
s
lo
w
v
o
lta
g
e
an
d
m
a
k
e
it
m
o
r
e
u
s
ef
u
l,
d
o
ze
n
s
o
f
P
V
ce
lls
ar
e
co
n
n
ec
t
ed
in
s
er
ies
f
o
r
m
in
g
t
h
e
P
V
m
o
d
u
le
[
2
1
]
.
T
h
e
p
h
o
to
v
o
ltaic
m
o
d
u
le
c
u
r
r
en
t I
p
v
m
i
s
[
1
8
]:
1
s
N
sh
R
s
N
s
R
PV
I
pv
V
AT
b
K
s
N
PV
V
s
R
PV
I
q
e
I
ph
I
I
DS
PVM
(
1
)
w
h
er
e,
I
p
v
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th
e
c
u
r
r
en
t
g
e
n
e
r
ated
b
y
t
h
e
ce
ll,
I
p
h
is
th
e
s
o
lar
g
e
n
er
ated
cu
r
r
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n
t,
I
s
h
is
th
e
s
h
u
n
t
r
esis
ta
n
ce
cu
r
r
en
t
an
d
I
D
is
th
e
d
io
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e
cu
r
r
en
t,
q
is
an
elec
tr
o
n
ch
ar
g
e
(
1
.
6
1
0
×
10
−
19
C
)
,
T
is
th
e
ce
ll’s
o
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atin
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te
m
p
er
atu
r
e,
k
b
is
th
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m
an
n
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s
co
n
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ta
n
t
(
1
.
3
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×
10
−
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/
K)
,
A
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th
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io
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id
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lity
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ac
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R
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th
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er
ies
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ce
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p
v
ar
e
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h
e
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h
o
to
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o
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atin
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tag
e
a
n
d
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u
r
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t
r
esp
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ti
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el
y
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I
DS
i
s
t
h
e
d
io
d
e
s
atu
r
atio
n
cu
r
r
e
n
t.
E
q
u
atio
n
(
1
)
is
m
o
d
el
ed
in
M
A
T
L
A
B
/S
i
m
u
li
n
k
e
m
p
lo
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g
7
2
ce
lls
c
o
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ec
ted
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n
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er
ie
s
b
ased
o
n
t
h
e
elec
tr
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s
p
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if
i
ca
tio
n
s
p
r
o
v
id
ed
b
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UNT
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C
H
ST
P
2
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o
d
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l
e
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atash
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s
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ab
le
1
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T
ab
le
1
.
E
lectr
ical
s
p
ec
if
icatio
n
s
t
h
e
ST
P
2
7
0
-
2
4
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P
V
m
o
d
u
le
[
2
2
]
El
e
c
t
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c
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l
C
h
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r
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t
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t
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m
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g
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V
mp
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p
t
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mu
m
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p
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t
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r
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t
(
I
mp
)
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7
1
A
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p
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-
C
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r
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t
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5
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t
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r
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t
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r
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t
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sc
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8
.
2
0
A
M
a
x
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m
u
m
P
o
w
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r
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t
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C
(
P
m
a
x
)
2
7
0
W
T
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mp
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r
a
t
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r
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f
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sc
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5
%/
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C
T
h
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t
y
p
ical
P
-
V
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d
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V
n
o
n
l
in
ea
r
c
h
ar
ac
ter
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tic
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o
f
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h
e
P
V
m
o
d
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le
ar
e
s
h
o
w
n
i
n
Fig
u
r
e
1
.
As
ca
n
b
e
s
ee
n
f
r
o
m
t
h
e
c
u
r
v
es
in
Fi
g
u
r
e
1
,
m
ax
i
m
u
m
p
o
w
er
o
cc
u
r
s
at
a
u
n
iq
u
e
p
o
i
n
t
ca
lled
m
a
x
i
m
u
m
p
o
w
er
p
o
in
t
MP
P
.
MPPT
is
u
s
ed
to
m
ak
e
t
h
e
s
y
s
te
m
o
p
er
ate
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t
h
i
s
s
p
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if
ic
p
o
in
t.
T
h
e
p
ar
tial
s
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ad
i
n
g
o
cc
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r
s
w
h
en
a
p
ar
t
o
f
th
e
s
y
s
te
m
e
x
p
er
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ce
s
s
o
m
e
s
h
ad
o
w
in
g
.
M
u
ltip
le
p
ea
k
s
ap
p
ea
r
in
t
h
e
P
V
ch
ar
ac
ter
i
s
tic
w
h
e
n
t
h
e
s
y
s
te
m
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g
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r
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2
.
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h
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ex
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te
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ce
o
f
m
u
ltip
l
e
p
ea
k
s
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r
o
v
id
es
a
r
ea
l c
h
allen
g
e
f
o
r
MP
PT
alg
o
r
ith
m
s
.
(
a)
(
b)
Fig
u
r
e
1
.
P
o
w
er
cu
r
v
e
s
o
f
P
V
u
n
d
er
d
if
f
er
en
t i
n
s
u
lat
io
n
le
v
els,
(
a)
P
-
V
ch
ar
ac
ter
is
tics
,
(
b
)
I
-
V
ch
ar
ac
ter
is
t
ics
(
a)
(
b)
Fig
u
r
e
2
.
C
h
ar
ac
ter
is
tic
s
cu
r
v
es o
f
P
V
u
n
d
er
p
ar
tial sh
ad
i
n
g
(
a)
P
-
V
ch
ar
ac
ter
is
tics
,
(
b
)
I
-
V
ch
ar
ac
ter
is
tic
s
3.
M
P
P
T
AL
G
O
RI
T
H
M
S
T
h
e
p
o
w
er
p
r
o
d
u
ce
d
b
y
t
h
e
P
V
m
o
d
u
le
d
ep
en
d
s
o
n
t
h
e
v
o
ltag
e
d
eliv
er
ed
to
th
e
co
n
n
e
cted
lo
ad
.
B
o
o
s
t
co
n
v
er
to
r
s
co
n
tr
o
l
th
e
o
p
er
atin
g
v
o
lta
g
e
o
f
th
e
m
o
d
u
le
w
ith
o
u
t
t
h
e
n
ee
d
o
f
co
n
ti
n
u
o
u
s
l
y
ch
a
n
g
in
g
t
h
e
lo
ad
[
3
]
.
T
h
is
is
ac
h
iev
ed
u
s
i
n
g
a
tr
ain
o
f
p
u
ls
e
s
w
ith
v
ar
i
ab
le
d
u
t
y
c
y
cle
p
r
o
d
u
ce
d
b
y
a
p
u
ls
e
g
e
n
er
ato
r
.
T
h
er
ef
o
r
e,
a
M
P
PT
alg
o
r
ith
m
is
i
m
p
le
m
en
ted
to
f
in
d
th
e
o
p
ti
m
al
d
u
t
y
c
y
cle
to
m
ain
tain
t
h
e
m
a
x
i
m
u
m
p
o
w
er
lev
els.
3
.
1
.
P
er
t
urb a
nd
O
bs
er
v
e
(
P
&O
)
Alg
o
rit
h
m
T
h
e
d
etailed
d
escr
ip
tio
n
o
f
P&
O
ca
n
b
e
f
o
u
n
d
in
[
3
]
.
T
h
e
P
&
O
alg
o
r
ith
m
s
tep
s
ca
n
b
e
s
u
m
m
ar
ized
asf
o
llo
w
s
;
a
f
ter
r
ec
o
r
d
in
g
t
h
e
p
r
esen
t
p
o
w
er
lev
e
ls
p
r
o
d
u
ce
d
b
y
t
h
e
s
y
s
te
m
,
th
e
al
g
o
r
ith
m
p
er
f
o
r
m
s
a
p
er
tu
r
b
atio
n
to
th
e
o
p
er
atin
g
p
o
in
t
b
y
m
ea
n
s
o
f
ch
a
n
g
i
n
g
th
e
d
u
t
y
c
y
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ir
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tain
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3
.
2
.
F
uzzy
L
o
g
ic
Co
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ller
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F
L
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Un
li
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e
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e
tr
ad
itio
n
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b
in
ar
y
l
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ic
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er
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les
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n
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e
eith
er
tr
u
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alse,
th
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f
u
zz
y
l
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g
ic
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ls
w
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h
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ar
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ll
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ll
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u
e.
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f
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zz
y
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ased
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n
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ller
s
ca
n
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I
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PEDS
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2
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8
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694
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ased
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e
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s
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s
ed
to
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t
h
e
F
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s
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A
NFI
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T
ab
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2
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f
is
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3
.
P
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po
s
ed
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P
P
T
Alg
o
rit
h
m
T
h
e
id
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o
f
th
e
p
r
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p
o
s
ed
alg
o
r
ith
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is
in
s
p
ir
ed
b
y
u
s
in
g
t
h
e
b
en
ef
its
o
f
b
o
th
F
L
C
an
d
P
&
O
alg
o
r
ith
m
in
a
s
i
n
g
le
f
r
a
m
e
w
o
r
k
.
As
m
en
tio
n
ed
p
r
ev
io
u
s
l
y
,
th
e
F
L
C
ca
n
w
o
r
k
u
n
d
er
s
ev
er
e
w
ea
t
h
er
co
n
d
itio
n
s
w
it
h
li
m
ited
ac
c
u
r
ac
y
,
w
h
ile
P
&
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ca
n
b
e
h
i
g
h
l
y
ac
c
u
r
ate
w
h
e
n
u
s
i
n
g
s
m
al
l
s
tep
s
ize.
An
ef
f
i
cien
t
al
g
o
r
it
h
m
ca
n
b
e
co
n
s
tr
u
cted
w
h
en
u
ti
lizi
n
g
th
e
F
L
C
to
d
r
iv
e
t
h
e
s
y
s
te
m
cl
o
s
er
to
th
e
MP
P
,
th
en
u
s
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g
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&
O
to
p
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ce
ed
th
e
s
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r
ch
to
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n
d
th
e
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P
.
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ce
,
th
e
p
r
o
p
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s
ed
alg
o
r
ith
m
m
er
g
es th
e
s
w
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f
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n
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f
ap
p
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n
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P
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er
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d
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u
r
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3
s
h
o
w
s
th
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s
c
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m
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tic
d
iag
r
a
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s
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te
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it
h
h
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id
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s
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ild
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u
r
e
3
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s
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it
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id
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PT
4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
4
.
1
.
Cha
r
a
ct
er
is
t
ics o
f
F
uzz
y
Co
ntr
o
ller
T
h
e
f
u
zz
y
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n
tr
o
ller
d
ev
elo
p
ed
in
th
is
s
t
u
d
y
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e
n
er
ated
u
s
i
n
g
A
d
ap
ti
v
e
Neu
r
o
Fu
zz
y
I
n
f
er
en
ce
S
y
s
te
m
(
A
NFI
S)
b
ased
o
n
a
tr
ain
i
n
g
s
et
o
f
1
1
0
d
ata
p
o
in
t
s
.
I
n
o
r
d
er
to
ass
e
s
s
th
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cu
r
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y
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f
th
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f
u
zz
y
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n
tr
o
ller
,
t
w
o
s
ce
n
ar
io
s
ar
e
s
i
m
u
lated
;
(
1
)
T
esti
n
g
a
t
t
h
e
s
a
m
e
tr
ai
n
i
n
g
d
ata
p
o
in
ts
.
(
2
)
T
esti
n
g
f
ar
f
r
o
m
tr
ain
i
n
g
d
ata
p
o
in
ts
.
F
ig
u
r
e
(
4
-
a)
an
d
(
4
-
b
)
s
h
o
w
th
a
t
t
h
e
f
u
zz
y
co
n
tr
o
ller
r
ea
ch
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m
o
r
e
th
a
n
9
7
%
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f
th
e
av
ailab
le
p
o
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er
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e
n
ex
p
o
s
e
d
to
r
a
d
iatio
n
co
n
d
itio
n
s
ex
i
s
t
ed
in
th
e
tr
ain
i
n
g
d
ata
s
et.
Fi
g
u
r
e
(
4
-
c
)
an
d
(
4
-
d
)
s
h
o
w
t
h
at
th
e
ef
f
icie
n
c
y
o
f
th
e
f
u
zz
y
co
n
tr
o
ller
d
r
o
p
s
to
les
s
t
h
an
8
5
%
w
h
e
n
e
x
p
o
s
ed
to
r
ad
iatio
n
co
n
d
itio
n
s
d
if
f
er
f
r
o
m
t
h
o
s
e
u
s
ed
to
tr
ai
n
it.
I
t
'
s
clea
r
f
r
o
m
Fi
g
u
r
e
4
t
h
a
t
F
L
C
is
al
w
a
y
s
ca
p
ab
le
o
f
d
r
iv
in
g
th
e
s
y
s
te
m
to
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
: 2
0
8
8
-
8
694
IJ
PEDS
Vo
l.
8
,
No
.
3
,
Sep
tem
b
er
2
0
1
7
:
132
7
–
1
3
3
4
1331
th
e
v
ici
n
it
y
o
f
t
h
e
g
l
o
b
al
m
a
x
i
m
u
m
w
it
h
li
m
ited
ac
c
u
r
ac
y
th
at
n
ee
d
s
to
b
e
i
m
p
r
o
v
ed
.
E
m
p
lo
y
i
n
g
m
ass
iv
e
a
m
o
u
n
t
o
f
d
ata
p
o
in
ts
to
tr
ai
n
th
e
F
L
C
r
eq
u
ir
es
lar
g
e
ca
p
ac
it
y
o
f
co
n
tr
o
ller
's
m
e
m
o
r
y
a
n
d
h
i
g
h
er
p
r
o
ce
s
s
in
g
ti
m
e.
So
,
it
'
s
i
n
e
f
f
icien
t to
en
h
an
ce
th
e
ac
c
u
r
ac
y
o
f
F
L
C
b
y
i
n
cr
ea
s
i
n
g
tr
ai
n
i
n
g
d
ata
p
o
in
t
s
.
(
a)
(
b)
(
c)
(
d)
Fig
u
r
e
4
.
Fu
zz
y
co
n
tr
o
ller
p
er
f
o
r
m
a
n
ce
u
n
d
er
d
if
f
er
e
n
t r
ad
iatio
n
co
n
d
itio
n
s
,
(
a)
Un
if
o
r
m
r
ad
iatio
n
o
f
1
0
0
0
W
/m
2
(
b
)
p
ar
tial sh
ad
i
n
g
o
f
(
8
0
0
,
4
0
0
)
W
/m
2
(
c)
u
n
i
f
o
r
m
r
ad
iatio
n
o
f
6
3
5
W
/m
2
(
d
)
p
ar
tial sh
ad
in
g
o
f
(
9
8
5
,
3
1
7
)
W
/m
2
4
.
2
.
Cha
ra
c
t
er
is
t
ics o
f
P
er
t
u
rb
a
nd
O
bs
er
v
e
M
et
ho
d
P
er
tu
r
b
an
d
o
b
s
er
v
e
m
e
th
o
d
p
er
f
o
r
m
a
n
ce
d
ep
en
d
s
o
n
th
e
s
tep
s
ize.
T
o
illu
s
tr
ate
th
e
ef
f
ec
t
o
f
s
tep
s
ize
o
n
t
h
e
p
er
f
o
r
m
an
ce
o
f
P
&
O
al
g
o
r
ith
m
,
t
w
o
s
tep
s
ize
s
w
er
e
s
i
m
u
lated
u
n
d
er
u
n
i
f
o
r
m
s
h
ad
i
n
g
co
n
d
itio
n
s
.
Fig
u
r
e
5
s
h
o
w
s
th
at
u
s
in
g
lar
g
er
s
tep
s
ize
lead
s
to
f
aster
c
o
n
v
er
g
e
n
ce
w
i
th
w
id
er
o
s
cilla
tio
n
s
.
O
n
th
e
o
t
h
er
h
an
d
,
s
m
a
ller
s
tep
s
ize
lead
s
t
o
h
i
g
h
er
p
o
w
er
w
it
h
s
m
aller
o
s
cillatio
n
s
.
T
h
ese
o
b
s
er
v
at
io
n
s
ca
n
b
e
e
x
p
lai
n
e
d
as
f
o
llo
w
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tial sh
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in
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.
RE
F
E
R
E
NC
E
S
[1
]
K
.
Ba
tain
e
h
,
"
Op
ti
m
isa
ti
o
n
a
n
a
l
y
sis
o
f
so
lar
p
o
w
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Ra
n
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le
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,
IET
Re
n
e
w
a
b
le
P
o
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r
G
e
n
e
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a
ti
o
n
,
v
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l
.
1
1
(2
)
,
pp.
3
4
2
–
35
0
,
2
0
1
7
.
[2
]
A
A
ll
a
tai
f
e
h
e
t
a
l.
,
"
M
a
x
im
u
m
P
o
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P
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in
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T
ra
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g
Us
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F
u
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y
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Co
n
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r
o
ll
e
r
Un
d
e
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Co
n
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it
i
o
n
s"
,
Sm
a
rt
G
rid
a
n
d
Re
n
e
w
a
b
le E
n
e
rg
y
,
v
o
l.
6
(
1
)
,
p
p
.
1
-
1
3
,
2
0
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.
[3
]
V
.
S
a
las
e
t
a
l.
,
"
Re
v
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e
m
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p
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we
r
p
o
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n
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lo
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e
p
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o
to
v
o
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ic
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s
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,
S
o
lar E
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M
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teria
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o
lar Cells,
v
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l.
9
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,
p
p
.
1
5
5
5
–
1
5
7
8
,
2
0
0
6
.
[4
]
T
.
Ta
f
ti
c
h
t
e
t
a
l.
A.
A
n
im
p
ro
v
e
d
m
a
x
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m
u
m
p
o
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p
o
in
F
L
C
a
lg
o
rit
h
m
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trac
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e
th
o
d
f
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p
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o
t
o
v
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lt
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ic
sy
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s.
Re
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wa
b
le E
n
e
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y
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v
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l.
3
3
,
p
p
.
1
5
0
8
–
1
5
1
6
,
2
0
0
8
.
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
F
I
S
-
B
a
s
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I
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f
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&
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MPP
Tr
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in
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Meth
o
d
fo
r
P
h
o
to
vo
lta
ic
S
ystems
(
K
h
a
led
B
a
ta
in
eh
)
1334
[5
]
A
.
Am
iru
ll
a
h
,
A
.
Kis
w
a
n
to
n
o
,
"
P
o
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a
li
t
y
En
h
a
n
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e
m
e
n
t
o
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n
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ra
ti
o
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e
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to
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to
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rid
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e
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Va
riab
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lar
Irra
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ian
c
e
L
e
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u
sin
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P
P
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tern
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ti
o
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a
l
Jo
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e
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tri
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a
l
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g
(IJECE)
, v
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.
6
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N
o
6
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2
0
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.
[6
]
S.
Hass
a
n
,
"
A
n
A
d
v
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n
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e
d
M
P
P
T
Ba
se
d
o
n
A
rti
f
icia
l
Be
e
Co
lo
n
y
A
lg
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m
f
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P
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to
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y
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it
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o
n
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tern
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l
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u
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o
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r
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Driv
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y
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m
s
(I
JP
EDS
),
v
o
l.
8
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n
o
.
2
,
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0
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7
.
[7
]
C.
H.
L
in
,
C.
H.
,
"
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x
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m
p
h
o
to
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o
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o
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e
r
trac
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rra
y
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sin
g
th
e
f
ra
c
ti
o
n
a
l
-
o
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tal
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o
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d
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m
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o
d
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,
A
p
p
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d
E
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y
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v
o
l.
8
8
,
p
p
.
4
8
4
0
–
4
8
4
7
,
2
0
1
1
.
[8
]
R.
A
h
m
e
d
e
t
a
l.
,
"
I
m
p
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rt
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n
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Ob
se
rv
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M
e
th
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Us
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tate
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lo
w
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p
p
ro
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c
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,"
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e
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e
d
ia,
v
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l
.
4
2
,
p
p
.
6
1
4
–
6
2
3
,
2
0
1
3
.
[9
]
H.
T
a
h
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ri
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t
a
l.
2
0
1
0
,
"
A
No
v
e
l
M
a
x
i
m
u
m
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o
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o
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t
T
ra
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k
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tr
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h
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v
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lt
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ic
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y
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m
Un
d
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a
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n
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p
id
ly
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lu
c
tu
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ti
n
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S
h
a
d
o
w
Co
n
d
it
i
o
n
s
Us
in
g
Dif
fe
re
n
ti
a
l
Ev
o
lu
ti
o
n
"
,
P
ro
c
.
IEE
E
S
y
m
p
o
siu
m
o
n
In
d
u
strial
El
e
c
tro
n
ics
a
n
d
A
p
p
li
c
a
ti
o
n
s Co
n
f
.
,
pp.
82
-
87
,
2
0
1
0
.
[1
0
]
L
.
Jia
n
g
e
t
a
l.
,
"
A
n
o
v
e
l
a
n
t
c
o
l
o
n
y
o
p
ti
m
iza
ti
o
n
-
b
a
se
d
m
a
x
i
m
u
m
p
o
we
r
p
o
in
t
trac
k
in
g
f
o
r
p
h
o
t
o
v
o
lt
a
ic
sy
ste
m
s
u
n
d
e
r
p
a
rti
a
ll
y
sh
a
d
e
d
c
o
n
d
it
i
o
n
s
"
,
En
e
rg
y
a
n
d
Bu
il
d
in
g
s,
v
o
l
.
5
8
,
p
p
.
2
2
7
–
2
3
6
,
2
0
1
3
.
[1
1
]
Y.
L
iu
,
"
Ne
u
ra
l
-
n
e
tw
o
rk
-
b
a
se
d
m
a
x
i
m
u
m
p
o
we
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p
o
in
t
trac
k
in
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m
e
th
o
d
s
f
o
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p
h
o
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o
v
o
lt
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sy
st
e
m
s
o
p
e
ra
ti
n
g
u
n
d
e
r
f
a
st ch
a
n
g
in
g
e
n
v
iro
n
m
e
n
ts
"
,
S
o
l
a
r
En
e
rg
y
,
v
o
l.
8
9
,
p
p
.
42
–
53
,
2
0
1
3
.
[1
2
]
K.
P
u
n
it
h
a
,
"
A
rti
f
ici
a
l
n
e
u
ra
l
n
e
tw
o
rk
b
a
se
d
m
o
d
if
ied
in
c
re
m
e
n
tal
c
o
n
d
u
c
tan
c
e
a
lg
o
rit
h
m
f
o
r
m
a
x
i
m
u
m
p
o
w
e
r
p
o
i
n
t
trac
k
in
g
in
p
h
o
t
o
v
o
lt
a
ic sy
s
tem
u
n
d
e
r
p
a
rti
a
l
sh
a
d
in
g
c
o
n
d
it
i
o
n
s
"
,
En
e
rg
y
,
v
o
l.
6
2
,
p
p
.
3
3
0
-
3
4
0
,
2
0
1
3
.
[1
3
]
M
.
A
.
Yo
u
n
is,
"
A
n
Im
p
ro
v
e
d
M
a
x
i
m
u
m
P
o
w
e
r
P
o
in
t
T
ra
c
k
in
g
Co
n
tro
ll
e
r
f
o
r
P
V
S
y
ste
m
s
Us
in
g
Artif
icia
l
Ne
u
ra
l
Ne
tw
o
rk
"
,
P
RZE
G
LĄ
D
El
e
k
tro
te
c
h
n
icz
n
y
(El
e
c
tri
c
a
l
Re
v
ie
w),
v
o
l.
8
8
,
p
p
.
1
1
6
-
1
2
1
,
2
0
1
2
.
[1
4
]
S.
S
u
b
iy
a
n
to
e
t
a
l.
In
telli
g
e
n
t
m
a
x
i
m
u
m
p
o
we
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p
o
in
t
trac
k
in
g
f
o
r
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V
sy
ste
m
u
sin
g
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p
f
ield
n
e
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ra
l
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e
tw
o
rk
o
p
ti
m
ize
d
f
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z
z
y
lo
g
ic co
n
tro
ll
e
r
"
,
En
e
rg
y
a
n
d
Bu
il
d
i
n
g
s,
v
o
l.
5
1
,
p
p
.
29
–
38
,
2
0
1
2
.
[1
5
]
B.
N.
A
l
a
j
m
i
e
t
a
l.
,
"
A
M
a
x
i
m
u
m
P
o
w
e
r
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o
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n
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T
ra
c
k
in
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T
e
c
h
n
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q
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e
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o
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a
rti
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ll
y
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h
a
d
e
d
P
h
o
to
v
o
lt
a
ic
S
y
ste
m
s
in
M
icro
g
rid
s
"
,
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
In
d
u
strial
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e
c
tro
n
ics
,
v
o
l.
6
0
,
p
p
.
1
5
9
6
-
1
6
0
6
,
2
0
1
3
.
[1
6
]
S
.
S
in
g
h
e
t
a
l.
,
"
De
sig
n
a
n
d
S
im
u
latio
n
o
f
In
telli
g
e
n
t
Co
n
tr
o
l
M
P
P
T
T
e
c
h
n
iq
u
e
f
o
r
P
V
M
o
d
u
le
Us
in
g
M
ATLA
B/
S
IM
S
CA
P
E
,
"
I
n
tern
a
ti
o
n
a
l
Jo
u
rn
a
l
o
f
A
d
v
a
n
c
e
d
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se
a
rc
h
in
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e
c
tri
c
a
l,
El
e
c
t
ro
n
ics
a
n
d
In
stru
m
e
n
tatio
n
En
g
in
e
e
rin
g
,
2
,
p
p
.
4
5
5
4
-
4
5
6
6
,
2
0
1
3
.
[1
7
]
H.
T
sa
i
e
t
a
l.
,
"
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v
e
lo
p
m
e
n
t
o
f
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e
n
e
ra
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e
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h
o
to
v
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lt
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ic
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o
d
e
l
Us
in
g
M
A
TL
A
B/S
IM
U
L
INK
”
,
in
P
r
o
c
.
W
o
r
l
d
Co
n
g
re
ss
o
n
E
n
g
in
e
e
rin
g
a
n
d
Co
m
p
u
ter S
c
ien
c
e
W
CECS
,
S
a
n
F
ra
n
c
isc
o
,
2
0
0
8
.
[1
8
]
M.
S
e
y
e
d
m
a
h
m
o
u
d
ian
e
t
a
l.
,
"
A
n
a
l
y
ti
c
a
l
M
o
d
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li
n
g
o
f
P
a
rti
a
ll
y
S
h
a
d
e
d
P
h
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t
o
v
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lt
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ic S
y
ste
m
s
"
,
En
e
rg
ies
,
v
o
l.
6
,
p
p
.
128
-
1
4
4
,
2
0
1
3
.
[1
9
]
B
.
S
a
lah
e
t
a
l.
,
"
M
o
h
a
m
e
d
Ou
a
li
,
Co
m
p
a
riso
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o
f
f
u
z
z
y
lo
g
ic
a
n
d
n
e
u
ra
l
n
e
tw
o
rk
in
m
a
x
i
m
u
m
p
o
we
r
p
o
in
t
trac
k
e
r
f
o
r
P
V
sy
ste
m
s
"
,
El
e
c
tri
c
P
o
w
e
r
S
y
st
e
m
s Re
s
e
a
rc
h
,
v
o
l.
8
1
(1
),
p
p
.
43
-
50
,
2
0
1
1
.
[2
0
]
N.
S
.
D'
S
o
u
z
a
,
"
Co
m
p
a
ra
ti
v
e
stu
d
y
o
f
v
a
riab
le siz
e
p
e
rtu
rb
a
ti
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n
a
n
d
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b
se
rv
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ti
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n
m
a
x
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m
u
m
p
o
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t
ra
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k
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f
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r
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V
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m
s
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El
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c
tri
c
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o
w
e
r
S
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m
s Re
se
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rc
h
,
p
p
.
2
9
6
–
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0
5
,
2
0
1
0
.
[2
1
]
T
.
S
a
l
m
i
e
t
a
l
.,
"
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A
TL
A
B/S
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m
u
li
n
k
Ba
se
d
M
o
d
e
ll
in
g
o
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S
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lar
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h
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t
o
v
o
lt
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ic
Ce
ll
"
,
In
tern
a
ti
o
n
a
l
Jo
u
rn
a
l
o
f
Re
n
e
wa
b
le E
n
e
rg
y
Re
se
a
r
c
h
,
v
o
l.
2
,
p
p
.
2
1
3
-
2
1
8
,
2
0
1
2
.
[2
2
]
h
tt
p
:
//
ww
w
.
a
rc
m
a
n
so
lar.co
m
/p
ro
d
u
c
ts/2
8
.
a
sp
x
?
c
id
=
7
-
12
-
11
B
I
O
G
RAP
H
I
E
S
O
F
AUTH
O
RS
Dr.
Ba
tain
e
h
h
a
s
is
c
u
rre
n
tl
y
wo
rk
in
g
a
s
p
ro
f
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ss
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r
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f
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e
c
h
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g
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rd
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iv
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h
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.
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f
ro
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in
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it
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u
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g
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n
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e
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trate
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h
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p
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t
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v
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rn
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n
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p
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ly
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tern
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ic co
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a
m
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ro
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so
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e
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c
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f
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m
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.
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is
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a
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re
v
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rn
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p
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ly
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ti
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l
sc
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ti
f
ic co
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f
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re
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c
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s.
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