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[
5
]
,
[
6
]
.
M
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(
M
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[
7
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[
8
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[
9
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1
1
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[
1
2
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n
g
-
t
e
r
m
t
e
m
p
o
r
a
l
d
y
n
a
m
i
c
s
a
s
w
e
l
l
as
n
o
n
-
s
t
a
t
i
o
n
a
r
y
v
a
r
i
a
t
i
o
n
s
o
f
P
V
p
o
w
e
r
d
a
t
a
.
A
l
s
o
,
t
h
e
p
r
o
p
o
s
e
d
d
e
s
i
g
n
h
a
s
b
e
t
t
e
r
p
r
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d
i
c
t
i
v
e
a
c
c
u
r
a
c
y
a
n
d
r
o
b
u
s
t
n
e
s
s
t
o
n
o
i
s
e
as
c
o
m
p
a
r
e
d
t
o
t
r
a
d
i
ti
o
n
al
m
o
d
e
l
s
t
h
at
a
p
p
r
o
x
i
m
a
t
e
t
h
e
tr
e
n
d
b
y
u
s
i
n
g
l
i
n
e
a
r
m
o
d
e
l
s
o
r
s
h
a
l
l
o
w
l
a
y
e
r
s
.
T
h
e
i
m
p
o
r
t
a
n
c
e
o
f
t
h
i
s
r
e
s
e
a
r
ch
i
s
t
h
a
t
i
t
c
o
u
l
d
f
u
r
t
h
e
r
d
e
v
e
l
o
p
t
h
e
r
e
s
e
a
r
c
h
c
o
m
m
u
n
i
t
y
a
n
d
t
h
e
u
s
e
o
f
P
V
p
o
w
e
r
f
o
r
e
c
as
t
i
n
g
.
P
r
e
c
is
e
a
n
d
r
e
l
i
a
b
l
e
P
V
f
o
r
e
c
as
t
i
n
g
i
s
es
s
e
n
t
i
a
l
i
n
i
n
c
r
e
as
i
n
g
g
r
id
s
t
a
b
i
li
t
y
,
e
n
e
r
g
y
m
a
n
a
g
e
m
e
n
t
o
p
t
i
m
i
z
a
ti
o
n
,
a
n
d
f
a
c
i
l
i
t
at
i
n
g
t
h
e
l
a
r
g
e
s
ca
l
e
i
n
te
g
r
a
t
i
o
n
r
e
g
a
r
d
i
n
g
r
e
n
e
w
a
b
l
e
e
n
e
r
g
y
s
o
u
r
c
e
s
.
T
h
e
p
r
o
p
o
s
e
d
a
p
p
r
o
a
c
h
h
e
l
p
s
t
o
d
e
v
e
l
o
p
m
o
r
e
e
f
f
i
c
i
e
n
t
a
n
d
r
o
b
u
s
t
f
o
r
e
c
a
s
t
i
n
g
f
r
a
m
e
w
o
r
k
s
,
a
s
it
d
e
a
l
s
w
it
h
s
o
m
e
o
f
t
h
e
m
a
i
n
i
s
s
u
e
s
i
n
m
o
d
e
l
i
n
g
c
o
m
p
l
e
x
t
e
m
p
o
r
a
l
d
y
n
a
m
i
c
s
.
As
a
r
e
s
e
a
r
c
h
p
e
r
s
p
e
ct
i
v
e
,
f
i
n
d
i
n
g
s
g
i
v
e
u
s
a
n
i
n
s
i
g
h
t
i
n
t
o
h
o
w
t
o
i
m
p
r
o
v
e
t
i
m
e
s
er
i
e
s
l
e
a
r
n
i
n
g
t
o
p
r
o
p
e
r
l
y
m
a
n
a
g
e
d
i
f
f
e
r
e
n
t
t
e
m
p
o
r
a
l
p
a
t
t
e
r
n
s
.
P
r
a
c
ti
c
a
ll
y
,
t
h
e
e
n
h
a
n
c
e
d
f
o
r
e
c
a
s
t
i
n
g
a
c
c
u
r
a
c
y
c
a
n
g
u
i
d
e
g
r
i
d
o
p
e
r
a
t
o
r
s
,
e
n
e
r
g
y
p
l
a
n
n
e
r
s
a
n
d
s
m
a
r
t
g
r
i
d
s
y
s
t
e
m
s
f
o
r
m
a
k
i
n
g
w
e
l
l
-
i
n
f
o
r
m
e
d
d
e
c
i
s
i
o
n
s
,
d
e
cr
e
a
s
e
t
h
e
o
p
e
r
a
t
i
o
n
a
l
u
n
c
e
r
t
ai
n
t
y
a
n
d
e
n
h
a
n
c
e
t
h
e
o
v
e
r
a
l
l
p
e
r
f
o
r
m
a
n
c
e
a
n
d
s
u
s
ta
i
n
a
b
i
li
t
y
o
f
t
h
e
e
n
e
r
g
y
s
y
s
t
e
m
s
.
T
h
e
r
e
s
e
a
r
c
h
i
s
s
t
r
u
c
t
u
r
e
d
a
s
f
o
l
l
o
w
s
:
i
)
S
e
c
ti
o
n
2
p
r
o
v
i
d
e
s
a
c
o
m
p
r
e
h
e
n
s
i
v
e
r
e
v
i
e
w
o
f
t
h
e
l
i
t
e
r
a
t
u
r
e
i
n
t
h
e
f
i
el
d
o
f
P
V
p
o
we
r
f
o
r
e
c
ast
i
n
g
;
ii
)
S
e
c
ti
o
n
3
e
x
p
l
ai
n
s
t
h
e
m
e
t
h
o
d
o
l
o
g
y
o
f
t
h
e
p
l
a
n
n
e
d
S
T
L
-
T
C
M
-
f
o
r
m
e
r
m
o
d
e
l
;
i
ii
)
S
ec
t
i
o
n
4
p
r
o
v
i
d
es
t
h
e
e
x
p
e
r
i
m
e
n
t
al
f
i
n
d
i
n
g
s
a
n
d
i
n
c
l
u
d
e
s
q
u
a
n
ti
t
a
ti
v
e
a
n
d
q
u
a
l
i
t
at
i
v
e
a
n
al
y
s
is
o
n
m
o
d
e
l
p
e
r
f
o
r
m
a
n
c
e
;
a
n
d
i
v
)
S
ec
t
i
o
n
5
s
u
m
m
a
r
i
z
es
t
h
e
r
es
e
a
r
ch
a
n
d
p
r
e
s
e
n
t
s
p
o
s
s
i
b
le
f
u
t
u
r
e
r
e
s
e
a
r
c
h
d
i
r
e
ct
i
o
n
s
.
2.
RE
L
AT
E
D
WO
RK
I
n
th
e
r
ec
e
n
t
p
ast,
PV
p
o
wer
p
r
ed
ictio
n
h
as
r
ec
eiv
ed
m
u
ch
atten
tio
n
o
n
h
y
b
r
id
d
ee
p
lear
n
in
g
(
DL
)
ar
ch
itectu
r
es
to
en
h
an
ce
p
r
e
d
ictio
n
ac
cu
r
ac
y
a
n
d
r
o
b
u
s
t
n
ess
.
C
GAf
o
r
m
er
m
o
d
el
[
1
3
]
co
n
s
is
ts
o
f
o
n
e
-
d
im
en
s
io
n
al
co
n
v
o
lu
tio
n
al
n
e
u
r
al
n
etwo
r
k
s
(
C
NN1
D)
f
o
r
e
x
tr
ac
tin
g
lo
ca
l
f
ea
tu
r
es,
a
Glo
b
al
Ad
d
itiv
e
AM
f
o
r
ca
p
tu
r
in
g
g
lo
b
al
d
ep
en
d
en
cies,
an
d
an
au
to
-
co
r
r
elatio
n
m
o
d
u
le
to
lear
n
p
er
io
d
ic
p
atter
n
s
.
T
h
e
last
p
r
ed
ictio
n
is
p
r
o
d
u
ce
d
b
y
a
m
u
ltil
ay
er
p
e
r
ce
p
tr
o
n
(
ML
P).
E
x
p
er
im
e
n
tal
f
in
d
in
g
s
in
d
icate
d
th
at
th
e
s
u
g
g
ested
m
o
d
els
ar
e
s
ig
n
if
ican
tly
b
etter
th
a
n
th
e
t
r
ad
itio
n
al
L
STM
m
o
d
els
in
ter
m
s
o
f
R
MSE
an
d
MA
E
,
a
n
d
also
in
ter
m
s
o
f
g
en
er
aliza
tio
n
.
Nev
er
t
h
eless
,
t
h
e
co
m
p
lex
ity
o
f
th
e
m
o
d
el
a
n
d
its
d
ep
en
d
en
ce
o
n
lar
g
e
-
s
c
ale
d
ata
m
ay
b
e
th
e
o
n
ly
r
estrictio
n
s
.
A
h
y
b
r
id
m
o
d
el
th
at
in
co
r
p
o
r
ates
a
b
etter
wh
ale
v
ar
iatio
n
al
m
o
d
e
d
ec
o
m
p
o
s
itio
n
(
I
W
VM
D)
with
a
co
n
tex
t
-
e
m
b
ed
d
ed
ca
u
s
al
co
n
v
o
lu
tio
n
al
t
r
a
n
s
f
o
r
m
e
r
(
C
C
T
r
an
s
)
is
p
r
esen
ted
in
[
1
4
]
to
s
o
lv
e
th
e
task
o
f
lo
n
g
-
s
eq
u
e
n
ce
f
ea
tu
r
e
ex
tr
ac
ti
o
n
.
T
h
e
o
p
tim
izatio
n
s
tr
ateg
y
o
f
th
e
C
D
C
T
F
also
im
p
r
o
v
es
th
e
p
er
f
o
r
m
a
n
ce
o
f
f
o
r
ec
asti
n
g
.
C
o
m
p
ar
ab
le,
[
1
5
]
p
r
esen
ts
a
m
u
lti
-
s
tep
p
r
ed
ictio
n
m
o
d
el
th
at
in
teg
r
ates
C
NN
a
s
a
s
h
o
r
t
-
ter
m
d
y
n
am
ics
n
etwo
r
k
a
n
d
t
r
a
n
s
f
o
r
m
er
f
o
r
l
o
n
g
-
te
r
m
d
e
p
e
n
d
en
cies.
Alth
o
u
g
h
t
h
ese
m
eth
o
d
s
b
ased
o
n
t
r
an
s
f
o
r
m
er
s
ar
e
ef
f
ec
tiv
e
at
ca
p
tu
r
in
g
g
l
o
b
al
tem
p
o
r
al
in
ter
ac
tio
n
s
,
th
ey
ca
n
h
av
e
d
if
f
i
cu
lty
at
ca
p
tu
r
in
g
s
h
o
r
t
-
ter
m
o
r
lo
ca
l
v
ar
iatio
n
b
ec
au
s
e
o
f
th
eir
in
h
er
en
t
f
o
cu
s
o
n
lo
n
g
-
r
a
n
g
e
d
ep
en
d
en
cies
a
n
d
g
l
o
b
al
AM
s
.
I
n
o
r
d
er
to
ca
p
tu
r
e
lo
ca
l
tem
p
o
r
al
d
y
n
am
ics,
a
n
u
m
b
er
o
f
s
tu
d
ie
s
in
teg
r
ate
co
n
v
o
lu
tio
n
al
an
d
r
ec
u
r
r
e
n
t
ar
ch
itectu
r
es.
T
h
e
T
C
N
-
E
C
ANe
t
-
GR
U
m
o
d
el
[
1
6
]
c
o
m
b
in
es
th
e
tim
e
co
n
v
o
lu
tio
n
a
l
n
etwo
r
k
s
(
T
C
N)
,
ef
f
icien
t
ch
an
n
el
atten
tio
n
,
a
n
d
GR
U
to
p
r
o
ce
s
s
n
o
n
lin
ea
r
an
d
h
ig
h
-
d
im
e
n
s
io
n
PV
d
a
ta
d
u
r
in
g
d
if
f
er
e
n
t
wea
th
er
co
n
d
itio
n
s
.
T
h
e
m
o
d
e
l h
as a
n
ex
ce
llen
t p
e
r
f
o
r
m
an
ce
in
all
s
ea
s
o
n
s
.
Similar
ly
,
[
1
7
]
s
u
g
g
ests
a
co
m
p
lex
h
y
b
r
id
f
r
am
ewo
r
k
(
I
C
E
E
MD
AN
-
T
C
N
-
B
iL
STM
-
M
HA)
wh
ich
b
r
ea
k
s
th
e
s
ig
n
als
d
o
wn
in
to
in
tr
in
s
ic
m
o
d
e
f
u
n
ctio
n
s
an
d
i
n
tr
o
d
u
ce
s
AM
s
to
a
m
p
lify
th
e
f
ea
tu
r
e
r
ep
r
esen
tatio
n
,
lead
in
g
to
g
r
ea
ter
s
tab
ilit
y
in
d
if
f
er
en
t
wea
th
er
co
n
d
itio
n
s
.
T
r
a
n
s
f
o
r
m
e
r
-
b
a
s
ed
ar
ch
itectu
r
e
h
as
also
b
ee
n
ex
p
an
d
ed
to
m
e
d
iu
m
-
an
d
lo
n
g
-
ter
m
f
o
r
ec
a
s
tin
g
.
SP
-
t
r
an
s
f
o
r
m
er
,
p
r
ese
n
ted
in
[
1
8
]
,
u
s
es
s
p
atio
tem
p
o
r
al
p
o
s
itio
n
al
en
co
d
in
g
an
d
s
elf
-
atten
tio
n
f
o
r
ca
p
tu
r
i
n
g
th
e
r
elatio
n
s
b
et
wee
n
g
eo
g
r
ap
h
ical,
m
eteo
r
o
lo
g
ical,
an
d
PV d
ata.
I
n
[
1
9
]
,
th
e
I
FTf
o
r
m
e
r
m
o
d
el
in
co
r
p
o
r
ates
o
u
tlier
d
etec
t
io
n
,
tim
e
-
s
er
ies
d
ec
o
m
p
o
s
itio
n
,
an
d
a
Pro
Sp
ar
s
e
AM
to
im
p
r
o
v
e
p
r
ed
ictio
n
ac
cu
r
ac
y
an
d
r
o
b
u
s
tn
ess
.
E
v
en
th
o
u
g
h
th
ey
o
u
tp
er
f
o
r
m
,
th
e
s
e
t
r
an
s
f
o
r
m
er
-
b
ased
m
o
d
els
co
n
tin
u
e
to
h
av
e
d
r
awb
ac
k
s
in
te
r
m
s
o
f
th
eir
a
b
ilit
y
to
ca
p
tu
r
e
f
in
e
-
g
r
ain
ed
lo
ca
l
v
ar
iatio
n
s
an
d
s
h
o
r
t
-
ter
m
d
y
n
am
ics,
wh
ich
ar
e
in
s
tr
u
m
en
ta
l
to
h
ig
h
ly
v
o
latile
PV
g
en
er
atio
n
.
T
h
e
r
esear
ch
[
2
0
]
o
u
tlin
es
a
s
y
s
tem
atic
r
e
s
ea
r
ch
o
n
th
e
s
ig
n
if
ican
ce
o
f
co
m
b
i
n
in
g
m
eteo
r
o
lo
g
ical
d
ata
an
d
ir
r
ad
ian
ce
m
o
d
ellin
g
with
t
r
a
n
s
f
o
r
m
er
n
e
two
r
k
s
,
en
h
an
ci
n
g
f
o
r
ec
asti
n
g
ac
cu
r
ac
y
with
Op
e
n
Me
teo
in
f
o
r
m
atio
n
.
A
h
y
b
r
id
VM
D
-
W
OA
-
L
STM
m
o
d
el
is
p
r
o
p
o
s
ed
i
n
[
2
1
]
,
in
wh
ich
d
ec
o
m
p
o
s
itio
n
an
d
r
ec
o
n
s
tr
u
ctio
n
o
f
PV
s
ig
n
als
ar
e
o
p
tim
ized
to
y
ield
h
ig
h
a
cc
u
r
ac
y
a
n
d
s
tab
ilit
y
in
p
r
ed
ictio
n
.
I
n
[
2
2
]
,
t
h
ey
in
tr
o
d
u
ce
a
n
ew
t
r
an
s
f
o
r
m
er
-
b
ased
f
r
am
ewo
r
k
r
eg
ar
d
in
g
u
ltra
-
s
h
o
r
t
-
ter
m
PV
p
o
wer
f
o
r
ec
asti
n
g
th
at
tak
es
in
to
ac
co
u
n
t
wea
th
er
p
atter
n
r
ec
o
g
n
itio
n
,
in
wh
ich
m
eteo
r
o
lo
g
ical
f
e
at
u
r
es
an
d
s
o
lar
ir
r
ad
iatio
n
p
at
ter
n
s
ar
e
m
o
d
eled
to
g
eth
er
.
T
h
r
o
u
g
h
ex
p
er
im
en
t
al
d
ata,
it
is
estab
lis
h
ed
th
at
th
er
e
ar
e
g
r
ea
t
im
p
r
o
v
em
e
n
ts
in
th
e
f
o
r
ec
asti
n
g
ac
cu
r
ac
y
in
v
er
y
s
h
o
r
t
tim
e
h
o
r
izo
n
s
b
u
t
t
h
e
m
o
d
el
p
er
f
o
r
m
an
ce
is
v
er
y
r
elia
n
t
o
n
th
e
q
u
ality
o
f
t
h
e
in
p
u
t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
6
9
4
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
,
Vo
l.
1
7
,
No
.
3
,
Sep
tem
b
er
20
2
6
:
2127
-
2
1
4
8
2130
d
ata.
I
n
[
2
3
]
,
a
t
r
an
s
f
o
r
m
er
m
o
d
el
with
f
ea
t
u
r
e
au
g
m
en
ta
tio
n
is
en
h
an
ce
d
to
f
o
r
ec
ast
s
h
o
r
t
-
ter
m
PV
p
o
wer
th
at
u
s
es
ad
v
an
ce
d
f
ea
tu
r
e
ex
tr
ac
tio
n
an
d
n
o
r
m
aliza
tio
n
m
o
d
u
les
to
en
h
an
ce
n
o
is
e
r
ed
u
ctio
n
an
d
p
r
ed
ictio
n
s
tab
ilit
y
.
I
n
th
is
wo
r
k
,
it
is
d
em
o
n
s
tr
ated
th
at
AM
s
in
co
m
b
in
atio
n
with
f
ea
t
u
r
e
en
h
an
ce
m
en
t
ar
e
ab
le
to
s
u
cc
ess
f
u
lly
r
ed
u
ce
R
MSE
an
d
MA
E
er
r
o
r
s
in
en
er
g
y
d
i
s
tr
ib
u
tio
n
n
etwo
r
k
s
,
b
u
t
at
t
h
e
co
s
t
o
f
a
h
i
g
h
co
m
p
u
tatio
n
al
c
o
s
t a
n
d
tr
ain
i
n
g
tim
e.
I
n
[
2
4
]
,
th
e
s
tu
d
y
p
r
o
v
id
es
a
d
ee
p
p
r
o
b
ab
ilis
tic
m
eth
o
d
o
f
s
o
lar
p
o
wer
f
o
r
ec
asti
n
g
an
d
i
n
v
o
lv
es
th
e
co
m
b
in
atio
n
o
f
a
t
r
a
n
s
f
o
r
m
er
n
etwo
r
k
with
Ga
u
s
s
ian
p
r
o
ce
s
s
ap
p
r
o
x
im
atio
n
to
q
u
an
titativ
ely
m
o
d
el
p
r
ed
ictio
n
u
n
ce
r
tain
t
y
.
I
t
s
h
o
ws
th
at
t
r
an
s
f
o
r
m
er
-
b
ased
m
o
d
els
ca
n
b
e
u
s
ed
to
f
o
r
ec
ast
p
o
in
ts
as
well
as
est
im
ate
a
p
r
o
b
ab
ilit
y
d
is
tr
ib
u
tio
n
o
f
PV
p
o
we
r
,
an
d
ca
n
b
e
u
s
ed
in
r
is
k
m
an
a
g
em
e
n
t
in
s
m
ar
t
g
r
id
s
.
Nev
er
th
eless
,
th
e
m
ain
lim
ita
tio
n
s
o
f
th
is
ap
p
r
o
ac
h
ar
e
th
e
s
tatis
tical
co
m
p
lex
ity
an
d
th
e
lar
g
e
am
o
u
n
ts
o
f
tr
ain
in
g
d
ata
r
eq
u
ir
e
d
.
I
n
[
2
5
]
,
a
th
o
r
o
u
g
h
co
m
p
a
r
ati
v
e
an
aly
s
is
o
f
th
e
class
ical
ML
alg
o
r
ith
m
s
an
d
th
e
t
r
an
s
f
o
r
m
er
-
b
ased
d
ee
p
m
o
d
els
in
s
o
lar
en
er
g
y
f
o
r
ec
asti
n
g
is
ca
r
r
ie
d
o
u
t
o
n
r
ea
l
-
wo
r
ld
d
ataset.
I
t
h
as
b
ee
n
s
h
o
wn
th
a
t
t
r
an
s
f
o
r
m
er
m
o
d
els
ar
e
b
etter
th
an
tr
a
d
itio
n
al
o
n
es,
esp
ec
ial
ly
wh
en
u
s
in
g
m
u
lti
-
s
o
u
r
ce
d
ata
an
d
in
d
if
f
e
r
en
t
wea
th
er
co
n
d
itio
n
s
,
b
u
t
s
till
,
h
ig
h
atten
tio
n
s
h
o
u
ld
b
e
p
ai
d
to
h
y
p
e
r
p
ar
am
ete
r
o
p
tim
izatio
n
,
o
th
er
wis
e
r
esu
lts
ca
n
d
eter
io
r
ate
d
r
am
atica
lly
.
T
h
e
r
esear
ch
in
[
2
6
]
ex
p
lo
r
es th
e
is
s
u
e
o
f
f
ea
tu
r
e
s
elec
tio
n
as
well
as h
y
p
er
p
ar
am
eter
o
p
tim
izatio
n
in
t
r
an
s
f
o
r
m
er
m
o
d
els
to
f
o
r
ec
a
s
t
PV
p
o
wer
with
th
e
u
s
e
o
f
Swo
r
d
f
is
h
m
o
v
em
en
t
o
p
tim
izatio
n
alg
o
r
ith
m
(
SMOA)
.
T
h
is
p
ap
er
d
em
o
n
s
tr
ates
th
at
ef
f
icien
t
f
ea
t
u
r
e
s
elec
tio
n
an
d
au
to
m
atic
h
y
p
e
r
p
ar
am
eter
s
o
p
tim
izatio
n
co
u
ld
s
ig
n
if
ican
tly
in
cr
ea
s
e
th
e
p
r
e
d
ictiv
e
ac
cu
r
ac
y
an
d
s
tab
ilit
y
o
f
th
e
m
o
d
el
in
ch
a
n
g
ea
b
le
wea
th
er
co
n
d
itio
n
s
,
h
o
wev
e
r
,
it
is
s
til
l
u
n
clea
r
h
o
w
th
e
c
o
n
v
er
g
en
ce
b
eh
av
i
o
r
o
f
th
e
o
p
tim
izatio
n
alg
o
r
ith
m
an
d
its
s
en
s
it
iv
ity
to
in
itial
p
a
r
am
eter
s
ar
e
af
f
ec
ted
b
y
ch
an
g
in
g
wea
th
er
co
n
d
itio
n
s
.
I
n
g
en
er
al,
th
ese
wo
r
k
s
co
n
f
ir
m
th
at
th
e
u
s
e
o
f
h
y
b
r
id
m
o
d
els
th
at
in
teg
r
ate
s
ig
n
al
d
ec
o
m
p
o
s
itio
n
,
AM
s
,
an
d
DL
m
o
d
els
a
r
e
h
el
p
f
u
l
in
PV
f
o
r
ec
asti
n
g
,
an
d
also
i
n
d
icate
th
at
t
r
a
n
s
f
o
r
m
er
-
b
ase
d
m
o
d
els
n
ee
d
to
b
e
co
m
p
le
m
en
ted
b
y
ad
d
itio
n
al
m
ec
h
an
is
m
s
to
o
v
er
co
m
e
th
e
ef
f
ec
t
o
f
s
h
o
r
t
-
ter
m
an
d
lo
ca
l
v
ar
iab
ilit
y
.
A
co
m
p
ar
is
o
n
o
f
th
e
r
ev
iewe
d
m
eth
o
d
s
is
p
r
o
v
id
ed
in
T
ab
le
1
.
T
ab
le
1
.
C
o
m
p
a
r
is
o
n
o
f
r
elate
d
wo
r
k
s
R
e
f
.
M
e
t
h
o
d
A
d
v
a
n
t
a
g
e
s
D
i
sad
v
a
n
t
a
g
e
s
[
1
3
]
C
G
A
f
o
r
mer (
C
N
N
1
D
+
G
A
D
A
t
t
e
n
t
i
o
n
+
A
u
t
o
-
C
o
r
r
e
l
a
t
i
o
n
+
M
LP)
Ef
f
e
c
t
i
v
e
m
u
l
t
i
-
sc
a
l
e
f
e
a
t
u
r
e
e
x
t
r
a
c
t
i
o
n
;
s
t
r
o
n
g
g
l
o
b
a
l
d
e
p
e
n
d
e
n
c
y
m
o
d
e
l
i
n
g
;
i
m
p
r
o
v
e
d
R
M
S
E
a
n
d
M
A
E;
g
o
o
d
g
e
n
e
r
a
l
i
z
a
t
i
o
n
H
i
g
h
m
o
d
e
l
c
o
mp
l
e
x
i
t
y
;
r
e
q
u
i
r
e
s
l
a
r
g
e
d
a
t
a
se
t
s;
l
i
mi
t
e
d
i
n
t
e
r
p
r
e
t
a
b
i
l
i
t
y
[
1
4
]
I
W
V
M
D
+
C
C
Tr
a
n
s
(
t
r
a
n
sf
o
r
mer)
+
C
D
C
TF
P
o
w
e
r
f
u
l
m
u
l
t
i
-
s
c
a
l
e
d
e
c
o
m
p
o
s
i
t
i
o
n
;
st
r
o
n
g
l
o
n
g
-
seq
u
e
n
c
e
m
o
d
e
l
i
n
g
;
h
i
g
h
a
c
c
u
r
a
c
y
a
n
d
r
o
b
u
st
n
e
ss
H
i
g
h
c
o
m
p
u
t
a
t
i
o
n
a
l
c
o
st
;
c
o
mp
l
e
x
a
r
c
h
i
t
e
c
t
u
r
e
;
l
i
m
i
t
e
d
a
b
i
l
i
t
y
t
o
c
a
p
t
u
r
e
s
h
o
r
t
-
t
e
r
m/
l
o
c
a
l
v
a
r
i
a
t
i
o
n
s
d
u
e
t
o
t
r
a
n
sf
o
r
m
e
r
[
1
5
]
C
N
N
+
t
r
a
n
sf
o
r
m
e
r
(
mu
l
t
i
-
st
e
p
f
o
r
e
c
a
s
t
i
n
g
)
C
o
m
b
i
n
e
s
sh
o
r
t
-
t
e
r
m
(
C
N
N
)
a
n
d
l
o
n
g
-
t
e
r
m
(
t
r
a
n
sf
o
r
mer)
f
o
r
e
c
a
st
i
n
g
;
f
l
e
x
i
b
l
e
a
c
r
o
ss
t
i
m
e
sca
l
e
s
M
o
d
e
l
b
a
l
a
n
c
i
n
g
i
s
c
h
a
l
l
e
n
g
i
n
g
;
Tr
a
n
sf
o
r
mer
p
a
r
t
w
e
a
k
i
n
m
o
d
e
l
i
n
g
f
i
n
e
-
g
r
a
i
n
e
d
l
o
c
a
l
/
s
h
o
r
t
-
t
e
r
m
f
l
u
c
t
u
a
t
i
o
n
s
[
1
6
]
TC
N
-
EC
A
N
e
t
-
G
R
U
S
t
r
o
n
g
l
o
c
a
l
a
n
d
t
e
m
p
o
r
a
l
f
e
a
t
u
r
e
e
x
t
r
a
c
t
i
o
n
;
g
o
o
d
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-
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m
d
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d
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n
c
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s
[
1
7
]
I
C
EEM
D
A
N
-
TC
N
-
B
i
LST
M
-
M
H
A
S
t
r
o
n
g
n
o
i
s
e
r
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s
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st
a
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;
e
f
f
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c
t
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v
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d
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f
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r
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n
t
w
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c
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d
i
t
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o
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s;
g
o
o
d
f
e
a
t
u
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p
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se
n
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a
t
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V
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y
c
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h
i
g
h
c
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m
p
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a
t
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a
l
c
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s
t
[
1
8
]
SP
-
t
r
a
n
sf
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mer
C
a
p
t
u
r
e
s
s
p
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m
p
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h
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a
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y
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n
m
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m
/
l
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t
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m f
o
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c
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st
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H
i
g
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p
l
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x
i
t
y
;
r
e
q
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d
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;
l
i
m
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l
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b
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n
[
1
9
]
I
F
Tf
o
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mer (
D
I
F
+
LO
F
+
D
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m
p
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P
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p
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sf
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R
o
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t
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d
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l
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s;
st
r
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f
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a
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x
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c
t
i
o
n
;
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h
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n
d
g
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M
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st
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s
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t
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v
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a
t
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s
[
2
0
]
Tr
a
n
sf
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r
mer
+
met
e
o
r
o
l
o
g
i
c
a
l
d
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t
a
(
O
p
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M
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mp
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d
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D
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p
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d
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r
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sf
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l
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m
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t
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p
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l
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l
f
l
u
c
t
u
a
t
i
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n
s
[
2
1
]
V
M
D
-
W
O
A
-
LSTM
H
i
g
h
a
c
c
u
r
a
c
y
;
e
f
f
e
c
t
i
v
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f
o
r
n
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n
-
st
a
t
i
o
n
a
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d
a
t
a
;
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a
b
l
e
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n
d
e
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f
l
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c
t
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a
t
i
o
n
s
Ti
me
-
c
o
n
s
u
mi
n
g
o
p
t
i
mi
z
a
t
i
o
n
;
l
a
c
k
s
g
l
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b
a
l
d
e
p
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n
d
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n
c
y
m
o
d
e
l
i
n
g
3.
P
RO
P
O
SE
D
M
E
T
H
O
D
I
n
t
h
is
r
esear
ch
p
ap
er
s
u
g
g
ests
a
n
ew
tr
an
s
f
o
r
m
er
-
b
ased
ar
ch
itectu
r
e,
wh
ich
is
ca
lled
T
C
M
-
Fo
r
m
er
,
to
f
o
r
ec
ast
PV
p
o
wer
.
T
h
e
m
ajo
r
aim
o
f
s
u
ch
a
r
ch
itectu
r
e
is
ad
d
r
ess
in
g
th
e
i
n
h
er
e
n
t
co
n
s
tr
ain
ts
o
f
s
elf
-
atten
tio
n
(
SA)
-
b
ased
m
o
d
els
in
m
o
d
elin
g
s
h
o
r
t
-
te
r
m
an
d
lo
ca
lized
d
ep
en
d
en
cies
in
tim
e
-
s
er
ies
d
ata.
T
h
o
u
g
h
th
e
AM
h
as
a
h
ig
h
ca
p
a
b
ilit
y
o
f
m
o
d
elin
g
lo
n
g
-
r
an
g
e
d
ep
en
d
en
cies,
it
ten
d
s
to
u
n
d
er
-
p
er
f
o
r
m
in
th
e
ca
s
e
o
f
r
ap
id
f
lu
ct
u
atio
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s
,
tr
an
s
ien
t
v
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s
an
d
f
in
e
-
g
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ain
ed
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ca
l
p
atter
n
s
.
I
n
o
v
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r
co
m
in
g
th
is
d
if
f
icu
lty
,
th
e
s
u
g
g
ested
ar
ch
itectu
r
e
i
n
co
r
p
o
r
ates
a
T
C
M
in
p
ar
allel
en
c
o
d
er
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d
ec
o
d
er
lin
es,
th
u
s
,
allo
win
g
an
in
tellig
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t
m
ix
o
f
g
l
o
b
al
an
d
lo
ca
l d
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cy
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g
.
T
h
is
d
esig
n
f
a
cilitates a
r
ich
,
m
u
ltis
ca
le
tem
p
o
r
al
r
ep
r
esen
tatio
n
o
f
PV p
o
wer
d
ata.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Po
w
E
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&
Dr
i Sy
s
t
I
SS
N:
2088
-
8
6
9
4
TC
M
-
F
o
r
me
r
:
a
tr
a
n
s
fo
r
mer
w
ith
temp
o
r
a
l c
o
n
vo
lu
tio
n
fo
r
p
h
o
to
v
o
lta
ic
p
o
w
er
…
(
S
a
r
a
b
A
l
-
C
h
la
ih
a
w
i
)
2131
In
th
e
f
ir
s
t
s
tag
e,
th
e
in
p
u
t
ti
m
e
-
s
er
ies
d
ata
ar
e
d
ec
o
m
p
o
s
ed
u
tili
zin
g
s
ea
s
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n
al
-
tr
en
d
d
ec
o
m
p
o
s
itio
n
u
s
in
g
lo
ess
(
STL
)
in
to
two
p
r
in
cip
al
co
m
p
o
n
e
n
ts
:
tr
en
d
co
m
p
o
n
en
t
(
)
an
d
th
e
s
ea
s
o
n
al/p
er
io
d
i
c
co
m
p
o
n
en
t
(
)
.
T
h
e
d
ec
o
m
p
o
s
itio
n
is
u
s
ef
u
l
in
h
elp
in
g
th
e
m
o
d
el
to
in
d
e
p
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d
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tly
lear
n
b
o
th
th
e
lo
n
g
-
ter
m
v
ar
iatio
n
s
a
n
d
th
e
s
h
o
r
t
-
ter
m
p
er
io
d
ic
s
tr
u
ctu
r
es
in
th
e
PV
p
o
wer
s
ig
n
al.
T
h
e
d
e
-
co
m
p
o
s
ed
tim
e
-
s
er
ies
co
m
p
o
n
en
ts
ar
e
th
en
f
ed
in
t
o
th
e
p
r
o
p
o
s
ed
tr
an
s
f
o
r
m
er
n
etwo
r
k
s
im
u
ltan
e
o
u
s
ly
a
n
d
at
th
e
e
n
co
d
er
an
d
d
ec
o
d
er
s
tag
es,
two
p
ar
allel
p
r
o
ce
s
s
in
g
p
ath
s
ar
e
u
s
ed
.
T
wo
co
m
p
lem
en
tar
y
s
u
b
m
o
d
u
les
ar
e
u
s
ed
in
th
e
en
co
d
er
,
th
e
Per
io
d
E
n
co
d
er
,
wh
ich
u
s
es
th
e
AM
t
o
ca
p
t
u
r
e
lo
n
g
-
r
a
n
g
e
d
ep
e
n
d
en
cies
an
d
r
ec
u
r
r
in
g
tim
e
p
atter
n
s
in
th
e
s
ea
s
o
n
al
co
m
p
o
n
en
t,
an
d
th
e
tem
p
o
r
al
en
c
o
d
er
,
wh
ich
is
b
ased
o
n
th
e
T
C
N,
an
d
ex
tr
ac
ts
s
h
o
r
t
-
ter
m
an
d
lo
ca
l
f
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r
es lik
e
ab
r
u
p
t c
h
a
n
g
es a
n
d
h
ig
h
-
f
r
eq
u
en
cy
n
o
is
e.
T
h
e
o
u
tp
u
ts
r
eg
ar
d
in
g
s
u
ch
tw
o
p
ath
s
ar
e
f
u
s
ed
f
o
r
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e
n
er
atin
g
an
im
p
r
o
v
e
d
m
u
ltis
ca
le
r
ep
r
esen
tatio
n
o
f
th
e
s
ea
s
o
n
al
co
m
p
o
n
e
n
t
en
ca
p
s
u
latin
g
b
o
th
lo
n
g
-
ter
m
d
e
p
en
d
en
cies
an
d
lo
ca
lized
tem
p
o
r
al
s
tr
u
ctu
r
es.
T
h
e
d
ec
o
d
er
c
o
m
p
r
is
es
two
p
ar
allel
s
u
b
m
o
d
u
les:
p
er
io
d
d
ec
o
d
er
,
wh
ich
a
p
p
lies
m
ask
ed
AM
to
m
o
d
el
f
u
tu
r
e
lo
n
g
-
ter
m
d
ep
en
d
en
cies;
an
d
tem
p
o
r
al
d
ec
o
d
er
,
w
h
ich
u
s
es
T
C
N
f
o
r
r
ef
in
in
g
an
d
e
n
r
ich
in
g
s
h
o
r
t
-
ter
m
f
ea
tu
r
es
f
o
r
ac
cu
r
ate
p
r
ed
icti
o
n
r
eg
ar
d
in
g
t
h
e
s
ea
s
o
n
al
co
m
p
o
n
e
n
t.
T
h
e
o
u
tp
u
ts
f
r
o
m
th
ese
two
d
ec
o
d
er
s
u
b
m
o
d
u
les ar
e
in
te
g
r
ated
f
o
r
p
r
o
d
u
cin
g
th
e
f
in
al
p
r
e
d
icted
PV p
o
wer
s
eq
u
en
ce
.
A
d
ed
ica
ted
T
C
N
n
etwo
r
k
is
in
co
r
p
o
r
ated
f
o
r
ex
tr
ac
tin
g
d
y
n
am
ic
tem
p
o
r
al
f
ea
tu
r
es
f
r
o
m
,
en
s
u
r
in
g
ac
cu
r
ate
m
o
d
eli
n
g
r
eg
a
r
d
in
g
lo
n
g
-
ter
m
v
ar
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n
s
an
d
tr
en
d
s
.
T
h
is
ar
ch
itectu
r
e
p
r
o
d
u
ce
s
a
r
o
b
u
s
t,
co
m
p
r
eh
e
n
s
iv
e
an
d
h
i
er
ar
ch
ically
awa
r
e
m
o
d
el
th
at
h
as
th
e
ab
ilit
y
to
s
im
u
ltan
eo
u
s
ly
ca
p
tu
r
e
g
lo
b
al
an
d
lo
ca
l
tem
p
o
r
al
s
tr
u
ctu
r
e
s
.
As
a
r
esu
lt,
t
h
e
s
u
g
g
ested
T
C
M
-
f
o
r
m
er
s
h
o
ws
m
o
r
e
s
tab
ilit
y
an
d
ac
cu
r
ac
y
in
ter
m
s
o
f
p
r
e
d
ictin
g
PV
p
o
wer
as
o
p
p
o
s
ed
to
tr
ad
itio
n
al
tr
an
s
f
o
r
m
er
-
b
ased
f
r
am
ewo
r
k
s
.
T
h
e
s
u
g
g
ested
STL
-
T
C
M
-
Fo
r
m
er
alg
o
r
ith
m
is
ef
f
ec
tiv
e
i
n
i
n
cr
ea
s
in
g
th
e
i
n
ter
p
r
etab
ilit
y
o
f
m
o
d
els
in
co
m
p
ar
is
o
n
with
th
e
b
aselin
e
m
o
d
els,
wh
ich
is
m
o
s
tly
ex
p
lain
ed
b
y
th
e
in
c
o
r
p
o
r
atio
n
o
f
th
e
ST
L
d
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o
m
p
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s
itio
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ap
p
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ac
h
an
d
a
d
u
al
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p
ath
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ec
h
a
n
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u
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
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w
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lec
&
Dr
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s
t
I
SS
N:
2088
-
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TC
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2133
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2
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
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8
6
9
4
I
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t J Po
w
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lec
&
Dr
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,
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1
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3
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Sep
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20
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2127
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2134
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ter
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as
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f
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ter
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m
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e
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h
e
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M
p
ath
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iv
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as
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=
(
2
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5
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T
h
e
r
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lts
o
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th
e
t
r
a
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s
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en
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d
er
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n
d
th
e
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C
M
m
o
d
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le
ar
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en
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e
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to
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1
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)
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h
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m
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atio
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etwe
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th
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g
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ter
m
d
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en
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elf
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n
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d
s
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o
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t
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ter
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n
am
ics
(
t
em
p
o
r
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n
v
o
lu
tio
n
)
.
T
h
is
d
u
al
-
pa
th
en
co
d
in
g
ar
ch
itectu
r
e
o
f
f
er
s
a
p
o
ten
t
a
n
d
f
le
x
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le
s
tr
u
ctu
r
e
f
o
r
m
u
lt
is
ca
le
tim
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-
s
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ies
m
o
d
elin
g
,
wh
ich
s
ig
n
if
ican
tly
en
h
an
ce
s
th
e
q
u
ality
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d
v
alid
ity
o
f
p
h
o
to
v
o
ltaic
p
o
wer
f
o
r
e
ca
s
tin
g
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
I
SS
N:
2088
-
8
6
9
4
TC
M
-
F
o
r
me
r
:
a
tr
a
n
s
fo
r
mer
w
ith
temp
o
r
a
l c
o
n
vo
lu
tio
n
fo
r
p
h
o
to
v
o
lta
ic
p
o
w
er
…
(
S
a
r
a
b
A
l
-
C
h
la
ih
a
w
i
)
2135
3
.
3
.
T
CM
-
F
o
rm
er
deco
der
T
h
e
d
ec
o
d
er
o
f
th
e
p
r
o
p
o
s
ed
T
C
M
-
Fo
r
m
er
n
etwo
r
k
tak
es
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d
u
al
-
p
at
h
d
esig
n
s
im
ilar
to
th
e
en
co
d
e
r
,
wh
ich
allo
ws
it
to
m
o
d
el
b
o
th
th
e
lo
n
g
-
ter
m
g
lo
b
al
an
d
th
e
s
h
o
r
t
-
ter
m
lo
ca
l
ch
a
r
ac
ter
is
tics
at
th
e
s
am
e
tim
e
,
wh
ile
th
e
en
co
d
er
r
ec
o
n
s
tr
u
ct
s
an
d
p
r
ed
icts
th
e
f
u
t
u
r
e
s
ea
s
o
n
al
co
m
p
o
n
en
ts
.
T
h
e
f
ir
s
t
b
r
an
ch
f
o
llo
ws
th
e
ar
ch
itectu
r
e
o
f
a
tr
an
s
f
o
r
m
er
d
ec
o
d
er
,
a
n
d
th
e
s
ec
o
n
d
b
r
a
n
ch
em
p
lo
y
s
th
e
T
C
M
as
ex
p
lain
ed
p
r
ev
i
o
u
s
ly
.
T
h
r
o
u
g
h
th
e
i
n
teg
r
atio
n
o
f
t
h
e
two
c
o
m
p
lem
e
n
tar
y
m
ec
h
a
n
is
m
s
,
th
e
d
ec
o
d
er
is
p
r
o
v
id
e
d
with
th
e
ca
p
ab
ilit
y
to
f
o
r
ec
ast
th
e
f
u
tu
r
e
s
ea
s
o
n
a
l
tr
en
d
s
ac
cu
r
ately
an
d
co
n
s
id
er
b
o
th
g
lo
b
al
an
d
lo
ca
l
tem
p
o
r
al
d
e
p
en
d
e
n
cies.
T
h
e
p
r
o
p
o
s
ed
T
C
M
-
Fo
r
m
e
r
d
ec
o
d
er
h
as th
e
f
o
llo
win
g
s
tr
u
c
tu
r
e,
as sh
o
wn
in
Fig
u
r
e
4
.
Fig
u
r
e
4
.
Stru
ctu
r
e
o
f
th
e
d
ec
o
d
er
in
th
e
p
r
o
p
o
s
ed
T
C
M
-
Fo
r
m
er
n
etwo
r
k
I
n
th
e
f
ir
s
t
p
ath
,
th
e
in
p
u
t
to
t
h
e
d
ec
o
d
er
,
i.e
.
,
th
e
p
r
e
d
icted
s
ea
s
o
n
al
co
m
p
o
n
en
ts
u
p
to
ti
m
e
s
tep
,
is
p
r
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ce
s
s
ed
b
y
th
e
m
ask
ed
m
u
lti
-
h
ea
d
atten
tio
n
(
MH
A)
lay
er
.
T
h
is
lay
er
o
p
er
ates
s
im
ilar
ly
to
t
h
e
atten
tio
n
m
ec
h
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is
m
in
th
e
e
n
co
d
e
r
,
w
ith
th
e
k
ey
d
if
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er
e
n
ce
b
ein
g
t
h
at
it
ap
p
lies
a
lo
wer
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tr
ian
g
u
l
ar
m
ask
to
p
r
ev
en
t
in
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o
r
m
atio
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leak
ag
e
f
r
o
m
f
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t
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r
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tep
s
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h
is
en
s
u
r
es
t
h
at
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ch
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o
s
itio
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ca
n
o
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ly
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r
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g
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o
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itio
n
s
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m
ain
tain
in
g
ca
u
s
al
(
au
to
r
eg
r
ess
iv
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m
o
d
elin
g
.
Ma
th
em
atica
lly
,
it is
f
o
r
m
u
lated
a
s
(
1
7
)
.
(
.
.
)
=
(
√
+
)
(
1
7
)
W
h
er
e
(
)
r
ef
er
s
to
th
e
m
ask
m
atr
ix
,
th
e
v
alu
es
o
f
wh
ich
ar
e
s
et
to
(
−∞)
in
f
u
tu
r
e
p
o
s
itio
n
s
to
ap
p
ly
ze
r
o
atten
tio
n
weig
h
ts
.
T
h
is
o
p
er
at
io
n
g
u
ar
an
tees seq
u
en
tial
s
tep
-
by
-
s
tep
p
r
ed
ictio
n
an
d
is
in
lin
e
with
ca
u
s
al
-
tem
p
o
r
al
m
o
d
ellin
g
.
T
h
e
r
esu
lt
o
f
th
is
lay
er
is
ad
d
ed
to
t
h
e
in
p
u
t
th
r
o
u
g
h
a
r
esid
u
al
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n
n
ec
tio
n
,
an
d
th
e
n
lay
er
n
o
r
m
aliza
tio
n
(
Ad
d
&
No
r
m
)
is
p
er
f
o
r
m
ed
to
i
n
cr
ea
s
e
th
e
s
tab
ilit
y
o
f
th
e
tr
ain
in
g
.
Nex
t,
th
e
o
u
tp
u
t
is
p
ass
ed
in
to
a
s
ec
o
n
d
m
u
lti
-
h
e
ad
atten
tio
n
lay
e
r
,
wh
er
e
th
e
Qu
er
y
(
Q)
is
th
e
o
u
tp
u
t
f
r
o
m
t
h
e
p
r
ev
i
o
u
s
d
ec
o
d
er
lay
er
,
wh
ile
th
e
k
ey
(
K)
a
n
d
v
alu
e
(
V)
ar
e
d
er
iv
e
d
f
r
o
m
th
e
en
co
d
er
’
s
f
in
al
r
ep
r
esen
tatio
n
(
)
.
T
h
is
cr
o
ss
-
atten
tio
n
alig
n
s
th
e
d
ec
o
d
er
in
ter
m
ed
iate
r
ep
r
esen
tatio
n
s
wit
h
th
e
co
n
te
x
tu
al
f
ea
tu
r
es
o
f
th
e
en
co
d
er
o
n
m
a
n
y
s
ca
les,
th
u
s
p
r
o
v
i
d
in
g
th
e
d
e
co
d
er
with
th
e
a
b
ilit
y
to
ef
f
e
ctiv
ely
u
tili
ze
th
e
h
is
to
r
ical
t
em
p
o
r
al
c
o
n
tex
t
to
p
r
ed
ict
f
u
t
u
r
e
s
ea
s
o
n
al
co
m
p
o
n
en
t
s.
A
s
ec
o
n
d
Ad
d
&
No
r
m
s
tep
is
s
u
b
s
eq
u
en
tly
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s
ed
,
wh
ic
h
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th
en
f
o
llo
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b
y
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FF
N
co
m
p
r
is
in
g
two
lin
ea
r
tr
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s
f
o
r
m
atio
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ep
ar
at
ed
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y
a
R
eL
U
ac
tiv
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f
u
n
c
tio
n
.
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h
e
s
u
b
n
etwo
r
k
p
r
o
v
i
d
e
s
n
o
n
lin
ea
r
f
ea
tu
r
e
tr
an
s
f
o
r
m
atio
n
s
an
d
r
e
m
ap
p
i
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g
th
at
en
ab
le
th
e
m
o
d
el
to
lear
n
s
o
p
h
is
ticated
r
elatio
n
s
b
etwe
en
tem
p
o
r
al
p
atter
n
s
.
On
ce
th
e
f
i
n
al
Ad
d
&
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m
o
p
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atio
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is
d
o
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th
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u
tp
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t o
f
th
is
b
r
an
c
h
is
r
ep
r
ese
n
ted
as
−
.
Similar
to
th
e
en
co
d
er
,
in
t
h
e
s
ec
o
n
d
p
ath
a
T
C
M
is
ad
d
ed
t
o
ca
p
tu
r
e
l
o
ca
l
v
ar
iatio
n
s
a
n
d
s
h
o
r
t
-
ter
m
d
ep
en
d
e
n
cies
in
th
e
p
r
ed
ict
ed
s
ea
s
o
n
al
co
m
p
o
n
e
n
t.
T
h
e
T
C
M
in
th
e
d
ec
o
d
er
co
n
s
is
t
s
o
f
s
eq
u
en
tial
co
n
v
o
l
u
tio
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lo
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s
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n
o
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k
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lo
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ca
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m
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ter
m
d
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p
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d
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er
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
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8
8
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6
9
4
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
,
Vo
l.
1
7
,
No
.
3
,
Sep
tem
b
er
20
2
6
:
2127
-
2
1
4
8
2136
co
n
tex
tu
al
tr
a
n
s
itio
n
s
.
T
h
e
r
es
u
lt
o
f
th
e
T
C
M
p
ath
is
r
ep
r
esen
ted
as
−
.
T
h
e
r
esu
lts
o
f
t
h
e
two
d
ec
o
d
er
p
ath
s
ar
e
co
m
b
in
ed
to
p
r
o
d
u
ce
th
e
f
in
al
d
ec
o
d
er
r
ep
r
esen
tati
o
n
:
=
(
−
.
−
)
(
1
8
)
T
h
is
co
m
b
in
ed
r
ep
r
esen
tatio
n
is
th
en
p
ass
ed
th
r
o
u
g
h
a
f
u
l
ly
co
n
n
ec
ted
(
FC
)
lay
er
th
at
m
ap
s
th
e
lear
n
ed
f
ea
tu
r
e
s
p
ac
e
to
th
e
f
i
n
al
p
r
ed
ictio
n
s
p
ac
e:
̂
S
eas
o
n
=
σ
(
∗
+
)
(
1
9
)
I
n
wh
ich
(
)
an
d
(
)
ar
e
th
e
p
a
r
am
eter
s
to
b
e
t
r
ain
ed
i
n
th
e
FC
lay
er
,
an
d
(
σ
)
is
th
e
o
u
tp
u
t
ac
tiv
atio
n
f
u
n
ctio
n
.
T
h
e
r
esu
ltan
t
en
h
an
ce
d
s
ea
s
o
n
al
f
o
r
ec
ast
̂
S
eas
o
n
co
m
b
in
ed
with
th
e
tr
en
d
co
m
p
o
n
en
t,
wh
ich
h
as
b
ee
n
p
r
o
ce
s
s
ed
b
y
t
h
e
s
p
ec
ialized
T
C
M,
is
th
e
u
ltima
te
p
o
w
er
p
r
ed
ictio
n
o
f
p
h
o
to
v
o
ltaic
o
u
tp
u
t.
T
h
is
d
esig
n
allo
ws
th
e
T
C
M
-
F
o
r
m
er
d
ec
o
d
er
to
attain
a
b
alan
ce
d
r
ep
r
e
s
en
tatio
n
o
f
g
lo
b
al
a
n
d
lo
ca
l
t
em
p
o
r
al
s
tr
u
ctu
r
es,
wh
ich
p
r
o
v
id
es
r
o
b
u
s
t a
n
d
h
ig
h
ly
ac
cu
r
ate
PV p
o
wer
f
o
r
ec
asti
n
g
o
u
tco
m
es.
4.
RE
SU
L
T
S E
V
AL
U
AT
I
O
N
Fo
r
ass
ess
in
g
th
e
p
er
f
o
r
m
a
n
c
e
r
eg
ar
d
in
g
th
e
s
u
g
g
ested
ap
p
r
o
ac
h
i
n
esti
m
atin
g
th
e
o
u
tp
u
t
p
o
wer
o
f
PV
s
y
s
tem
s
,
a
s
er
ies
o
f
ex
p
er
im
en
ts
wer
e
ca
r
r
ie
d
o
u
t
o
n
b
o
t
h
s
h
o
r
t
-
te
r
m
an
d
lo
n
g
-
ter
m
b
ases
.
T
h
ese
ex
p
er
im
en
ts
ar
e
aim
ed
at
d
et
er
m
in
in
g
th
e
ac
cu
r
ac
y
,
th
e
s
tab
ilit
y
,
an
d
th
e
g
en
e
r
aliza
tio
n
p
o
ten
tial
o
f
th
e
p
r
o
p
o
s
ed
m
o
d
el
in
d
i
f
f
e
r
en
t
t
em
p
o
r
al
c
o
n
d
itio
n
s
an
d
en
v
ir
o
n
m
en
tal
v
ar
iatio
n
s
.
T
o
th
is
e
n
d
,
th
e
Yu
lar
a
So
lar
Po
wer
Sy
s
tem
in
Ulu
r
u
(
Ay
er
s
R
o
ck
)
,
Au
s
tr
alia
was
s
elec
ted
as
th
e
test
d
ata.
T
wo
-
tim
e
h
o
r
izo
n
s
wer
e
f
o
r
ec
asted
:
a
s
h
o
r
t
-
ter
m
h
o
r
iz
o
n
(
6
0
h
o
u
r
s
)
an
d
a
lo
n
g
-
ter
m
h
o
r
izo
n
(
3
0
0
h
o
u
r
s
)
.
T
h
e
e
n
tire
co
m
p
u
tatio
n
al
ex
p
er
im
en
t w
as
ca
r
r
ie
d
o
u
t in
MA
T
L
AB
o
n
a
co
m
p
u
te
r
r
u
n
n
in
g
W
in
d
o
ws 1
1
,
with
8
GB
R
AM
,
an
I
n
tel
C
o
r
e
i7
p
r
o
ce
s
s
o
r
,
a
n
8
GB
g
r
a
p
h
ic
s
ca
r
d
,
an
d
a
1
T
B
h
ar
d
d
is
k
.
4
.
1
.
Da
t
a
s
et
des
cr
iptio
n
T
h
e
d
ata
in
th
is
ex
p
er
im
en
t
was
d
er
iv
ed
f
r
o
m
th
e
Yu
lar
a
So
lar
Po
wer
Statio
n
in
Ulu
r
u
(
Ay
er
s
R
o
ck
)
,
Au
s
tr
alia,
co
v
er
in
g
th
e
tim
ef
r
am
e
o
f
1
J
an
u
ar
y
2
0
1
8
to
3
1
Dec
em
b
er
2
0
1
8
(
DKA
So
lar
C
en
tr
e,
2
0
1
8
)
.
T
h
is
d
ata
is
ac
ce
s
s
ib
le
o
n
th
e
DKA
So
lar
C
en
tr
e
web
s
i
te
[
2
7
]
.
PV
ar
r
ay
s
d
o
n
o
t
p
r
o
d
u
ce
elec
tr
icity
at
n
ig
h
t
tim
e,
an
d
th
e
r
ef
o
r
e
,
th
e
d
ata
th
at
f
ell
with
in
th
e
r
a
n
g
e
o
f
0
7
:
0
0
AM
an
d
0
7
:0
0
PM
wer
e
an
aly
ze
d
.
As
a
r
esu
lt,
13
s
a
m
p
l
e
s
w
e
r
e
t
a
k
e
n
d
a
i
l
y
,
a
n
d
f
o
r
3
6
5
d
a
y
s
,
t
h
i
s
r
e
s
u
lt
e
d
i
n
4
7
4
5
h
o
u
r
l
y
s
a
m
p
l
e
s
.
T
h
e
d
a
t
a
t
e
m
p
o
r
a
l
r
e
s
o
l
u
t
i
o
n
is
o
n
e
h
o
u
r
,
wh
ich
p
r
o
d
u
ce
s
4
7
4
5
tim
e
p
o
in
ts
.
T
h
e
d
ataset
o
f
f
er
s
a
r
ea
lis
tic
an
d
r
ep
r
esen
tativ
e
s
tan
d
ar
d
o
f
ass
ess
in
g
s
h
o
r
t
a
n
d
lo
n
g
-
ter
m
p
r
e
d
ictio
n
o
f
P
V
p
o
wer
m
o
d
els
in
d
if
f
er
en
t
s
o
lar
an
d
clim
atic
co
n
d
itio
n
s
.
4
.
2
.
E
v
a
lua
t
i
o
n m
et
rics
T
o
q
u
a
n
titativ
ely
d
eter
m
in
e
t
h
e
p
er
f
o
r
m
an
ce
an
d
ac
c
u
r
ac
y
o
f
th
e
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
in
p
r
ed
ictin
g
PV
o
u
tp
u
t
p
o
wer
,
f
o
u
r
m
etr
ics
o
f
s
tatis
tical
ev
alu
atio
n
h
av
e
b
e
en
u
s
ed
:
R
MSE
,
MA
E
,
m
ea
n
ab
s
o
lu
te
p
er
ce
n
tag
e
er
r
o
r
(
MA
PE)
,
a
n
d
c
o
ef
f
icien
t
o
f
d
eter
m
i
n
atio
n
(
2
)
.
All
t
h
ese
m
etr
ics
as
s
ess
th
e
m
o
d
el
p
er
f
o
r
m
an
ce
f
r
o
m
a
d
if
f
er
e
n
t
p
er
s
p
ec
tiv
e
as d
ef
in
e
d
b
elo
w
:
i)
R
o
o
t
m
ea
n
s
q
u
ar
e
e
r
r
o
r
(
R
MSE
)
T
h
e
R
MSE
is
u
s
ed
to
m
ea
s
u
r
e
th
e
ex
ten
t
o
f
th
e
er
r
o
r
i
n
p
r
e
d
ict
io
n
s
b
y
co
m
p
u
tin
g
t
h
e
s
q
u
ar
e
d
d
if
f
er
en
ce
s
b
etwe
en
th
e
p
r
e
d
i
cted
an
d
ac
tu
al
v
alu
es.
T
h
is
m
ea
s
u
r
e
is
esp
ec
ially
s
en
s
itiv
e
to
lar
g
e
er
r
o
r
s
,
th
u
s
ef
f
ec
tiv
ely
h
ig
h
lig
h
tin
g
s
ig
n
if
ican
t
d
ev
iatio
n
s
.
A
s
m
aller
R
MSE
in
d
icate
s
h
ig
h
e
r
ac
cu
r
a
cy
o
f
th
e
f
o
r
ec
ast.
W
h
er
e,
(
)
an
d
(
̂
)
ar
e
th
e
ac
t
u
al
an
d
p
r
ed
icted
v
al
u
es o
f
PV p
o
wer
,
r
esp
ec
tiv
ely
.
=
√
1
×
∑
(
−
̂
)
2
=
1
(
2
0
)
ii)
Me
an
ab
s
o
lu
te
er
r
o
r
(
MA
E
)
T
h
e
MA
E
is
an
av
er
ag
e
o
f
th
e
m
ag
n
itu
d
e
o
f
th
e
ab
s
o
lu
te
d
ev
iatio
n
s
b
etwe
en
ac
tu
al
an
d
p
r
ed
icted
v
alu
es.
I
n
co
m
p
ar
is
o
n
t
o
R
MSE
,
th
is
m
ea
s
u
r
e
is
less
s
en
s
i
tiv
e
to
o
u
tlier
s
an
d
p
r
o
v
id
es
a
d
ir
ec
t
m
ea
s
u
r
e
o
f
av
er
ag
e
p
r
ed
ictio
n
d
ev
iatio
n
.
MAE
=
1
∑
|
−
̂
|
=
1
(
2
1
)
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