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Science
Vo
l.
3
6
,
No
.
3
,
Dec
em
b
er
20
24
,
p
p
.
1
3
4
7
~
1
355
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7
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,
DOI
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1347
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[
1
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−
[
3
]
.
I
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[
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−
[
6
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.
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ar
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r
id
in
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[
7
]
−
[
1
0
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
6
,
No
.
3
,
Dec
em
b
er
20
24
:
1
3
4
7
-
1
3
5
5
1348
I
n
teg
r
atio
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ch
allen
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with
r
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b
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:
w
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r
s
h
o
r
t
-
an
d
m
ed
iu
m
-
ter
m
u
s
e
[
1
2
]
.
E
n
v
ir
o
n
m
en
tal
f
ac
t
o
r
s
m
u
s
t
b
e
tak
en
i
n
to
ac
co
u
n
t
wh
ile
p
r
o
jectin
g
th
e
p
r
o
d
u
ctio
n
o
f
r
en
ewa
b
le
en
er
g
y
.
R
en
e
wab
le
en
er
g
y
in
s
tallatio
n
s
ca
n
b
e
co
n
f
ig
u
r
ed
an
d
s
ited
o
p
tim
ally
with
th
e
u
s
e
o
f
m
ac
h
in
e
lear
n
in
g
[
1
3
]
−
[
1
6
]
.
I
n
in
tellig
en
t
g
r
id
m
an
ag
em
e
n
t
,
m
ac
h
in
e
lear
n
in
g
is
also
a
u
s
ef
u
l
tec
h
n
iq
u
e
f
o
r
f
au
lt
d
etec
tio
n
a
n
d
r
eg
u
latio
n
.
Fo
r
in
s
tan
ce
,
u
tili
zin
g
th
e
alg
o
r
ith
m
s
r
a
n
d
o
m
f
o
r
est
(
R
F)
an
d
ex
tr
em
e
g
r
a
d
i
en
t
b
o
o
s
tin
g
(
XGBo
o
s
t)
o
n
T
r
ip
u
r
a,
I
n
d
ia
d
ata
ca
n
im
p
r
o
v
e
th
e
in
teg
r
atio
n
o
f
r
en
ewa
b
le
en
er
g
y
s
o
u
r
ce
s
in
a
r
ea
s
with
in
s
u
f
f
icien
t in
f
r
astru
ctu
r
e
[
1
7
]
–
[
2
0
]
.
So
lu
tio
n
s
o
f
f
e
r
ed
f
o
r
t
h
e
d
if
f
icu
lties
o
f
in
teg
r
ate
d
r
e
n
ewa
b
l
e
en
er
g
y
:
th
e
c
h
allen
g
es
cr
ea
t
ed
b
y
th
e
v
a
r
i
a
b
i
l
i
t
y
a
n
d
u
n
p
r
e
d
i
c
t
a
b
i
l
i
t
y
o
f
r
e
n
e
w
a
b
l
e
e
n
e
r
g
y
(
R
E
)
o
u
t
p
u
t
h
a
v
e
b
e
e
n
a
d
d
r
e
s
s
e
d
i
n
a
n
u
m
b
e
r
o
f
w
a
y
s
[
2
1
]
.
Netwo
r
k
f
ea
tu
r
es a
n
d
co
s
t
-
ef
f
ec
tiv
en
ess
o
f
tech
n
o
lo
g
y
s
h
o
u
ld
b
e
tak
en
i
n
to
ac
co
u
n
t w
h
ile
ch
o
o
s
in
g
s
o
lu
tio
n
s
.
T
h
e
m
o
s
t
p
r
ac
ticab
le
o
p
tio
n
s
ar
e
d
eter
m
in
ed
b
y
f
a
cto
r
s
lik
e
g
r
id
in
f
r
astru
ctu
r
e,
o
p
e
r
a
tio
n
al
p
r
o
ce
d
u
r
es,
g
en
er
atio
n
ty
p
e,
an
d
laws.
T
h
e
m
an
ag
em
e
n
t
o
f
th
e
in
ter
m
itten
t
n
atu
r
e
o
f
r
en
ewa
b
le
e
n
er
g
y
s
o
u
r
ce
s
ca
n
b
e
f
ac
ilit
ated
b
y
s
ev
er
al
tech
n
i
q
u
es
s
u
ch
as
d
em
an
d
-
s
id
e
f
lex
ib
ilit
y
,
en
er
g
y
s
to
r
ag
e,
f
lex
ib
le
g
en
er
atio
n
,
im
p
r
o
v
e
d
f
o
r
ec
asti
n
g
,
an
d
o
p
er
atio
n
al
tactics
[
2
2
]
,
[
2
3
]
.
Alth
o
u
g
h
th
ey
ar
e
s
im
p
ler
,
s
h
o
r
t
-
ter
m
f
o
r
ec
asts
wh
o
s
e
f
o
r
ec
ast
m
is
tak
es
m
ig
h
t
r
an
g
e
f
r
o
m
3
-
6
%
an
h
o
u
r
ah
ea
d
o
f
tim
e
to
6
-
8
%
p
er
d
ay
ar
e
ess
en
tial
f
o
r
ef
f
icien
t m
an
ag
e
m
en
t
:
−
Op
er
atio
n
al
tech
n
iq
u
es:
f
aster
d
is
p
atch
tech
n
iq
u
es
an
d
b
r
o
ad
er
b
alan
cin
g
au
th
o
r
ity
r
e
g
io
n
s
in
cr
ea
s
e
ef
f
icien
cy
a
n
d
p
r
o
v
id
e
ac
ce
s
s
to
a
g
r
ea
ter
r
an
g
e
o
f
r
eso
u
r
ce
s
f
o
r
b
alan
cin
g
,
w
h
ich
elim
in
at
es
th
e
n
ee
d
f
o
r
p
r
icey
r
e
g
u
latin
g
r
eser
v
es.
−
R
eser
v
e
m
an
ag
em
en
t:
t
h
e
u
n
p
r
ed
ictab
ilit
y
o
f
win
d
an
d
s
o
lar
p
o
wer
is
less
en
ed
b
y
m
o
d
if
ied
r
eser
v
e
m
an
ag
em
en
t
tec
h
n
iq
u
es,
s
u
ch
as
lo
wer
in
g
p
o
wer
r
am
p
s
an
d
p
er
m
itti
n
g
r
e
n
ewa
b
les
to
d
eli
v
er
r
eser
v
es
o
r
s
u
p
p
lem
en
tal
s
er
v
ices.
−
Geo
g
r
ap
h
ic
d
is
p
er
s
io
n
:
l
o
ca
l
ch
an
g
es
af
f
ec
t
s
m
aller
u
n
its
r
ath
er
th
an
th
e
o
v
e
r
all
o
u
t
p
u
t
p
o
wer
,
h
en
ce
co
n
n
ec
tin
g
s
ca
tter
ed
r
eso
u
r
ce
s
o
v
er
a
wid
e
r
g
e
o
g
r
ap
h
ic
ar
ea
less
en
s
th
e
im
p
ac
t o
f
R
E
in
ter
m
itten
ce
.
−
E
n
er
g
y
s
to
r
ag
e:
r
at
h
er
o
f
d
ep
en
d
in
g
o
n
ex
p
e
n
s
iv
e
s
to
r
ag
e
s
y
s
tem
s
,
lar
g
e
-
s
ca
le
"o
v
er
b
u
ild
in
g
"
o
r
cu
r
tailm
en
t
ca
n
p
r
o
v
id
e
en
er
g
y
s
to
r
ag
e
,
wh
ich
is
n
ec
ess
ar
y
f
o
r
m
i
n
im
izin
g
g
en
er
atio
n
cu
r
tailm
en
t,
esp
ec
ially
with
in
cr
ea
s
in
g
R
E
p
en
etr
atio
n
.
−
Hy
b
r
id
s
y
s
tem
s
an
d
d
e
m
an
d
r
esp
o
n
s
e:
to
m
in
im
ize
o
v
er
all
p
o
wer
f
lu
ctu
ati
o
n
s
,
win
d
-
p
h
o
t
o
v
o
ltaic
(
PV)
h
y
b
r
id
s
y
s
tem
s
tak
e
ad
v
an
tag
e
o
f
th
e
co
m
p
lim
en
tar
y
n
atu
r
e
o
f
s
o
lar
an
d
win
d
o
u
tp
u
ts
.
Dem
an
d
r
esp
o
n
s
e
p
r
o
v
id
es
s
av
in
g
s
o
v
er
s
u
s
tain
in
g
a
d
d
itio
n
al
r
en
ewa
b
le
p
o
wer
d
u
r
in
g
r
ar
e
ca
s
es
o
f
co
n
s
id
er
ab
le
u
n
d
er
-
o
r
s
u
r
p
lu
s
g
en
er
atio
n
b
y
o
f
f
e
r
in
g
f
lex
ib
ilit
y
o
n
t
h
e
d
em
a
n
d
s
id
e
to
m
itig
ate
r
ap
id
r
am
p
in
g
im
p
ac
ts
.
T
h
r
o
u
g
h
th
e
ap
p
licatio
n
o
f
m
ac
h
in
e
lear
n
in
g
,
b
etter
f
o
r
ec
a
s
tin
g
,
an
d
o
p
er
atio
n
al
m
eth
o
d
s
,
th
ese
d
if
f
icu
lties
will
b
e
ad
d
r
ess
ed
in
o
r
d
er
t
o
in
cr
ea
s
e
th
e
in
teg
r
atio
n
o
f
r
en
ewa
b
le
en
er
g
y
s
o
u
r
ce
s
,
p
r
o
m
o
te
s
u
s
tain
ab
ilit
y
,
an
d
m
ain
tain
g
r
id
s
tab
ilit
y
[
2
4
]
,
[
2
5
]
.
2.
M
E
T
H
O
D
E
n
s
u
r
in
g
tr
a
n
s
p
ar
en
c
y
an
d
r
e
p
ea
tab
ilit
y
f
o
r
co
lleag
u
e
r
esea
r
ch
er
s
,
th
e
e
x
p
er
im
e
n
tal/m
eth
o
d
s
ec
tio
n
p
r
o
v
id
es
a
th
o
r
o
u
g
h
o
v
er
v
iew
o
f
th
e
r
esear
ch
m
et
h
o
d
s
d
o
n
e
an
d
th
e
m
eth
o
d
o
lo
g
ies
a
p
p
lied
.
T
h
e
e
x
p
er
im
e
n
t'
s
s
etu
p
,
d
ata
an
aly
s
is
,
an
d
d
ec
is
io
n
-
m
ak
i
n
g
p
r
o
ce
d
u
r
es a
r
e
all
ex
p
lain
ed
in
g
r
ea
t d
e
p
th
b
elo
w:
2
.
1
.
E
x
perim
ent
a
l
c
o
nfig
ura
t
io
n
T
h
e
p
r
o
ject
f
o
cu
s
es
o
n
ap
p
ly
in
g
an
i
n
teg
r
ated
s
y
s
tem
s
ap
p
r
o
ac
h
to
in
co
r
p
o
r
ate
d
is
tr
ib
u
ted
g
en
er
atio
n
,
en
er
g
y
s
to
r
ag
e,
d
e
m
an
d
r
esp
o
n
s
e,
an
d
r
en
ewa
b
l
e
en
er
g
y
s
o
u
r
ce
s
in
to
th
e
elec
tr
ical
g
r
id
.
I
n
o
r
d
er
to
en
ab
le
s
ea
m
less
in
teg
r
atio
n
,
th
is
s
tr
ateg
y
tack
les
in
s
titu
tio
n
al,
f
in
an
cial,
leg
al,
an
d
tech
n
o
lo
g
ica
l
im
p
ed
im
en
ts
.
Key
to
o
ls
f
o
r
es
tim
atin
g
win
d
s
p
ee
d
an
d
s
u
n
r
ad
iatio
n
,
s
u
ch
as p
y
r
a
n
o
m
eter
s
an
d
an
em
o
m
eter
s
,
wer
e
u
s
ed
to
g
ath
er
d
ata
f
r
o
m
r
e
n
ewa
b
le
s
o
u
r
ce
s
.
T
h
e
ex
p
er
im
en
tal
s
etu
p
p
r
o
ce
s
s
es
win
d
s
p
ee
d
,
s
u
n
elev
atio
n
,
ir
r
a
d
ian
ce
,
an
d
wea
t
h
er
co
n
d
itio
n
s
u
s
in
g
m
ac
h
in
e
l
ea
r
n
in
g
a
p
p
r
o
ac
h
es.
2
.
2
.
E
x
perim
ent
a
l c
o
nfig
ura
t
io
n
C
ar
ef
u
lly
g
ath
er
ed
d
ata
was
g
ath
er
ed
f
r
o
m
m
an
y
s
o
u
r
ce
s
,
in
clu
d
in
g
th
e
State
L
o
ad
Desp
atch
C
en
tr
e
(
SLDC),
T
r
ip
u
r
a,
an
d
th
e
Nin
ja
R
en
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b
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Pro
ject.
Fo
r
ex
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p
le,
win
d
p
o
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ata
f
o
r
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r
2
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in
Ag
ar
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r
ip
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r
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f
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r
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e
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u
s
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T
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e
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ataset
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clu
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tial f
ac
to
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s
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d
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asts
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m
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an
u
ar
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2
0
1
6
to
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v
em
b
er
2
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1
9
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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d
o
n
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J
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&
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p
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52
Leve
r
a
g
in
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ma
ch
in
e
lea
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n
in
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r
s
u
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ta
in
a
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le
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r
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(
P
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s
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p
a
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ee
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iv
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1349
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3
.
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x
perim
ent
a
l c
o
nfig
ura
t
io
n
Pre
d
ictio
n
a
r
ch
itectu
r
e:
I
O,
NAR,
an
d
NA
R
X
ar
e
th
r
ee
ty
p
es
o
f
au
to
r
eg
r
ess
iv
e
m
o
d
els:
in
p
u
t
-
o
u
tp
u
t,
n
o
n
lin
ea
r
au
to
r
eg
r
ess
iv
e
,
an
d
NAR
with
ex
o
g
en
o
u
s
in
p
u
ts
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ar
e
th
e
th
r
ee
m
ain
d
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s
f
o
r
tim
e
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er
ies
esti
m
atio
n
ex
am
in
ed
in
th
is
p
ap
er
.
B
ec
au
s
e
NARX
in
co
r
p
o
r
ates
h
is
to
r
ical
v
alu
es
in
a
d
d
itio
n
to
e
x
ter
n
al
in
p
u
ts
,
it o
u
tp
e
r
f
o
r
m
s
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O
an
d
NAR in
s
itu
atio
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wh
en
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o
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e
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o
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s
in
p
u
ts
h
av
e
a
m
aj
o
r
im
p
a
ct
o
n
th
e
g
o
al.
2
.
4
.
E
x
perim
ent
a
l c
o
nfig
ura
t
io
n
T
h
e
in
teg
r
ated
p
r
ed
ictio
n
f
r
am
ewo
r
k
u
s
ed
a
f
ea
tu
r
e
el
im
in
atio
n
tech
n
iq
u
e
to
ch
o
o
s
e
in
p
u
t.
I
ter
ativ
ely
f
itti
n
g
r
ec
u
r
s
iv
e
al
g
o
r
ith
m
s
o
n
s
m
aller
f
ea
tu
r
e
s
ets
allo
wed
th
em
to
o
p
tim
ize
f
o
r
r
elev
an
ce
wh
ile
av
o
id
in
g
th
e
o
v
er
f
itti
n
g
th
at
is
o
f
ten
ass
o
ciate
d
with
tr
ee
-
b
as
ed
m
o
d
els.
2
.
5
.
E
x
perim
ent
a
l c
o
nfig
ura
t
io
n
R
F
was
u
s
ed
to
p
ick
f
ea
tu
r
es
in
o
r
d
e
r
to
r
e
d
u
ce
c
o
m
p
lex
ity
.
XGBo
o
s
t
(
XGB),
wh
ich
is
we
ll
-
k
n
o
wn
f
o
r
its
ac
cu
r
ac
y
in
g
r
ad
ie
n
t
-
b
o
o
s
ted
d
ec
is
io
n
tr
ee
s
,
was
th
en
ap
p
lie
d
to
tr
ai
n
in
g
d
at
asets
.
T
o
im
p
r
o
v
e
p
r
ed
ictio
n
p
er
f
o
r
m
an
ce
,
1
0
-
f
o
ld
cr
o
s
s
-
v
alid
atio
n
was
u
s
ed
to
o
p
tim
ize
h
y
p
e
r
p
ar
am
ete
r
s
s
u
ch
lear
n
in
g
r
ate
(
eta)
,
m
ax
im
u
m
d
e
p
th
,
an
d
s
u
b
s
am
p
le
r
atio
.
2
.
6
.
E
x
perim
ent
a
l c
o
nfig
ura
t
io
n
Valid
atin
g
an
d
im
p
r
o
v
i
n
g
p
r
e
d
ictiv
e
m
o
d
els
r
eq
u
ir
ed
a
t
h
o
r
o
u
g
h
in
v
esti
g
atio
n
o
f
th
e
d
at
a.
Strictly
im
p
lem
en
ted
in
clu
s
io
n
/ex
clu
s
io
n
cr
iter
ia
wer
e
b
ased
o
n
m
o
d
el
p
e
r
f
o
r
m
an
ce
s
tan
d
ar
d
s
d
r
awn
f
r
o
m
tr
ain
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g
an
d
test
in
g
d
atasets
as we
ll a
s
s
tatis
t
ical
s
ig
n
if
ican
ce
.
2
.
7
.
E
x
perim
ent
a
l c
o
nfig
ura
t
io
n
Sp
ec
if
ically
co
n
f
ig
u
r
e
d
h
ar
d
war
e
o
n
a
W
in
d
o
ws
GPU
p
l
atf
o
r
m
was
u
s
ed
f
o
r
ex
p
er
im
en
ts
,
wh
ich
allo
wed
f
o
r
ef
f
ec
tiv
e
Py
th
o
n
ex
ec
u
tio
n
.
An
ess
en
tial
co
m
p
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en
t
o
f
s
u
s
tain
ab
le
p
o
wer
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an
ag
e
m
en
t,
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n
f
ig
u
r
atio
n
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ar
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tee
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p
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tatio
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al
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b
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m
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elin
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ce
n
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r
io
s
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en
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Fig
u
r
e
1
s
h
o
ws
th
e
o
v
er
v
iew
o
f
p
o
wer
g
r
id
with
in
teg
r
ated
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e
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ewa
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le
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o
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r
ce
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d
its
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s
ag
e
o
f
m
ac
h
in
e
lear
n
in
g
tech
n
iq
u
es.
Fig
u
r
e1
.
Ov
er
v
iew
o
f
p
o
wer
g
r
id
with
in
teg
r
ated
r
en
ewa
b
le
s
o
u
r
ce
s
an
d
its
u
s
ag
e
o
f
m
ac
h
i
n
e
lear
n
in
g
tech
n
iq
u
es
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
6
,
No
.
3
,
Dec
em
b
er
20
24
:
1
3
4
7
-
1
3
5
5
1350
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
m
ain
s
tu
d
y
f
in
d
in
g
s
ar
e
p
r
esen
ted
in
th
is
ar
ea
,
with
an
em
p
h
asis
o
n
elec
tr
ical
lo
a
d
p
r
o
jectio
n
s
,
win
d
en
e
r
g
y
,
s
o
lar
PV
p
o
wer
,
an
d
m
o
d
el
v
alid
atio
n
.
I
n
ea
ch
p
a
r
ag
r
ap
h
,
d
ata
attr
i
b
u
tes
ar
e
h
ig
h
lig
h
ted
an
d
p
r
ed
ictio
n
alg
o
r
ith
m
s
ar
e
co
m
p
ar
ed
.
T
a
b
le
1
s
u
m
m
ar
izes
th
e
in
p
u
ts
f
o
r
esti
m
ates
o
f
win
d
en
er
g
y
,
s
o
lar
PV
p
o
wer
,
an
d
elec
tr
ical
lo
ad
.
T
ab
le
1
.
P
ar
am
eter
s
f
o
r
f
o
r
ec
a
s
tin
g
elec
tr
icity
lo
ad
,
s
o
lar
PV
p
o
wer
,
a
n
d
win
d
en
er
g
y
I
n
p
u
t
W
i
n
d
e
n
e
r
g
y
p
r
e
d
i
c
t
i
o
n
S
o
l
a
r
P
V
p
o
w
e
r
p
r
e
d
i
c
t
i
on
El
e
c
t
r
i
c
i
t
y
l
o
a
d
p
r
e
d
i
c
t
i
o
n
H
o
u
r
l
y
met
e
o
r
o
l
o
g
i
c
a
l
p
a
r
a
m
e
t
e
r
s
❖
❖
❖
En
e
r
g
y
f
r
o
m
w
i
n
d
(
K
W
)
❖
P
V
so
l
a
r
p
o
w
e
r
(
W
)
❖
P
o
w
e
r
d
e
m
a
n
d
(
M
W
)
❖
1
0
a
n
d
5
0
met
r
e
w
i
n
d
s
p
e
e
d
s
❖
❖
❖
D
i
r
e
c
t
i
o
n
o
f
t
h
e
w
i
n
d
❖
I
n
t
e
n
s
i
t
y
o
f
s
u
n
l
i
g
h
t
(
m
e
a
s
u
r
e
d
i
n
k
i
l
o
w
a
t
t
s)
❖
❖
A
n
g
l
e
o
f
t
h
e
s
u
n
a
b
o
v
e
t
h
e
h
o
r
i
z
o
n
❖
3
.
1
.
Wind
ener
g
y
predict
io
ns
T
h
e
s
tu
d
y
h
ig
h
lig
h
ted
th
e
s
u
b
s
tan
tial
r
elatio
n
s
h
ip
b
etwe
en
win
d
p
o
wer
an
d
win
d
s
p
ee
d
b
y
u
s
in
g
R
F
f
ea
tu
r
e
s
elec
tio
n
to
d
is
co
v
er
s
ig
n
if
ican
t
p
a
r
am
eter
s
f
o
r
win
d
p
o
wer
p
r
e
d
ictio
n
.
W
in
d
p
o
wer
is
also
af
f
ec
ted
b
y
o
th
er
v
ar
iab
les
s
u
c
h
as
h
u
m
id
ity
,
tem
p
er
atu
r
e,
a
n
d
tim
e
o
f
y
ea
r
.
Du
r
in
g
tr
ain
in
g
,
wea
k
ly
co
r
r
elate
d
ch
ar
ac
ter
is
tics
wer
e
r
em
o
v
ed
,
an
d
f
iv
e
-
f
o
ld
cr
o
s
s
-
v
alid
atio
n
r
ev
ea
led
th
at
th
e
p
r
ed
icted
win
d
s
p
ee
d
d
if
f
er
ed
v
er
y
litt
le
f
r
o
m
th
e
ac
tu
al
d
ata.
Fig
u
r
e
2
'
s
co
m
p
ar
is
o
n
o
f
th
e
p
r
e
d
icted
an
d
o
b
s
er
v
ed
win
d
s
p
ee
d
d
ata
illu
s
tr
ates
th
is
d
is
p
ar
ity
.
Fig
u
r
e
2
(
a
)
d
e
p
icts
a
f
o
r
ec
ast
f
o
r
th
e
n
ex
t
d
ay
,
Sep
tem
b
er
1
,
2
0
1
9
;
Fig
u
r
e
2
(
b
)
d
ep
icts
a
p
r
e
d
ictio
n
f
o
r
th
e
n
ex
t
wee
k
,
Sep
tem
b
er
1
,
2
0
1
9
;
an
d
Fig
u
r
e
2
(
c)
d
ep
icts
a
lo
n
g
-
ter
m
f
o
r
ec
ast
f
o
r
win
d
s
p
ee
d
.
3
.
2
.
So
la
r
P
V
po
wer
predict
io
ns
T
h
e
s
o
lar
PV
p
o
wer
an
d
ir
r
a
d
ian
ce
wer
e
p
r
o
jecte
d
u
s
in
g
a
s
im
p
le
alg
o
r
ith
m
.
Af
ter
g
en
er
atin
g
th
e
tar
g
et
m
atr
ix
(
Y_
E
PV)
u
s
in
g
th
e
r
eliab
ly
co
r
r
elate
d
v
alu
e
s
f
r
o
m
th
e
f
ea
tu
r
es
m
atr
ix
(
X_
E
PV)
,
f
iv
e
-
f
o
ld
cr
o
s
s
-
v
alid
atio
n
was
p
er
f
o
r
m
ed
.
Fig
u
r
e
3
co
m
p
ar
es
th
e
le
v
els
o
f
p
lan
n
e
d
an
d
ac
tu
al
s
o
lar
PV
p
o
wer
an
d
ir
r
ad
iatio
n
.
3
.
3
.
E
lect
ricit
y
lo
a
d pre
dict
io
ns
Data
f
r
o
m
m
u
ltip
le
s
o
u
r
ce
s
,
i
n
clu
d
in
g
Nin
ja
Pro
jects
f
o
r
e
n
er
g
y
a
n
d
T
SECL,
SLDC
f
o
r
lo
ad
d
ata,
wer
e
u
s
ed
in
th
e
elec
tr
ical
lo
a
d
f
o
r
ec
ast.
Un
ce
r
tain
ties
an
d
e
r
r
o
r
s
wer
e
ca
u
s
ed
b
y
m
alf
u
n
ct
io
n
in
g
in
s
tr
u
m
en
ts
in
th
e
lo
a
d
d
ataset
(
Ag
t_
lo
ad
)
.
Af
ter
th
e
d
ataset
was
clea
n
e
d
u
p
,
k
e
y
c
h
ar
ac
ter
is
tics
wer
e
f
o
u
n
d
.
T
h
e
m
o
d
el
was
tr
ain
ed
u
s
in
g
XGBo
o
s
t,
an
d
b
asic
co
r
r
elatio
n
m
atr
ices w
er
e
g
en
er
ated
.
A
co
m
b
i
n
ed
a
n
aly
s
is
o
f
p
r
ed
icted
elec
tr
icity
lo
ad
,
s
o
lar
PV
p
o
wer
,
an
d
win
d
en
e
r
g
y
is
s
h
o
wn
in
T
ab
le
2
.
Fig
u
r
e
4
s
h
o
ws
th
e
co
m
p
ar
is
o
n
o
f
d
if
f
er
en
t m
o
d
els o
f
p
r
ed
ictio
n
.
T
a
bl
e
2.
An
i
nt
e
gr
at
e
d
f
o
r
e
c
a
s
t
in
g
of
w
i
n
d
en
er
g
y,
s
o
la
r
P
V
p
o
w
er
,
a
n
d
el
ec
tr
i
c
al
l
o
a
d
M
o
d
e
l
W
i
n
d
e
n
e
r
g
y
S
o
l
a
r
PV
p
o
w
e
r
El
e
c
t
r
i
c
a
l
l
o
a
d
R
2
-
s
c
o
r
e
R
M
S
E
R
2
s
c
o
r
e
R
M
S
E
R
2
-
s
c
o
r
e
R
M
S
E
Tr
e
e
-
b
a
se
d
d
e
c
i
s
i
o
n
mo
d
e
l
.
6
1
1
.
3
5
.
7
9
5
.
3
4
.
2
9
4
.
8
6
En
h
a
n
c
e
d
d
e
c
i
s
i
o
n
t
r
e
e
.
6
5
1
.
2
2
.
8
2
5
.
3
1
.
3
8
3
.
2
4
S
u
p
p
o
r
t
v
e
c
t
o
r
r
e
g
r
e
ss
i
o
n
.
6
1
2
.
3
2
.
8
0
5
.
7
1
.
5
9
3
.
1
7
S
t
o
c
h
a
st
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c
f
o
r
e
st
.
6
6
1
.
2
4
.
8
5
5
.
2
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.
6
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.
8
2
En
h
a
n
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e
d
st
o
c
h
a
s
t
i
c
f
o
r
e
st
.
7
8
0
.
9
7
.
8
6
5
.
2
0
.
7
3
2
.
6
9
En
se
mb
l
e
mo
d
e
l
u
si
n
g
X
G
B
o
o
st
.
8
2
3
0
.
9
5
.
8
9
5
.
0
2
.
7
6
2
.
4
6
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.
4
.
Sy
s
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m
mo
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f
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re
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ble int
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ra
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io
n o
f
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ble so
urce
s
T
o
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Ag
ar
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g
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ested
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T
h
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R
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i
m
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ce
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ar
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ilit
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icatio
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e
k
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d
s
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d
q
u
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y
o
f
d
ev
ices.
Fig
u
r
e
5
s
h
o
ws
t
h
e
p
r
o
p
o
s
ed
m
o
d
el
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d
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e
m
o
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co
m
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icatio
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elo
w,
a
n
d
th
e
o
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n
f
ig
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r
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n
m
in
im
izes
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o
th
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an
d
L
C
E
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
Leve
r
a
g
in
g
ma
ch
in
e
lea
r
n
in
g
fo
r
s
u
s
ta
in
a
b
le
in
teg
r
a
tio
n
o
f
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en
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le
…
(
P
u
s
h
p
a
S
r
ee
n
iv
a
s
a
n
)
1351
−
PV:
1
KW
g
en
er
ic
f
lat
p
late
PV,
ca
p
ital
co
s
t:
2
,
5
0
0
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r
e
p
la
ce
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en
t:
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0
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M:
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d
:
g
en
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ic
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ca
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ital c
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s
t: 7
,
0
0
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,
r
e
p
la
ce
m
en
t: 7
,
0
0
0
,
O&
M:
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0
/y
.
−
B
atter
y
:
6
V
lith
iu
m
i
o
n
with
1
k
W
h
o
f
e
n
er
g
y
s
to
r
a
g
e,
n
o
m
in
al
ca
p
ac
ity
1
6
7
Ah
,
m
ax
ch
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g
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c
u
r
r
en
t
1
6
7
a,
m
ax
d
is
ch
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cu
r
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en
t 5
0
0
a,
ca
p
ital c
o
s
t: 5
5
0
,
r
e
p
lace
m
en
t: 5
5
0
,
O&
M:
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0
/y
.
−
C
o
n
v
er
ter
:
g
en
e
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ic
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ca
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ital: 3
0
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,
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en
t: 3
0
0
,
O
&
M:
0
.
0
−
Gen
er
ato
r
:
it
au
to
m
atica
lly
s
izes
its
elf
to
m
ee
t
th
e
lo
ad
.
in
itial
ca
p
ital:
5
0
0
,
r
ep
lace
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e
n
t:
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0
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M:
0
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0
5
/o
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o
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r
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f
u
el
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r
ice:
8
0
,
e
m
is
s
io
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s
: CO(
g
/L
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el)
: 1
6
.
5
,
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n
b
u
r
n
ed
HC
: 0
.
7
2
,
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u
el
s
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lf
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r
: 2
.
2
,
NOx
: 1
5
.
5
.
C
o
n
f
ig
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r
atio
n
s
with
1
,
4
7
1
KW
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3
1
5
win
d
,
an
d
6
,
9
9
9
b
atter
ies ar
e
ec
o
n
o
m
ical
wh
en
co
m
p
ar
ed
to
L
C
E
an
d
NPC
as
ec
o
n
o
m
ic
b
en
ch
m
ar
k
s
;
d
ep
en
d
ab
ilit
y
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g
u
ar
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teed
b
y
1
DG,
2
,
7
9
3
KW
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2
2
2
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d
,
a
n
d
5
,
2
4
6
b
atter
ies.
T
h
ese
ar
r
an
g
em
en
ts
an
d
th
e
d
is
tr
ib
u
tio
n
o
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th
eir
elec
tr
ical
l
o
ad
ar
e
t
h
e
s
u
b
ject
o
f
m
o
r
e
in
v
esti
g
atio
n
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T
h
e
co
m
p
ar
ativ
e
ex
am
in
atio
n
o
f
th
e
p
e
n
etr
at
io
n
o
f
r
e
n
ewa
b
les
is
s
h
o
wn
in
Fig
u
r
e
6
.
Fig
u
r
es
6
(
a)
an
d
6
(
b
)
d
ep
ict
th
e
co
s
t
o
f
en
er
g
y
a
n
d
o
v
er
all
o
p
er
ati
n
g
co
s
ts
,
r
esp
ec
tiv
ely
,
with
t
h
e
h
ig
h
est
p
o
s
s
ib
le
p
en
etr
atio
n
o
f
r
e
n
ewa
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le
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er
g
y
s
o
u
r
ce
s
.
Fig
u
r
e
s
6
(
a
)
an
d
6
(
b
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p
r
esen
ts
an
ex
a
m
in
atio
n
o
f
th
e
g
r
ea
test
p
en
etr
atio
n
o
f
r
en
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b
les
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th
en
er
g
y
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d
to
tal
co
s
ts
.
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o
r
d
in
g
to
th
e
s
im
u
latio
n
r
esu
lts
,
u
n
less
b
atter
y
ca
p
ac
ity
is
lar
g
e,
m
o
r
e
th
an
3
1
%
o
f
PV
an
d
win
d
en
e
r
g
y
o
u
tp
u
t
m
u
s
t
r
em
ain
u
n
u
s
ed
f
o
r
th
e
f
u
ll
r
en
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b
le
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n
tr
i
b
u
tio
n
(
R
C
=1
)
.
As
R
C
f
alls
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waste
f
alls
.
I
m
p
o
r
tan
t
s
itu
atio
n
s
co
n
s
is
t
o
f
:
i)
l
o
w
en
er
g
y
ex
ce
s
s
ca
u
s
es
th
e
lo
ad
to
n
o
t
b
e
s
atis
f
ied
;
ii)
d
esp
ite
s
u
r
p
lu
s
,
a
th
ir
d
en
er
g
y
s
o
u
r
ce
(
DG)
is
r
eq
u
ir
ed
t
o
s
atis
f
y
8
5
–
1
0
0
%
o
f
th
e
lo
a
d
;
an
d
iii)
t
ec
h
n
ical
lo
ad
s
u
p
p
ly
co
u
ld
n
o
t b
e
e
n
er
g
etica
lly
s
atis
f
y
in
g
.
(
a)
(
b
)
(
c)
F
i
g
u
r
e
2.
C
o
m
p
ar
i
s
o
n
b
e
t
w
e
e
n
f
or
e
c
a
s
t
e
d
w
i
n
d
s
p
e
e
d
an
d
o
b
s
er
v
ed
v
al
u
e
s
:
(
a)
1
-
d
ay
ah
ea
d
p
r
e
d
ictio
n
o
n
0
1
/0
9
/2
0
1
9
,
(
b
)
1
-
w
e
e
k
a
h
e
ad
pr
e
di
ct
io
n
(
f
r
o
m
01
-
07
S
e
pt
.
20
19
)
,
an
d
(
c
)
l
ong
t
er
m
pr
e
di
ct
i
o
n
of
w
i
n
d
s
p
e
e
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
6
,
No
.
3
,
Dec
em
b
er
20
24
:
1
3
4
7
-
1
3
5
5
1352
Fig
u
r
e
3
.
T
h
e
co
m
p
ar
is
o
n
o
f
a
ctu
al
an
d
p
r
ed
icted
v
alu
es o
f
s
o
lar
PV p
o
wer
Fig
u
r
e
4
.
C
o
m
p
a
r
is
o
n
o
f
d
if
f
e
r
en
t m
o
d
els o
f
p
r
e
d
ictio
n
Fig
u
r
e
5
.
Pro
p
o
s
ed
m
o
d
el
3
.
5
.
I
nte
rpre
t
a
t
io
n
o
f
t
he
re
s
ult
s
I
m
p
r
o
v
ed
p
r
ed
ictio
n
ac
c
u
r
ac
y
f
o
r
win
d
en
er
g
y
,
s
o
lar
PV
p
o
wer
,
an
d
elec
tr
ical
d
em
an
d
s
,
as
well
as
im
p
r
o
v
e
d
in
teg
r
atio
n
o
f
r
en
ew
ab
le
en
er
g
y
s
o
u
r
ce
s
,
wh
ich
a
r
e
am
o
n
g
t
h
e
g
o
als
o
f
th
e
s
tu
d
y
,
wh
ich
th
e
r
esu
lts
s
u
p
p
o
r
t.
Similar
to
p
r
ev
i
o
u
s
r
esear
ch
,
th
e
r
esu
lts
d
em
o
n
s
tr
ate
h
o
w
well
en
s
em
b
le
m
o
d
e
ls
lik
e
as
XGBo
o
s
t
p
er
f
o
r
m
in
o
b
tain
in
g
lo
w
r
o
o
t
m
ea
n
s
q
u
ar
e
er
r
o
r
(
R
MSE
)
v
alu
es
an
d
h
ig
h
R
2
-
s
co
r
e
s
.
So
m
e
d
r
awb
ac
k
s
in
clu
d
e
th
o
s
e
co
r
r
ec
t
d
ata
in
p
u
ts
ar
e
n
ec
ess
ar
y
f
o
r
t
r
u
s
two
r
th
y
f
o
r
ec
asts
,
an
d
a
lar
g
e
b
atter
y
ca
p
ac
ity
is
r
eq
u
ir
ed
to
p
r
e
v
en
t
en
er
g
y
wa
s
te.
Fo
r
th
e
in
co
r
p
o
r
atio
n
o
f
g
r
ee
n
e
n
er
g
y
in
Ag
ar
tala,
th
e
r
e
co
m
m
en
d
e
d
h
y
b
r
id
s
etu
p
p
r
o
v
id
es
an
af
f
o
r
d
ab
le
an
d
d
ep
en
d
ab
le
o
p
tio
n
.
Op
tim
al
p
er
f
o
r
m
an
ce
is
ac
h
iev
ed
with
p
ar
ticu
lar
co
m
b
in
atio
n
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
Leve
r
a
g
in
g
ma
ch
in
e
lea
r
n
in
g
fo
r
s
u
s
ta
in
a
b
le
in
teg
r
a
tio
n
o
f
r
en
ewa
b
le
…
(
P
u
s
h
p
a
S
r
ee
n
iv
a
s
a
n
)
1353
(
a)
(
b
)
Fig
u
r
e
6
.
C
o
m
p
a
r
ativ
e
an
aly
s
i
s
o
f
r
en
ewa
b
le
p
en
etr
atio
n
with
(
a)
c
o
s
t o
f
en
er
g
y
a
n
d
(
b
)
to
t
al
co
s
t
4.
CO
NCLU
SI
O
N
As
tr
ad
itio
n
al
en
er
g
y
s
o
u
r
ce
s
d
is
ap
p
ea
r
,
r
e
n
ewa
b
le
en
er
g
y
is
b
ec
o
m
in
g
m
o
r
e
an
d
m
o
r
e
p
o
p
u
la
r
.
Acc
u
r
ate
m
an
ag
em
e
n
t
tech
n
iq
u
es
an
d
f
o
r
ec
asti
n
g
ar
e
c
r
u
cial
f
o
r
a
s
u
cc
ess
f
u
l
in
teg
r
atio
n
in
to
p
o
wer
s
y
s
tem
s
,
ev
en
in
t
h
e
f
ac
e
o
f
u
n
ce
r
tain
t
y
.
R
eg
ar
d
in
g
s
o
lar
,
win
d
,
a
n
d
o
th
er
r
ep
len
is
h
ab
le
e
n
er
g
y
s
o
u
r
ce
s
,
m
etr
ics
s
u
ch
as
R
2
an
d
R
M
SE
ar
e
ess
en
tia
l
f
o
r
ev
alu
atin
g
p
r
ed
ictiv
e
an
a
ly
tics
.
E
n
er
g
y
-
ef
f
icien
t
an
d
co
s
t
-
ef
f
ec
tiv
e
h
y
b
r
id
s
to
r
ag
e
-
b
ased
PV
an
d
win
d
s
y
s
tem
s
,
o
p
tim
ized
with
m
o
d
els.
B
y
d
ef
in
in
g
th
e
n
ee
d
s
f
o
r
p
o
we
r
s
u
p
p
l
y
p
r
o
b
a
b
ilit
y
m
eth
o
d
,
an
d
s
y
s
tem
d
ep
en
d
a
b
ilit
y
d
ir
ec
ts
d
ec
is
io
n
-
m
ak
in
g
.
E
f
f
ec
tiv
e
u
s
e
o
f
r
en
ewa
b
le
en
er
g
y
d
ep
en
d
s
o
n
b
atter
y
ca
p
ac
ity
,
a
n
d
o
p
tim
izin
g
th
e
u
s
e
o
f
ex
ce
s
s
en
er
g
y
ca
n
b
e
ac
h
iev
e
d
b
y
i
n
teg
r
atin
g
d
iesel
as
a
b
ac
k
u
p
s
u
p
p
ly
an
d
lo
wer
in
g
ep
en
s
es.
Data
-
d
r
iv
en
m
o
d
elin
g
h
elp
s
with
th
e
s
m
o
o
th
in
teg
r
atio
n
o
f
r
en
ewa
b
le
en
er
g
y
s
o
u
r
ce
s
in
to
th
e
g
r
id
a
n
d
en
h
an
ce
s
in
v
estme
n
t
d
ec
is
io
n
s
f
o
r
p
o
wer
s
to
r
ag
e.
Ke
y
f
in
d
in
g
s
em
p
h
asize
th
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[
5
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