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I
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Vo
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17
,
No
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3
,
Sep
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2
7
:
2029
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2030
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iv
en
m
o
d
ellin
g
an
d
a
d
ap
tiv
e
lear
n
in
g
,
en
ab
lin
g
m
o
r
e
r
eliab
le
o
p
er
atio
n
o
f
r
en
ewa
b
le
-
in
teg
r
ated
p
o
wer
s
y
s
tem
s
[
1
6
]
-
[
2
3
]
.
Desp
ite
th
ese
ad
v
an
ce
s
,
cu
r
r
en
t
r
esear
ch
p
r
im
ar
ily
in
v
e
s
tig
ates
d
ig
ital
twin
s
,
FL,
a
n
d
MA
S
in
d
ep
en
d
en
tly
o
r
co
m
b
in
es
o
n
ly
two
o
f
th
ese
tech
n
o
lo
g
ies
f
o
r
s
p
ec
if
ic
ap
p
licatio
n
s
.
Dig
ital
twin
-
b
ased
ap
p
r
o
ac
h
es
m
ain
ly
f
o
cu
s
o
n
v
ir
tu
al
m
o
d
ellin
g
an
d
p
r
ed
ictiv
e
m
o
n
ito
r
in
g
,
wh
ile
f
ed
er
ated
lear
n
in
g
em
p
h
asizes
p
r
iv
ac
y
-
p
r
eser
v
in
g
d
is
tr
ib
u
ted
m
o
d
el
tr
ain
in
g
with
o
u
t
d
ir
ec
tly
s
u
p
p
o
r
tin
g
co
o
r
d
i
n
ated
g
r
i
d
co
n
tr
o
l.
Similar
ly
,
m
u
lti
-
ag
e
n
t
s
y
s
tem
s
im
p
r
o
v
e
d
ec
en
tr
alize
d
d
ec
is
io
n
-
m
ak
in
g
b
u
t
g
en
e
r
al
ly
o
p
er
ate
with
o
u
t
co
n
tin
u
o
u
s
ly
s
y
n
ch
r
o
n
ized
v
ir
tu
al
s
y
s
tem
m
o
d
els
o
r
co
l
lab
o
r
ativ
e
lear
n
in
g
m
ec
h
an
is
m
s
.
C
o
n
s
eq
u
en
tly
,
ex
is
tin
g
f
r
am
ewo
r
k
s
ca
n
n
o
t
s
im
u
ltan
eo
u
s
ly
p
r
o
v
id
e
r
e
al
-
tim
e
d
ig
ital
twin
s
y
n
ch
r
o
n
izatio
n
,
p
r
iv
ac
y
-
p
r
eser
v
in
g
d
is
tr
ib
u
te
d
f
o
r
ec
as
tin
g
,
au
to
n
o
m
o
u
s
ag
e
n
t
co
o
r
d
in
atio
n
,
an
d
ad
ap
tiv
e
co
n
tr
o
l
with
in
a
u
n
if
ied
in
tellig
en
t
ar
ch
itectu
r
e.
Fu
r
th
er
m
o
r
e,
lim
ited
atten
tio
n
h
as
b
ee
n
g
iv
e
n
to
a
n
aly
s
in
g
th
e
r
elatio
n
s
h
ip
b
etwe
en
f
o
r
ec
asti
n
g
ac
cu
r
ac
y
an
d
g
r
id
co
n
tr
o
l
p
er
f
o
r
m
a
n
ce
,
d
i
s
tr
ib
u
ted
m
o
d
el
c
o
n
v
e
r
g
en
c
e,
co
m
m
u
n
icatio
n
ef
f
icien
cy
,
s
ca
lab
ilit
y
u
n
d
er
in
cr
ea
s
in
g
n
u
m
b
er
s
o
f
in
te
llig
en
t
ag
en
ts
,
an
d
co
o
r
d
i
n
ated
o
p
tim
izatio
n
in
r
en
ewa
b
le
-
r
ich
s
m
ar
t g
r
id
s
[
2
0
]
-
[
2
5
]
.
T
h
ese
lim
itatio
n
s
in
d
icate
th
e
n
ee
d
f
o
r
an
in
teg
r
ated
f
r
am
ewo
r
k
ca
p
a
b
le
o
f
co
m
b
in
in
g
p
r
ed
ictiv
e
m
o
d
ellin
g
,
d
is
tr
ib
u
ted
in
tellig
en
ce
,
s
ec
u
r
e
co
llab
o
r
ativ
e
lear
n
in
g
,
an
d
a
u
to
n
o
m
o
u
s
en
er
g
y
m
an
ag
em
e
n
t.
T
o
o
v
e
r
co
m
e
th
ese
lim
itatio
n
s
,
th
is
p
ap
er
p
r
o
p
o
s
es
a
d
i
g
ital
twin
-
d
r
iv
en
f
ed
e
r
ated
m
u
lti
-
ag
en
t
in
tellig
en
ce
(
DT
-
FMAI
)
f
r
a
m
ewo
r
k
f
o
r
au
to
n
o
m
o
u
s
r
en
ewa
b
le
f
o
r
ec
asti
n
g
an
d
s
m
ar
t
g
r
id
o
p
tim
izatio
n
.
Un
lik
e
p
r
ev
io
u
s
s
tu
d
ies
in
teg
r
atin
g
o
n
ly
d
ig
ital
twin
s
with
f
ed
er
ated
lear
n
i
n
g
o
r
m
u
lti
-
ag
en
t
s
y
s
tem
s
,
th
e
p
r
o
p
o
s
ed
f
r
am
ewo
r
k
estab
li
s
h
es
a
clo
s
ed
-
lo
o
p
c
y
b
er
-
p
h
y
s
ical
ar
ch
itectu
r
e
in
w
h
ich
d
ig
ital
twin
s
co
n
tin
u
o
u
s
ly
s
y
n
ch
r
o
n
ize
p
h
y
s
ical
an
d
v
ir
tu
al
g
r
id
s
tates,
f
ed
er
ated
lear
n
in
g
co
lla
b
o
r
ativ
ely
u
p
d
ates
f
o
r
ec
asti
n
g
m
o
d
els
with
o
u
t
e
x
ch
an
g
i
n
g
r
aw
o
p
er
atio
n
al
d
ata,
an
d
in
tellig
e
n
t
ag
en
ts
co
o
p
er
ativ
ely
p
er
f
o
r
m
r
en
ewa
b
le
s
ch
ed
u
lin
g
,
b
atter
y
en
er
g
y
m
an
ag
e
m
en
t,
d
em
an
d
r
esp
o
n
s
e,
an
d
v
o
ltag
e
r
eg
u
latio
n
.
T
h
is
in
teg
r
ate
d
f
r
am
ewo
r
k
e
n
h
an
ce
s
f
o
r
ec
asti
n
g
ac
cu
r
ac
y
,
o
p
er
atio
n
al
r
esil
ien
ce
,
co
m
m
u
n
icatio
n
ef
f
icie
n
cy
,
an
d
s
ca
lab
ilit
y
wh
ile
p
r
eser
v
in
g
d
ata
co
n
f
i
d
en
tiality
.
C
o
m
p
r
eh
e
n
s
iv
e
s
im
u
latio
n
s
tu
d
ies
ar
e
co
n
d
u
cte
d
u
s
in
g
r
en
ewa
b
le
g
en
er
atio
n
,
wea
th
er
,
b
atter
y
s
tate
-
of
-
ch
ar
g
e,
a
n
d
lo
ad
d
e
m
an
d
d
atasets
to
ev
alu
ate
f
o
r
ec
asti
n
g
ac
cu
r
ac
y
,
v
o
ltag
e
s
tab
ilit
y
,
en
er
g
y
ef
f
icien
cy
,
co
m
m
u
n
icatio
n
o
v
e
r
h
ea
d
,
co
n
v
er
g
en
ce
b
e
h
av
io
u
r
,
an
d
d
is
tr
ib
u
ted
s
ca
lab
ilit
y
.
T
h
e
p
r
o
p
o
s
ed
DT
-
FMAI
f
r
am
ewo
r
k
p
r
o
v
id
es
a
p
r
ac
tical
an
d
s
ca
lab
le
s
o
lu
tio
n
f
o
r
n
e
x
t
-
g
e
n
er
atio
n
r
en
ewa
b
le
-
in
teg
r
ate
d
s
m
ar
t
g
r
id
s
b
y
co
m
b
in
i
n
g
p
r
e
d
ictiv
e
d
ig
ital
r
ep
r
esen
tatio
n
s
,
p
r
iv
ac
y
-
p
r
eser
v
in
g
d
is
tr
ib
u
ted
in
tellig
en
ce
,
a
n
d
a
u
to
n
o
m
o
u
s
m
u
lti
-
ag
e
n
t c
o
n
tr
o
l w
ith
in
a
s
in
g
le
u
n
if
ied
ar
ch
it
ec
tu
r
e.
2.
M
E
T
H
O
D
T
h
e
p
r
o
p
o
s
ed
DT
-
FMAI
f
r
am
ewo
r
k
in
teg
r
ates
d
ig
ital
twin
(
DT
)
,
f
ed
er
ate
d
lear
n
i
n
g
(
FL)
,
an
d
m
u
lti
-
ag
en
t
s
y
s
tem
s
(
MA
S)
to
en
ab
le
au
to
n
o
m
o
u
s
r
en
ewa
b
le
en
er
g
y
f
o
r
ec
asti
n
g
an
d
p
r
e
d
ictiv
e
s
m
ar
t
g
r
id
o
p
tim
izatio
n
.
T
h
e
f
r
am
ewo
r
k
co
n
s
is
ts
o
f
f
iv
e
f
u
n
ctio
n
al
la
y
er
s
:
p
h
y
s
ical
lay
er
,
d
ig
ital
twin
lay
er
,
f
ed
er
ated
lear
n
in
g
lay
er
,
m
u
lti
-
ag
e
n
t
la
y
er
,
a
n
d
d
ec
is
io
n
la
y
er
,
as
i
llu
s
tr
ated
in
Fig
u
r
e
1
R
ea
l
-
tim
e
m
ea
s
u
r
em
e
n
ts
co
llected
f
r
o
m
p
h
o
to
v
o
ltaic
(
P
V)
s
y
s
tem
s
,
win
d
tu
r
b
in
es,
B
E
SS
,
E
Vs,
an
d
s
m
ar
t
lo
ad
s
ar
e
s
y
n
ch
r
o
n
ized
with
th
eir
co
r
r
esp
o
n
d
in
g
d
ig
ital
twi
n
s
.
E
ac
h
in
tellig
en
t
a
g
en
t
p
e
r
f
o
r
m
s
lo
ca
l
f
o
r
ec
asti
n
g
u
s
in
g
i
ts
o
wn
o
p
er
atio
n
al
d
ata,
wh
ile
o
n
ly
m
o
d
el
p
ar
a
m
eter
s
ar
e
ex
c
h
an
g
e
d
with
th
e
f
ed
er
ate
d
s
er
v
er
to
p
r
eser
v
e
d
ata
p
r
iv
ac
y
.
T
h
e
u
p
d
ated
g
lo
b
al
m
o
d
el
is
r
ed
is
tr
ib
u
ted
to
all
a
g
en
ts
f
o
r
co
o
r
d
i
n
ated
en
er
g
y
m
a
n
ag
em
en
t
.
2
.
1
.
Da
t
a
s
et
a
nd
da
t
a
pre
-
pro
ce
s
s
ing
T
h
e
f
r
a
m
ewo
r
k
was
ev
alu
ated
u
s
in
g
h
is
to
r
ical
r
en
ewa
b
le
g
e
n
er
atio
n
,
elec
tr
ical
lo
ad
d
em
a
n
d
,
b
atter
y
s
tate
-
of
-
ch
ar
g
e
(
SOC
)
,
an
d
we
ath
er
v
ar
ia
b
les
in
clu
d
in
g
s
o
lar
ir
r
ad
ian
ce
a
n
d
a
m
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ien
t
tem
p
e
r
atu
r
e.
T
h
e
d
ataset
was
d
iv
id
ed
in
to
t
r
ain
in
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7
0
%),
v
alid
atio
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(
1
5
%),
an
d
test
in
g
(
1
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%)
s
u
b
s
ets.
Miss
in
g
s
am
p
les
wer
e
r
em
o
v
ed
,
an
d
n
u
m
e
r
ical
f
ea
tu
r
es we
r
e
n
o
r
m
alize
d
u
s
in
g
m
in
-
m
ax
n
o
r
m
aliza
tio
n
,
n
o
r
m
=
−
m
in
m
ax
−
m
in
(
1
)
W
h
er
e
an
d
d
en
o
te
th
e
m
in
im
u
m
an
d
m
ax
im
u
m
v
alu
es o
f
e
ac
h
f
ea
tu
r
e.
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
Dig
ita
l tw
in
d
r
iven
fed
era
ted
mu
lti
-
a
g
en
t in
tellig
en
ce
f
o
r
a
u
to
n
o
mo
u
s
…
(
P
u
s
h
p
a
S
r
ee
n
iv
a
s
a
n
)
2031
Fig
u
r
e
1
.
Dig
ital twin
d
r
iv
en
f
ed
er
ated
m
u
lti a
g
en
t sm
ar
t g
r
i
d
f
r
am
ewo
r
k
2
.
2
.
M
a
t
hema
t
ica
l
f
o
rm
ula
t
i
o
n
T
h
e
s
m
ar
t g
r
id
d
y
n
am
ic
s
tate
is
r
ep
r
esen
ted
b
y
(
2
)
.
̇
(
)
=
(
)
+
(
)
+
(
)
(
2
)
W
h
er
e
(
)
d
en
o
tes
th
e
s
y
s
tem
s
tate
v
ec
to
r
,
(
)
is
th
e
co
n
tr
o
l
in
p
u
t,
an
d
(
)
r
ep
r
esen
ts
r
en
ew
ab
le
g
en
er
atio
n
u
n
ce
r
tain
ty
.
E
ac
h
p
h
y
s
ical
ass
et
is
a
s
s
o
ciate
d
with
a
d
ig
ital
twin
th
at
p
r
ed
i
cts
f
u
tu
r
e
o
p
er
atin
g
co
n
d
itio
n
s
ac
co
r
d
in
g
to
(
3
)
.
DT
(
)
=
(
)
−
̂
(
)
(
3
)
W
h
er
e
(
)
r
ep
r
esen
ts
th
e
p
h
y
s
ical
s
y
s
tem
s
tate
an
d
̂
(
)
d
en
o
tes
th
e
co
r
r
esp
o
n
d
in
g
d
ig
ital
twin
s
tate.
T
h
e
s
y
n
ch
r
o
n
izatio
n
er
r
o
r
is
co
n
tin
u
o
u
s
ly
m
in
im
ize
d
to
m
ain
ta
in
co
n
s
is
ten
cy
b
etwe
en
th
e
p
h
y
s
ical
an
d
v
ir
tu
al
s
y
s
tem
s
.
(
+
1
)
=
(
)
−
(
)
(
4
)
W
h
er
e
(
)
d
en
o
tes
th
e
lo
ca
l
f
o
r
ec
asti
n
g
m
o
d
el
p
a
r
am
eter
s
o
f
ag
en
t
at
co
m
m
u
n
icatio
n
r
o
u
n
d
,
is
th
e
lear
n
in
g
r
ate,
an
d
ℒ
is
th
e
lo
ca
l
lo
s
s
f
u
n
ctio
n
.
(
+
1
)
=
∑
∑
=
1
=
1
(
+
1
)
(
5
)
W
h
er
e
(
+
1
)
is
th
e
u
p
d
ate
d
g
lo
b
al
f
o
r
ec
asti
n
g
m
o
d
el,
is
th
e
n
u
m
b
er
o
f
lo
ca
l
tr
ain
i
n
g
s
am
p
le
s
at
ag
en
t
,
an
d
is
th
e
to
tal
n
u
m
b
er
o
f
p
ar
ticip
atin
g
ag
en
ts
.
2
.
3
.
P
re
dict
iv
e
s
m
a
rt
g
rid o
ptim
iza
t
io
n
T
h
e
f
o
r
ec
asti
n
g
o
u
tp
u
ts
ar
e
u
s
ed
to
d
eter
m
i
n
e
o
p
tim
al
s
ch
e
d
u
lin
g
o
f
r
en
ewa
b
le
r
eso
u
r
ce
s
,
b
atter
ies,
an
d
E
V
ch
a
r
g
in
g
.
T
h
e
o
p
tim
iz
atio
n
o
b
jectiv
e
is
f
o
r
m
u
lated
a
s
(
6
).
=
+
1
+
2
(
6
)
W
h
er
e
d
en
o
tes
th
e
o
p
er
atin
g
co
s
t,
is
th
e
n
etwo
r
k
p
o
wer
lo
s
s
,
an
d
r
ep
r
esen
ts
v
o
ltag
e
d
e
v
iatio
n
.
T
h
e
o
p
tim
izatio
n
is
s
u
b
ject
to
th
e
f
o
llo
win
g
c
o
n
s
tr
ain
ts
:
+
+
+
=
+
+
(
7
)
≤
≤
(
8
)
T
h
e
o
p
tim
ized
co
n
t
r
o
l
ac
tio
n
s
ar
e
d
is
tr
ib
u
ted
to
all
in
tellig
en
t
ag
en
ts
f
o
r
r
en
ewa
b
l
e
d
is
p
atch
,
b
atter
y
s
ch
ed
u
lin
g
,
d
em
an
d
r
esp
o
n
s
e,
an
d
v
o
lta
g
e
r
eg
u
latio
n
.
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.
17
,
No
.
3
,
Sep
tem
b
er
2
0
2
7
:
2029
-
2
0
3
8
2032
2
.
4
.
I
m
ple
m
ent
a
t
io
n
p
ro
ce
d
ure
T
h
e
im
p
lem
en
tatio
n
o
f
th
e
D
T
-
FMAI
f
r
am
ewo
r
k
c
o
n
s
is
ts
o
f
th
e
f
o
llo
win
g
s
tep
s
:
i)
Ac
q
u
ir
e
r
ea
l
-
tim
e
m
ea
s
u
r
em
en
ts
f
r
o
m
d
is
tr
ib
u
ted
s
m
ar
t
g
r
id
ass
ets
;
ii)
Sy
n
ch
r
o
n
ize
d
i
g
ital
twin
m
o
d
els
with
p
h
y
s
ical
o
p
er
atin
g
s
tates
;
iii)
Pre
p
r
o
ce
s
s
lo
ca
l
d
atase
ts
an
d
tr
ai
n
f
o
r
ec
asti
n
g
m
o
d
els
;
iv
)
Up
lo
ad
lo
ca
l
m
o
d
el
p
ar
am
eter
s
to
th
e
f
ed
er
ated
s
e
r
v
er
;
v
)
Ag
g
r
e
g
ate
lo
ca
l
m
o
d
els
u
s
in
g
th
e
Fed
Av
g
alg
o
r
ith
m
;
v
i)
R
ed
is
tr
ib
u
te
th
e
u
p
d
ated
g
lo
b
al
m
o
d
el
;
v
ii)
Fo
r
ec
ast
r
en
ewa
b
le
g
en
er
atio
n
an
d
elec
tr
ical
d
em
an
d
;
v
iii
)
Op
tim
ize
b
atter
y
s
ch
ed
u
lin
g
,
E
V
ch
a
r
g
in
g
,
an
d
p
o
we
r
d
is
p
atch
;
an
d
ix
)
E
x
ec
u
te
co
n
tr
o
l
ac
tio
n
s
an
d
c
o
n
tin
u
o
u
s
ly
u
p
d
ate
d
ig
ital twin
s
tates.
2
.
5
.
Sim
ula
t
i
o
n set
up
a
nd
p
er
f
o
rma
nce
ev
a
lua
t
io
n
T
h
e
p
r
o
p
o
s
ed
f
r
am
ewo
r
k
w
as
im
p
lem
en
ted
u
s
in
g
MA
T
L
AB
/Si
m
u
lin
k
R
2
0
2
4
a
in
teg
r
ated
with
Py
th
o
n
3
.
1
1
a
n
d
T
en
s
o
r
Flo
w
2
.
1
6
.
Fed
e
r
ated
lear
n
in
g
was
im
p
lem
en
ted
u
s
in
g
T
e
n
s
o
r
Flo
w
Fed
er
ated
.
Simu
latio
n
s
wer
e
co
n
d
u
cte
d
o
n
an
I
n
tel
C
o
r
e
i7
wo
r
k
s
tatio
n
with
3
2
GB
R
AM
u
n
d
er
W
in
d
o
ws
1
1
.
T
h
e
p
r
in
cip
al
s
im
u
latio
n
p
ar
am
eter
s
ar
e
s
u
m
m
ar
ized
in
T
a
b
le
1.
T
h
e
p
r
o
p
o
s
ed
DT
-
FMAI
f
r
am
ewo
r
k
was c
o
m
p
ar
e
d
with
ce
n
tr
alize
d
m
ac
h
in
e
lear
n
in
g
,
Dig
ital T
win
-
b
ased
f
o
r
ec
asti
n
g
,
an
d
f
ed
er
at
ed
lear
n
in
g
-
b
ased
f
o
r
ec
asti
n
g
u
n
d
er
id
e
n
tical
o
p
er
atin
g
co
n
d
itio
n
s
.
Fo
r
ec
asti
n
g
ac
cu
r
ac
y
was e
v
alu
ated
u
s
in
g
m
ea
n
ab
s
o
lu
te
er
r
o
r
(
MA
E
)
an
d
r
o
o
t
m
ea
n
s
q
u
a
r
e
er
r
o
r
(
R
M
SE)
:
≤
≤
(
9
)
=
1
∑
|
−
̂
|
=
1
(
1
0
)
Ad
d
itio
n
al
p
er
f
o
r
m
a
n
ce
in
d
icato
r
s
in
clu
d
ed
v
o
ltag
e
d
ev
iati
o
n
,
co
m
m
u
n
icatio
n
o
v
er
h
ea
d
,
en
er
g
y
ef
f
icien
c
y
,
o
p
er
atin
g
co
s
t,
an
d
p
ea
k
lo
a
d
r
ed
u
ctio
n
t
o
co
m
p
r
e
h
en
s
iv
ely
ev
alu
ate
f
o
r
ec
asti
n
g
p
er
f
o
r
m
an
ce
an
d
g
r
id
o
p
er
atio
n
.
T
ab
le
1
.
Simu
latio
n
p
ar
am
eter
s
P
a
r
a
me
t
e
r
V
a
l
u
e
P
a
r
a
me
t
e
r
V
a
l
u
e
Le
a
r
n
i
n
g
r
a
t
e
0
.
0
0
1
O
p
t
i
mi
z
e
r
A
d
a
m
B
a
t
c
h
si
z
e
64
N
u
mb
e
r
o
f
a
g
e
n
t
s
10
Tr
a
i
n
i
n
g
e
p
o
c
h
s
1
0
0
S
a
mp
l
i
n
g
i
n
t
e
r
v
a
l
5
m
i
n
C
o
mm
u
n
i
c
a
t
i
o
n
r
o
u
n
d
s
50
S
i
mu
l
a
t
i
o
n
d
u
r
a
t
i
o
n
2
4
h
Lo
c
a
l
e
p
o
c
h
s
5
A
g
g
r
e
g
a
t
i
o
n
m
e
t
h
o
d
F
e
d
A
v
g
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
Fig
u
r
e
2
co
m
p
ar
es
th
e
f
o
r
e
ca
s
tin
g
p
er
f
o
r
m
a
n
ce
o
f
th
e
p
r
o
p
o
s
ed
DT
-
FMAI
f
r
am
e
wo
r
k
with
ce
n
tr
alize
d
m
ac
h
in
e
lear
n
in
g
,
d
ig
ital
t
win
-
o
n
ly
,
an
d
f
ed
er
ated
lear
n
in
g
-
b
ased
m
eth
o
d
s
.
T
h
e
p
r
o
p
o
s
ed
f
r
am
ewo
r
k
ac
h
iev
ed
th
e
lo
w
est
f
o
r
ec
asti
n
g
er
r
o
r
,
r
ed
u
cin
g
R
MSE
b
y
1
5
–
2
5
%
th
r
o
u
g
h
co
n
tin
u
o
u
s
d
ig
ital
twin
s
y
n
ch
r
o
n
izatio
n
,
co
lla
b
o
r
ativ
e
f
ed
er
ated
m
o
d
el
u
p
d
atin
g
,
an
d
d
ec
en
tr
alize
d
ag
en
t
lea
r
n
in
g
.
T
h
ese
r
esu
lts
d
em
o
n
s
tr
ate
th
at
i
n
teg
r
atin
g
p
r
ed
ictiv
e
v
i
r
tu
al
m
o
d
ellin
g
with
p
r
iv
ac
y
-
p
r
eser
v
in
g
d
is
tr
ib
u
ted
in
tellig
en
ce
im
p
r
o
v
es f
o
r
ec
asti
n
g
r
eliab
ilit
y
u
n
d
e
r
v
ar
y
in
g
r
en
ewa
b
le
g
e
n
er
atio
n
an
d
lo
ad
co
n
d
itio
n
s
.
Fig
u
r
e
3
illu
s
tr
ates
th
e
v
o
lta
g
e
r
eg
u
latio
n
p
er
f
o
r
m
a
n
ce
u
n
d
er
d
y
n
am
ic
o
p
er
atin
g
co
n
d
itio
n
s
.
T
h
e
p
r
o
p
o
s
ed
f
r
am
ew
o
r
k
r
ed
u
ce
d
v
o
ltag
e
d
ev
iatio
n
b
y
1
0
–
1
8
%
co
m
p
ar
ed
with
co
n
v
en
tio
n
al
ap
p
r
o
ac
h
es.
T
h
is
im
p
r
o
v
em
e
n
t
is
m
ain
ly
attr
ib
u
ted
to
th
e
p
r
ed
ictiv
e
ca
p
a
b
i
lity
o
f
th
e
d
ig
ital
twin
,
wh
ic
h
esti
m
ates
f
u
tu
r
e
o
p
er
atin
g
co
n
d
itio
n
s
b
ef
o
r
e
s
ig
n
if
ican
t
v
o
ltag
e
f
l
u
ctu
atio
n
s
o
cc
u
r
.
B
ased
o
n
th
ese
p
r
ed
icti
o
n
s
,
th
e
in
tellig
en
t
ag
en
ts
p
er
f
o
r
m
c
o
o
r
d
in
ated
c
o
r
r
ec
tiv
e
ac
tio
n
s
th
r
o
u
g
h
b
att
er
y
s
ch
ed
u
lin
g
a
n
d
r
en
ewa
b
le
p
o
wer
r
eg
u
latio
n
.
T
h
e
d
is
tr
ib
u
ted
co
n
tr
o
l
s
tr
ateg
y
th
er
ef
o
r
e
m
ain
tain
s
ac
ce
p
ta
b
le
v
o
ltag
e
p
r
o
f
iles
ev
en
d
u
r
i
n
g
r
ap
id
r
en
ewa
b
le
g
en
er
atio
n
c
h
an
g
es a
n
d
p
ea
k
d
em
an
d
p
e
r
io
d
s
.
3
.
1
.
L
o
a
d
m
a
t
ching
ef
f
iciency
T
h
e
p
r
o
p
o
s
ed
DT
-
FMAI
f
r
am
ewo
r
k
ac
h
iev
ed
a
lo
a
d
-
m
atch
i
n
g
ef
f
icien
cy
o
f
9
2
–
9
6
%,
d
em
o
n
s
tr
atin
g
ef
f
ec
tiv
e
co
o
r
d
in
atio
n
am
o
n
g
r
en
ewa
b
le
g
en
er
atio
n
,
b
atter
y
s
to
r
ag
e,
an
d
co
n
s
u
m
er
d
e
m
an
d
.
As
s
h
o
wn
in
Fig
u
r
e
4
,
p
r
e
d
ictiv
e
s
ch
ed
u
lin
g
r
ed
u
ce
d
g
en
er
atio
n
–
lo
ad
m
is
m
atch
an
d
in
cr
ea
s
ed
o
v
e
r
all
en
er
g
y
ef
f
icien
cy
b
y
12
–
2
0
%
co
m
p
ar
ed
with
co
n
v
en
tio
n
al
m
eth
o
d
s
.
T
h
ese
im
p
r
o
v
em
en
ts
r
esu
lted
f
r
o
m
c
o
o
r
d
in
ated
m
u
lti
-
a
g
en
t
co
n
tr
o
l su
p
p
o
r
ted
b
y
d
ig
ital twin
f
o
r
ec
asti
n
g
an
d
f
e
d
er
ated
lear
n
in
g
.
3
.
2
.
O
pera
t
ing
co
s
t
a
nd
co
mm
un
ica
t
io
n per
f
o
rm
a
nce
T
h
e
p
r
o
p
o
s
ed
DT
-
FMAI
f
r
a
m
ewo
r
k
r
ed
u
ce
d
o
p
er
atin
g
c
o
s
t
b
y
o
p
tim
ally
s
ch
e
d
u
lin
g
r
en
ewa
b
le
r
eso
u
r
ce
s
,
b
atter
y
s
to
r
a
g
e,
a
n
d
E
V
c
h
ar
g
i
n
g
b
ased
o
n
f
o
r
e
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I
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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.
17
,
No
.
3
,
Sep
tem
b
er
2
0
2
7
:
2029
-
2
0
3
8
2036
T
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RE
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[
1
]
A
.
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m
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:
r
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m
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@g
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c
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
:
2
0
8
8
-
8
6
9
4
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
,
Vo
l.
17
,
No
.
3
,
Sep
tem
b
er
2
0
2
7
:
2029
-
2
0
3
8
2038
Ra
d
h
e
y
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h
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Mee
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c
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in
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