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o
urna
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Science
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25
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J
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ttp
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ee
cs.ia
esco
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e.
co
m
Renewab
le
energ
y
ba
sed
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mic
tariff
sy
ste
m
for
do
mes
tic
lo
a
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ma
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ement
K
uh
eli
G
o
s
wa
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i
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Arinda
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ticle
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y:
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ev
is
ed
No
v
25
,
2
0
2
1
Acc
ep
ted
Dec
8
,
2
0
2
1
To
d
e
a
l
with
t
h
e
p
re
se
n
t
p
o
we
r
-
s
c
e
n
a
rio
,
th
is
p
a
p
e
r
p
ro
p
o
se
s
a
m
o
d
e
l
of
an
a
d
v
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n
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e
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e
n
e
r
g
y
m
a
n
a
g
e
m
e
n
t
sy
ste
m
,
wh
ich
tri
e
s
to
a
c
h
iev
e
p
e
a
k
c
li
p
p
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g
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p
e
a
k
to
a
v
e
ra
g
e
ra
ti
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re
d
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c
ti
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n
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d
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c
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o
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b
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se
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on
e
ffe
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e
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ti
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z
a
ti
o
n
of
d
istri
b
u
ted
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e
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e
ra
t
io
n
s
.
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is
h
e
lp
s
to
m
a
n
a
g
e
c
o
n
v
e
n
ti
o
n
a
l
lo
a
d
s
b
a
se
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on
f
lex
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tariff
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tem
.
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e
m
a
in
c
o
n
tri
b
u
ti
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of
t
h
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wo
rk
is
th
e
d
e
v
e
lo
p
m
e
n
t
of
th
re
e
-
p
a
rt
d
y
n
a
m
ic
tariff
sy
ste
m
on
t
h
e
b
a
sis
of
t
ime
of
u
ti
li
z
i
n
g
p
o
we
r,
a
v
a
il
a
b
le
re
n
e
wa
b
le
e
n
e
rg
y
so
u
rc
e
s
(RE
S
)
a
n
d
c
o
n
su
m
e
rs’
lo
a
d
p
ro
fil
e
.
Th
is
in
c
o
r
p
o
ra
tes
c
o
n
su
m
e
rs’
c
h
o
ice
to
s
u
it
a
b
l
y
se
lec
t
fo
r
e
it
h
e
r
c
o
n
su
m
in
g
p
o
we
r
fro
m
c
o
n
v
e
n
ti
o
n
a
l
e
n
e
rg
y
so
u
rc
e
s
a
n
d
/o
r
re
n
e
wa
b
le
e
n
e
rg
y
so
u
rc
e
s
d
u
ri
n
g
p
e
a
k
or
o
f
f
-
p
e
a
k
h
o
u
rs.
To
v
a
li
d
a
te
t
h
e
e
fficie
n
c
y
of
th
e
p
ro
p
o
se
d
m
o
d
e
l
we
h
a
v
e
c
o
m
p
a
ra
ti
v
e
ly
e
v
a
lu
a
ted
th
e
m
o
d
e
l
p
e
rfo
rm
a
n
c
e
with
e
x
isti
n
g
o
p
t
imiz
a
ti
o
n
tec
h
n
iq
u
e
s
u
sin
g
g
e
n
e
ti
c
a
lg
o
rit
h
m
a
n
d
p
a
rti
c
le
sw
a
rm
o
p
ti
m
iza
ti
o
n
.
A
n
e
w
o
p
t
imiz
a
ti
o
n
tec
h
n
iq
u
e
,
h
y
b
ri
d
g
re
e
d
y
p
a
rti
c
le
sw
a
rm
o
p
ti
m
iza
ti
o
n
h
a
s
b
e
e
n
p
ro
p
o
se
d
wh
ich
is
b
a
se
d
on
th
e
two
a
fo
re
m
e
n
ti
o
n
e
d
tec
h
n
i
q
u
e
s.
It
is
f
o
u
n
d
th
a
t
th
e
p
ro
p
o
se
d
m
o
d
e
l
is
su
p
e
rio
r
wit
h
th
e
imp
r
o
v
e
d
tariff
sc
h
e
m
e
wh
e
n
su
b
jec
ted
to
lo
a
d
m
a
n
a
g
e
m
e
n
t
a
n
d
c
o
n
s
u
m
e
rs’
fin
a
n
c
ial
b
e
n
e
fit
.
Th
is
wo
r
k
lea
d
s
to
m
a
in
tain
a
h
e
a
lt
h
y
re
latio
n
sh
i
p
b
e
twe
e
n
th
e
u
ti
l
it
y
se
c
to
rs
a
n
d
t
h
e
c
o
n
s
u
m
e
rs,
th
e
re
b
y
m
a
k
in
g
t
h
e
e
x
isti
n
g
g
ri
d
m
o
re
re
li
a
b
le,
ro
b
u
st,
flex
i
b
le
y
e
t
c
o
st
e
ffe
c
ti
v
e
.
K
ey
w
o
r
d
s
:
AE
MS
AR
I
MA
X
E
n
er
g
y
m
an
ag
e
m
en
t
G
en
etic
a
lg
o
r
ith
m
HGPSO
Par
ticle
s
war
m
o
p
tim
izatio
n
T
h
r
ee
-
p
a
r
t
t
ar
if
f
T
h
is
is
an
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r
th
e
CC
BY
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Ku
h
eli
Go
s
wam
i
Dep
ar
tm
en
t o
f
E
lectr
ical
E
n
g
i
n
ee
r
in
g
,
Ma
u
lan
a
Ab
u
l K
alam
Aza
d
Un
iv
er
s
ity
o
f
T
ec
h
n
o
lo
g
y
Ko
lk
ata,
I
n
d
ia
E
m
ail:
k
g
g
2
0
1
7
ju
r
esear
ch
@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
A
s
m
ar
t
an
d
in
tellig
en
t
en
er
g
y
m
an
a
g
em
en
t
s
y
s
tem
is
r
eq
u
ir
ed
to
ad
d
r
ess
th
e
d
if
f
er
e
n
c
e
b
etwe
en
g
en
er
atio
n
an
d
d
em
an
d
.
T
h
er
e
is
a
lar
g
e
v
o
lu
m
e
of
p
u
b
lis
h
ed
s
tu
d
ies
d
escr
ib
in
g
th
e
r
o
le
of
d
em
an
d
s
id
e
m
an
ag
em
en
t
(
DSM)
in
p
o
we
r
s
y
s
tem
p
lan
n
i
n
g
.
O
v
er
th
e
p
ast
d
ec
ad
e,
m
o
s
t
r
esear
ch
in
th
is
is
s
u
e
h
av
e
em
p
h
asized
th
e
u
s
e
of
r
en
ewa
b
le
en
er
g
y
s
o
u
r
ce
s
(
R
E
S)
an
d
in
clin
e
b
lo
ck
tar
if
f
.
T
h
ese
can
be
o
b
s
er
v
ed
in
th
e
DSM
ap
p
r
o
ac
h
es
p
r
o
p
o
s
ed
by
s
o
m
e
a
u
th
o
r
s
[1
]
-
[
3
]
.
A
p
p
licatio
n
of
lo
ad
m
an
ag
e
m
en
t
as
an
ef
f
ec
tiv
e
tech
n
iq
u
e
f
o
r
h
an
d
lin
g
th
e
p
e
ak
lo
ad
m
an
ag
em
e
n
t
is
s
u
es
can
be
o
b
s
er
v
ed
in
th
e
wo
r
k
of
L
o
g
e
n
th
ir
an
an
d
Srin
iv
asan
[
4
]
.
Ho
wev
er
,
f
o
r
ap
p
ly
in
g
th
is
s
o
lu
tio
n
in
th
e
p
r
ac
tical
wo
r
k
,
p
ea
k
lo
ad
m
a
n
ag
em
en
t
ca
n
n
o
t
be
th
e
s
o
le
cr
iter
ia.
I
n
co
r
p
o
r
atio
n
of
s
ev
er
al
o
th
er
f
ac
to
r
s
s
u
ch
as
co
n
s
u
m
er
s
s
ati
s
f
ac
tio
n
lev
el
an
d
co
s
t
of
en
er
g
y
ar
e
also
r
eq
u
ir
e
d
f
o
r
d
ev
elo
p
in
g
an
ef
f
icien
t
e
n
er
g
y
m
an
a
g
e
m
en
t
s
y
s
tem
(
E
MS)
wh
ich
h
as
b
ee
n
d
em
o
n
s
tr
ated
by
th
e
wo
r
k
of
Xu
et
al
.
[
5
]
.
In
r
ec
en
t
d
ay
s
R
E
S
h
as
g
ai
n
ed
im
p
o
r
ta
n
ce
in
e
n
er
g
y
m
an
ag
em
en
t
s
y
s
tem
.
au
th
o
r
s
in
[6
]
,
[
7
]
,
c
o
n
clu
s
iv
el
y
ag
r
ee
d
to
th
is
an
d
e
x
p
lain
ed
how
by
d
is
p
atch
in
g
t
h
e
s
h
if
tab
le
d
o
m
esti
c
lo
ad
s
an
d
av
ailab
le
s
to
r
ag
e
r
eso
u
r
ce
s
e
n
er
g
y
m
an
ag
em
e
n
t
s
o
lu
tio
n
can
be
ac
h
iev
ed
.
In
a
d
d
itio
n
to
th
e
wid
ely
u
s
ed
R
E
S,
b
io
m
ass
can
be
u
s
ed
f
o
r
s
elf
-
g
en
er
atio
n
in
r
u
r
al
ar
ea
s
h
as
b
ee
n
p
r
o
p
o
s
ed
by
Naz
et
al
.
[
8
].
Desp
ite
th
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:
2502
-
4
7
5
2
R
en
ewa
b
le
en
erg
y
b
a
s
ed
d
yn
a
mic
ta
r
iff s
y
s
tem
fo
r
d
o
mestic
lo
a
d
ma
n
a
g
eme
n
t
(
K
u
h
eli
Go
s
w
a
mi)
627
s
im
p
licity
of
th
ese
m
o
d
els,
I
s
s
i
an
d
Kap
lan
in
[
9]
an
d
A
h
m
ad
et
al
.
in
[
1
0
]
f
o
u
n
d
th
at
it
is
n
ec
es
s
ar
y
to
d
eter
m
in
e
th
e
lo
ad
p
r
o
f
iles
an
d
p
o
wer
co
n
s
u
m
p
tio
n
s
of
h
o
m
e
ap
p
lian
ce
s
in
d
iv
id
u
ally
f
o
r
s
ch
ed
u
lin
g
th
e
lo
a
d
ju
d
icio
u
s
ly
,
wh
ic
h
in
t
u
r
n
h
elp
s
to
f
o
r
m
u
late
a
r
esid
en
ti
al
en
er
g
y
m
an
a
g
em
en
t
p
r
o
b
l
em
u
n
d
er
v
ar
io
u
s
p
r
ac
tical
co
n
s
tr
ain
ts
lik
e
h
u
m
an
in
ter
ac
tio
n
,
u
n
av
ailab
le
p
o
wer
s
u
p
p
ly
an
d
co
n
s
u
m
e
r
p
r
e
f
er
en
ce
.
In
co
n
tr
ast,
M
a
li
k
et
al
.
in
[1
1]
an
d
Ng
u
y
en
et
al
.
in
[
1
2
]
in
d
icate
d
th
at
b
esid
e
R
E
S
in
teg
r
atio
n
an
d
lo
ad
s
ch
ed
u
lin
g
,
ef
f
icien
t
co
m
m
u
n
icatio
n
an
d
o
p
tim
izatio
n
s
ch
em
e
is
u
tm
o
s
t
im
p
o
r
ta
n
t.
Similar
ly
,
a
u
th
o
r
s
in
[1
3
]
-
[
1
5
]
d
is
cu
s
s
ed
s
ev
er
al
m
eth
o
d
o
lo
g
ies
an
d
f
u
tu
r
e
tech
n
iq
u
es
to
o
p
tim
ize
en
er
g
y
co
n
s
u
m
p
t
io
n
with
m
in
im
u
m
co
n
s
u
m
er
i
n
ter
ac
tio
n
.
A
n
o
th
e
r
p
o
s
s
ib
ilit
y
wo
u
ld
be
tr
a
d
in
g
of
s
elf
-
g
en
er
atio
n
am
o
n
g
t
h
e
p
r
o
s
u
m
er
s
an
d
co
n
s
u
m
er
s
wh
ich
ca
n
h
elp
to
in
cr
ea
s
e
g
r
id
s
tab
ilit
y
[
16
].
Si
m
ilar
ly
,
a
co
n
t
r
ac
t
-
b
ased
en
e
r
g
y
tr
ad
in
g
s
ch
em
e
h
as
b
ee
n
p
r
o
p
o
s
ed
by
Z
h
an
g
et
al
.
[1
7
]
a
n
d
th
e
e
co
n
o
m
ic
i
m
p
ac
t
of
d
em
an
d
r
esp
o
n
s
e
h
a
s
b
ee
n
d
is
cu
s
s
ed
by
C
o
n
ch
ad
o
an
d
L
in
ar
es
[
18
].
Sev
er
al
DSM
ap
p
r
o
ac
h
es
b
as
ed
on
r
ea
l
tim
e
p
r
icin
g
h
as
b
ee
n
p
r
o
p
o
s
ed
by
th
e
au
th
o
r
s
in
th
eir
r
esear
ch
ar
ticl
es
[1
9
]
,
[
20
].
Ho
wev
er
,
a
n
u
m
b
er
of
s
tu
d
ies
[
21
]
s
h
o
w
th
at
th
er
e
ar
e
n
u
m
er
o
u
s
ch
allen
g
es
an
d
r
estrictio
n
s
in
im
p
lem
en
tatio
n
s
of
DSM.
E
v
en
Go
v
t.
of
I
n
d
ia
h
as
tak
en
v
ar
io
u
s
ac
tio
n
s
to
im
p
lem
en
t
DSM
s
tr
ateg
ies
[
22
].
Desp
ite
th
e
n
u
m
er
o
u
s
wo
r
k
s
ca
r
r
ied
out
,
m
en
tio
n
e
d
in
T
ab
le
1
,
no
p
r
ev
i
o
u
s
s
tu
d
y
h
as
th
o
r
o
u
g
h
ly
in
v
esti
g
ated
an
d
a
n
aly
s
ed
th
e
c
o
n
s
u
m
er
s
p
r
ef
er
e
n
ce
on
th
e
b
asis
of
R
E
S
av
ailab
ilit
y
an
d
lo
ad
p
r
o
f
ile.
On
th
e
o
th
er
h
an
d
,
a
s
ea
r
ch
of
th
e
liter
atu
r
e
r
ev
ea
led
t
h
at
lim
ited
s
tu
d
ie
s
h
av
e
f
o
c
u
s
ed
on
lo
ad
an
aly
s
is
an
d
tar
if
f
s
y
s
te
m
.
Sin
ce
th
e
im
p
ac
t
of
tar
if
f
on
EMS
is
u
n
d
er
s
tu
d
ied
,
t
h
er
e
is
a
n
ee
d
to
d
ev
elo
p
an
im
p
r
o
v
ed
tar
if
f
s
y
s
tem
b
ased
on
tim
e
of
u
tili
zin
g
p
o
wer
,
av
ailab
le
R
E
S
an
d
co
n
s
u
m
e
r
s
’
lo
ad
p
r
o
f
ile.
T
ab
le
1
.
Su
m
m
a
r
ized
r
elate
d
wo
r
k
Te
c
h
n
i
q
u
e
s
A
i
ms
A
t
t
r
i
b
u
t
e
s
Li
mi
t
a
t
i
o
n
s
EA
[
4
]
C
o
s
t
r
e
d
u
c
t
i
o
n
En
e
r
g
y
o
p
t
i
m
i
z
a
t
i
o
n
in
i
n
d
u
s
t
r
i
a
l
,
c
o
mm
e
r
c
i
a
l
a
n
d
r
e
si
d
e
n
t
i
a
l
s
e
c
t
o
r
s
C
o
m
p
l
e
x
s
y
st
e
m
GA
[
2
3
]
C
o
s
t
r
e
d
u
c
t
i
o
n
O
p
t
i
mi
z
a
t
i
o
n
of
e
n
e
r
g
y
c
o
n
su
mp
t
i
o
n
C
o
m
p
l
e
x
s
y
st
e
m
a
n
d
C
o
n
s
u
mers
’
p
r
e
f
e
r
e
n
c
e
is
i
g
n
o
r
e
d
FP
[
2
4
]
C
o
s
t
r
e
d
u
c
t
i
o
n
C
o
s
t
e
f
f
e
c
t
i
v
e
m
o
d
e
l
w
i
t
h
DG
P
A
R
a
n
d
C
o
n
su
m
e
r
s’
p
r
e
f
e
r
e
n
c
e
n
o
t
c
o
n
si
d
e
r
e
d
GA
[
2
5
]
C
o
s
t
a
n
d
P
A
R
r
e
d
u
c
t
i
o
n
G
e
n
e
r
i
c
m
o
d
e
l
C
o
n
s
u
mers
’
p
r
e
f
e
r
e
n
c
e
is
i
g
n
o
r
e
d
B
P
S
O
[
2
6
]
C
o
s
t
a
n
d
P
A
R
r
e
d
u
c
t
i
o
n
c
o
n
si
d
e
r
i
n
g
c
o
n
s
u
mers
’
p
r
e
f
e
r
e
n
c
e
Ef
f
i
c
i
e
n
c
y
of
B
P
S
O
Ti
me
sl
o
t
s
a
r
e
d
i
v
i
d
e
d
i
n
t
o
su
b
t
i
m
e
sl
o
t
s,
w
h
i
c
h
is
c
o
mp
l
e
x
H
y
b
r
i
d
Te
c
h
n
i
q
u
e
(
LP
a
n
d
B
P
S
O
)
[
2
7
]
C
o
s
t
r
e
d
u
c
t
i
o
n
c
o
n
s
i
d
e
r
i
n
g
c
o
n
su
mers
’
p
r
e
f
e
r
e
n
c
e
DAP
mo
d
e
l
P
A
R
r
e
d
u
c
t
i
o
n
n
o
t
a
c
h
i
e
v
e
d
GA,
B
P
S
O
,
A
C
O
[
2
8
]
C
o
s
t
a
n
d
P
A
R
r
e
d
u
c
t
i
o
n
c
o
n
si
d
e
r
i
n
g
c
o
n
s
u
mers
’
p
r
e
f
e
r
e
n
c
e
Lo
a
d
s
c
h
e
d
u
l
i
n
g
by
c
o
n
s
i
d
e
r
i
n
g
c
o
n
su
mers
’
p
r
e
f
e
r
e
n
c
e
a
n
d
R
ES
C
o
m
p
l
e
x
s
y
st
e
m
a
n
d
b
e
t
t
e
r
man
a
g
e
me
n
t
a
r
e
p
o
ss
i
b
l
e
GA
[
2
9
]
C
o
s
t
a
n
d
P
A
R
r
e
d
u
c
t
i
o
n
M
o
d
e
l
t
e
s
t
e
d
u
si
n
g
r
a
d
i
a
l
r
e
si
d
e
n
t
i
a
l
n
e
t
w
o
r
k
C
o
m
p
l
e
x
s
y
st
e
m
a
n
d
b
e
t
t
e
r
man
a
g
e
me
n
t
a
r
e
p
o
ss
i
b
l
e
GA
[
3
0
]
C
o
s
t
r
e
d
u
c
t
i
o
n
c
o
n
s
i
d
e
r
i
n
g
c
o
n
su
mers
’
p
r
e
f
e
r
e
n
c
e
O
p
t
i
mi
z
a
t
i
o
n
of
e
n
e
r
g
y
c
o
n
su
mp
t
i
o
n
on
t
h
e
b
a
si
s
of
R
ES
a
v
a
i
l
a
b
i
l
i
t
y
P
A
R
r
e
d
u
c
t
i
o
n
n
o
t
a
c
h
i
e
v
e
d
DP
[
3
1
]
C
o
s
t
a
n
d
P
A
R
r
e
d
u
c
t
i
o
n
O
p
t
i
mi
z
a
t
i
o
n
of
e
n
e
r
g
y
c
o
n
su
mp
t
i
o
n
on
t
h
e
b
a
si
s
of
R
ES
a
v
a
i
l
a
b
i
l
i
t
y
C
o
m
p
l
e
x
s
y
st
e
m
a
n
d
C
o
n
s
u
mers
’
p
r
e
f
e
r
e
n
c
e
is
i
g
n
o
r
e
d
I
LP
[
3
2
]
C
o
s
t
a
n
d
P
A
R
r
e
d
u
c
t
i
o
n
Lo
a
d
a
n
a
l
y
si
s
u
si
n
g
D
a
y
A
h
e
a
d
P
r
i
c
i
n
g
(DAP)
P
A
R
r
e
d
u
c
t
i
o
n
n
o
t
a
c
h
i
e
v
e
d
H
y
b
r
i
d
Te
c
h
n
i
q
u
e
(GA
a
n
d
P
S
O
)
[
3
3
]
C
o
s
t
a
n
d
P
A
R
r
e
d
u
c
t
i
o
n
C
o
n
si
d
e
r
e
d
E
n
e
r
g
y
S
t
o
r
a
g
e
S
y
st
e
m
C
o
n
s
u
mers
’
p
r
e
f
e
r
e
n
c
e
is
i
g
n
o
r
e
d
G
H
S
A
[
1
4
]
C
o
s
t
a
n
d
P
A
R
r
e
d
u
c
t
i
o
n
c
o
n
si
d
e
r
i
n
g
c
o
n
s
u
mers
’
p
r
e
f
e
r
e
n
c
e
A
n
a
l
y
s
i
s
on
t
h
e
b
a
si
s
of
S
i
n
g
l
e
a
n
d
M
u
l
t
i
p
l
e
H
o
m
e
s
S
y
st
e
m
is
c
o
m
p
l
e
x
a
n
d
t
i
me
c
o
n
su
mi
n
g
PSO
[
3
4
]
C
o
s
t
a
n
d
P
A
R
r
e
d
u
c
t
i
o
n
Ef
f
i
c
i
e
n
t
u
se
of
R
ES
C
o
n
s
u
mers
’
p
r
e
f
e
r
e
n
c
e
is
i
g
n
o
r
e
d
In
v
iew
of
th
ese
s
h
o
r
tco
m
in
g
s
,
an
a
d
v
an
ce
d
en
er
g
y
m
an
ag
e
m
en
t
s
y
s
tem
(
AE
MS)
h
as
b
ee
n
p
r
o
p
o
s
e
d
in
th
is
p
ap
er
.
T
h
e
c
u
r
r
en
t
s
tu
d
y
co
n
tr
ib
u
tes
to
th
e
ex
p
an
s
io
n
of
th
e
k
n
o
wled
g
e
in
th
is
f
ield
by
ad
d
r
ess
in
g
f
o
u
r
im
p
o
r
tan
t
is
s
u
es.
First,
elec
tr
icity
co
s
t
h
as
b
ee
n
r
ed
u
ce
d
by
in
tr
o
d
u
cin
g
ad
v
a
n
ce
d
th
r
ee
-
p
ar
t
d
y
n
am
ic
tar
if
f
s
tr
u
ctu
r
e.
Seco
n
d
,
g
r
id
s
tab
ilit
y
h
as
b
ee
n
m
ai
n
tain
ed
by
m
in
im
izin
g
p
ea
k
to
a
v
er
ag
e
r
atio
(
PAR
)
.
T
h
ir
d
,
p
ea
k
d
em
an
d
h
as
b
ee
n
ad
d
r
ess
ed
by
lo
ad
s
h
if
tin
g
an
d
v
alley
f
illi
n
g
.
Fo
u
r
th
,
co
n
s
u
m
er
c
o
m
f
o
r
t
s
an
d
b
en
ef
its
h
av
e
b
ee
n
m
ax
im
ized
by
in
teg
r
ati
n
g
R
E
S
an
d
d
esig
n
in
g
a
u
s
e
r
-
f
r
ien
d
ly
ap
p
licatio
n
.
T
h
er
eb
y
an
ef
f
ec
tiv
e
lo
a
d
m
an
ag
em
en
t
s
y
s
tem
b
ased
on
lo
ad
s
ch
ed
u
lin
g
h
as
b
ee
n
p
r
o
p
o
s
ed
wh
ich
in
tu
r
n
en
c
o
u
r
a
g
es
r
en
ewa
b
le
en
er
g
y
u
s
ag
e
r
ed
u
ci
n
g
th
e
ad
v
er
s
e
e
f
f
ec
ts
of
ca
r
b
o
n
e
m
is
s
io
n
an
d
en
s
u
r
es
p
r
o
p
er
u
tili
za
tio
n
of
elec
tr
ical
p
o
wer
in
co
r
p
o
r
atin
g
an
ad
v
a
n
ce
d
tar
i
f
f
s
tr
u
ctu
r
e.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
25
,
No
.
2
,
Feb
r
u
a
r
y
20
22
:
6
2
6
-
6
3
8
628
2.
P
RO
B
L
E
M
F
O
R
M
U
L
AT
I
O
N
I
d
en
tify
in
g
th
e
g
a
p
s
in
th
e
af
o
r
em
en
tio
n
e
d
liter
atu
r
e
wo
r
k
,
we
p
r
o
p
o
s
ed
a
n
o
v
el
AE
MS
w
ith
RE
S
in
teg
r
atio
n
to
r
ed
u
ce
PAR
an
d
elec
tr
icity
co
s
t
at
u
s
er
en
d
,
w
h
ich
is
b
ased
on
cr
itical
lo
ad
a
n
aly
s
is
,
co
n
s
u
m
er
s
co
m
f
o
r
t
lev
el
an
d
p
r
o
p
o
s
ed
d
y
n
am
ic
tar
if
f
s
tr
u
ctu
r
e.
S
ec
o
n
d
ly
,
w
e
ev
alu
ated
th
e
p
r
o
p
o
s
ed
AE
MS
by
p
er
f
o
r
m
in
g
ex
ten
s
iv
e
ca
s
e
s
tu
d
ies
an
d
s
im
u
latio
n
s
.
First,
we
ap
p
lied
m
u
lti
-
o
b
jectiv
e
o
p
ti
m
izatio
n
tech
n
i
q
u
es
b
ased
on
g
e
n
etic
a
lg
o
r
ith
m
(
GA)
an
d
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
PS
O)
to
r
ea
ch
th
e
o
p
tim
u
m
e
n
er
g
y
m
an
ag
em
en
t
s
o
lu
tio
n
.
Fu
r
th
er
we
an
aly
s
ed
our
AE
MS
with
th
e
ef
f
ec
ts
of
p
r
o
p
o
s
ed
th
r
ee
-
p
ar
t
d
y
n
am
ic
tar
if
f
s
tr
u
ctu
r
e.
In
ad
d
itio
n
,
b
ased
on
a
h
y
b
r
id
c
o
m
b
in
atio
n
of
g
en
etic
a
lg
o
r
ith
m
an
d
p
ar
ticle
s
w
ar
m
o
p
tim
izatio
n
a
n
ew
o
p
tim
izatio
n
tech
n
iq
u
e
h
as
b
ee
n
p
r
o
p
o
s
ed
an
d
f
o
u
n
d
to
p
er
f
o
r
m
b
etter
th
an
th
e
ex
is
tin
g
o
p
tim
izatio
n
tech
n
iq
u
es.
B
ased
on
th
e
se
af
o
r
em
en
tio
n
e
d
s
tep
s
,
an
AE
MS
h
as
b
ee
n
d
esig
n
ed
,
d
ev
elo
p
e
d
an
d
test
ed
.
3.
AE
M
S
ARCH
I
T
E
CT
URE
Fo
r
ef
f
icien
t
e
n
er
g
y
m
a
n
ag
em
en
t
with
th
e
e
x
is
tin
g
g
r
id
,
AE
MS
is
of
u
tm
o
s
t
im
p
o
r
tan
t.
Ac
co
r
d
in
g
to
u
tili
ty
p
er
s
p
ec
tiv
e
th
e
p
r
im
a
r
y
task
of
AE
MS
is
to
m
an
ag
e
th
e
en
er
g
y
co
n
s
u
m
p
tio
n
,
th
er
eb
y
r
e
d
u
cin
g
PAR
an
d
in
co
n
s
u
m
e
r
s
’
p
er
s
p
ec
tiv
e,
it
is
to
r
ed
u
ce
co
s
t
of
elec
tr
icity
.
Her
e
we
h
av
e
d
esig
n
ed
a
m
o
d
el
in
m
atr
ix
lab
o
r
ato
r
y
s
im
u
latio
n
an
d
lin
k
(
MA
T
L
AB
/
S
im
u
lin
k
)
p
latf
o
r
m
c
o
n
s
id
er
in
g
f
iv
e
r
esid
en
t
ial
co
n
s
u
m
er
s
with
d
if
f
er
en
t
lo
a
d
p
atter
n
s
.
T
h
e
u
til
ity
co
m
p
an
ies
s
en
d
s
u
s
ef
u
l
d
ay
ah
ea
d
f
o
r
ec
asted
in
f
o
r
m
atio
n
s
u
ch
as
d
em
an
d
p
r
o
f
ile,
tar
if
f
an
d
also
av
ailab
ilit
y
of
R
E
S
th
r
o
u
g
h
a
s
m
ar
t
ap
p
licatio
n
.
T
h
is
Mic
r
o
s
o
f
t.
N
et
tech
n
o
lo
g
y
-
b
ase
d
ap
p
licatio
n
h
as
b
ee
n
d
ev
el
o
p
e
d
f
o
r
th
e
b
en
e
f
it
of
th
e
co
n
s
u
m
er
s
so
th
at
th
ey
can
p
lan
th
eir
elec
tr
icity
u
s
ag
e
b
ased
on
th
eir
c
o
m
f
o
r
ts
an
d
p
r
ef
er
en
ce
s
.
At
th
e
s
am
e
tim
e
th
e
ap
p
licatio
n
its
elf
will
s
u
g
g
est
th
e
m
o
s
t
o
p
tim
al
s
o
lu
tio
n
to
ad
o
p
t
f
o
r
d
o
m
esti
c
co
n
s
u
m
er
s
.
A
n
ew
ad
v
an
ce
d
an
d
f
lex
ib
le
d
y
n
am
ic
tar
if
f
s
tr
u
ctu
r
e
h
as
b
ee
n
p
r
o
p
o
s
ed
to
e
n
s
u
r
e
c
o
n
s
u
m
er
s
p
r
ef
er
en
ce
.
B
ased
on
th
e
p
r
o
p
o
s
ed
tar
if
f
an
o
p
tim
u
m
p
o
in
t
h
as
b
ee
n
ac
h
iev
e
d
wh
er
e
u
s
ag
e
of
co
n
v
e
n
tio
n
al
en
er
g
y
an
d
r
e
n
ewa
b
le
en
er
g
y
r
esu
lts
in
r
ea
s
o
n
ab
le
elec
tr
icity
p
r
icin
g
an
d
s
ig
n
if
ican
t
r
ed
u
ctio
n
in
PAR
.
T
h
er
ef
o
r
e,
r
est
of
th
is
p
ap
e
r
h
as
b
ee
n
o
r
g
an
is
ed
as
s
h
o
wn
in
Fig
u
r
e
1
.
In
s
ec
tio
n
3,
m
o
d
ellin
g
of
d
if
f
er
en
t
p
a
r
ts
of
th
e
s
y
s
tem
will
be
d
is
cu
s
s
ed
s
u
ch
as
:
i)
d
em
an
d
f
o
r
ec
asti
n
g
,
ii)
R
E
S
an
d
E
SS
,
iii)
p
r
o
p
o
s
ed
tar
if
f
,
iv
)
Heu
r
is
tic
alg
o
r
ith
m
f
o
r
o
p
tim
izatio
n
,
a
n
d
v)
e
n
er
g
y
co
n
s
u
m
p
tio
n
m
o
d
el
r
esp
ec
tiv
ely
.
In
s
ec
tio
n
4
an
d
5,
we
will
p
r
esen
t
an
d
d
is
cu
s
s
th
e
r
esu
lts
an
d
co
n
clu
s
io
n
r
esp
ec
tiv
ely
.
Fig
u
r
e
1
.
Sy
s
tem
m
o
d
ellin
g
4.
SYST
E
M
M
O
D
E
L
L
I
NG
T
h
e
p
r
o
p
o
s
ed
AE
MS
in
co
r
p
o
r
ates
th
e
u
s
e
of
p
h
o
to
v
o
ltaic
(
PV)
s
y
s
tem
as
R
E
S
an
d
en
er
g
y
s
to
r
ag
e
s
y
s
tem
(
E
SS
)
to
s
to
r
e
elec
tr
ici
ty
eith
er
f
r
o
m
m
ain
g
r
id
at
lo
w
p
r
ice
tim
e
or
f
r
o
m
R
E
S
f
o
r
home
ap
p
lian
ce
s
at
p
ea
k
p
r
ice
tim
e.
T
h
is
in
tu
r
n
h
elp
s
to
r
ed
u
c
e
t
h
e
ca
r
b
o
n
e
m
is
s
io
n
lev
el.
T
h
e
en
tire
s
y
s
tem
can
be
b
r
ief
ly
d
escr
ib
ed
u
s
in
g
a
b
lo
ck
d
iag
r
a
m
as
s
h
o
wn
in
Fig
u
r
e
2.
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:
2502
-
4
7
5
2
R
en
ewa
b
le
en
erg
y
b
a
s
ed
d
yn
a
mic
ta
r
iff s
y
s
tem
fo
r
d
o
mestic
lo
a
d
ma
n
a
g
eme
n
t
(
K
u
h
eli
Go
s
w
a
mi)
629
Fig
u
r
e
2
.
B
asic
b
lo
ck
d
iag
r
am
of
s
y
s
tem
4
.
1
.
De
m
a
nd
f
o
re
ca
s
t
ing
Dem
an
d
f
o
r
ec
asti
n
g
is
th
e
in
itial
an
d
m
o
s
t
im
p
o
r
tan
t
p
ar
t
of
elec
tr
ical
p
o
wer
s
y
s
tem
,
s
p
ec
if
ically
lo
ad
m
an
ag
em
e
n
t
s
y
s
tem
[
3
5
]
.
In
th
is
ar
ticle,
we
h
av
e
co
m
p
ar
ed
d
if
f
er
en
t
f
o
r
ec
asti
n
g
to
o
l
an
d
f
in
ally
u
s
ed
a
u
to
r
eg
r
ess
iv
e
i
n
teg
r
ate
d
m
o
v
in
g
a
v
er
a
g
e
with
ex
o
g
en
o
u
s
v
ar
iab
les
(
AR
I
MA
X
)
,
a
m
u
ltiv
ar
iate
m
eth
o
d
to
p
er
f
o
r
m
lo
a
d
f
o
r
ec
asti
n
g
,
w
h
ich
is
p
er
f
o
r
m
in
g
c
o
m
p
ar
ativ
el
y
b
etter
th
an
o
th
er
tech
n
iq
u
es
[
36
].
By
u
s
in
g
th
is
class
ical
m
eth
o
d
,
we
h
av
e
ac
h
iev
ed
an
alm
o
s
t
er
r
o
r
f
r
ee
f
o
r
e
ca
s
ted
d
em
an
d
p
r
o
f
ile
[
37
]
,
[
38
].
Au
to
r
eg
r
ess
iv
e
in
teg
r
ated
m
o
v
in
g
with
ex
o
g
en
o
u
s
v
ar
iab
l
es
,
h
er
e
to
d
esig
n
AR
I
MA
X
m
o
d
el
f
o
r
f
o
r
ec
asti
n
g
Yt
an
d
Xt
h
av
e
b
e
en
co
n
s
id
er
ed
as
two
s
tatio
n
ar
y
tim
e
s
er
ies.
T
h
e
t
r
an
s
f
er
f
u
n
ctio
n
m
o
d
el
(
T
FM)
can
be
wr
itten
as,
=
+
(
)
+
(
1
)
wh
er
e,
Yt
is
r
esp
o
n
s
e
s
er
ies,
Xt
is
p
r
ed
icto
r
d
ata
s
er
ies,
C
is
co
n
s
tan
t
ter
m
,
N
t
is
th
e
s
to
ch
asti
c
d
is
tu
r
b
an
ce
,
(
)
is
th
e
tr
an
s
f
er
f
u
n
ctio
n
a
n
d
B
is
b
ac
k
s
h
if
t
o
p
er
at
o
r
.
(
)
=
(
0
+
1
+
2
2
+
⋯
+
)
(
2
)
In
AR
I
MA
X,
we
d
ea
l
with
two
d
if
f
er
e
n
t
tim
e
s
er
ies
Xt
an
d
Yt.
T
h
e
T
r
an
s
f
er
Fu
n
ctio
n
ca
n
be
wr
itten
as,
(
)
=
[
ℎ
(
)
(
)
]
(
3
)
t
h
eo
r
etica
lly
,
(
)
h
as
in
f
in
ite
n
u
m
b
er
of
co
ef
f
icien
ts
.
W
h
er
e,
ℎ
(
)
=
0
+
1
+
⋯
(
4
)
(
)
=
1
−
1
(
)
−
⋯
−
(
5)
wh
er
e,
h
is
th
e
n
u
m
b
er
of
ter
m
s
p
lu
s
one
of
th
e
in
d
ep
en
d
e
n
t
v
ar
iab
les,
r
is
th
e
n
u
m
b
e
r
of
ter
m
s
p
lu
s
one
of
th
e
d
ep
en
d
en
t
v
a
r
iab
les
an
d
b
is
th
e
d
ea
d
tim
e.
Nt
can
be
wr
itten
as,
=
[
(
)
Θ
(
B
s
)
ϕ
(
B
)
(
)
(
1
−
)
(
1
−
)
]
(
6
)
W
h
er
e,
at
is
ze
r
o
m
ea
n
an
d
n
o
r
m
ally
d
is
tr
ib
u
ted
wh
ite
n
o
is
e.
T
h
er
ef
o
r
e,
T
FM
can
be
f
in
ally
ex
p
r
ess
ed
as,
=
+
(
0
+
1
+
2
2
+
⋯
+
)
+
[
(
)
Θ
(
B
s
)
ϕ
(
B
)
ϕ
(
B
s
)
(
1
−
)
(
1
−
)
]
(
7
)
i
n
itially
,
th
e
v
alu
e
of
K
an
d
Nt
m
u
s
t
be
s
p
ec
if
ied
to
f
in
d
out
(
b
,
r,
h
)
.
By
o
b
s
er
v
in
g
an
d
co
m
p
ar
i
n
g
th
e
esti
m
ated
im
p
u
ls
e
r
esp
o
n
s
e
f
u
n
ctio
n
with
s
o
m
e
co
m
m
o
n
th
e
o
r
etica
l
f
u
n
ctio
n
s
(
b
,
r
,
h
)
can
a
ls
o
be
id
en
tifie
d
to
r
ep
r
esen
t
T
FM
.
Sev
er
al
d
iag
n
o
s
tic
ch
ec
k
s
ar
e
in
v
o
lv
ed
to
ch
ec
k
th
e
s
tatu
s
of
r
esid
u
als
in
th
e
s
er
ies
an
d
to
co
n
clu
d
e
wh
eth
e
r
th
e
m
o
d
el
is
ad
eq
u
ate
or
n
o
t.
Ak
aik
e
in
f
o
r
m
atio
n
c
r
iter
io
n
(
AI
C
)
is
one
of
th
em
.
A
f
o
r
ec
asti
n
g
m
o
d
el
is
h
ig
h
ly
ac
ce
p
tab
le
if
th
e
v
alu
e
of
A
k
aik
e’
s
i
n
f
o
r
m
atio
n
c
r
iter
io
n
is
s
m
all.
B
ay
es
ian
i
n
f
o
r
m
atio
n
c
r
iter
io
n
(
B
I
C
)
an
d
S
ch
war
z
i
n
f
o
r
m
atio
n
c
r
iter
io
n
(
SIC)
ar
e
also
v
er
y
ef
f
ec
t
iv
e
in
ch
o
o
s
in
g
th
e
ac
cu
r
ate
m
o
d
el.
4
.
2
.
Av
a
ila
bil
it
y
of
RE
S
Av
ailab
ilit
y
of
R
E
S:
We
ass
u
m
e
th
at
s
o
m
e
of
t
h
e
c
o
n
s
u
m
er
s
ar
e
eq
u
ip
p
e
d
with
PV
s
y
s
tem
.
We
h
a
v
e
u
s
ed
th
e
g
iv
e
n
m
ath
em
atica
l
m
o
d
el
to
ca
lcu
late
th
e
PV
o
u
t
p
u
t
(P
PV
)
at
t.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
25
,
No
.
2
,
Feb
r
u
a
r
y
20
22
:
6
2
6
-
6
3
8
630
(
Ʈ
)
=
(
)
.
.
∀
0
≤
Ʈ
≤
24
(
8
)
W
h
er
e
g
lo
b
al
h
o
r
izo
n
tal
ir
r
ad
i
atio
n
(
GHI
)
is
(
k
W
/m
2
)
.
A
is
th
e
ar
ea
of
s
o
lar
p
an
el
an
d
η
is
th
e
ef
f
icien
cy
of
th
e
PV
s
y
s
tem
.
T
h
e
elec
tr
ical
en
er
g
y
g
en
er
ate
d
(
E
PV)
by
th
e
PV
s
y
s
tem
in
tim
e
d
u
r
atio
n
∆t,
(
)
=
(
Ʈ
)
.
∆
(
9
)
w
h
er
e
Ʈ
is
th
e
r
ea
l
tim
e.
T
h
is
en
er
g
y
will
be
u
s
ed
f
o
r
home
ap
p
lian
ce
s
(
.
)
an
d
en
er
g
y
s
to
r
ag
e
(
.
)
.
(
)
=
.
(
)
+
.
(
)
(
1
0
)
C
o
n
s
tr
ain
ts
:
0
≤
.
(
)
≤
(
)
.
.
.
∆
(
1
1
)
0
≤
.
(
)
≤
(
)
.
.
.
∆
(
1
2
)
4
.
3
.
E
nerg
y
s
t
o
r
a
g
e
s
y
s
t
e
m
(
E
SS
)
T
h
e
aim
of
E
SS
is
to
u
s
e
R
E
S
an
d
m
ain
g
r
id
elec
tr
icity
ef
f
ici
en
tly
.
E
SS
ac
ts
as
a
s
in
k
to
s
to
r
e
en
er
g
y
f
r
o
m
R
E
S
an
d
m
ain
g
r
id
at
l
o
w
p
r
ice
tim
e
an
d
s
o
u
r
ce
f
o
r
d
o
m
esti
c
ap
p
lian
ce
s
.
T
h
e
m
at
h
em
atica
l
m
o
d
el
of
E
SS
is
,
.
ℎ
(
)
=
.
(
)
(
1
−
(
)
)
(
1
3
)
.
ℎ
(
)
=
(
.
ℎ
(
)
+
.
ℎ
(
)
)
.
(
)
(
1
4
)
(
)
=
{
1
,
ℎ
0
,
ℎ
(
1
5
)
.
(
)
=
.
(
−
1
)
+
.
ℎ
(
)
.
−
.
ℎ
(
)
/
(
1
6
)
h
er
e
.
is
th
e
en
er
g
y
lev
el
of
E
S
S
af
ter
tim
e
t
an
d
η
ES
S
ef
f
icien
cy
of
E
SS
.
As
we
ar
e
co
n
s
id
er
in
g
our
s
y
s
tem
as
a
d
ay
ah
ea
d
s
y
s
tem
,
t
h
er
ef
o
r
e
e
n
er
g
y
lev
el
of
E
SS
m
u
s
t
r
etu
r
n
to
th
e
in
itial
lev
el
(
0
)
at
th
e
en
d
of
th
e
d
ay
.
(
)
=
0
(
1
7
)
C
o
n
s
tr
ain
ts
:
T
h
e
E
SS
ch
ar
g
e/
d
is
ch
ar
g
e
r
ate
s
h
o
u
ld
not
e
x
c
ee
d
th
e
cr
itical
v
al
u
e
an
d
ch
ar
g
e
lev
el
of
E
SS
s
h
o
u
ld
lie
b
etwe
en
m
i
n
im
u
m
(
_
min
)
an
d
m
ax
im
u
m
en
e
r
g
y
le
v
el
(
_
).
4
.
4.
E
nerg
y
c
o
ns
um
ptio
n
m
o
del
A
E
M
S
d
e
p
e
n
d
s
on
s
e
v
e
r
al
f
a
ct
o
r
s
s
u
c
h
as
d
e
m
a
n
d
p
r
o
f
i
le
,
av
a
i
l
a
b
i
li
t
y
of
r
e
n
e
w
a
b
l
e
e
n
e
r
g
y
,
j
u
d
i
c
i
o
u
s
t
a
r
i
f
f
s
t
r
u
c
t
u
r
e
,
c
o
n
s
u
m
e
r
s
’
f
l
ex
i
b
l
e
a
tt
i
t
u
d
e
a
n
d
t
h
e
i
r
d
i
r
e
ct
p
a
r
t
i
c
i
p
a
ti
o
n
in
el
e
c
t
r
i
c
i
t
y
t
r
a
d
e
m
a
r
k
e
t
.
H
e
r
e
,
we
h
a
v
e
c
o
n
s
i
d
e
r
e
d
f
i
v
e
d
i
f
f
e
r
e
n
t
c
o
n
s
u
m
e
r
s
a
n
d
each
home
w
ith
s
e
t
of
a
p
p
l
i
a
n
c
es
A
a
n
d
N
is
t
h
e
t
o
t
a
l
n
u
m
b
e
r
of
a
p
p
l
i
a
n
c
e
s
.
a
1
,
a
2
,
….
aN
a
r
e
N
n
u
m
b
e
r
of
d
o
m
es
t
i
c
a
p
p
l
i
a
n
c
e
s
u
s
e
d
in
a
h
o
m
e
.
T
h
e
y
a
r
e
o
p
e
r
a
t
e
d
o
v
e
r
a
t
i
m
e
p
e
r
i
o
d
t
є
T,
w
h
e
r
e
S
u
p
p
o
s
e
,
S
a
1
is
t
h
e
s
t
a
r
ti
n
g
t
i
m
e
i
n
s
t
a
n
t
s
of
a
p
p
l
i
a
n
c
e
a1
a
n
d
F
a
1
is
t
h
e
f
i
n
i
s
h
i
n
g
t
i
m
e
i
n
s
t
a
n
ts
of
a
p
p
l
i
a
n
ce
a
1
.
T
h
e
r
e
f
o
r
e
,
o
p
e
r
a
t
i
o
n
t
i
m
e
i
n
te
r
v
a
l
f
o
r
s
c
h
e
d
u
l
e
d
a
p
p
l
i
a
n
ce
s
a1
is
[S
a1
,
F
a1
].
A
≜
{a
1
,
a2
,
a
3
,
……………
……,
aN}
(1
8)
T
≜
{1
,
2,
3,
………………
….
.
.
,
24}
(
1
9
)
Her
e,
in
t
h
is
m
o
d
el
we
h
a
v
e
co
n
s
id
er
ed
c
o
n
v
en
tio
n
al
e
n
er
g
y
s
o
u
r
ce
s
(
C
E
S)
an
d
R
E
S
to
s
atis
f
y
th
e
d
em
an
d
.
We
h
av
e
ass
u
m
ed
,
∈
.
as
g
en
er
ated
or
av
ailab
le
s
o
lar
en
er
g
y
at
tim
e
t,
wh
ich
s
h
o
u
ld
be
k
n
o
wn
or
f
o
r
ec
asted
.
Ho
wev
e
r
,
th
e
p
r
ic
e
of
th
e
r
en
ewa
b
le
en
er
g
y
is
v
ar
iab
le.
Her
e,
t.M
G
is
d
en
o
tin
g
f
o
r
ec
asted
p
r
ice
of
en
er
g
y
f
r
o
m
m
ain
g
r
i
d
at
tim
e
t,
t.PV
is
d
en
o
tin
g
f
o
r
ec
ast
ed
p
r
ice
of
s
o
lar
en
e
r
g
y
at
tim
e
t.
We
h
av
e
co
n
s
id
er
ed
ψa1
as
th
e
o
p
er
atio
n
tim
e
v
ec
to
r
of
a
p
p
lian
ce
a1
.
T
h
e
r
ef
o
r
e
,
ψa1
=
[
β
1Ga1
,
β
1P
V
a
1
,
β
2G
a
1
,
β
2PVa1
,
…….
,
β
24Ga1
,
β
24PVa1
]
(
2
0
)
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:
2502
-
4
7
5
2
R
en
ewa
b
le
en
erg
y
b
a
s
ed
d
yn
a
mic
ta
r
iff s
y
s
tem
fo
r
d
o
mestic
lo
a
d
ma
n
a
g
eme
n
t
(
K
u
h
eli
Go
s
w
a
mi)
631
β
tG
a1
is
u
s
ed
g
r
id
en
er
g
y
to
s
atis
f
y
d
em
a
n
d
of
a1
at
tim
e
t
(
k
n
o
wn
/f
o
r
ec
asted
)
.
β
tPVa1
is
u
s
ed
s
o
lar
en
er
g
y
to
s
atis
f
y
d
em
an
d
of
a1
at
tim
e
t
(
k
n
o
wn
/f
o
r
ec
asted
)
.
State
of
o
p
er
atio
n
of
an
ap
p
lian
ce
a1
at
tim
e
,
t,
ɸ
a1
(
t
)
=
{
0
ℎ
1
ℎ
(
2
1
)
C
o
n
s
u
m
er
will
p
lace
a
d
ay
ah
ea
d
r
eq
u
est
f
o
r
a1
a
p
p
lian
ce
in
tim
e
in
ter
v
al
[
Sa1
,
Fa1
]
,
wh
er
e
[
Sa1
,
Fa1
]
є
T.
C
o
n
s
u
m
er
n
ee
d
s
to
s
p
ec
if
y
αa
a
n
d
fa
f
o
r
av
ailin
g
t
h
e
b
est
s
u
ited
tar
if
f
s
ch
em
e.
H
er
e
f
a1
is
th
e
n
o
.
of
s
witch
in
g
ON
of
ap
p
lian
ce
a1
.
T
o
tal
en
e
r
g
y
d
em
an
d
of
a1
c
an
be
s
atis
f
ied
by
C
E
S
an
d
R
E
S.
Hen
ce
th
e
to
tal
en
er
g
y
c
o
n
s
u
m
e
d
by
a1
can
be
d
eter
m
in
ed
as,
1
=
∑
∑
1
(
1
є
A
1
+
1
)
=
1
(
2
2
)
s
im
ilar
ly
,
th
e
co
s
t
of
th
e
e
n
er
g
y
co
n
s
u
m
e
d
by
a1
o
v
er
24
h
o
u
r
s
can
be
ca
lcu
lated
as,
1
=
∑
∑
1
(
1
є
A
1
+
1
)
=
1
(
23
)
4
.
5.
L
o
a
d
c
a
t
eg
o
riz
a
t
io
n
In
th
is
s
ec
tio
n
,
d
o
m
esti
c
co
n
s
u
m
er
s
h
av
e
b
ee
n
class
if
ied
as
ac
tiv
e
co
n
s
u
m
er
s
an
d
p
ass
iv
e
co
n
s
u
m
er
s
.
Activ
e
co
n
s
u
m
er
s
ar
e
eq
u
ip
p
e
d
with
PV
s
y
s
tem
an
d
E
SS
,
wh
er
ea
s
p
ass
iv
e
co
n
s
u
m
er
s
ar
e
eq
u
ip
p
e
d
with
E
SS
o
n
ly
.
T
h
e
d
o
m
esti
c
lo
ad
s
f
u
r
th
e
r
can
be
ca
teg
o
r
ized
b
ased
on
th
eir
p
o
wer
co
n
s
u
m
p
tio
n
,
o
p
er
atio
n
tim
e,
n
u
m
b
er
of
s
witch
in
g
ON
-
OFF
o
v
er
24
h
o
u
r
s
an
d
co
n
s
u
m
er
p
r
ef
er
en
ce
s
.
T
h
ey
ar
e
class
if
ied
as
:
i)
i
n
ter
r
u
p
tib
le
l
o
a
d
s
,
ii)
n
on
-
in
ter
r
u
p
tib
le
lo
ad
s
,
a
n
d
iii)
i
n
ter
r
u
p
tib
le
l
o
ad
s
with
m
in
im
u
m
d
elay
.
Her
e
p
o
wer
c
o
n
s
u
m
p
tio
n
of
d
if
f
er
e
n
t
d
o
m
esti
c
lo
ad
s
s
u
ch
as
r
ef
r
ig
er
ato
r
,
wash
in
g
m
ac
h
in
e,
in
d
u
ctio
n
o
v
en
,
ir
o
n
,
f
a
n
,
lig
h
t,
co
m
p
u
ter
,
a
n
d
telev
is
io
n
h
as
b
ee
n
d
is
cu
s
s
ed
an
d
an
al
y
s
ed
in
d
etail
f
o
r
d
if
f
er
en
t
o
p
er
atin
g
m
o
d
es
wh
ich
h
as
b
ee
n
s
h
o
wn
in
Fig
u
r
e
3
.
Fig
u
r
e
3
.
Po
wer
c
o
n
s
u
m
p
tio
n
of
d
if
f
e
r
en
t
h
o
m
e
ap
p
lian
ce
s
Fig
u
r
e
4
.
C
ateg
o
r
izatio
n
o
f
d
o
m
esti
c
lo
ad
s
f
o
r
5
h
o
u
s
eh
o
ld
s
u
s
in
g
K
-
m
ea
n
s
clu
s
ter
in
g
Her
e,
th
e
K
-
m
ea
n
s
clu
s
ter
in
g
t
ec
h
n
iq
u
e
h
as
b
ee
n
u
s
ed
to
p
r
i
o
r
itize
th
e
lo
ad
s
.
Fig
u
r
e
4
is
s
h
o
win
g
th
e
clu
s
ter
s
b
ased
on
wh
ich
th
e
lo
ad
s
a
r
e
m
a
r
k
ed
with
th
e
ir
p
r
io
r
ity
r
an
k
in
g
f
o
r
f
iv
e
d
if
f
er
en
t
d
o
m
esti
c
co
n
s
u
m
er
s
r
esp
ec
tiv
ely
.
T
h
e
c
lu
s
ter
in
g
r
esu
lt
h
as
b
ee
n
v
er
if
ied
ag
ain
u
s
in
g
a
m
ath
e
m
atica
l
m
o
d
el.
Su
p
p
o
s
e,
r
eq
u
est
tim
e
of
th
e
ap
p
lian
ce
a1
is
1
an
d
waitin
g
tim
e
of
th
e
a
p
p
lian
ce
a1
is
1
.
T
h
er
ef
o
r
e,
1
=
1
−
1
(
2
4
)
T
o
tal
waitin
g
tim
e,
τ
w
=
∑
τ
w
ai
=
1
(
2
5
)
Av
er
ag
e
waitin
g
tim
e,
w.
av
g
=
τ
w
/
N
(
2
6
)
Her
e,
we
h
av
e
co
n
s
id
er
e
d
α
ai
as
th
e
r
atin
g
of
ap
p
lian
ce
ai
wh
er
e
i
=
{1
,
2
,
3
,
….
.
,
N},
1
as
th
e
o
p
er
atin
g
tim
e
of
a1
o
v
e
r
24
h
o
u
r
s
an
d
f
a1
as
th
e
f
r
eq
u
e
n
cy
of
o
p
e
r
atio
n
of
a1
or
No
.
of
s
witch
ON.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
25
,
No
.
2
,
Feb
r
u
a
r
y
20
22
:
6
2
6
-
6
3
8
632
1
∗
=
t
i
m
e
of
r
un
No
.
of
s
w
i
t
ch
ON
1
∗
=
1
/
1
(
27
)
∗
=
∑
∑
/
1
∈
24
=
1
ꓯ
ai
є
A
(
28
)
Utilizatio
n
f
ac
to
r
,
=
1
24
∑
(
2
9
)
Prio
r
ity
R
an
k
in
g
,
=
[
]
∗
[
∗
]
ꓯ
ai
є
A
(
30
)
B
ased
on
th
is
r
a
n
k
in
g
f
in
ally
th
e
lo
ad
h
as
b
ee
n
ca
teg
o
r
ized
as
n
o
n
-
in
ter
r
u
p
tib
le
l
o
ad
,
in
t
er
r
u
p
tib
le
lo
ad
with
m
in
im
u
m
d
ela
y
tim
e
an
d
in
ter
r
u
p
tib
le
lo
ad
.
4.
6
.
P
r
o
po
s
ed
t
a
rif
f
s
t
ruct
ur
e
Sev
er
al
tar
if
f
m
o
d
els
ar
e
a
v
ailab
le
to
d
e
f
in
e
elec
tr
icity
p
r
ice
s
f
o
r
a
d
ay
.
Am
o
n
g
s
t
th
ese,
ti
m
e
of
u
s
e
(T
o
U)
tar
if
f
m
o
d
el
is
u
s
ed
to
d
ef
in
e
th
e
elec
tr
icity
p
r
ice
on
th
e
b
asis
of
tim
e
of
u
s
e
in
a
d
ay
,
wh
er
ea
s
cr
itical
p
ea
k
p
r
icin
g
(
C
PP
)
an
d
cr
itic
al
p
ea
k
r
eb
ate
(
C
PR
)
ar
e
v
ar
i
an
ts
of
T
o
U.
An
o
t
h
er
tar
if
f
s
tr
u
ctu
r
e,
r
ea
l
tim
e
p
r
icin
g
(
R
T
P)
d
ef
i
n
es
th
e
u
ti
lity
co
s
t
of
s
u
p
p
ly
in
g
elec
tr
i
city
at
a
s
p
ec
if
ic
tim
e.
In
th
i
s
s
ec
tio
n
,
we
h
av
e
p
r
o
p
o
s
ed
a
th
r
ee
-
p
ar
t
d
y
n
am
ic
tar
if
f
(
C
)
s
tr
u
ctu
r
e,
wh
ich
is
b
ased
on
T
o
U,
C
PP
,
C
PR
an
d
R
T
P.
C
=
α
+
β
x
+
γ
(
xt
)
(
31
)
Her
e,
α
c
o
m
p
r
is
es
of
m
eter
r
en
t
an
d
m
o
n
t
h
ly
v
a
r
iab
le
co
s
t
ad
ju
s
tm
en
t
(
MV
C
A)
.
is
a
f
ix
ed
ch
ar
g
e
in
d
ep
en
d
en
t
of
m
ax
im
u
m
d
e
m
an
d
a
n
d
en
er
g
y
c
o
n
s
u
m
p
tio
n
.
d
e
p
en
d
s
on
m
ax
im
u
m
d
em
an
d
(
k
VA)
or
s
an
ctio
n
ed
d
em
a
n
d
(
k
VA)
.
γ
d
ep
en
d
s
on
en
er
g
y
co
n
s
u
m
p
tio
n
(
k
W
h
)
.
=
+
(
3
2
)
Her
e,
is
th
e
co
s
t
of
e
n
er
g
y
f
r
o
m
m
ain
g
r
i
d
an
d
is
th
e
co
s
t
of
r
en
ewa
b
le
en
e
r
g
y
w
h
ich
is
f
i
x
ed
co
s
t.
=
{
1
.
ℎ
(
06
:
00
−
05
:
00
)
2
.
ℎ
(
05
:
00
−
11
:
00
)
3
.
ℎ
(
11
:
00
−
06
:
00
)
(
3
3
)
P
s
eudo
co
de
Input:
forecasted
demand
data,
forecasted
tariff
(RTP).
For t = 1 to 24
If
6
≤
≤
17
1
.
=
ℎ
Else If
17
≤
≤
23
2
.
=
ℎ
Calculate
=
ℎ
24
ℎ
∗
100
%
If
≥
25%
ℎ
24
ℎ
Apply Penalty
2
.
.
=
2
+
(
%
2
)
Else if
≤
20%
ℎ
24
ℎ
Apply Rebate
=
(
20
+
(
20
−
)
)
%
(
ℎ
∗
2
.
)
End If
End Else If
Else
3
.
=
ℎ
End If
End
4
.
7
.
H
euristic
a
lg
o
rit
hm
T
h
e
d
e
m
a
n
d
p
r
o
f
i
l
e
s
of
d
o
m
e
s
t
ic
c
o
n
s
u
m
e
r
s
d
e
p
e
n
d
on
g
e
o
g
r
a
p
h
i
c
a
l
c
o
n
d
i
t
i
o
n
s
a
n
d
d
em
o
g
r
a
p
h
y
.
K
e
e
p
i
n
g
in
v
i
e
w
t
h
is
f
a
ct
,
d
u
e
to
h
i
g
h
l
y
v
o
l
a
t
il
e
b
e
h
a
v
i
o
u
r
of
c
o
n
s
u
m
e
r
s
a
n
d
i
n
t
e
r
m
it
t
en
t
c
h
a
r
a
c
t
e
r
i
s
t
i
cs
of
R
E
Ss
,
we
h
a
v
e
d
e
a
lt
w
it
h
d
i
f
f
er
e
n
t
h
e
u
r
i
s
ti
c
a
l
g
o
r
it
h
m
s
.
H
e
r
e
,
a
h
y
b
r
i
d
o
p
t
i
m
i
z
a
ti
o
n
t
e
c
h
n
i
q
u
e
b
a
s
e
d
on
GA
a
n
d
PSO
h
a
s
b
e
e
n
d
e
v
e
l
o
p
e
d
w
h
i
ch
f
o
l
l
o
w
s
g
r
e
e
d
y
s
e
l
e
ct
i
o
n
te
c
h
n
i
q
u
e
a
n
d
can
be
u
s
e
d
f
o
r
p
e
r
s
o
n
a
l
b
e
s
t
a
n
d
g
l
o
b
al
b
e
s
t
s
o
l
u
ti
o
n
.
It
h
a
s
b
e
e
n
r
e
p
r
e
s
e
n
t
e
d
as
h
y
b
r
i
d
g
r
e
e
d
y
p
a
r
t
i
c
l
e
s
w
a
r
m
o
p
t
i
m
i
za
t
i
o
n
(
H
GPS
O
)
.
W
e
h
a
v
e
u
s
e
d
m
u
l
t
i
p
l
e
k
n
a
p
s
a
c
k
p
r
o
b
l
e
m
(
MK
P
)
to
b
a
l
a
n
ce
t
h
e
d
e
m
a
n
d
a
n
d
s
u
p
p
l
y
a
n
d
H
G
PS
O
to
r
ea
c
h
o
p
t
i
m
u
m
p
o
i
n
t
.
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:
2502
-
4
7
5
2
R
en
ewa
b
le
en
erg
y
b
a
s
ed
d
yn
a
mic
ta
r
iff s
y
s
tem
fo
r
d
o
mestic
lo
a
d
ma
n
a
g
eme
n
t
(
K
u
h
eli
Go
s
w
a
mi)
633
P
s
eudo
co
de
Input:
Fitness
function
(based
on
RES
availability,
Tariff
and
Consumers’
c
om
fo
rt
),
lb,
ub,
Population
Size,
NP
(based
on
home
appliances),
T
(terminating
criteria).
Evaluate
the
objective
function
value
(f)
of
P
Assign
Pbest
and
fpbest
Identify
the
solution
as
best
fitness
and
assign
that
solution
as
gbest
and
fitness
as
fgbest.
For
t
=
1
to
T
For
i
=
1
to
NP
Determine
the
velocity
of
ith
particle
Determine
the
new
position
of
ith
particle
Bound
position
Evaluate
the
objective
function
value
Update
the
population
Update
Pbest,
i
and
fpbest
Update
gbest
and
fgbest
End
Combine
P
and
Pbest
to
perform
(
+
λ)
for
selecting
P
in
next
iteration
End
Repeat
T
iterations
5.
RE
SU
L
T
S
AND
D
I
SCU
SS
I
O
N
B
ased
on
th
e
d
ata
o
b
tain
e
d
f
r
o
m
p
h
y
s
ical
s
u
r
v
ey
an
d
o
n
li
n
e
s
u
r
v
e
y
an
ef
f
icien
t
m
o
d
el
h
as
b
ee
n
d
esig
n
ed
in
MA
T
L
AB
/
S
im
u
li
n
k
p
latf
o
r
m
wh
ich
h
as
b
ee
n
an
aly
ze
d
on
t
h
e
b
asis
of
p
r
o
p
o
s
ed
o
p
tim
izatio
n
tech
n
iq
u
e
to
f
ig
u
r
e
out
th
e
im
p
r
o
v
em
e
n
ts
o
v
er
th
e
ex
is
tin
g
s
y
s
tem
.
T
h
e
ef
f
icien
cy
of
th
e
m
o
d
el
h
as
also
b
ee
n
an
aly
ze
d
in
th
e
f
o
llo
win
g
s
ec
tio
n
s
b
ased
on
th
e
co
n
s
u
m
er
s
’
an
d
u
tili
ty
s
ec
to
r
’
s
p
er
s
p
ec
tiv
e.
T
h
is
can
f
u
r
th
er
be
ca
teg
o
r
ized
as
m
o
n
th
l
y
ele
ctr
icity
b
ill,
waitin
g
tim
e
an
d
PAR
,
p
ea
k
d
em
an
d
r
esp
ec
tiv
e
ly
.
5
.
1
.
Co
ns
um
er
s
’
pref
er
ence
5
.
1
.
1
.
M
o
nthly
elec
t
ricit
y
bill
T
o
tal
en
er
g
y
co
s
t
in
our
s
y
s
tem
h
as
b
ee
n
r
ed
u
ce
d
b
ased
on
two
p
ar
am
eter
s
:
i)
f
lex
ib
le
an
d
ef
f
icien
t
u
s
e
of
R
E
S
an
d
E
SS
an
d
ii)
p
r
o
p
o
s
ed
d
y
n
a
m
ic
tar
if
f
.
C
o
n
s
u
m
er
s
n
ee
d
to
eith
er
d
ec
lar
e
th
e
ir
lo
ad
r
eq
u
ir
em
en
t
with
th
e
r
atin
g
s
of
th
e
ap
p
lian
ce
s
a
d
ay
ah
ea
d
or
th
ey
can
f
o
llo
w
th
e
s
u
g
g
ested
d
em
an
d
p
r
o
f
ile
by
t
h
e
u
tili
ty
co
m
p
an
y
.
T
h
ey
ca
n
ch
o
o
s
e
an
d
d
ec
lar
e
th
e
b
est
s
u
ited
tar
if
f
p
lan
a
d
ay
ah
ea
d
.
Usi
n
g
th
is
ap
p
r
o
ac
h
co
n
s
u
m
e
r
s
will
g
et
m
ax
im
u
m
b
e
n
ef
its
as
s
h
o
wn
in
Fig
u
r
e
s
5
(
a)
an
d
5
(
b
)
an
d
T
a
b
le
2.
T
ab
le
2
.
T
h
e
p
er
f
o
r
m
a
n
ce
of
AE
MS
on
th
e
b
asis
of
m
o
n
th
l
y
elec
tr
icity
b
ill
C
o
n
s
u
mers
M
o
n
t
h
l
y
El
e
c
t
r
i
c
i
t
y
Ex
p
e
n
se
S
a
v
i
n
g
s
in
M
o
n
t
h
l
y
El
e
c
t
r
i
c
i
t
y
E
x
p
e
n
se
(
i
n
%)
W
i
t
h
o
u
t
A
E
M
S
W
i
t
h
H
G
P
S
O
A
E
M
S
H
o
u
s
e
h
o
l
d
1
3
,
5
9
7
.
8
0
2
,
4
4
0
.
5
5
32
H
o
u
s
e
h
o
l
d
2
2
,
2
0
3
.
2
1
1
,
6
6
4
.
8
1
24
H
o
u
s
e
h
o
l
d
3
2
,
3
3
2
.
1
5
1
,
4
9
9
.
1
0
36
H
o
u
s
e
h
o
l
d
4
1
,
8
5
2
.
4
1
1
,
3
7
1
.
0
0
26
H
o
u
s
e
h
o
l
d
5
3
,
9
5
3
.
6
7
2
,
8
1
0
.
4
7
29
(
a)
(
b
)
Fig
u
r
e
5
.
C
o
s
t
cu
r
v
e
f
o
r
(
a)
s
i
n
g
le
c
o
n
s
u
m
e
r
(
h
o
u
s
eh
o
ld
3)
an
d
(
b
)
m
u
ltip
le
c
o
n
s
u
m
er
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
25
,
No
.
2
,
Feb
r
u
a
r
y
20
22
:
6
2
6
-
6
3
8
634
In
o
u
r
s
y
s
tem
we
h
av
e
u
s
ed
E
SS
in
a
f
lex
i
b
le
way
s
u
c
h
th
at
E
SS
is
ch
ar
g
e
d
f
o
r
m
m
ain
g
r
id
in
lo
w
p
r
icin
g
tim
e
(
1
2
:0
0
am
to
0
6
:
0
0
am
)
as
s
h
o
w
n
in
Fig
u
r
e
6
a
n
d
f
r
o
m
R
E
S
in
m
o
d
er
ate
p
r
ic
in
g
tim
e
(
1
0
:
0
0
am
to
0
3
:
0
0
p
m
)
.
T
h
is
c
h
ea
p
e
n
er
g
y
h
as
b
ee
n
u
s
ed
f
o
r
h
o
m
e
ap
p
lian
ce
s
at
p
ea
k
p
r
icin
g
tim
e
as
s
h
o
wn
in
Fig
u
r
e
7.
T
h
er
ef
o
r
e,
th
e
en
e
r
g
y
av
ailab
le
f
r
o
m
R
E
S
is
not
o
n
ly
u
s
ed
f
o
r
home
ap
p
lian
c
es
but
f
o
r
ch
ar
g
in
g
E
SS
also
as
s
h
o
wn
in
Fig
u
r
e
8
wh
er
e
as
T
ab
le
3
s
h
o
ws
th
e
p
ar
am
eter
s
of
o
u
r
E
SS
.
In
th
is
p
ap
er
we
h
a
v
e
s
im
u
lated
our
s
y
s
tem
with
E
SS
of
im
p
r
o
v
ed
ca
p
ac
ity
an
d
ch
ar
g
in
g
/
d
is
ch
ar
g
in
g
r
ate.
E
SS
with
b
etter
c
h
ar
g
in
g
/d
is
ch
ar
g
in
g
r
ate
h
elp
s
to
r
ed
u
ce
t
h
e
elec
tr
icity
c
o
s
t.
Hen
ce
th
e
ef
f
ec
t
of
E
SS
in
r
ed
u
cin
g
elec
tr
icity
co
s
t
h
as
b
ee
n
s
h
o
wn
in
Fig
u
r
es
9
an
d
10.
Fig
u
r
e
6
.
E
n
er
g
y
s
to
r
ed
in
E
SS
f
r
o
m
m
ain
g
r
id
Fig
u
r
e
7.
E
n
er
g
y
u
s
ed
f
r
o
m
E
SS
f
o
r
home
a
p
p
lian
ce
s
Fig
u
r
e
8
.
Use
of
R
E
S
T
ab
le
3.
E
SS
p
ar
am
ete
r
s
C
a
p
a
c
i
t
y
of
ESS
M
i
n
.
En
e
r
g
y
Le
v
e
l
M
a
x
.
En
e
r
g
y
Le
v
e
l
C
h
a
r
g
i
n
g
/
D
i
sc
h
a
r
g
i
n
g
R
a
t
e
2
k
W
h
0
.
5
k
W
h
0
.
5
k
W
h
0
.
3
kW
Fig
u
r
e
9
.
E
f
f
ec
t o
f
E
SS
ca
p
ac
ity
o
n
c
o
s
t r
ed
u
ctio
n
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:
2502
-
4
7
5
2
R
en
ewa
b
le
en
erg
y
b
a
s
ed
d
yn
a
mic
ta
r
iff s
y
s
tem
fo
r
d
o
mestic
lo
a
d
ma
n
a
g
eme
n
t
(
K
u
h
eli
Go
s
w
a
mi)
635
Fig
u
r
e
1
0
.
E
f
f
ec
t
o
f
E
SS
ch
ar
g
e/d
is
ch
ar
g
e
r
ate
o
n
co
s
t r
e
d
u
ctio
n
5.
1
.
2
.
Wa
it
ing
t
im
e
Her
e
,
in
th
is
ar
ticle
c
o
n
s
u
m
er
s
’
p
r
e
f
er
en
ce
h
as
b
ee
n
co
n
s
id
er
ed
as
an
im
p
o
r
ta
n
t
p
a
r
am
eter
to
ev
alu
ate
th
e
ef
f
icien
cy
of
th
e
p
r
o
p
o
s
ed
m
o
d
el.
In
Fig
u
r
e
11
it
h
as
b
ee
n
s
h
o
wn
th
at
with
m
o
r
e
f
lex
ib
le
waitin
g
tim
e
co
n
s
u
m
er
s
will
a
v
ail
m
o
r
e
b
en
e
f
it
in
ter
m
s
of
to
tal
co
s
t.
We
h
av
e
tr
ied
to
ac
h
iev
e
an
AE
MS
u
s
in
g
th
e
p
r
o
p
o
s
ed
tar
if
f
an
d
h
eu
r
is
tic
t
ec
h
n
iq
u
e
with
m
in
im
u
m
waitin
g
tim
e
to
m
ain
tain
th
e
co
m
f
o
r
t
lev
el
of
d
o
m
esti
c
co
n
s
u
m
er
s
,
wh
ich
h
as
b
ee
n
s
h
o
wn
in
Fig
u
r
e
12.
Fig
u
r
e
11
.
T
r
ad
e
o
f
f
b
etwe
en
co
s
t
an
d
waitin
g
tim
e
of
ap
p
li
an
ce
s
Fig
u
r
e
12
.
R
ed
u
ctio
n
in
waitin
g
tim
e
u
s
in
g
HGPSO
AE
MS
5.
2.
Ut
ility
s
ec
t
o
rs’
pref
er
ence
5
.
2
.
1
.
P
AR
PAR
is
th
e
r
atio
of
th
e
m
a
x
i
m
u
m
ag
g
r
eg
ated
l
o
ad
co
n
s
u
m
p
tio
n
o
v
e
r
a
ce
r
tain
tim
e
p
er
i
o
d
an
d
th
e
av
er
ag
e
of
th
e
a
g
g
r
eg
ate
d
lo
ad
.
PAR
=
(
∑
)
=
1
/
1
(
∑
=
1
)
(
3
4
)
T
h
e
h
ig
h
PAR
af
f
ec
ts
th
e
g
r
i
d
s
tab
ilit
y
an
d
in
cr
ea
s
es
th
e
e
lectr
icity
co
s
t.
W
h
ile
r
ed
u
ctio
n
in
PAR
im
p
r
o
v
es
th
e
s
tab
ilit
y
an
d
r
eliab
ilit
y
of
th
e
g
r
id
an
d
r
ed
u
ce
s
th
e
ele
ctr
icity
co
s
t
f
o
r
th
e
co
n
s
u
m
er
s
.
I
m
p
r
o
v
em
en
t
of
PAR
u
s
in
g
HGPS
O
AE
MS
is
s
h
o
wn
in
Fig
u
r
e
1
3
a
n
d
T
a
b
le
4
.
T
ab
le
4
.
T
h
e
p
er
f
o
r
m
a
n
ce
of
EMS
on
th
e
b
asis
of
PAR
P
A
R
R
e
d
u
c
t
i
o
n
in
P
A
R
(
i
n
%)
W
i
t
h
o
u
t
A
E
M
S
W
i
t
h
H
G
P
S
O
A
E
M
S
2
.
8
6
1
.
6
4
43
3
.
6
4
2
.
1
6
41
3
.
1
1
2
.
0
7
33
3
.
6
9
2
.
4
6
33
3
.
6
3
2
.
3
7
35
Evaluation Warning : The document was created with Spire.PDF for Python.