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m
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p
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[
1
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.
Dem
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DR
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r
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[
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[
3
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Gen
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4
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[
5
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FAC
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STA
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am
ically
co
n
t
r
o
llin
g
p
o
we
r
f
l
o
w.
R
esp
o
n
s
e
tim
es
o
f
th
ese
d
ev
ices
is
f
ast
b
u
t
th
ey
r
eq
u
ir
e
s
ig
n
if
ican
t
ca
p
ital
i
n
v
estme
n
t
[
6
]
.
Simu
ltan
eo
u
s
em
p
lo
y
m
en
t
o
f
g
en
e
r
atio
n
r
esch
ed
u
lin
g
a
n
d
in
ce
n
tiv
e
-
b
ased
DR
p
r
o
g
r
am
s
f
o
r
c
o
n
tin
g
e
n
cy
co
n
g
esti
o
n
m
a
n
ag
em
e
n
t
is
p
r
o
p
o
s
ed
in
[
7
]
.
Ko
h
a
n
et
a
l
.
[
8
]
h
av
e
d
e
m
o
n
s
tr
ated
th
at
co
o
r
d
in
ated
DR
an
d
g
en
e
r
atio
n
r
esch
ed
u
lin
g
ca
n
ef
f
icien
tly
co
n
tr
o
l
co
n
g
esti
o
n
wh
il
e
m
ee
tin
g
tech
n
ical
an
d
ec
o
n
o
m
ic
g
o
als
b
y
p
r
es
en
tin
g
a
m
u
lti
-
o
b
jectiv
e
tr
an
s
m
is
s
io
n
co
n
g
esti
o
n
m
an
ag
e
m
en
t
p
ar
ad
i
g
m
th
at
tak
es
DR
p
r
o
g
r
am
s
a
n
d
g
en
e
r
atio
n
r
esch
e
d
u
lin
g
in
to
ac
c
o
u
n
t.
A
h
y
b
r
id
I
PS
O
-
I
GSA
(
i
m
p
r
o
v
e
d
PS
O
with
im
p
r
o
v
e
d
g
r
av
itatio
n
al
s
ea
r
ch
alg
o
r
ith
m
)
f
o
r
co
n
g
esti
o
n
m
an
ag
em
en
t,
im
p
lem
en
tin
g
th
e
af
f
ec
tab
ilit
y
f
ac
to
r
co
n
ce
p
t
f
o
r
o
p
tim
al
r
esch
ed
u
lin
g
o
f
g
e
n
er
ato
r
ac
tiv
e
p
o
wer
o
n
b
o
th
I
E
E
E
3
0
-
b
u
s
an
d
I
E
E
E
1
1
8
-
b
u
s
s
y
s
tem
s
is
p
r
o
p
o
s
ed
in
[
9
]
.
T
h
e
o
b
jecti
v
es
o
f
r
ed
u
cin
g
lo
s
s
es,
v
o
ltag
e
d
ev
iatio
n
,
a
n
d
n
etwo
r
k
c
o
s
ts
ar
e
co
n
s
id
er
e
d
f
o
r
o
p
tim
izatio
n
,
a
n
d
th
e
p
r
o
p
o
s
ed
m
eth
o
d
is
a
p
p
lied
f
o
r
a
3
3
-
b
u
s
s
y
s
tem
in
[
1
0
]
.
T
h
e
m
u
ltio
b
jectiv
e
co
n
g
esti
o
n
m
an
ag
em
en
t
p
r
o
b
lem
is
ad
d
r
ess
ed
b
y
u
s
in
g
g
en
er
atio
n
r
es
ch
ed
u
lin
g
an
d
lo
a
d
s
h
ed
d
in
g
b
ased
o
n
v
o
ltag
e
-
d
ep
en
d
e
n
t
lo
ad
m
o
d
eli
n
g
,
t
h
e
p
r
o
p
o
s
ed
m
o
d
el
is
test
ed
o
n
an
I
E
E
E
3
0
b
u
s
s
y
s
tem
.
Stre
n
g
th
Par
eto
E
v
o
lu
tio
n
a
r
y
Alg
o
r
ith
m
2
+(
S
PEA2
+)
is
ad
o
p
ted
f
o
r
m
u
ltio
b
jectiv
e
co
n
g
esti
o
n
p
r
o
b
lem
in
[
1
1
]
.
A
co
m
b
in
atio
n
o
f
r
esch
ed
u
lin
g
o
f
g
en
er
at
o
r
s
an
d
DSM
u
s
in
g
v
ar
io
u
s
DR
p
r
o
g
r
am
s
is
an
aly
ze
d
f
o
r
c
o
n
g
esti
o
n
m
an
ag
em
en
t.
T
h
e
co
n
g
esti
o
n
m
an
ag
em
en
t
p
r
o
b
lem
is
m
o
d
eled
in
th
e
GAM
S
en
v
ir
o
n
m
en
t
an
d
s
o
lv
ed
b
y
u
s
in
g
th
e
C
ONOPT
s
o
lv
er
.
Am
o
n
g
all
th
e
d
if
f
e
r
en
t
ty
p
e
s
o
f
DR
p
r
o
g
r
am
s
,
th
e
b
est
-
s
u
ited
p
r
o
g
r
am
f
o
r
co
n
g
esti
o
n
m
an
ag
e
m
en
t
is
f
o
u
n
d
b
y
Pra
jap
ati
an
d
Ma
h
ajan
[
1
2
]
.
T
h
e
s
ch
em
e
f
o
r
co
s
t
-
ef
f
ec
tiv
e
co
n
g
esti
o
n
m
an
ag
em
en
t
f
o
r
s
m
ar
t
g
r
id
s
i
s
in
v
esti
g
ated
b
y
co
n
s
id
er
in
g
th
e
o
p
tim
al
m
ix
o
f
g
en
er
atio
n
r
esch
ed
u
lin
g
an
d
DR
o
f
p
ar
ticip
atin
g
b
u
s
es.
An
t
co
lo
n
y
o
p
tim
izatio
n
with
a
f
u
zz
y
s
atis
f
y
in
g
tech
n
iq
u
e
is
a
d
o
p
ted
t
o
o
b
tain
a
co
m
p
r
o
m
is
e
s
o
lu
tio
n
f
r
o
m
a
s
et
o
f
Par
eto
o
p
tim
al
s
o
lu
tio
n
f
o
r
m
u
ltio
b
jectiv
e
co
n
g
esti
o
n
p
r
o
b
lem
in
[
1
3
]
.
T
o
r
ed
u
ce
th
e
im
p
ac
t
o
n
p
o
wer
ex
ch
an
g
es,
im
p
r
o
v
e
p
o
r
tab
ilit
y
,
an
d
r
ed
u
ce
co
n
g
es
tio
n
s
im
u
ltan
eo
u
s
im
p
lem
en
tatio
n
o
f
DR
p
r
o
g
r
a
m
s
alo
n
g
with
th
e
o
p
tim
al
lo
ca
tio
n
o
f
win
d
p
o
wer
p
la
n
ts
at
th
e
b
u
s
is
p
r
o
p
o
s
ed
.
B
ased
o
n
th
e
co
m
p
u
tatio
n
o
f
AT
C
,
PTDF,
an
d
DDCOP
F,
th
e
b
est
b
u
s
f
o
r
im
p
lem
en
ti
n
g
DR
p
r
o
g
r
am
s
is
d
eter
m
in
ed
a
n
d
e
v
alu
ated
o
n
t
h
e
I
E
E
E
3
9
b
u
s
[
1
4
]
.
DR
im
p
l
em
en
tatio
n
in
c
o
llab
o
r
atio
n
w
ith
r
etail
elec
tr
icity
p
r
o
v
id
e
r
s
f
o
r
co
n
g
esti
o
n
m
a
n
ag
em
en
t
b
ased
o
n
m
ar
k
et
m
ec
h
an
is
m
s
f
o
r
th
e
n
atio
n
al
g
r
id
is
p
r
o
p
o
s
ed
.
Stack
elb
er
g
g
am
e
th
eo
r
y
is
ad
o
p
ted
f
o
r
id
en
tify
in
g
th
eir
o
p
tim
al
d
em
an
d
s
in
th
e
DR
m
ar
k
e
t
an
d
th
en
u
s
ed
b
y
in
d
ep
en
d
en
t
s
y
s
tem
o
p
er
ato
r
s
(
I
SO)
to
an
aly
ze
g
r
id
co
n
g
esti
o
n
b
y
au
t
h
o
r
s
in
[
1
5
]
.
B
ased
o
n
two
m
etr
ics,
i.e
.
,
n
u
m
b
er
o
f
h
o
u
r
s
o
f
lo
ad
i
n
g
v
io
latio
n
s
an
d
t
h
e
n
u
m
b
er
o
f
co
n
s
u
m
er
s
ex
p
e
r
ien
cin
g
u
n
d
er
v
o
ltag
e,
th
e
p
er
f
o
r
m
an
ce
o
f
v
ar
i
o
u
s
DR
s
tr
ateg
ies f
o
r
r
eliev
in
g
th
e
co
n
g
e
s
tio
n
is
in
v
esti
g
ated
in
[
1
6
]
.
Fo
r
allev
iatin
g
tr
a
n
s
m
is
s
io
n
co
n
g
esti
o
n
,
a
B
ac
ter
ia
f
o
r
ag
i
n
g
o
p
tim
izatio
n
a
p
p
r
o
ac
h
b
a
s
ed
o
n
a
b
id
d
in
g
s
tr
ateg
y
f
o
r
g
en
er
ato
r
s
is
p
r
esen
ted
in
[
1
7
]
.
A
d
is
tr
i
b
u
tio
n
co
n
g
esti
o
n
p
r
ice
-
b
ased
m
ar
k
et
m
ec
h
an
is
m
to
allev
iate
d
is
tr
ib
u
tio
n
s
y
s
tem
co
n
g
esti
o
n
is
p
r
o
p
o
s
ed
i
n
[
1
8
]
.
A
n
L
MP
-
b
ased
m
o
d
el
i
s
u
s
ed
to
co
m
p
u
te
d
ir
ec
t
co
n
g
esti
o
n
p
r
ices,
wh
ic
h
ac
cu
r
ately
r
ef
lect
r
ea
l
c
o
n
g
e
s
tio
n
co
s
ts
an
d
g
u
i
d
e
th
e
s
ch
e
d
u
lin
g
o
f
r
esp
o
n
s
es
to
elec
tr
icity
d
em
an
d
.
I
n
s
m
ar
t
d
is
tr
ib
u
tio
n
s
y
s
tem
s
,
PT
DF
ar
e
u
tili
ze
d
to
im
p
lem
en
t
DR
s
tr
ateg
ies
f
o
r
co
n
g
esti
o
n
m
an
a
g
em
en
t.
Haq
u
e
et
a
l.
[
1
9
]
em
p
lo
y
ed
PTDF
ca
lcu
latio
n
s
to
o
p
tim
ally
id
en
tify
b
u
s
es
th
at
ca
n
p
ar
ticip
ate
in
DR
to
r
eliev
e
co
n
g
esti
o
n
.
A
co
n
g
esti
o
n
m
a
n
ag
em
en
t
tech
n
iq
u
e
f
o
r
lo
w
-
v
o
ltag
e
r
esid
en
tial
n
etwo
r
k
s
u
s
in
g
b
o
th
d
ir
ec
t
an
d
in
d
ir
ec
t
c
o
n
tr
o
l
DR
p
r
o
g
r
am
s
h
as
also
b
ee
n
p
r
o
p
o
s
ed
.
Fu
r
th
e
r
m
o
r
e
,
r
esear
ch
er
s
in
[
2
0
]
in
tr
o
d
u
c
ed
an
ef
f
ec
tiv
e
m
eth
o
d
o
lo
g
y
f
o
r
id
en
tify
i
n
g
o
p
tim
al
b
u
s
es
an
d
tim
in
g
f
o
r
im
p
lem
en
tin
g
DR
p
r
o
g
r
am
s
at
th
e
b
est
lo
ca
tio
n
s
.
No
n
lin
e
ar
p
r
o
g
r
am
m
in
g
is
u
s
ed
f
o
r
s
o
lv
in
g
t
h
e
o
p
tim
al
p
o
wer
f
lo
w
p
r
o
b
lem
.
Ad
a
p
t
iv
e
E
lep
h
an
t
Her
d
Op
tim
iza
tio
n
(
AE
HO)
is
p
r
o
p
o
s
ed
f
o
r
lo
ad
b
alan
cin
g
,
d
em
o
n
s
tr
atin
g
s
u
p
e
r
io
r
p
er
f
o
r
m
an
ce
co
m
p
ar
ed
to
o
th
er
a
p
p
r
o
ac
h
es
in
[
2
1
]
.
Fo
r
allev
i
atin
g
co
n
g
esti
o
n
in
d
is
tr
ib
u
tio
n
n
etwo
r
k
s
with
h
i
g
h
p
e
n
etr
atio
n
o
f
elec
tr
ic
v
e
h
icles,
d
is
tr
ib
u
tio
n
al
L
MP
h
a
s
b
ee
n
p
r
o
p
o
s
ed
in
[
2
2
]
,
[
2
3
]
.
Au
th
o
r
s
h
av
e
p
r
o
p
o
s
ed
r
esch
ed
u
lin
g
g
en
er
atio
n
s
o
u
r
ce
s
in
c
o
n
ju
n
ctio
n
with
DR
p
r
o
g
r
a
m
s
u
s
in
g
a
m
u
ltio
b
jectiv
e
PS
O
ap
p
r
o
ac
h
to
r
ed
u
ce
co
s
ts
an
d
m
itig
ate
tr
an
s
m
is
s
io
n
lin
e
co
n
g
esti
o
n
[
8
]
.
A
g
r
awa
l
et
a
l.
[
2
4
]
h
av
e
p
r
o
p
o
s
ed
a
m
u
lti
o
b
jectiv
e
Salp
s
war
m
alg
o
r
ith
m
ap
p
r
o
ac
h
f
o
r
m
a
n
ag
in
g
co
n
g
e
s
tio
n
u
s
in
g
DR
an
d
d
is
tr
ib
u
ted
g
e
n
er
atio
n
,
v
alid
a
ted
o
n
I
E
E
E
3
0
b
u
s
an
d
1
1
8
b
u
s
s
y
s
tem
s
.
T
ab
le
1
s
h
o
ws
th
e
co
m
p
ar
ativ
e
ad
v
an
tag
es
o
f
p
r
o
p
o
s
ed
wo
r
k
o
v
er
ex
is
tin
g
wo
r
k
s
.
Ou
r
p
r
o
p
o
s
ed
wo
r
k
u
s
es
ME
HO
alg
o
r
ith
m
f
o
r
m
u
lti
-
o
b
jectiv
e
co
n
g
esti
o
n
m
a
n
ag
e
m
en
t
with
co
o
r
d
in
ate
d
g
en
er
a
tio
n
an
d
DR
p
r
o
g
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ab
le
1
.
C
o
m
p
a
r
ativ
e
ad
v
an
ta
g
es o
f
p
r
o
p
o
s
ed
w
o
r
k
A
sp
e
c
t
Ex
i
s
t
i
n
g
T
e
c
h
n
i
q
u
e
s
P
r
o
p
o
se
d
w
o
r
k
I
mp
r
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v
e
m
e
n
t
s
M
o
d
e
l
l
i
n
g
o
f
D
R
P
r
o
g
r
a
ms
S
t
a
t
i
c
El
a
st
i
c
D
y
n
a
mi
c
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t
i
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M
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c
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f
f
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c
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n
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i
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h
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h
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l
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t
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a
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t
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a
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p
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b
e
t
t
e
r
so
l
u
t
i
o
n
T
h
is
wo
r
k
a
n
aly
ze
s
th
e
im
p
ac
t
o
f
DR
p
r
o
g
r
a
m
s
an
d
g
en
e
r
a
tio
n
u
n
ce
r
tain
ties
o
n
k
ey
p
o
w
er
s
y
s
tem
n
etwo
r
k
p
ar
a
m
eter
s
.
A
m
o
d
if
ied
elep
h
an
t
h
er
d
o
p
tim
iza
tio
n
(
ME
HO)
alg
o
r
ith
m
is
ap
p
lied
to
s
o
lv
e
a
m
u
ltio
b
jectiv
e
co
n
g
esti
o
n
m
a
n
ag
em
en
t
p
r
o
b
lem
,
ta
k
in
g
in
to
ac
co
u
n
t
v
a
r
io
u
s
o
p
e
r
atio
n
al
co
n
s
tr
ain
ts
.
DR
s
tr
ateg
ies
s
u
ch
as
d
ir
ec
t
lo
a
d
c
o
n
tr
o
l
(
DL
C
)
,
p
ea
k
lo
ad
s
h
if
tin
g
,
a
n
d
d
y
n
am
ic
p
r
icin
g
s
ch
e
m
es
in
clu
d
in
g
tim
e
-
of
-
u
s
e
(
T
OU)
an
d
r
ea
l
-
tim
e
p
r
icin
g
(
R
T
P)
ar
e
u
tili
ze
d
to
m
a
n
ag
e
co
n
g
esti
o
n
.
T
h
e
n
o
v
elty
o
f
th
is
s
tu
d
y
lies
in
its
p
r
ac
tical
ev
alu
atio
n
o
n
t
h
e
I
E
E
E
3
0
-
b
u
s
s
y
s
tem
,
f
ea
tu
r
in
g
a
tr
ad
e
-
o
f
f
an
aly
s
is
am
o
n
g
c
o
s
t,
em
is
s
io
n
s
,
an
d
th
e
co
n
g
esti
o
n
in
d
ex
(
C
I
)
.
T
h
eo
r
etica
l
n
o
v
elt
y
o
f
th
e
p
r
o
p
o
s
ed
wo
r
k
in
clu
d
es
ad
v
an
ce
d
DR
m
o
d
elin
g
,
en
h
an
ce
d
m
u
ltio
b
jectiv
e
o
p
ti
m
izatio
n
.
T
h
e
alg
o
r
ith
m
ic
n
o
v
elty
in
clu
d
es
ad
ap
tiv
e
cla
n
s
izin
g
an
d
h
y
b
r
id
lo
ca
l
s
ea
r
ch
.
T
h
e
m
o
d
elin
g
n
o
v
elty
in
clu
d
es
in
teg
r
ated
u
n
ce
r
tain
t
y
m
o
d
elin
g
an
d
d
y
n
a
m
ic
co
n
g
esti
o
n
f
o
r
ec
asti
n
g
.
T
h
e
r
esear
ch
co
n
tr
ib
u
tio
n
s
o
f
p
r
o
p
o
s
ed
wo
r
k
ar
e
th
eo
r
etic
al,
m
eth
o
d
o
lo
g
ical
an
d
p
r
ac
ti
ca
l
o
n
e.
T
h
e
m
ain
co
n
tr
ib
u
tio
n
s
o
f
th
is
wo
r
k
a
r
e
i)
Dev
elo
p
m
en
t
o
f
n
o
v
el
m
u
lt
io
b
jectiv
e
o
p
tim
izatio
n
f
r
am
e
wo
r
k
f
o
r
m
an
a
g
in
g
n
etwo
r
k
co
n
g
esti
o
n
ii)
T
r
ip
l
e
o
b
jectiv
e
o
p
tim
izatio
n
wh
i
ch
p
r
o
v
id
es
p
ar
eto
o
p
tim
al
s
o
lu
tio
n
f
o
r
s
y
s
tem
p
lan
n
er
s
iii)
T
h
e
ad
v
a
n
ce
d
m
o
d
elin
g
o
f
DR
lead
s
to
m
o
r
e
r
ea
lis
tic
an
d
ef
f
ec
tiv
e
DR
s
ch
ed
u
lin
g
i
v
)
T
h
e
ME
HO
alg
o
r
ith
m
is
p
r
o
p
o
s
ed
f
o
r
s
o
lv
in
g
co
n
g
esti
o
n
m
an
a
g
em
en
t
p
r
o
b
lem
as
it
ca
n
h
an
d
le
m
ix
ed
in
teg
er
,
n
o
n
lin
ea
r
an
d
m
u
ltio
b
jectiv
e
n
atu
r
e
o
f
p
r
o
b
lem
v
)
R
ig
o
r
o
u
s
test
in
g
an
d
p
e
r
f
o
r
m
an
ce
ev
a
lu
atio
n
o
f
p
r
o
p
o
s
ed
f
r
am
ewo
r
k
is
v
er
if
ied
a
n
d
ev
al
u
ated
o
n
I
E
E
E
3
0
b
u
s
an
d
1
1
8
b
u
s
s
y
s
tem
d
em
o
n
s
tr
atin
g
its
s
u
p
er
io
r
ity
.
T
h
e
p
ap
er
is
o
r
g
an
ize
d
as
f
o
llo
ws:
th
e
f
o
r
m
u
latio
n
o
f
t
h
e
co
n
g
esti
o
n
m
an
ag
e
m
en
t
p
r
o
b
lem
f
o
r
o
p
tim
al
s
ch
ed
u
lin
g
is
d
is
cu
s
s
ed
in
Sectio
n
2
,
i
n
Sectio
n
3
th
e
im
p
lem
en
tatio
n
o
f
th
e
M
E
HO
alg
o
r
ith
m
f
o
r
o
p
tim
al
s
ch
ed
u
lin
g
is
d
escr
ib
ed
,
o
p
tim
izatio
n
r
esu
lts
f
o
r
d
i
f
f
er
en
t
ca
s
e
s
ce
n
ar
io
s
ar
e
d
is
cu
s
s
ed
in
Sectio
n
4
,
an
d
Sectio
n
5
co
n
clu
d
es th
e
p
ap
er
.
2.
F
O
RM
UL
AT
I
O
N
O
F
CO
NG
E
ST
I
O
N
M
A
NAG
E
M
E
N
T
P
RO
B
L
E
M
2
.
1
.
M
o
del
des
cr
iptio
n
T
h
e
co
n
g
esti
o
n
m
an
a
g
em
en
t
b
y
allev
iatin
g
th
e
tr
an
s
m
is
s
io
n
lin
e
o
v
er
lo
ad
in
g
in
co
n
tin
g
en
cy
s
itu
atio
n
s
b
y
m
ea
n
s
o
f
co
o
r
d
in
atin
g
an
d
s
ch
e
d
u
lin
g
th
e
g
en
er
ato
r
s
an
d
DR
is
f
o
r
m
u
la
ted
as
a
n
o
n
lin
ea
r
o
p
tim
izatio
n
p
r
o
b
lem
.
Op
tim
a
l
lo
ca
tio
n
a
n
d
a
p
p
r
o
p
r
iate
s
izin
g
o
f
g
e
n
er
atio
n
s
o
u
r
ce
s
ar
e
g
o
o
d
alter
n
ativ
es
f
o
r
co
n
g
esti
o
n
m
an
a
g
em
en
t.
T
h
e
m
ain
o
b
jectiv
es
co
n
s
id
er
ed
wh
ile
f
o
r
m
u
latin
g
th
e
co
n
g
e
s
tio
n
m
an
ag
em
en
t
p
r
o
b
lem
ar
e
to
m
i
n
im
ize
th
e
co
n
g
esti
o
n
,
th
e
co
s
t
o
f
o
p
er
atio
n
,
an
d
th
e
em
is
s
io
n
lev
el
.
T
h
e
p
r
o
b
lem
o
f
tr
an
s
m
is
s
io
n
co
n
g
esti
o
n
m
an
ag
em
en
t
is
ex
p
r
ess
ed
as
a
m
u
ltio
b
jectiv
e
co
n
s
tr
ain
ed
n
o
n
l
in
ea
r
o
p
tim
izatio
n
p
r
o
b
lem
.
T
h
is
is
d
o
n
e
b
y
c
h
o
o
s
in
g
th
e
o
p
tim
al
m
ix
o
f
th
e
g
en
er
atio
n
r
esch
ed
u
lin
g
an
d
DR
at
p
ar
ticip
atin
g
b
u
s
es.
T
h
e
r
esch
ed
u
lin
g
co
s
ts
f
o
r
r
eliev
in
g
th
e
co
n
g
esti
o
n
with
an
d
with
o
u
t
co
n
s
id
er
i
n
g
th
e
DR
p
r
o
g
r
am
at
d
if
f
er
en
t lo
a
d
lev
els ar
e
c
o
m
p
u
ted
an
d
an
aly
ze
d
.
2
.
2
.
M
o
delin
g
o
f
DR
pro
g
r
a
m
s
DR
r
ef
er
s
to
th
e
ac
tio
n
ta
k
en
b
y
t
h
e
co
n
s
u
m
er
to
m
o
d
if
y
th
e
s
h
o
r
t
-
ter
m
d
e
m
an
d
a
s
p
er
th
e
r
eq
u
ir
em
e
n
ts
o
f
th
e
p
o
wer
u
til
ity
.
C
o
n
s
u
m
er
s
ca
n
p
ar
ticip
ate
in
d
em
an
d
c
h
an
g
e
b
ased
o
n
t
h
e
d
y
n
am
ic
p
o
wer
tar
if
f
s
p
r
o
v
id
ed
o
r
b
ased
o
n
t
h
e
in
ce
n
tiv
es
p
r
o
v
id
ed
b
y
th
e
p
o
wer
u
tili
ty
co
m
p
an
y
.
T
h
e
D
R
p
r
o
g
r
a
m
s
ca
n
b
e
class
if
ied
in
to
two
ty
p
es
p
r
ic
e
p
r
ice
-
b
ased
an
d
in
ce
n
tiv
e
-
b
ased
DR
p
r
o
g
r
a
m
s
[
2
5
]
.
T
O
U,
R
T
P,
an
d
cr
itical
p
ea
k
p
r
icin
g
co
m
e
u
n
d
er
t
h
e
ca
teg
o
r
y
o
f
p
r
ice
-
b
ased
p
r
o
g
r
am
s
.
DL
C
,
in
ter
r
u
p
tib
le/
cu
r
t
ailab
le,
em
er
g
en
c
y
d
em
an
d
r
esp
o
n
s
e
p
r
o
g
r
am
,
an
d
an
cillar
y
s
er
v
ice
m
ar
k
et
p
r
o
g
r
am
ar
e
th
e
in
ce
n
tiv
es
-
b
ased
DR
p
r
o
g
r
am
s
.
T
h
e
s
et
o
f
lo
ad
b
u
s
es
in
th
e
test
s
y
s
tem
s
h
o
u
ld
b
e
s
elec
ted
b
as
ed
o
n
th
ei
r
im
p
ac
t
o
n
th
e
tr
a
n
s
m
is
s
io
n
n
etwo
r
k
lo
ad
in
g
f
o
r
ef
f
ec
tiv
e
im
p
le
m
en
tatio
n
o
f
DR
p
r
o
g
r
am
s
.
As
co
n
s
u
m
er
s
’
co
m
f
o
r
t
is
im
p
ac
ted
d
u
e
to
p
ar
ticip
atio
n
i
n
DR
p
r
o
g
r
am
s
,
s
o
m
e
ec
o
n
o
m
ic
in
ce
n
tiv
es
s
h
o
u
ld
b
e
p
r
o
v
id
ed
b
y
th
e
p
o
wer
u
tili
ty
to
t
h
e
co
n
s
u
m
er
s
.
T
h
e
s
elf
an
d
cr
o
s
s
-
elasticity
f
ac
to
r
s
ar
e
co
n
s
id
er
ed
in
th
e
m
o
d
el
to
co
m
p
u
te
th
e
m
o
d
if
ied
d
em
a
n
d
d
u
e
to
ch
a
n
g
es
in
elec
tr
icity
p
r
ices.
T
h
ese
f
ac
to
r
s
r
elate
c
o
n
s
u
m
er
d
em
a
n
d
to
t
h
e
tim
e
o
f
u
s
ag
e
an
d
elec
tr
icity
p
r
ices.
T
h
e
f
o
r
m
u
latio
n
o
f
th
e
m
o
d
if
ie
d
d
e
m
an
d
is
b
ased
o
n
th
e
c
o
n
s
u
m
er
b
en
e
f
it
f
u
n
ctio
n
,
wh
ich
r
elate
s
th
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
Mu
ltio
b
jective
fr
a
mewo
r
k
fo
r
co
n
g
esti
o
n
ma
n
a
g
eme
n
t t
h
r
o
u
g
h
co
o
r
d
i
n
a
ted
…
(
Ja
ye
s
h
P
r
io
lka
r
)
1691
in
itial
d
em
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d
,
elec
tr
icity
p
r
ic
e,
an
d
elasticity
f
ac
to
r
s
as
d
is
cu
s
s
ed
in
[
2
6
]
,
[
2
7
]
.
Fo
r
m
o
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elin
g
th
e
c
o
n
s
u
m
e
r
d
em
an
d
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b
o
t
h
th
e
r
esp
o
n
s
iv
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an
d
n
o
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-
r
esp
o
n
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iv
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co
n
s
u
m
er
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ad
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ar
e
co
n
s
id
er
e
d
.
T
h
e
m
o
d
if
ied
co
n
s
u
m
er
d
em
an
d
as
p
e
r
th
e
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n
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u
m
er
b
en
ef
it
f
u
n
ctio
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elate
d
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s
elf
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elasticity
f
ac
to
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s
a
n
d
th
e
c
r
o
s
s
-
elastic
ity
f
ac
to
r
.
E
q
u
atio
n
(
1
)
r
e
p
r
esen
ts
th
e
o
v
er
all
ch
an
g
e
i
n
d
em
a
n
d
d
u
e
to
th
e
ef
f
ec
t
o
f
b
o
th
th
e
s
elf
an
d
cr
o
s
s
-
elasticity
f
ac
to
r
s
as
ass
es
s
ed
b
y
[
2
6
]
.
T
h
e
d
y
n
am
ic
lo
ad
m
o
d
el
g
iv
es
th
e
ch
an
g
e
in
co
n
s
u
m
er
s
d
e
m
an
d
p
atter
n
s
with
r
esp
ec
t to
ch
an
g
es in
en
er
g
y
p
r
ices,
co
n
s
id
er
in
g
i
n
ce
n
tiv
es a
s
well
as p
en
alties.
(
)
=
0
(
)
[
(
)
∗
{
0
(
)
−
(
)
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(
)
+
(
)
0
(
)
}
+
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(
,
)
∗
{
0
(
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−
(
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(
)
+
(
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24
=
1
≠
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(
1
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Af
ter
co
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id
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in
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p
r
ices
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n
d
elasticity
f
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ased
p
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em
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p
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th
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r
ice,
p
is
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ew
p
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,
I
n
c
is
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n
ce
n
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f
f
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d
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P
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is
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e
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l(
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e
s
e
lf
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e
an
d
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l(
i,
j)
is
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e
cr
o
s
s
-
elasticity
v
alu
e.
T
h
e
co
s
t
f
o
r
th
e
im
p
le
m
en
tatio
n
o
f
th
e
DR
p
r
o
g
r
am
is
co
n
s
id
er
ed
in
th
e
o
b
jectiv
e
f
u
n
ctio
n
s
f
o
r
th
e
o
p
tim
al
s
ch
ed
u
lin
g
o
f
th
e
g
en
er
atio
n
.
I
n
th
e
ca
s
e
o
f
t
h
e
in
ce
n
tiv
e
-
b
ased
DR
p
r
o
g
r
a
m
s
,
co
n
s
u
m
e
r
s
g
en
er
a
te
r
ev
en
u
es
in
th
e
f
o
r
m
o
f
in
ce
n
tiv
es
af
ter
p
ar
ticip
atin
g
in
th
em
a
n
d
ar
e
co
m
p
u
ted
at
tim
e
p
er
io
d
.
W
h
en
co
n
s
u
m
er
s
d
o
n
o
t
h
o
n
o
u
r
t
h
eir
co
m
m
itm
en
t
as
p
er
th
e
c
o
n
tr
ac
t
s
ig
n
e
d
with
th
e
u
tili
ty
r
eg
ar
d
in
g
d
em
an
d
c
h
an
g
e
a
p
en
alty
is
im
p
o
s
ed
o
n
th
em
b
ased
o
n
th
e
p
en
alty
f
ac
to
r
at
tim
e
p
er
io
d
.
T
h
e
tech
n
ical
p
er
f
o
r
m
a
n
ce
p
a
r
am
eter
s
lik
e
lo
ad
f
ac
to
r
an
d
p
ea
k
co
m
p
en
s
ate
ar
e
co
n
s
id
er
e
d
to
ass
ess
th
e
ef
f
ec
tiv
en
ess
o
f
th
e
im
p
lem
en
tatio
n
o
f
DR
p
r
o
g
r
am
s
wh
ich
m
o
d
if
ies
an
d
im
p
r
o
v
es
th
e
lo
ad
cu
r
v
e.
T
h
e
lo
ad
f
ac
t
o
r
is
th
e
r
atio
o
f
th
e
av
er
ag
e
lo
ad
o
v
e
r
a
g
i
v
en
p
er
io
d
to
th
e
m
ax
im
u
m
d
em
an
d
o
cc
u
r
r
in
g
o
v
er
th
e
s
am
e
p
er
io
d
.
I
t
in
d
icate
s
t
h
e
s
m
o
o
th
n
ess
o
f
th
e
lo
a
d
c
u
r
v
e,
an
d
th
e
id
ea
l
v
alu
e
s
h
o
u
l
d
b
e
1
.
T
h
e
lo
a
d
f
ac
to
r
is
co
m
p
u
ted
as
p
er
(
2
)
.
I
n
th
e
eq
u
atio
n
s
d
0t
is
th
e
d
em
an
d
b
ef
o
r
e
DR
p
r
o
g
r
am
im
p
lem
en
tatio
n
,
d
t
is
th
e
d
em
an
d
at
an
y
tim
e
p
er
i
o
d
,
a
n
d
d
(
t)
max
is
th
e
m
ax
im
u
m
d
e
m
an
d
.
=
∑
=
1
×
(
)
(2
)
2
.
3
.
O
bje
c
t
iv
e
f
un
ct
io
ns
Fo
r
f
o
r
m
u
latin
g
th
e
p
r
o
b
lem
o
f
co
n
g
esti
o
n
m
an
a
g
em
en
t
i
n
a
p
o
wer
s
y
s
tem
n
etwo
r
k
,
th
r
e
e
o
b
jectiv
e
f
u
n
ctio
n
s
ar
e
c
o
n
s
id
er
ed
s
u
b
je
ct
to
a
s
et
o
f
co
n
s
tr
ain
ts
.
2
.
3
.
1
.
T
o
t
a
l
o
pera
t
io
n c
o
s
t
min
im
iza
t
io
n
R
ed
u
cin
g
th
e
to
tal
o
p
er
atio
n
co
s
t
i.e
.
g
e
n
er
atio
n
co
s
t
r
elat
ed
to
th
e
o
p
er
atio
n
o
f
t
h
e
p
o
wer
p
lan
t
g
en
er
ato
r
s
in
te
r
m
s
o
f
th
e
f
u
el
co
s
t a
n
d
DR
o
p
er
atio
n
co
s
t is g
iv
en
as p
er
(
3
)
.
1
=
∑
[
∑
(
2
(
)
+
(
)
+
)
+
∑
(
)
=
1
=
1
]
=
1
(
3
)
W
h
er
e
a
i
,
b
i
,
a
n
d
c
i
a
r
e
th
e
co
s
t c
o
ef
f
icien
ts
o
f
th
e
i
th
g
en
er
at
o
r
.
2
.
3
.
2
.
P
o
wer
pla
nt
e
m
is
s
io
n m
ini
m
iza
t
io
n
T
h
e
s
ec
o
n
d
o
b
jectiv
e
is
to
m
in
im
ize
th
e
em
is
s
io
n
s
f
r
o
m
t
h
e
o
p
er
atio
n
o
f
p
o
wer
p
lan
t
g
en
er
ato
r
s
m
ee
tin
g
th
e
lo
a
d
d
em
a
n
d
,
as p
er
(
4
)
.
2
=
(
∑
2
+
+
=
1
)
(
4
)
W
h
er
e
α
i
,
β
i
,
an
d
γ
i
ar
e
th
e
co
s
t
co
ef
f
icien
ts
o
f
t
h
e
i
th
g
en
e
r
ato
r
.
2
.
3
.
3
.
T
ra
ns
m
is
s
io
n line c
o
n
g
estio
n ind
ex
m
ini
m
iza
t
io
n
T
h
e
f
u
n
ctio
n
to
m
in
im
ize
th
e
co
n
g
esti
o
n
to
im
p
r
o
v
e
th
e
lo
ad
in
g
ca
p
ac
ity
is
ex
p
r
ess
ed
as
p
er
(
5
)
.
T
h
e
o
b
jectiv
e
is
to
in
c
r
ea
s
e
th
e
lo
ad
ab
ilit
y
o
f
th
e
lin
e.
3
=
∑
∑
[
|
(
)
|
[
]
]
∑
=
1
∑
2
=
1
(
5
)
W
h
er
e
S
l
is
th
e
lin
e
lo
ad
in
g
in
MV
A,
S
l
max
is
th
e
m
ax
im
u
m
li
n
e
lo
ad
in
g
lim
it.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
1
6
,
No
.
4
,
Au
g
u
s
t
20
2
6
:
1
6
8
8
-
1
703
1692
2
.
3
.
4
.
Co
m
bin
ed
o
bje
ct
iv
e
f
u
nct
io
n
T
h
e
co
n
g
esti
o
n
m
a
n
ag
em
en
t
p
r
o
b
lem
in
v
o
lv
es
th
r
ee
co
n
f
lictin
g
o
b
jectiv
es
th
at
m
u
s
t
b
e
o
p
tim
ized
s
im
u
ltan
eo
u
s
ly
.
I
t
is
f
o
r
m
u
lat
ed
to
f
in
d
a
s
et
o
f
Par
eto
o
p
tim
al
s
o
lu
tio
n
s
.
Fo
r
m
u
latio
n
allo
ws
th
e
ME
HO
alg
o
r
ith
m
to
e
f
f
ec
tiv
ely
e
x
p
l
o
r
e
th
e
tr
ad
e
-
o
f
f
s
b
etwe
en
e
co
n
o
m
ic,
e
n
v
ir
o
n
m
en
tal,
a
n
d
s
ec
u
r
ity
o
b
jectiv
es
wh
ile
m
an
ag
in
g
co
n
g
esti
o
n
th
r
o
u
g
h
co
o
r
d
in
ated
g
en
er
atio
n
an
d
DR
s
ch
ed
u
lin
g
.
(
⃗
)
=
[
1
(
⃗
)
,
2
(
⃗
)
,
3
(
⃗
)
]
(
6
)
I
n
(
6
)
,
F
1
(
x
)
:
T
o
tal
o
p
er
atio
n
al
co
s
t
(
$
)
,
F
2
(
x
)
:
T
o
tal
em
is
s
io
n
s
(
k
g
)
,
F
3
(
x
)
:
T
r
a
n
s
m
is
s
io
n
co
n
g
esti
o
n
in
d
e
x
.
Dec
is
io
n
v
ar
iab
les
ar
e
g
iv
e
n
b
y
th
e
v
ec
to
r
x
as
p
er
(
7
)
.
T
h
e
d
ec
is
io
n
v
ar
iab
les
ar
e
ac
tiv
e,
r
ea
ctiv
e
p
o
wer
,
a
n
d
m
o
d
if
ied
lo
a
d
d
em
a
n
d
v
alu
es.
⃗
=
(
)
(
7
)
No
r
m
aliza
tio
n
is
n
ee
d
ed
an
d
cr
u
cial
in
co
n
g
esti
o
n
m
a
n
ag
em
en
t
m
u
lti
-
o
b
jectiv
e
o
p
tim
i
za
tio
n
b
ec
au
s
e
th
e
th
r
ee
o
b
jectiv
es
h
av
e
d
if
f
er
en
t
u
n
its
an
d
n
u
m
e
r
ical
s
ca
les.
T
o
en
ab
le
o
p
tim
izatio
n
with
th
e
ME
HO
Alg
o
r
ith
m
,
th
e
n
o
r
m
alize
d
m
u
lti
-
o
b
jectiv
e
p
r
o
b
lem
ca
n
b
e
co
n
v
er
te
d
to
a
s
in
g
le
o
b
jectiv
e
u
s
in
g
weig
h
ted
s
u
m
as
p
er
(
8
)
.
I
n
th
e
eq
u
atio
n
ω
1
,
ω
2
,
a
n
d
ω
3
ar
e
th
e
weig
h
t
f
ac
to
r
s
.
F
1
norm
is
th
e
n
o
r
m
aliz
ed
o
p
er
atio
n
al
co
s
t,
F
2
norm
is
th
e
n
o
r
m
alize
d
p
o
wer
p
lan
t e
m
is
s
io
n
s
co
s
t a
n
d
F
3
norm
is
th
e
n
o
r
m
alize
d
c
o
n
g
esti
o
n
in
d
ex
.
(
⃗
)
=
[
1
1
(
⃗
)
+
2
2
(
⃗
)
+
3
3
(
⃗
)
]
(
8
)
2
.
3
.
5
.
E
qu
a
lity
co
ns
t
ra
ints
Po
wer
B
alan
ce
:
Fo
r
ea
ch
b
u
s
in
th
e
s
y
s
tem
n
etwo
r
k
,
th
e
s
u
p
p
ly
s
h
o
u
ld
m
atch
t
h
e
d
em
a
n
d
ad
ju
s
ted
b
y
DR
.
T
h
e
ac
tiv
e
p
o
wer
b
al
an
ce
an
d
r
ea
ctiv
e
p
o
wer
b
ala
n
ce
in
th
e
n
etwo
r
k
ar
e
th
e
eq
u
ality
co
n
s
tr
ain
ts
o
f
th
e
o
p
tim
izatio
n
p
r
o
b
lem
.
T
h
e
to
tal
r
ea
l
p
o
wer
g
e
n
er
atio
n
m
u
s
t
b
e
b
alan
ce
d
with
to
tal
lo
ad
at
tim
e
t
s
im
ilar
ly
r
ea
ctiv
e
p
o
wer
g
en
er
atio
n
m
u
s
t
b
e
b
alan
ce
d
with
to
tal
r
ea
c
tiv
e
p
o
wer
d
em
a
n
d
.
T
h
e
eq
u
a
tio
n
f
o
r
th
e
ac
tiv
e
an
d
r
ea
ctiv
e
p
o
wer
b
alan
ce
is
g
iv
en
as p
er
(
9
)
an
d
(
1
0
)
r
esp
e
ctiv
ely
wh
er
e
N
b
is
th
e
to
tal
n
u
m
b
er
o
f
b
u
s
es.
∑
=
1
(
)
−
∑
[
0
(
)
+
(
)
+
(
)
]
=
(
)
=
1
∀
(
9
)
∑
=
1
(
)
−
∑
[
0
(
)
+
(
)
+
(
)
]
=
(
)
=
1
∀
(
1
0
)
2
.
3
.
6
.
I
nequ
a
lity
co
ns
t
ra
ints
T
h
e
o
p
er
atin
g
a
n
d
p
h
y
s
ical
lim
its
o
f
th
e
g
en
er
ato
r
s
an
d
tr
an
s
m
is
s
io
n
lin
es
ar
e
th
e
in
eq
u
ality
co
n
s
tr
ain
ts
.
T
h
e
v
o
ltag
e
lim
its
an
d
lin
e
f
lo
w
lim
its
ar
e
o
th
er
co
n
s
tr
ain
ts
.
T
h
e
(
1
1
)
to
(
1
4
)
ar
e
th
e
in
eq
u
ality
co
n
s
tr
ain
ts
co
n
s
id
er
ed
f
o
r
s
o
lv
in
g
th
e
m
u
ltio
b
jectiv
e
o
p
tim
iz
atio
n
p
r
o
b
lem
.
(
1
1
)
(
1
2
)
(
1
3
)
|
(
)
|
≤
(
1
4
)
3.
P
RO
P
O
SE
D
M
E
H
O
AL
G
O
RIT
H
M
I
M
P
L
E
M
E
N
T
AT
I
O
N
F
O
R
O
P
T
I
M
A
L
SCH
E
DULI
NG
T
h
e
elep
h
a
n
t
h
e
r
d
o
p
tim
izatio
n
alg
o
r
it
h
m
is
a
n
atu
r
e
-
i
n
s
p
ir
e
d
m
eth
o
d
p
r
o
p
o
s
ed
b
y
W
an
g
et
a
l.
[
2
8
]
.
T
h
e
alg
o
r
ith
m
is
b
ased
o
n
t
h
e
h
er
d
in
g
b
eh
a
v
io
r
o
f
ele
p
h
an
ts
.
T
h
e
s
ea
r
ch
in
g
a
b
ilit
y
,
c
o
n
v
er
g
en
ce
s
p
ee
d
,
ex
p
lo
r
atio
n
ca
p
a
b
ilit
y
,
ab
ilit
y
to
o
b
tain
s
o
lu
tio
n
s
with
a
s
m
a
ller
n
u
m
b
er
o
f
f
u
n
ctio
n
ev
al
u
a
tio
n
s
,
an
d
p
o
te
n
tial
o
f
f
in
d
in
g
o
p
tim
al
s
o
lu
tio
n
s
ar
e
s
o
m
e
o
f
th
e
f
ea
tu
r
es o
f
E
HO
th
at
ar
e
b
etter
co
m
p
a
r
ed
to
o
t
h
er
n
atu
r
e
-
in
s
p
ir
e
d
alg
o
r
ith
m
s
as
ass
e
s
s
ed
in
[
2
9
]
,
[
3
0
]
.
T
h
e
elep
h
an
t
h
er
d
co
n
s
is
ts
o
f
s
ev
er
al
clan
s
o
f
f
em
ale
elep
h
an
ts
,
th
eir
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
Mu
ltio
b
jective
fr
a
mewo
r
k
fo
r
co
n
g
esti
o
n
ma
n
a
g
eme
n
t t
h
r
o
u
g
h
co
o
r
d
i
n
a
ted
…
(
Ja
ye
s
h
P
r
io
lka
r
)
1693
ca
lv
es,
an
d
m
ale
elep
h
an
ts
.
T
o
o
b
tain
th
e
o
p
tim
al
s
o
lu
tio
n
,
it
m
im
ics
th
e
clan
b
eh
av
i
o
r
i
n
an
elep
h
a
n
t
h
e
r
d
.
T
h
e
Ma
tr
iar
ch
is
th
e
lead
er
o
f
th
e
clan
,
an
d
all
th
e
elep
h
an
t
s
ar
e
u
n
d
er
h
is
in
f
lu
en
ce
.
T
h
e
b
est
s
o
lu
tio
n
in
th
e
h
er
d
o
f
elep
h
a
n
ts
is
b
ased
o
n
th
e
p
o
s
itio
n
o
f
th
e
g
r
o
u
p
o
f
Ma
tr
iar
ch
s
,
an
d
th
e
wo
r
s
t
s
o
l
u
tio
n
is
b
ased
o
n
th
e
p
o
s
itio
n
o
f
a
g
r
o
u
p
o
f
m
ale
ele
p
h
an
ts
.
T
h
e
h
e
r
d
in
g
b
e
h
av
io
r
o
f
th
e
elep
h
an
ts
ca
n
b
e
m
o
d
ele
d
m
ath
em
atica
lly
th
r
o
u
g
h
f
o
u
r
b
asic
s
tep
s
,
wh
ich
in
clu
d
e
i)
U
p
d
atin
g
th
e
p
o
s
itio
n
o
f
ele
p
h
an
ts
in
ea
ch
clan
,
ii)
Up
d
atin
g
th
e
p
o
s
itio
n
o
f
th
e
f
ittes
t
elep
h
an
t
in
ea
ch
cla
n
,
iii)
Sep
ar
atin
g
th
e
wo
r
s
t
m
ale
elep
h
a
n
t
iv
)
C
o
n
v
er
g
en
ce
.
T
h
er
e
ar
e
s
o
m
e
lim
itatio
n
s
o
f
th
e
s
tan
d
ar
d
E
HO
alg
o
r
ith
m
.
I
n
th
e
s
tan
d
ar
d
alg
o
r
ith
m
,
t
h
e
Ma
tr
iar
ch
p
o
s
itio
n
lead
in
g
th
e
clan
is
u
p
d
ated
b
y
f
o
llo
win
g
th
e
m
ea
n
p
o
s
itio
n
o
f
all
th
e
elep
h
an
ts
o
r
av
er
ag
e
in
f
o
r
m
atio
n
r
ec
ei
v
ed
f
r
o
m
th
at
p
ar
ticu
lar
clan
o
n
ly
,
an
d
also
th
e
v
alu
e
o
f
t
h
e
s
ca
le
f
ac
to
r
is
r
an
d
o
m
ly
c
h
o
s
en
,
wh
ich
im
p
ac
ts
th
e
s
o
lu
tio
n
.
T
h
e
p
r
o
ce
s
s
f
o
llo
wed
r
esu
lts
in
a
p
o
o
r
f
it
s
o
lu
tio
n
an
d
d
eter
i
o
r
ates
th
e
m
ea
n
p
o
s
itio
n
o
f
th
e
clan
.
T
h
e
r
esu
lt
o
f
th
is
is
th
at
th
e
h
er
d
is
n
o
t
a
b
le
to
r
ea
ch
t
h
e
g
lo
b
al
b
est
s
o
lu
tio
n
.
I
t
h
as
p
o
o
r
d
iv
er
s
ity
,
lim
ited
ca
p
ab
il
ity
f
o
r
h
an
d
lin
g
th
e
co
m
p
lex
p
o
wer
s
y
s
tem
c
o
n
s
tr
ain
ts
,
an
d
a
s
ca
lab
ilit
y
is
s
u
e
d
u
e
to
th
e
d
if
f
ic
u
lty
o
f
h
an
d
lin
g
h
ig
h
-
d
im
en
s
io
n
al
d
ec
is
io
n
s
p
ac
es.
T
h
ese
lim
itatio
n
s
ar
e
o
v
e
r
co
m
e
in
th
e
ME
HO
al
g
o
r
ith
m
.
T
h
e
ME
HO
alg
o
r
ith
m
is
p
r
o
p
o
s
ed
in
th
is
p
ap
er
as
it
h
as
b
etter
s
ea
r
ch
in
g
ab
ilit
y
,
g
o
o
d
ex
p
lo
r
atio
n
ca
p
ab
ilit
y
,
f
aster
co
n
v
er
g
e
n
ce
,
a
n
d
th
e
ab
ilit
y
to
f
in
d
th
e
b
est
f
it
as
co
m
p
ar
ed
to
o
th
er
n
atu
r
e
-
i
n
s
p
ir
ed
al
g
o
r
ith
m
s
,
as
p
er
[
3
0
]
,
[
3
1
]
.
I
t
h
as
th
e
a
d
v
an
ta
g
e
o
f
en
h
an
ce
d
ex
p
lo
r
atio
n
,
e
f
f
ec
ti
v
e
co
n
s
tr
ain
t
h
a
n
d
lin
g
,
im
p
r
o
v
ed
d
iv
e
r
s
ity
,
b
etter
co
n
v
er
g
en
ce
,
an
d
ad
ap
tiv
e
b
eh
av
io
r
.
At
ea
ch
cu
r
r
e
n
t
p
o
s
itio
n
,
th
e
alg
o
r
ith
m
u
s
es
th
e
clan
u
p
d
atin
g
o
p
er
ato
r
with
t
h
e
Ma
tr
iar
ch
as
th
e
r
esp
o
n
d
in
g
clan
.
T
h
e
alg
o
r
ith
m
th
en
u
s
es a
s
ep
ar
atin
g
o
p
er
a
to
r
to
r
e
p
lace
th
e
p
o
p
u
latio
n
'
s
wo
r
s
t e
lep
h
an
t.
E
ac
h
elep
h
an
t
i
n
th
e
h
e
r
d
is
a
ca
n
d
id
ate
s
o
lu
tio
n
v
ec
to
r
r
ep
r
esen
tin
g
th
e
s
y
s
tem
'
s
s
tate.
T
h
e
u
p
d
ated
p
o
s
itio
n
o
f
th
e
elep
h
an
t
j
i
n
t
h
e
clan
k
i
p
o
s
itio
n
is
g
i
v
en
b
y
(
1
5
)
.
W
h
er
e
r
,
α
,
an
d
β
ar
e
r
an
d
o
m
n
u
m
b
er
a
n
d
s
ca
le
f
ac
to
r
s
r
esp
ec
tiv
ely
.
T
h
e
r
an
d
o
m
n
u
m
b
er
d
ec
id
es
th
e
d
is
tr
ib
u
tio
n
,
s
ca
le
f
ac
to
r
α
in
f
l
u
en
ce
s
th
e
elep
h
an
t
p
o
s
itio
n
,
an
d
β im
p
ac
ts
th
e
b
e
s
t e
lep
h
an
t p
o
s
itio
n
in
t
h
e
b
as
e
E
HO
alg
o
r
ith
m
.
,
,
=
,
+
(
,
−
,
)
×
(
1
5
)
,
,
=
×
,
(
1
6
)
,
=
1
∑
,
=
1
(
1
7
)
=
1
∑
,
=
1
(
1
8
)
T
o
o
v
e
r
co
m
e
t
h
e
lim
itatio
n
s
o
f
th
e
b
ase
E
HO
alg
o
r
ith
m
t
h
e
eq
u
atio
n
s
u
s
ed
f
o
r
th
e
ME
HO
alg
o
r
ith
m
ar
e
m
o
d
if
ied
co
n
s
id
er
i
n
g
v
elo
city
V
j
wh
en
in
itializin
g
th
e
p
o
s
it
io
n
,
R
j
.
T
h
e
in
itializin
g
p
o
s
itio
n
an
d
v
elo
city
ar
e
g
iv
en
as p
er
(
1
9
)
to
(
2
1
)
.
=
×
(
−
)
×
(
1
9
)
=
×
(
−
)
×
(
2
0
)
=
(
−
(
)
)
(
2
1
)
At
ea
ch
n
ew
g
en
e
r
atio
n
,
th
e
v
elo
city
o
f
th
e
ele
p
h
an
ts
is
u
p
d
ated
b
y
(
2
2
)
.
,
,
=
×
,
+
(
,
−
,
)
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