Indonesi
an
Journa
l
of El
ect
ri
cal Engineer
ing
an
d
Comp
ut
er
Scie
nce
Vo
l.
23
,
No.
3
,
Septem
ber
2021
, pp.
13
06
~
13
14
IS
S
N:
25
02
-
4752, DO
I: 10
.11
591/ijeecs
.v
23
.i
3
.
pp
13
06
-
13
14
1306
Journ
al h
om
e
page
:
http:
//
ij
eecs.i
aesc
or
e.c
om
Loa
d
sheddin
g schem
e bas
ed metaheuri
sti
c techni
qu
e for power
system
contr
olled
islandin
g
N.
Z
. Sah
aruddi
n
1
, I
.
Z
aina
l
Ab
idi
n
2
, H.
Mokhlis
3
, E
.
F.
Sha
ir
4
1
,4
Facul
t
y
of Electrical E
ng
ine
er
i
ng,
Univer
si
ti T
e
knika
l
Malay
si
a M
el
aka,
Duri
an Tungga
l
,
Me
la
k
a,
Ma
lay
si
a
2
Depa
rtment of
El
e
ct
ri
ca
l
and
E
l
ec
tron
ic
s E
ng
ineeri
ng,
Univer
si
ti
Te
nag
a
Nasion
al,
Kaj
ang, Selang
or,
Mal
a
y
s
ia
3
Depa
rtment of
El
e
ct
ri
ca
l
Eng
in
ee
ring
,
Fa
cul
t
y
o
f
Engi
n
ee
ring
,
Univer
sit
y
of
Ma
l
a
y
a, Kua
l
a Lum
pur,
Mal
a
y
s
ia
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
Ma
y
10
,
2021
Re
vised
Ju
l
2
1
,
2021
Accepte
d
Aug
4
,
2021
Pow
er
s
y
stem
-
c
ontrol
le
d
isla
nd
i
ng
is
one
of
the
m
it
iga
ti
on
techn
ique
s
ta
k
en
to
pre
v
ent
b
la
ck
outs
during
seve
re
out
age
.
Th
e
i
m
ple
m
ent
at
ion
o
f
cont
rol
led
isla
nding
wi
ll
l
ea
d
to
the
fo
rm
at
ion
of
few
isl
ands,
that
c
an
o
per
ate
as
a
stand
-
al
on
e
island.
How
eve
r,
som
e
of
the
se
isl
a
nds
m
a
y
not
b
e
bal
an
ce
d
in
te
rm
s
of
gene
ration
and
loa
d
afte
r
the
isla
nd
ing
e
xec
ut
ion.
Th
ere
f
ore
,
a
goo
d
loa
d
shedd
ing
sc
heme
is
req
u
ire
d
to
m
eet
th
e
po
wer
balanc
e
cr
iterion
so
that
it
c
an
op
era
t
e
as
a
ba
la
n
ce
d
st
an
d
-
al
one
isla
nd
.
Thus,
t
his
p
ape
r
deve
lop
ed
a
loa
d
shedding
sche
m
e
-
base
d
m
et
ahe
urist
ic
s
t
ec
hniqu
e
namel
y
m
odifi
ed
discre
t
e
evol
u
tionar
y
progra
m
m
ing
(MD
EP)
te
chn
ique
to
d
e
te
rm
ine
th
e
opti
m
al
amount
of
loa
d
to
be
sh
ed
in
orde
r
to
produc
e
balanc
ed
stand
-
al
on
e
isla
nds.
The
d
ev
el
oped
lo
ad
shed
ding
sche
m
e
is
eva
luated
and
va
l
ida
t
ed
with
two
othe
r
loa
d
shedding
te
ch
nique
s
which
are
conv
ent
ion
al
EP
an
d
exha
ustiv
e
sea
rc
h
te
chni
qu
es.
Th
e
IEE
E
30
-
bus
a
nd
39
-
bus
te
st
sy
stems
were
uti
lized
for
thi
s
purpose.
Th
e
r
esult
s
prove
s
th
at
th
e
lo
ad
she
dding
base
d
MD
EP
te
chni
qu
e
produc
es
the
opti
m
al
amount
of
loa
ds
to
be
shed
with
shortest
computat
ion
al
ti
m
e
as
compare
d
with
the
conve
n
ti
on
al
EP
and
exha
ustiv
e
se
arch t
e
chni
ques
.
Ke
yw
or
d
s
:
Ba
la
nced
isl
a
nd
MDEP l
oad s
he
dd
i
ng tech
nique
Mi
ni
m
al
p
ow
e
r
im
balance
Power bal
a
nce
crit
erion
Power sy
ste
m
i
sla
nd
i
ng
This
is an
open
acc
ess arti
cl
e
un
der
the
CC
B
Y
-
SA
l
ic
ense
.
Corres
pond
in
g
Aut
h
or
:
N.
Z
. S
a
haru
dd
i
n
Faculty
of Elec
tric
al
En
gin
eer
ing
Un
i
ver
sit
i Te
knikal M
al
ay
sia
Mel
aka
76100 D
ur
ia
n Tu
nggal, Mel
a
ka,
Mal
ay
sia
Em
a
il
: nu
rza
w
ani@
utem
.ed
u.m
y
1.
INTROD
U
CTION
Con
tr
olled
isl
and
i
ng
is
e
xe
cuted
to
save
the
powe
r
sy
stem
fr
om
sever
e
casca
di
ng
fail
ur
es
a
nd
black
ou
ts
[
1]
.
O
ne
of
t
he
im
po
rtant
crit
erio
n
co
ns
i
der
e
d
afte
r
it
s
im
plem
entat
ion
is
the
power
ba
la
nc
e
crit
erion
[
2]
.
Each
isl
an
d
f
orm
ed
du
ri
ng
isl
and
in
g
e
xec
ution
m
us
t
fu
lfil
le
d
the
power
balance
c
rite
rion.
I
n
oth
e
r
w
ords
,
th
e
total
power
ge
ner
at
io
n
in
ea
ch
isl
an
d
m
us
t
be
s
uffici
ent
to
cat
er
the
total
load
dem
and
.
This
is
ver
y
i
m
po
rt
ant
for
su
cce
ss
fu
l
im
ple
m
entat
ion
of
isl
andi
ng
exe
cutio
n
[3]
.
H
oweve
r,
there
are
po
s
sible
to
form
un
balanc
ed
isl
and
s
(the
tot
al
load
is
m
or
e
than
the
total
gen
erati
on)
afte
r
isl
and
i
ng
e
xecu
ti
on.
I
n
su
c
h
cases,
it
is
very
i
m
po
rtant
to
balance
t
he
isl
ands
to
a
vo
i
d
any
f
ur
the
r
ou
t
ages
that
c
ou
l
d
cause
the
isl
a
nd
s
to
colla
ps
e.
Th
us
,
a
load
s
he
dd
i
ng
schem
e
is
need
e
d
to
bala
nce
the
is
la
nds
by
rem
ov
in
g
the
necessa
ry
load
s.
Thro
ugh
t
his,
t
he
isl
an
ds
will
b
e
balance
d
a
nd a
ble to o
per
a
te
as stan
d
-
al
one isl
an
ds
.
Ther
e
are
num
ber
of
co
ntr
olled
isl
an
di
ng
te
ch
niques
propose
d
by
pr
e
vious
resea
rche
r
s
i
n
rece
nt
ye
ars.
So
m
e
of
these
te
ch
niq
ue
s
are
o
rder
ed
b
i
nar
y
d
eci
sion
d
ia
gram
s
(
OBD
D
)
[
4]
,
[5]
,
slo
w
co
he
ren
c
y
appr
oach
es
[6]
-
[9]
,
li
near
pro
gr
am
m
ing
te
chn
i
qu
e
s
[10
]
-
[12]
,
m
et
aheu
risti
c
te
ch
niques
s
uc
h
as
bin
a
ry
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
Load
sh
e
ddin
g sche
me b
as
ed
meta
heuri
sti
c tec
hn
i
qu
e
for
power syste
m
c
ontroll
ed…
(
N.
Z. Sah
ar
ud
din
)
1307
par
ti
cl
e
s
war
m
opti
m
iz
at
ion
(
BPSO
)
[13]
,
a
ng
le
m
odulate
d
par
ti
cl
e
s
warm
op
tim
iz
a
ti
on
(A
MPS
O
)
[
14]
,
ta
bu
search
al
gorithm
[15]
.
Deta
il
exp
la
natio
n
on
the
isl
an
di
ng
te
ch
niques
can
be
f
oun
d
in
[
16]
.
Th
e
m
ai
n
obj
ect
ive
of
th
ese
isl
and
in
g
t
echn
i
qu
e
s
is
to
determ
ine
the
su
it
a
ble
isl
and
i
ng
st
rategy
for
a
powe
r
s
yst
e
m
netw
ork
.
On
ly
te
chn
iq
ues
propose
d
in
[6]
-
[9]
ha
d
m
entio
ne
d
on
t
he
ut
il
iz
ation
of
U
FLS
loa
d
s
he
dd
i
ng
schem
e
fo
r
islan
di
ng
e
xecu
ti
on.
H
ow
e
ver,
detai
l
exp
la
na
ti
on
is
no
t
pro
vid
e
d.
Ot
her
te
chn
iq
ues
do
not
highli
gh
t
t
he
l
oad
sh
e
ddin
g
t
echn
i
qu
e
util
iz
ed
to
bala
nce
the
isl
ands
if
any
un
balance
d
isl
an
ds
a
re
f
or
m
ed
after
the
im
ple
m
entat
ion
of
the
co
ntr
olled
isl
an
ding.
Howe
ver,
achi
evin
g
balance
d
isl
an
ds
in
te
rm
s
of
gen
e
rati
on a
nd load bala
nce i
s cruci
al
im
po
rtant to e
nsure
a
su
cces
sf
ul isla
nd
i
ng ex
ec
utio
n.
Ther
e
a
re
tw
o
com
m
on
ty
pes
of
l
oad
sh
e
ddin
g
sc
hem
e
a
pp
li
ed
i
n
pow
er
syst
em
area
,
w
hich
a
re
unde
r
volt
age lo
ad
s
he
dd
i
ng
(
UV
L
S)
a
nd
under
fre
q
ue
ncy load
s
he
dd
i
ng
(
UF
LS
)
schem
e
s
[17]
.
The
U
V
LS is
util
iz
ed
to
m
a
i
ntain
the
acce
ptable
le
vel
of
vo
lt
age
i
n
the
power
syst
em
,
w
her
eas
th
e
unde
r
fr
e
quen
c
y
load
sh
e
dd
i
ng
(
UFLS)
is
im
plem
ented
to
av
oi
d
any
fr
e
que
ncy
dr
op
s
in
the
po
we
r
sys
tem
caused
by
powe
r
i
m
balance
[
18]
.
In
t
h
is
rese
arch,
the
de
ve
lop
e
d
loa
d
s
he
dd
i
ng
schem
e
is
base
d
on
the
U
VLS
sc
hem
e.
Gen
e
rall
y,
th
e
U
VLS
sc
hem
e
can
be
i
m
ple
m
ented
us
i
ng
the
e
xh
a
us
ti
ve
sea
rch,
c
onve
ntion
al
or
com
pu
ta
ti
on
al
intel
li
gen
ce
ap
proac
hes.
T
he
exh
a
us
ti
ve
sea
rch
is
a
ba
sic
te
chn
i
qu
e
t
hat
u
se
d
to
dete
rm
ine
th
e
op
ti
m
al
load
to
be
s
he
d
[19]
.
It
com
bin
es
al
l
the
possible
c
om
bin
at
ion
s
of
so
luti
on
s
to
de
te
rm
ine
the
optim
al
a
m
ou
nt
of
loa
ds
t
o
be
s
he
d
(
op
ti
m
al
so
luti
on
)
.
F
or
ex
am
pl
e,
if
t
he
t
otal
num
ber
of
buse
s
avail
able
f
or
lo
a
d
sh
e
dd
i
ng
is
te
n,
t
hen
the
pos
sible
com
bin
at
ion
s
of
s
olu
ti
ons
a
re
2
10
-
1
=
1023.
Thes
e
possible
c
om
bina
ti
on
s
will
increase
as
the
syst
e
m
si
ze
increases.
T
her
e
fore,
this
t
echn
i
qu
e
is
not
relevan
t
an
d
i
m
pr
act
ic
al
fo
r
la
rg
e
scal
e
power
sy
stem
s,
as
it
involves
with
hu
ge
nu
m
ber
of
possible
c
om
bin
at
ion
s
of
so
l
ution
s
.
This
will
cause
the
te
chn
i
qu
e
to
consum
e
lon
ge
r
tim
e
to
find
the
opti
m
a
l
so
luti
on.
For
conven
ti
onal
te
chn
iq
ue,
t
he
fixe
d
a
m
ou
nt
of
the
loa
d
is
sh
e
d
wi
thin
the
ti
m
e
delay
set
ti
ng
w
hen
the
unde
r
volt
age
in
po
we
r
syst
em
is
detect
ed.
Howe
ver,
the
f
ixed
am
ount
is
al
ways
no
t
t
he
best
opti
on,
as
in
ce
rtai
n
case
s,
it
will
en
d
up
with
ov
e
rs
he
dd
i
ng
or
unde
rshed
di
ng
t
he
loa
ds
.
T
his
im
pr
op
e
r
load
s
he
ddin
g
a
m
ou
nt
will
fu
rt
her
le
a
d
to
othe
r
sta
bili
ty
pr
oble
m
s
within
the
pow
er
syst
em
su
ch
as
vo
lt
a
ge
col
la
ps
e
an
d
blackouts
[
20]
.
Mo
reover
,
co
nven
ti
on
al
loa
d
sh
e
ddi
ng
schem
e
is
n
ot
pr
act
ic
al
to
be
app
li
ed
for
toda
y’s
m
od
er
n
a
nd
c
om
plex
power
syst
em
as
this
te
chn
iq
ue
u
na
ble
to
pro
vid
e
the
op
ti
m
al
a
m
o
un
t
of
loa
d
to
be
sh
e
d
during
l
oad
s
he
dding
e
xecu
ti
on
[21]
.
Com
pu
ta
ti
on
a
l
intel
li
gen
ce
a
ppr
oac
hes
ca
n
pro
vid
e
the
opti
m
al
a
m
ou
nt
of
load
to
be
sh
e
d
to
ac
hiev
e
balanced
isl
an
ds
duri
ng
con
t
ro
ll
ed
isl
a
nd
i
ng
e
xec
utio
n.
T
hese
te
ch
ni
qu
e
s
a
re
the
be
st,
rob
us
t
an
d
adap
ta
ble
for
to
util
iz
e
in
com
plex,
non
-
li
near
pro
blem
s
su
ch
as
load
sh
e
ddin
g
pro
blem
.
Me
tah
eu
risti
cs
te
ch
nique
wh
ic
h
is
unde
r
c
om
pu
ta
ti
on
al
intel
li
gen
ce
te
c
hn
i
qu
e
s
a
re u
ti
li
zed
in
t
his r
es
earch
to
deter
m
ine
the o
ptim
al
am
ou
nt
of
l
oa
d
t
o
be
s
he
d,
in
a
ny
unbalance
d
isl
ands fo
rm
ed
dur
i
ng contr
olled isl
an
ding im
plem
entat
ion
.
Seve
ral
num
ber
of
m
et
aheu
risti
c
te
ch
niques
hav
e
bee
n
propose
d
f
or
l
oad
sh
e
dd
ing
sc
hem
e
in
the
powe
r
s
yst
e
m
app
li
cation
.
Am
on
g
th
e
m
are
PSO
te
chn
i
qu
e
[22]
,
firef
ly
al
gorithm
[23]
,
ant
c
olony
op
ti
m
iz
ation
[
24
]
,
gen
et
ic
a
lgorit
hm
[25]
,
ant
li
on
opti
m
iz
er
[26]
an
d
m
ulti
ob
j
ec
ti
ve
par
ti
cl
e
swar
m
op
ti
m
iz
ation
(
MOPS
O)
[
27]
.
All
of
these
load
s
he
dd
i
ng
s
chem
es
deter
m
ine
the
op
ti
m
al
load
an
d
locat
ion
to
be
s
hed
in
order
to
m
ain
ta
in
the
sec
ur
e
powe
r
sy
stem
op
erati
ng
sta
te
.
F
or
con
t
ro
ll
ed
isl
and
i
ng
i
m
ple
m
entat
io
n,
the
re
ar
e
no
detai
le
d
ex
pla
nation
highli
ghte
d
on
t
he
loa
d
s
heddin
g
sc
hem
e
util
iz
ed
with
it
s
im
ple
m
entat
io
n.
T
he
refor
e
,
t
his
pa
pe
r
pr
opos
es
a
ne
w
loa
d
s
heddin
g
sc
hem
e
based
m
etah
eu
risti
cs
te
chn
i
que
,
nam
ely
m
od
ifie
d
discrete
ev
ol
ution
a
ry
progr
a
m
m
ing
(MDE
P)
te
chn
i
qu
e
t
o
determ
ine
the
op
ti
m
a
l
a
m
o
un
t
of
load
to
be
s
he
d
to
obta
in
a
ba
la
nced
sta
nd
-
al
on
e
i
sla
nds
a
fter
co
ntr
olled
isl
and
in
g
im
pl
e
m
entat
ion
.
Mi
ni
m
al
powe
r
im
balance
is use
d
a
s th
e obj
ect
i
ve
f
un
ct
ion
in
th
e
propo
s
ed
te
ch
niqu
e.
2.
DEVELOPE
D
TE
C
HNIQ
UE
Power
gen
e
rati
on
d
efici
t
m
ay
occur
in
any
is
la
nd
s
f
orm
ed
du
ri
ng
c
on
tr
olle
d
isl
and
i
ng.
Th
is
sit
uatio
n
happe
ns
wh
e
n
the
total
po
we
r
ge
ne
rati
on
is
le
ss
than
the
t
otal
load
dem
and.
I
n
orde
r
to
m
a
intai
n
the
powe
r
balance
c
rite
rion
i
n
eac
h
isl
and,
a
loa
d
s
he
dd
i
ng
schem
e
is
require
d.
In
this
pa
per,
a
load
sh
e
ddin
g
s
chem
e
us
in
g
m
od
ifie
d
discrete
ev
olu
t
ion
a
ry
pr
ogra
m
m
ing
(MDE
P)
is
de
velo
pe
d
to
dete
rm
ine
the
optim
al
a
mo
unt
of
load
to
be
rem
ov
e
d
in
orde
r
to
f
ulfil
the
po
wer
balance
c
r
it
erion
in
th
e
isl
and
s
.
The
ge
ne
ral
ste
ps
in
vo
l
ved
i
n
the
load
sh
e
dd
ing
sc
hem
e
is
sh
ow
n
in
Fi
gu
re
1.
Re
ferrin
g
to
Fig
ur
e
1,
i
n
the
fi
rst
ste
p,
the
powe
r
im
balance
in each
isl
an
d
i
s calc
ulate
d usi
ng the
(
1
),
∑
=
∑
−
(
∑
+
∑
)
(1)
w
he
re
is
the
total
powe
r
ge
ne
rat
ion,
is
the
t
otal
loa
d
dem
a
nd
an
d
is
th
e
t
otal
powe
r
l
osse
s
for
a
n
isl
an
d
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
V
ol.
23
, N
o.
3
,
Se
ptem
ber
2
02
1
:
13
0
6
-
13
1
4
1308
Figure
1. Steps
involve
d
i
n
l
oa
d
s
he
dd
i
ng sc
hem
e
If
any
po
wer
i
m
balance
is
n
otice
d
in
the
isl
and,
the
sla
ck
bus
will
act
to
com
pen
sat
e
the
power
i
m
balance.
T
hi
s
proc
ess
will
con
ti
nue
unti
l
the
sla
c
k
bus
re
ached
it
s
m
axim
u
m
l
i
m
it
.
If
t
he
powe
r
im
balance
(power
def
ic
ie
ncy)
sti
ll
occurs,
the
n
ot
her
gen
e
rato
rs
wi
ll
fu
lfil
l
the
po
we
r
im
balance.
In
t
his
ste
p,
the
rem
ai
nin
g
power
im
balance
is
sh
ared
e
qu
al
ly
by
the
gen
e
rators.
T
his
process
c
on
ti
nues
un
ti
l
al
l
the
gen
e
rato
r
s
rea
ch
thei
r
m
axim
u
m
lim
it
.
If
t
he
powe
r
im
balance
is
sti
ll
present
afte
r
al
l
these
ste
ps
ha
ve
bee
n
execu
te
d,
t
hen
the
pr
opos
e
d
load
s
he
dd
i
ng
schem
e
is
init
ia
te
d.
The
im
plem
entat
ion
of
the
l
oad
sh
e
dd
i
ng
schem
e
will
e
ns
ure
the
pow
er
balance
c
rite
rio
n
is
m
et
in
each
isl
and
form
ed.
Det
ai
ls
of
the
pro
pose
d
loa
d
sh
e
dd
i
ng sch
e
m
e w
il
l be e
xpla
ined furthe
r
i
n
the
foll
owin
g sec
ti
on.
3.
METHO
DOL
OGY
In
this
researc
h,
the
pro
po
se
d
m
od
ifie
d
di
screte
ev
olu
ti
onary
pr
ogram
m
ing
(MDE
P)
is
cho
s
e
n
because
the
sel
ect
ion
of
the
buses
durin
g
loa
d
sh
e
ddin
g
act
ion
i
nvolv
e
d
with
discrete
num
ber
s
su
ch
as
bu
s
2,
bu
s
4
a
nd
bus
7.
T
he
pr
opose
d
loa
d
s
heddin
g
sch
em
e
base
d
disc
rete
op
ti
m
iz
a
ti
on
te
chn
iq
ue
ca
pa
ble
to
determ
ine
the
op
ti
m
al
loads
that
nee
ds
to
be
sh
ed
in
a
ny
isl
and
wh
e
re
powe
r
im
balance
is
fo
und.
Det
ai
ls
of
the pr
opos
e
d
te
chn
i
qu
e
are
d
e
scribe
d furthe
r i
n
this sect
i
on.
3.1.
Modifie
d
discrete e
volu
tionar
y
pr
ogr
a
mmi
n
g (M
D
EP)
lo
ad shed
ding
sc
heme
The
m
od
ifie
d
discrete
ev
olu
t
ion
a
ry
progra
m
m
i
ng
(MDE
P)
te
ch
nique
is
us
ed
to
dev
e
lop
the
loa
d
sh
e
dd
i
ng
sc
he
m
e
in
this
rese
arch.
The
proc
ess
involve
d
in
determ
ining
the
optim
al
loads
to
be
sh
e
d
usi
ng
the
MDEP
te
ch
nique
is
il
lustrate
d
by
t
he
flo
wc
har
t
sho
wn
in
Fig
ure
2.
Ba
se
d
on
Fig
ur
e
2,
the
init
ia
l
po
pula
ti
on
s
,
are
ge
ne
rated
ra
ndom
ly
fr
om
the
avail
able
buses
f
or
loa
d
s
heddi
ng
ei
t
her
as
sing
le
or
dif
f
eren
t
com
bin
at
ion
num
ber
of
buses
.
T
he
e
xam
ple o
f
r
a
ndom
ly
g
ener
at
e
d
init
ia
l pop
ulati
on
s
is
sh
ow
n
in
Ta
ble 1
.
Table
1
.
E
xam
ple of
rand
om
i
niti
al
p
opulati
ons
for
M
DEP
l
oad s
heddin
g
s
chem
e
No
.
o
f
r
an
d
o
m
l
y
c
h
o
sen
bu
se
s
1
s
t
bus
2
nd
bus
3
rd
bus
n
th
bus
1
1
2
2
3
3
4
5
6
7
8
9
Start
P
o
wer i
m
b
alan
ce
is
co
m
p
en
sated
b
y
th
e
slack
bus
Po
wer
im
b
alan
ce
is
calculated
in
each
islan
d
Po
wer
b
alan
ce
achi
ev
ed
?
Y
es
End
Po
wer i
m
b
alan
ce
is
co
m
p
en
sated
by
o
th
er
g
en
erators
(sh
are
th
e
lo
ad
d
em
an
d
)
Po
wer
b
alan
ce
ach
iev
ed
?
Y
es
No
No
Load sh
edd
ing
sch
em
e
activ
ated
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
Load
sh
e
ddin
g sche
me b
as
ed
meta
heuri
sti
c tec
hn
i
qu
e
for
power syste
m
c
ontroll
ed…
(
N.
Z. Sah
ar
ud
din
)
1309
Figure
2. MDE
P
loa
d
s
he
dd
i
ng tech
nique
Ba
sed
on
Ta
ble
1,
r
a
ndom
bus,
,
is
ch
os
e
n
f
ro
m
the
total
a
vaila
ble
buses
for
loa
d
sh
e
dding.
O
nc
e
the
rand
om
nu
m
ber
of
init
ia
l
popula
ti
on
s
is
gen
e
rated
,
the
fitness
f
un
ct
i
on
will
further
be
cal
culat
ed
for
each
init
ia
l
po
pu
la
ti
on.
Mi
nim
a
l
po
we
r
im
balance
is
us
ed
as
the
fitness
functi
on
(ob
j
ect
ive
f
unct
ion)
an
d
Eq
uation
1
is
us
e
d
to
c
al
culat
e
this
fi
tness
f
unct
io
n.
The
n,
the
al
gorithm
will
ch
eck
if
there
w
ere
a
ny
po
pu
l
at
ion
s
whose
fitness
f
un
ct
io
n
val
ue
i
s
le
ss
tha
n
the
desire
d
powe
r
i
m
balance
val
ue
.
I
f
t
her
e
is
a
ny
po
pu
la
ti
on
m
eet
with
this
crit
erion
,
it
will
re
-
gen
e
rate
a
new
rand
om
init
i
al
po
pula
ti
on.
On
ly
the
rand
om
init
ia
l
po
pula
ti
on
s
wh
ic
h
the
fitn
ess
functi
on
va
lue
is
sam
e
or
gr
eat
e
r
tha
n
the
desire
d
powe
r
i
m
balance
is
sel
ect
ed
as
the
feasible
init
ia
l
popula
ti
on
s
.
The
n,
t
he
it
erat
ion
sta
rted
by
m
utati
ng
each
bu
s
in
the
ra
ndom
init
ia
l
popula
ti
on
s
,
di
agonall
y
f
ro
m
the
avail
able
bu
s
es
for
loa
d
sh
e
ddin
g.
Ta
ble
2
s
how
s
t
he
e
xam
ple
of
the
m
uta
ti
on
tech
ni
qu
e a
ppli
ed
i
n a dia
gonal
for
m
.
Table
2.
M
utati
on
proces
s in
MDEP
l
oad s
he
dd
i
ng sc
hem
e
Ran
d
o
m
initial
po
p
u
latio
n
A
1
A
2
A
n
1
1
st
b
u
s is rand
o
m
ly
chan
g
ed
r
i1
A
2
A
n
2
2
nd
b
u
s is rand
o
m
l
y
chan
g
ed
A
1
r
i2
A
n
3
3
rd
b
u
s is rand
o
m
ly
chan
g
ed
A
1
A
2
r
in
Start
Gen
erate
rand
o
m
in
itial
p
o
p
u
latio
n
s (parents
),
x
p
Initial
p
o
p
u
latio
n
s,
x
p
is
m
u
tated
d
iag
o
n
ally
to
p
rod
u
ce
th
e
n
ew po
p
u
latio
n
s (of
f
sp
ring
),
x
p
’
u
sin
g
dis
crete
v
alu
e
Ran
k
and
select
th
e
b
est
20
p
o
p
u
latio
n
s,
x
b
accord
in
g
to
the
m
in
i
m
a
l
p
o
wer i
m
b
alan
ce
itr
=
itr
(
ma
x)
?
Y
es
itr
=
itr
+1
Y
es
No
No
Fin
al
list
o
f
the
b
est
20
p
o
p
u
latio
n
s,
x
b
b
End
Ass
ig
n
the
in
itial
p
o
p
u
latio
n
s,
x
p
=
x
b
Nu
m
b
er
o
f
itr
= 1?
Y
es
No
Calcu
late
th
e f
itn
ess
v
alu
e
(m
in
i
m
al
p
o
wer
im
b
alan
ce
v
alu
e)
f
o
r
each
cand
id
ate
in
th
e
in
itial
p
o
p
u
latio
n
s
An
y
po
p
u
latio
n
s
with
b
elo
w des
ired
p
o
wer
im
b
alance
v
alu
e?
Fitn
ess
v
alu
e
(m
in
i
m
al
p
o
wer
im
b
alan
ce
)
f
o
r
each
cand
id
ate
in
the
n
ew po
p
u
latio
n
s,
x
p
’
is
calculated
List
o
f
th
e
in
itial
p
o
p
u
latio
n
s
(parents
),
x
p
Selec
t
the
f
irst
o
p
tim
al
so
lutio
n
f
rom
th
e
f
in
al
list
An
y
po
p
u
latio
n
s
with
b
elo
w des
ired
p
o
wer
im
b
alan
ce
v
alu
e?
Set
th
e
f
itn
ess
v
alu
e
as
a nu
ll
v
alu
e
Y
es
No
Co
m
b
in
e
in
itial
p
o
p
u
latio
n
s,
x
p
an
d
the
n
ew
p
o
p
u
lation
s,
x
p
’
Fin
al
o
p
tim
al
lo
ad
sh
ed
d
in
g
so
lu
tio
n
V
o
ltag
e
at
each
b
u
s
with
in
lim
it?
No
Y
es
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
V
ol.
23
, N
o.
3
,
Se
ptem
ber
2
02
1
:
13
0
6
-
13
1
4
13
10
Re
fer
ri
ng
to
T
able
2,
eac
h
bus
from
the
ra
ndom
init
ia
l
popu
la
ti
on
(A
1,
A
2…
A
n
)
is
m
utate
d
an
d
rep
la
ce
d
by
a
rand
om
value,
r
in
fr
om
the
avail
able
bu
ses
f
or
loa
d
sh
e
dding.
For
exam
ple,
if
the
init
ia
l
popu
la
ti
on
co
ntains
three
buses
,
the
m
utati
on
proces
s
will
produce
a
no
t
her
new
th
ree
m
utate
d
loa
d
she
dd
i
ng
s
olu
ti
on
(
ne
w
popula
ti
on
s
),
a
s
il
lustrate
d
in
Table
2
.
T
he
s
a
m
e
pr
oces
s
w
il
l
be
app
li
ed
f
or
al
l
ge
ne
rated
init
ia
l
popula
ti
on
s
.
The
n,
t
he
fitne
ss
f
unct
ion
f
or
each
ne
w
popula
ti
on
is
cal
culat
ed.
If
a
ny
popula
ti
on
wit
h
fitness
value
lowe
r
than
t
he
desire
d
power
im
bal
ance
is fou
nd,
t
he
n
ull value
is
set
to
the
po
pula
ti
on
,
s
howi
ng
that
t
he
popu
la
ti
on
is n
ot a
fea
sibl
e
load
s
heddin
g
s
olu
ti
on.
Nex
t
,
the
c
ombinati
on
of
the
new
po
pu
la
ti
ons
with
the
init
ia
l
po
pula
ti
on
s
is
carried
out
and
the
best
20
po
pu
la
ti
ons
,
x
b
with
m
ini
m
al
fitness
f
unct
io
n
a
re
ra
nke
d
a
nd
sel
ect
ed
for
t
he
nex
t
it
erati
on.
T
he
process
con
ti
nues u
ntil
it
reached
the
m
axi
m
u
m
nu
m
ber
o
f
it
erati
ons
sp
eci
fied
.
Fin
al
ly
,
the
20
fin
al
best
so
luti
ons,
x
bb
with m
ini
m
al
p
ow
e
r
im
balance are
sel
ect
e
d
a
s the
best loa
d she
dd
i
ng so
l
ution.
The
fi
rst
load
sh
e
dd
i
ng
s
olu
t
ion
from
the
final
best
so
l
ution
s
,
x
bb
is
sel
ect
ed
as
the
optim
al
load
sh
e
dd
i
ng
s
olu
ti
on
a
nd
c
heck
e
d
if
any
buses
vio
la
te
d
the
al
lowa
ble
volt
age
lim
it
s.
The
so
luti
on
is
co
ns
ide
r
e
d
as
the
opti
m
a
l
load
s
he
dd
i
ng
so
luti
on
if
no
bu
s
on
the
isl
a
nd
vio
la
te
s
the
al
lowab
le
vo
lt
age
lim
it
.
Other
wise
,
the
al
gorithm
will
sel
ect
the
nex
t
best
so
l
ution
from
the
final
li
st
and
rep
eat
the
sa
m
e
pr
oces
s
un
ti
l
the
op
ti
m
al
load
sh
ed
ding
so
l
ution
is
obta
ined
fo
r
the
isl
an
d.
By
this
app
r
oac
h,
the
op
ti
m
a
l
load
sh
e
dd
i
ng
so
luti
on
will
be o
btained
for t
he
loa
d she
dding sc
hem
e.
4.
RESU
LT
S
A
ND
D
IS
C
USS
ION
The
I
EEE
30
-
bu
s
an
d
39
-
bu
s
te
st
syst
e
m
s
are
us
e
d
t
o
dem
on
strat
e
a
nd
valid
at
es
th
e
dev
el
oped
MDEP
l
oad
she
dd
i
ng
te
ch
nique.
Th
e
30
-
bu
s
te
st
syst
e
m
con
sist
s
of
6
ge
ner
at
or
s
an
d
41
tra
ns
m
issi
on
li
nes
wh
e
reas
the
39
-
bus
te
st
syste
m
con
sist
s
of
10
ge
ne
rato
r
and
46
tra
ns
m
i
ssion
li
nes
.
Co
m
pu
ta
ti
on
al
tim
e
and
op
ti
m
al
a
m
ou
nt
of
l
oa
d
to
be
sh
e
d
are
the
m
ai
n
tw
o
c
rite
ria
co
ns
ide
red
in
this
validat
io
n
process.
T
his
w
or
k
us
es
the
M
AT
LAB
R2
015a
on
a
n
In
te
l®
C
or
e
™
i7
-
55
00U
CPU
at
2.4
0GHz
with
8GB
of
R
AM
to
cod
e
t
he
dev
el
op
e
d
te
c
hniq
ue.
Tw
o
cas
e stu
dies of c
ontr
olled isl
an
di
ng strategy a
re
validat
ed
in
t
his p
a
rt.
4.1.
Ca
se
I: I
EE
E 30
-
bus
s
ys
te
m
In
Ca
s
e
I
,
t
he
con
t
ro
ll
ed
isl
and
i
ng
strat
e
gy
is
obta
ined
by
sp
li
tt
ing
the
sy
stem
into
tw
o
sta
nd
-
al
one
isl
and
s
base
d
on
t
heir
c
oher
ent
gro
up
of
ge
ner
at
or
s
,
G
1
=
{1,
2,
5,
13}
and
G
2
=
{
8,
11},
fo
ll
owin
g
crit
ic
al
li
ne
outa
ge
of
Line
1
-
2.
The
op
ti
m
al
isl
and
ing st
rate
gy
f
or
Ca
se I
is
sho
w
n
in
Ta
ble 3.
Table
3.
O
pti
m
al
isl
and
in
g
st
r
at
egy f
or
ca
se
I
(
befor
e
loa
d
s
hed
)
Islan
d
s
Bu
ses
I
n
f
o
Activ
e Power
(
M
W
)
Po
wer
I
m
b
alan
ce
(M
W
)
Bef
o
re
lo
ad
sh
ed
Total Pg
en
Total Plo
ad
Islan
d
1
1
-
5
,
1
2
-
1
8
,
2
3
3
2
7
.423
1
7
0
.400
-
Islan
d
2
6
-
1
1
,
1
9
-
2
2
,
2
4
-
30
7
7
.94
6
1
1
3
.000
3
5
.05
4
Accor
ding
to
the
Ta
ble
3,
it
i
s
f
ound
that
Isl
and
2
is
no
t
ba
la
nce
afte
r
c
ontrolle
d
isl
a
nd
i
ng
e
xecu
ti
on
as
the
total
lo
ad,
P
load
is
m
or
e
tha
n
the
tot
al
gen
e
rati
on
powe
r,
P
gen
.
T
he
po
wer
im
balance
in
this
case
is
35.05
4
M
W.
T
her
e
fore,
the
lo
ad
s
he
dd
i
ng
sc
hem
e
is
requir
ed
t
o
ob
ta
in
th
e
opti
m
a
l
a
m
ou
nt
of
l
oad
to
be
s
he
d
in
Islan
d
2.
He
re,
the
pro
pose
d
MDE
P
loa
d
sh
e
dd
i
ng
sc
he
m
e
is
util
iz
ed
fo
r
t
his
pur
pose
.
The
e
ff
e
ct
ive
ness
of
the
pro
po
se
d
MDEP
loa
d
she
dd
i
ng
sc
hem
e
is
fu
rthe
r
co
m
par
ed
and
va
li
dated
with
two
oth
e
r
ty
pes
of
loa
d
sh
e
dd
i
ng
sche
m
e
wh
ic
h
are
conve
ntion
al
E
P
an
d
e
xha
us
ti
ve
sea
rch
te
ch
niques.
The
to
ta
l
nu
m
ber
of
bu
s
es
el
igible
f
or
l
oa
d
s
heddi
ng
i
n
I
sla
nd
2
-
Ca
se
I
is
10
wh
ic
h
a
r
e
bus
7,
bus
8,
bu
s
10
,
bus
19,
bus
20,
bus
21,
bus
24, bus 2
6,
bu
s
29, b
us
30.
Ta
ble 4 s
umm
arize t
he results
obta
ined
fro
m
this a
naly
sis.
Table
4.
Res
ult
of
op
ti
m
al
a
mo
unt
of loa
d
to
be
s
he
d b
et
wee
n
the
c
on
ven
ti
on
al
EP,
exha
ust
ive s
earc
h, an
d
MDEP
te
c
hn
i
que
s
for
c
ase
I
Po
we
r
i
m
b
alan
ce
= 35
.05
4
M
W
Techn
iq
u
e
Op
ti
m
al a
m
o
u
n
t of
load
to b
e sh
ed
(
MW)
Bu
s(es)
Co
m
p
u
tatio
n
al ti
m
e (
sec
)
Co
n
v
en
tio
n
al E
P
3
5
.7
1
9
,21
,24
5
.40
0
9
Exh
au
stiv
e sear
ch
3
5
.1
1
9
,20
,21
,2
6
,29
7
1
.04
2
2
MDE
P
3
5
.1
1
9
,20
,21
,2
6
,29
4
.98
6
9
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
Load
sh
e
ddin
g sche
me b
as
ed
meta
heuri
sti
c tec
hn
i
qu
e
for
power syste
m
c
ontroll
ed…
(
N.
Z. Sah
ar
ud
din
)
1311
Re
fer
ri
ng
t
o
T
able
4,
t
he
e
xhaustive
sea
rch
and
M
DEP
l
oa
d
s
heddin
g
te
c
hn
i
qu
e
s
capa
bl
e
to
obta
in
a
bette
r
opti
m
a
l
a
m
ou
nt
of
loa
d
to
be
s
hed
whic
h
are
35.
1
M
W
as
com
par
e
d
to
c
onve
ntio
nal
EP
te
ch
nique
that
ob
ta
ine
d
35.
7
M
W
.
T
he
co
nventio
nal
E
P
un
a
ble
t
o
pro
du
ce
the
best
op
ti
m
al
value
du
e
to
the
us
a
ge
of
Gau
s
sia
n
f
un
ct
ion
w
hich
res
ul
t
in
sm
all
cha
ng
e
s
durin
g
m
utati
on
proce
ss
in
t
he
c
onve
nt
ion
al
EP
.
Alth
ough
the
e
xh
a
us
ti
ve
searc
h
a
ble
t
o
pro
du
ce
the
sam
e
op
ti
m
a
l
val
ue
as
the
MDEP
l
oad
s
heddin
g
te
ch
niq
ue
,
i
t
requires
a
lo
nger
com
pu
ta
ti
on
a
l
tim
e
of
71.
0422
sec
onds
to
pro
du
ce
the
optim
al
a
m
ou
nt
of
loa
d
to
be
sh
e
d
com
par
ed
with
the
MDEP
te
c
hn
i
qu
e
w
hich
on
ly
re
quires
4.9
869
sec
onds
to
pro
duce
the
sam
e
op
tim
a
l
value
.
The
ex
ha
us
ti
ve
search
ge
ne
r
al
ly
co
m
bin
es
al
l
the
po
ssibl
e
com
bin
at
ion
s
of
avai
la
ble
bu
s
es
in
the
syst
e
m
t
o
determ
ine
the
op
ti
m
al
so
luti
on.
Th
e
longer
com
pu
ta
ti
on
al
tim
e
is
req
uire
d
for
this
te
ch
nique
as
the
syst
e
m
siz
e
increases
(m
or
e
possible
com
bin
at
ion
s
of
s
olu
ti
ons)
.
The
refor
e
,
th
e
pro
posed
M
DEP
l
oa
d
s
he
dd
i
ng
te
chn
iq
ue
is
t
he
be
st
lo
ad
s
heddin
g
sche
m
e
as
it
can
determ
ine
the
op
ti
m
al
load
s
heddin
g
am
ou
nt
wit
h
sh
ort
est
ti
m
e c
om
par
ed
t
o oth
er tech
niques il
lustrate
d
i
n
Ta
ble 4.
The
MD
EP
lo
a
d
s
heddin
g
is
t
hen
util
iz
ed
to
sh
e
d
the
op
ti
m
al
a
m
ou
nt
of
l
oad
i
n
I
sla
nd
2
in
orde
r
to
m
eet
th
e
pow
er
balance
c
rite
rio
n
in
the
isl
and
.
Ta
ble
5
sh
ows
the
optim
al
isl
and
ing
strat
egy
a
fter
lo
a
d
sh
e
dd
i
ng
e
xec
ution
(35.1
00
M
W
)
in
Islan
d
2,
w
he
re
the
total
gen
e
rati
on
power,
P
gen
(
78.
517
M
W)
is
now
m
or
e
than
the
total
load
,
P
load
(77.9
00
M
W).
Th
us
,
Islan
d
2
can
now
opera
te
as
a
bala
nce
d
sta
nd
-
al
one
i
sla
nd
su
ccess
fu
ll
y.
Table
5.
O
pti
m
al
isl
and
in
g
st
r
at
egy f
or
ca
se
I
(
afte
r
loa
d
s
he
d
)
Islan
d
s
Bu
ses
I
n
f
o
Activ
e Power
(
M
W
)
Load
sh
ed
(M
W
)
Af
ter
lo
ad
sh
ed
Total Pg
en
Total Plo
ad
Islan
d
1
1
-
5
,
1
2
-
1
8
,
23
1
8
9
.446
1
7
0
.400
-
Islan
d
2
6
-
1
1
,
1
9
-
2
2
,
2
4
-
30
7
8
.51
7
7
7
.90
0
3
5
.10
0
4.2
.
C
as
e I
I
:
IEE
E 3
9
-
b
us s
yste
m
In
Ca
s
e
II
,
the
con
t
ro
ll
ed
isl
a
nd
i
ng
strat
egy
is
ob
ta
ine
d
by
sp
li
tt
ing
the
sy
stem
into
two
sta
nd
-
al
one
isl
and
s
ba
sed
on
their
co
he
rent
gr
ou
p
of
ge
ne
rators,
G
1
=
{
30,
31,
32,
37,
38
,
39}
an
d
G
2
=
{33,
34,
35
,
36
}
,
fo
ll
owin
g
c
riti
cal
li
ne
outa
ge
of Line
13
-
14. T
able
6
s
hows
the opti
m
al
is
l
and
i
ng strate
gy for
Case
II.
Table
6.
O
pti
m
al
isl
an
ding st
r
at
egy f
or
ca
se
I
I
(
be
fore loa
d s
hed
)
Islan
d
s
Bu
ses
I
n
f
o
Activ
e Power
(
M
W
)
Po
wer
I
m
b
alan
ce
(M
W
)
Bef
o
re
lo
ad
sh
ed
Total Pg
en
Total Plo
ad
Islan
d
1
1
-
1
5
,
1
8
,
2
5
,
2
6
,
2
8
-
3
2
,
3
7
-
39
4
0
2
1
.6
6
8
4
1
3
4
.1
3
0
1
1
2
.462
Islan
d
2
16
-
1
7
,
1
9
-
2
4
,
2
7
,
3
3
-
36
2
1
3
4
.1
9
8
2
1
2
0
.1
0
0
-
Re
fer
ri
ng
t
o
th
e
Table
6,
it
is
fou
nd
that
Isla
nd
1
is
not
balance
after
isl
an
ding
exec
utio
n
as
the
total
load,
P
load
is
m
or
e
t
han
the
t
ot
al
gen
er
at
ion
powe
r,
P
gen
.
T
he
power
im
ba
la
nce
in
t
his
c
ase
is
112.4
62
M
W
.
Ther
e
f
or
e,
a
l
oa
d
s
he
dd
i
ng
sc
hem
e
is
requir
ed
to
ob
ta
in
th
e
opti
m
a
l
a
m
ou
nt
of
loa
d
t
o
be
s
he
d
in
Isla
nd
1.
Her
e
,
the
pro
po
s
ed
MD
EP
load
s
heddin
g
schem
e
is
util
iz
ed
fo
r
this
purpose.
T
he
eff
ect
ive
ness
of
the
pro
po
se
d
M
D
EP
loa
d
s
he
dding
sc
hem
e
is
furthe
r
c
om
par
ed
an
d
valid
at
ed
with
tw
o
oth
e
r
ty
pes
of
loa
d
sh
e
dd
i
ng
sche
m
e
wh
ic
h
are
conve
ntion
al
E
P
an
d
e
xha
us
ti
ve
sea
rch
te
ch
niques.
The
to
ta
l
nu
m
ber
of
bu
s
es
el
igible
f
or
l
oa
d
s
heddi
ng
in
I
sla
nd
1
-
Ca
se
I
I
is
15
w
hich
a
re
bu
s
1,
bu
s
3,
bus
4,
bus
7,
bus
8,
bus
9,
bu
s
12,
bu
s
15,
bus
18
,
bus
25,
bus
26,
bus
28,
bus
29,
bu
s
31,
bu
s
39.
Ta
ble
7
s
u
m
m
arize
the
r
esults
obta
ine
d
from
this analy
sis.
Table
7.
Res
ult
of
op
ti
m
al
a
mo
unt
of loa
d
to
be
s
he
d b
et
wee
n
the
co
nve
nti
on
al
EP,
ex
ha
ust
ive searc
h, an
d
MDEP
al
gorith
m
s f
or
case
II
Po
wer
i
m
b
alan
ce
=1
1
2
.46
2
M
W
Techn
iq
u
e
Op
ti
m
al a
m
o
u
n
t of
load
to b
e sh
ed
(
MW)
Bu
s(es)
Co
m
p
u
tatio
n
al ti
m
e (
sec
)
Co
n
v
en
tio
n
al E
P
1
1
5
.33
1
,
1
2
,
3
1
8
.89
5
7
Exh
au
stiv
e sear
ch
1
1
2
.63
1
,
9
,
1
2
8
9
4
8
6
.72
6
4
MDE
P
1
1
2
.63
1
,
9
,
1
2
3
.19
3
5
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
V
ol.
23
, N
o.
3
,
Se
ptem
ber
2
02
1
:
13
0
6
-
13
1
4
1312
Accor
ding
to
Table
7,
sim
il
a
r
in
Ca
se
I,
the
exh
a
us
ti
ve
sea
rch
a
nd
MD
EP
load
sh
e
ddin
g
te
chn
iq
ues
are
ca
pab
le
to
obta
in
a
bette
r
op
ti
m
al
a
m
o
un
t
of
loa
d
to
be
sh
e
d
w
hic
h
a
re
112.6
3
M
W
as
com
par
ed
to
conve
ntion
al
E
P
te
ch
nique
th
at
ob
ta
ine
d
115.33
M
W.
The
us
a
ge
of
Gaus
sia
n
f
unct
ion
is
the
m
ai
n
con
tr
ibu
to
r
of
inacc
ur
at
e
optim
al
value
ob
ta
ined
in
the
conve
ntion
al
E
P.
Alth
ough
the
exh
a
us
ti
ve
se
arch
can
pro
duce
the
sam
e
op
tim
a
l
value
as
t
he
MDEP
te
ch
nique,
howe
ver,
it
ta
ke
s
a
longe
r
com
pu
ta
ti
on
a
l
tim
e
of
89
486.7
26
4
seco
nd
s
to
pro
du
ce
the
optim
al
so
luti
on
c
om
par
ed
to
t
he
MDEP
te
c
hn
i
que
wh
ic
h
on
ly
ta
kes
3.193
5
s
econds
to
pr
oduce
t
he
sam
e
op
tim
al
so
l
ution.
T
his
is
beca
us
e
th
e
ex
haust
ive
s
earch
te
ch
niqu
e
com
bin
es
al
l
the
po
s
sib
le
com
bin
at
ions
of
a
vaila
ble
buses
in
t
he
syst
em
to
determ
ine
the
optim
al
so
luti
on
wh
ic
h
inc
reas
es
the
com
pu
ta
ti
on
al
tim
e
as
the
s
yst
e
m
s
iz
e
increases.
T
her
e
f
or
e
,
both
co
nv
entional
EP
a
nd
e
xh
a
us
ti
ve
search
te
chn
iq
ues
a
re
no
t
s
uitable
t
o
be
us
e
d
as
t
he
loa
d
s
heddi
ng
schem
e
in
this
resea
rch.
Hen
ce
,
the
pro
po
s
ed
MDEP loa
d
she
dd
i
ng
tec
hn
i
que is pro
ven
to
b
e the b
est
loa
d
sh
e
ddin
g
sch
e
m
e as it
can d
et
erm
ine the optim
al
load
s
he
dd
i
ng
a
m
ou
nt
with
the
sho
rtest
co
m
pu
ta
ti
on
al
tim
e
co
m
par
ed
to
co
nv
e
ntio
na
l
EP
an
d
ex
ha
us
ti
ve
search
tech
niques.
The
M
DEP
l
oa
d
s
he
dd
i
ng
t
he
n
util
iz
ed
to
s
hed
the
optim
a
l
a
m
ou
nt
of
lo
ad
in
Isla
nd
1
in
ord
er
t
o
m
eet
the
pow
er
ba
la
nce
c
rite
rio
n
in
that
i
sla
nd.
Ta
ble
8
show
s
the
op
tim
a
l
isl
and
in
g
strat
e
gy
afte
r
loa
d
sh
e
dd
i
ng
exec
ution
(
112.6
30
M
W
)
in
Isla
nd
1,
w
here
the
total
ge
ner
at
io
n
powe
r,
P
gen
(
4063.
821
M
W)
is
no
w
m
or
e
than
the
total
load,
P
load
(4021.5
0
MW)
.
Th
us,
Isla
nd
1
ca
n
no
w
op
e
rate
as
a
balance
d
sta
nd
-
al
one
isl
and
s
uccess
f
ully
.
Table
8.
O
pti
m
al
isl
and
in
g
st
r
at
egy f
or
ca
se
I
I
(
a
fter l
oad s
he
d
)
Islan
d
s
Bu
ses
I
n
f
o
Activ
e Power
(
M
W
)
Load
sh
ed
(M
W
)
Af
ter
lo
ad
sh
ed
Total Pg
en
Total Plo
ad
Islan
d
1
1
-
1
5
,
1
8
,
2
5
,
2
6
,
2
8
-
3
2
,
3
7
-
39
4
0
6
3
.8
2
1
4
0
2
1
.5
0
1
1
2
.630
Islan
d
2
16
-
1
7
,
1
9
-
2
4
,
2
7
,
3
3
-
36
2
1
3
4
.1
9
8
2
1
2
0
.1
0
0
-
5.
CONCL
US
I
O
N
This
pa
per
pro
po
s
ed
a
new
MDEP
ba
sed
l
oad
s
he
dd
i
ng
s
chem
e
fo
r
co
nt
ro
ll
ed
isl
an
ding
ap
plica
ti
on.
The
pur
pose
of
this
schem
e
is
to
determ
ine
the
op
ti
m
al
a
m
ou
nt
of
loa
d
to
be
s
hed
in
order
to
ach
ie
ve
balance
d
sta
nd
-
al
one
isl
an
ds
after
isl
an
ding
i
m
ple
m
entat
i
on.
T
h
e
ef
fect
iveness
of
the
pro
po
se
d
sc
hem
e
is
validat
ed
with
two
di
ff
e
ren
t
te
chn
i
qu
e
s
w
hich
are
co
nvent
ion
al
EP
an
d
e
xh
a
us
ti
ve
sea
r
ch
te
chn
i
ques,
us
in
g
IEEE
30
-
bus a
nd
39
-
bu
s test
syst
e
m
s
. Th
e resu
lt
s p
r
oved
t
hat p
r
opos
e
d M
DEP
loa
d
she
dd
i
ng
sc
hem
e
capab
le
on
d
et
erm
ining
the
optim
al
a
m
ou
nt
of
lo
ad
to
be
s
hed
with
lowe
r
com
pu
ta
ti
on
al
tim
e
as
co
m
pa
red
t
o
conve
ntion
al
E
P
an
d
e
xha
us
ti
ve
sea
rc
h
te
ch
niques
as
pr
es
ented
in
Ca
se
I
an
d
Ca
se
I
I,
r
especti
vely
.
A
s
su
c
h,
MDEP
loa
d
s
he
dd
i
ng
schem
e
is
pro
po
se
d
as
the
best
sc
he
m
e
to
be
im
ple
m
ented
after
t
he
co
ntro
ll
ed
isl
and
i
ng
execu
ti
on,
to
fulfil
the
powe
r bala
nce
crit
eri
on in
a
ny isl
an
ds
wh
e
re l
oad
sh
e
dd
i
ng is re
quire
d.
ACKN
OWLE
DGE
MENTS
The
a
uthor
w
ou
l
d
li
ke
t
o
e
xpress
he
r
a
ppreciat
io
n
to
Mi
nistry
of
H
igh
e
r
E
du
cat
i
on
Ma
la
y
sia
(MO
HE)
via
F
RGS
G
ra
nt
(FR
GS
/1/
2018/TK0
7/UNI
TE
N/01
/
1)
t
o
f
und
t
his
resea
rch
.
I
n
ad
diti
on,
the
aut
ho
r
would
li
ke
to
thank
U
niv
e
rsiti
Tekn
ikal
Ma
la
ysi
a
M
el
aka
(U
TeM
)
and
U
niv
e
rsiti
Tenag
a
Na
sion
al
(UNI
T
EN
) for
their s
upport i
n t
his r
e
searc
h.
REFERE
NCE
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Sahar
udd
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olut
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eg
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Indon
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ems
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esi
a
n
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E
le
c Eng &
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m
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an
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”
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em
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m
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on
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,
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,
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e
Sw
arm
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t
ion
Based
De
fen
sive
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in
g
Of
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rge
Sc
ale
Pow
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iu,
W
.
L
iu,
D.
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es
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c
y
an
d
Angle
Modula
te
d
Particl
e
Sw
arm
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ti
on
base
d
isla
nd
in
g
of
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rge
-
s
cale
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s
y
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t
ems
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l
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ge
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te
d
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t
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R.
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“
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ch
for
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s
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ng
base
d
o
n
volt
ag
e
stabili
t
y
inde
x
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r
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F.
HE,
Y.
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K.
W
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Y.
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and
S.
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“
Optim
al
loa
d
shedding
strat
eg
y
b
ase
d
on
par
ti
c
le
sw
arm
opti
m
iz
ation,
”
in
8th
Inte
rnation
al
Confe
renc
e
on
Adv
ance
s
in
P
ower
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m
Control,
Operation
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ment
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AP
SCOM 2009)
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2009
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X.
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“
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l
y
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m
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ms
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C.
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ti
on
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nt
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“
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:
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ent
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it
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Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
V
ol.
23
, N
o.
3
,
Se
ptem
ber
2
02
1
:
13
0
6
-
13
1
4
1314
BIOGR
AP
HI
ES OF
A
UTH
ORS
Nu
r
Z
aw
ani
Sah
arudd
in
rec
e
ive
d
her
Diplo
m
a
in
El
ec
trica
l
Engi
nee
ring
a
nd
B.
Eng.
in
El
e
ct
ri
ca
l
Enginee
ring
(Indust
r
ia
l
Pow
er)
fro
m
Univer
siti
T
ekni
ka
l
Malay
s
ia
Mal
a
y
s
ia,
Malay
s
ia
in
20
05
and
2008,
respe
ctively
.
Th
en,
she
rec
e
ived
her
M.E
ng
.
i
n
El
ec
t
rical
Engi
ne
eri
ng
fro
m
Univer
sit
y
of
Malay
a
(UM
)
and
the
Ph.D.
d
egr
ee
from
Univer
siti
Te
na
g
a
Nasiona
l,
Malay
sia
,
i
n
2020.
Curre
ntly
she
i
s
a
lectur
er
in
the
Fa
cul
t
y
o
f
El
e
ct
r
ic
a
l
Engi
ne
eri
ng,
Un
ive
rsiti
T
ekni
ka
l
Malay
si
a
Mal
a
y
sia
,
Ma
lay
sia
.
Her
rese
arc
h
intere
sts
ar
e
in
the
area
r
el
a
te
d
t
o
power
s
y
s
te
m
ana
l
y
sis,
power s
y
stem i
sl
andi
ng
,
and
ren
ewa
bl
e ene
rg
y
.
I
z
ham
Z
ainal
A
bid
in
rec
ei
ved
h
is
Ordina
r
y
Na
tional
Diploma
in
Engi
nee
r
ing
fro
m
Covent
r
y
Te
chn
ic
a
l
Coll
e
ge
in
1994.
Th
en,
he
re
ce
iv
ed
his
B.
Eng.
in
El
e
ct
ri
ca
l
Engi
n
ee
ring
from
Univer
sit
y
of
So
utha
m
pton,
UK
,
in
1997
and
Ph
.
D.
degr
ee
in
Elec
tr
ic
a
l
Eng
ine
e
ring
(Pow
er)
from
Strat
hcly
d
e
Univer
sit
y
,
U.
K.,
in
2002.
Curre
ntly
he
is
a
Profess
or
in
the
D
epa
rtment
of
El
e
ct
ri
ca
l
and
E
le
c
troni
cs
Engi
n
ee
r
ing
,
Univ
ersi
ti
T
ena
g
a
Nasio
nal
,
Malay
si
a.
He
is
a
lso
a
Senior
Mem
ber
(80617173)
of
IEE
E
Pow
er
and
Ene
rg
y
Societ
y
.
His
rese
arc
h
intere
sts
are
in
the
area
r
el
a
te
d
to
prot
ec
t
ion,
vo
lt
ag
e
stab
il
i
t
y
,
r
ene
wal
en
erg
y
i
m
pac
t,
re
-
conf
ig
ura
ble
grids
and
power
s
y
st
e
m
stabi
lit
y
studi
es.
Haz
li
e
Mokhlis
(Senior
Mem
b
er,
I
EEE)
r
ec
e
i
ved
th
e
B
.
Eng.
and
M.
Eng.
Sc
.
degr
e
es
in
el
e
ct
ri
ca
l
engi
n
e
eri
ng
from
the
Univer
sit
y
of
Malay
a
(UM
),
Malay
s
ia,
in
19
99
and
2002,
respe
ctively
,
an
d
the
Ph.D.
d
egr
ee
from
The
Un
ive
rsit
y
of
Ma
n
c
heste
r,
Man
che
s
te
r,
U
.
K.,
in
2009.
He
is
cur
r
ent
l
y
a
Profess
or
with
the
Dep
artm
ent
of
El
e
ct
r
ical
Eng
ine
er
ing,
Univer
sit
y
o
f
Malay
a
(UM
),
a
nd
al
so
the
He
a
d
of
the
UM
Pow
er
and
Ene
rg
y
S
y
stem
(UM
PES
)
rese
arc
h
.
His
rese
arc
h
inte
rests
inc
lude
f
au
lt
locati
on
,
distribution
aut
om
ati
on,
power
s
y
ste
m
prote
ct
ion
,
and
ren
ewa
ble energ
y
.
He
is also a
Char
te
r
ed
Eng
ine
er in
th
e
U.K.
and
a
Profess
iona
l
Eng
inee
r
in
Mal
a
y
s
ia.
E
z
re
en
Far
ina
Sh
air
rec
ei
v
ed
her
B.
Eng
in
Elec
tri
c
al
-
Control
&
Instrum
ent
at
i
on
and
M.E
ng
in
Elec
tri
c
al
-
Mec
hat
ron
ic
s
&
Autom
at
ic
Con
trol
from
th
e
U
nive
rsiti
T
eknologi
Malay
si
a
(UTM)
in
2009
and
2011,
r
espe
ctively
.
Th
en,
she
r
ecei
ve
d
her
Ph.D.
in
El
e
ct
roni
cs
Engi
ne
eri
ng
fro
m
the
Univer
sit
i
Putra
Mal
a
y
si
a
in
2019.
Curr
entl
y
,
she
is
a
seni
or
le
c
ture
r
in
Univer
siti
Te
kn
i
kal
Malay
si
a
Mela
k
a
and
the
sec
re
ta
r
y
for
IEEE
-
EMBS
Malay
sia
Chapt
er
.
From
2018
unti
l
now,
she
is
one
of
the
t
ec
hni
cal
edi
torial
bo
ard
f
or
the
Int
ern
atio
nal
Journal
of
Hum
an
and
T
ec
hnolog
y
Int
er
ac
t
ion.
Her
rese
arc
h
in
te
rests
are
o
n
biom
edi
c
al
signa
l
proc
essing,
m
a
c
hine
le
arn
ing, a
n
d
IoT.
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