Int
ern
at
i
onal
Journ
al of
P
ower E
le
ctr
on
i
cs a
n
d
Drive
S
ystem
(I
J
PE
D
S
)
Vo
l.
11
,
No.
4
,
Decem
be
r
2020
, p
p.
1958
~
1965
IS
S
N:
20
88
-
8694
,
DOI: 10
.11
591/
ij
peds
.
v
1
1
.i
4
.
pp
1958
-
1965
1958
Journ
al h
om
e
page
:
http:
//
ij
pe
ds
.i
aescore.c
om
An
im
pr
oved m
eth
od for effi
cient cont
rolling o
f the dynami
c
vo
lt
age r
estore
r to enh
ance th
e power
quali
ty
i
n the
distri
bution
system
Ali B
as
im
M
ohamme
d
1
, M
ohd
Aifaa M
ohd Ari
ff
2
,
S
of
i
a Najw
a R
amli
3
1
Faculty
of
Elec
tri
c
al
and
El
e
ct
r
onic
Engi
ne
eri
n
g,
Univer
si
ty Tu
n
Hus
s
ei
n
Onn
Mala
ysia
,
Ma
la
y
sia.
2
,3
Facul
ty
of
Co
mput
er
Scie
n
ce
and
Inform
at
i
on
Te
chno
logy, Uni
ver
siti
Tun
Hus
sein
Onn Ma
la
ysi
a,
Ma
la
ysi
a.
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
Dec
1
1
, 201
9
Re
vised
Feb
12
, 2
0
20
Accepte
d
J
um
3
, 2
0
20
Thi
s
pap
er
rep
r
ese
nts
a
low
co
mpl
exity
of
the
DV
R
cont
rol
le
r
by
using
a
robust
diffe
ren
ti
at
or
n
amed
as
appr
oximate
cl
assic
al
slid
ing
mode
diffe
ren
ti
a
tor
(
ACS
MD
)
to
over
come
the
dra
wba
ck
of
the
l
inear
diffe
ren
ti
a
tor.
Additi
ona
ll
y
,
ut
il
i
ze
a
nonl
ine
a
r
sl
idi
ng
var
ia
b
le
n
am
ed
arcta
n
func
ti
on
(sigmo
id
func
ti
on)
in
orde
r
to
ke
ep
t
he
m
agni
tud
e
o
f
the
loa
d
volt
ag
e
appr
oxi
ma
t
el
y
1pu,
the
THD
at
the
st
anda
rd
l
eve
l
,
i
mprove
th
e
robustness
prope
rty
and
m
ai
nt
ai
n
th
e
ste
ady
-
state
err
or
withi
n
a
smal
l
bound
.
The
most
im
por
ta
nt
issues
of
th
e
power
sys
te
m
net
work
are
p
o
wer
qual
i
ty,
the
major
probl
em
s
of
power
q
ual
it
y
are
vol
tage
sag
/swell
an
d
har
moni
cs
which
ca
use
tr
ip
ping
or
m
al
fun
c
ti
oning
of
the
e
quipm
ent.
Thi
s
pape
r
give
s
an
e
conom
i
c
an
d
eff
e
ctive
solu
t
ion
by
u
ti
l
iz
ing
t
he
dyna
mi
c
vol
t
age
r
estore
r
to
pro
tect
th
e
sensiti
ve
loa
ds
f
rom
the
disturb
anc
es
th
at
happ
ene
d
in
th
e
sys
te
m
such
as
v
olt
ag
e
sag/swell
and
har
mon
ic
s.
The
proposed
sy
stem
of
th
e
DV
R
is
inve
stiga
t
ed
by
u
tili
zi
ng
MA
TL
AB
/Sim
uli
nk
to
e
nhanc
e
the
disturba
nc
es
wh
en
i
t
o
cc
urs
in
a
distri
bu
ti
on
sys
te
m.
The
pr
ese
nts
DV
R
mode
l
is e
v
al
u
ated
by
u
ti
l
iz
i
ng
s
ome
of
th
e
popul
ar
vol
ta
ge
sag
in
dic
es
.
Ke
yw
or
d
s
:
Dynamic
volt
age
resto
rer
PI
D
contr
oller
Power q
ualit
y
Sli
din
g m
od
e
c
on
t
ro
ll
er
Vo
lt
age
sa
g/swe
ll
This
is an
open
acc
ess arti
cl
e
un
der
the
CC
BY
-
SA
l
ic
ense
.
Corres
pond
in
g
Aut
h
or
:
M
oh
d Aifaa
Mohd
Ar
i
ff
Faculty
of Elec
tric
al
an
d
Ele
ct
ronic E
ng
i
neeri
ng
,
Un
i
ver
sit
y T
un Hussein
On
n
M
al
aysia
(
UT
HM)
,
86400,
M
al
ays
ia
.
Emai
l:
aifaa@
uth
m
.edu.
my
1.
INTROD
U
CTION
In
a
distrib
utio
n
s
ys
te
m,
po
w
er
qu
al
it
y
has
at
tract
ed
resea
rch
e
rs
a
nd
op
e
rators'
at
te
ntio
n
du
e
to
the
increme
nt
of
t
he
power
el
ect
ronic
eq
uipme
nt
an
d
the
no
n
-
li
near
loa
d
util
iz
at
ion
[
1].
T
he
powe
r
qual
it
y
issue
s
su
c
h
as
volt
ag
e
sag
a
nd
vo
lt
a
ge
s
well
aff
ect
the
pe
rfo
rma
nc
e
of
the
c
ons
ume
r
se
ns
it
ive
e
qu
i
pm
e
nt.
T
hu
s,
it
is
necessa
ry
to
i
mpro
ve
the
qu
al
it
y
of
t
he
po
wer
deli
ver
e
d
to
the
us
er
.
In
pract
ic
e,
t
her
e
are
va
rio
us
m
et
hods
repor
te
d
to im
pro
ve
the
pow
er quali
ty in
t
he
d
ist
rib
utio
n
ne
twork
. One of
the so
l
utions is t
he
util
iz
at
ion
of the
dynamic
volt
age
resto
rer
(
D
VR)
t
o
mit
igate
the
ha
rm
on
i
cs
an
d
co
mp
e
ns
at
e
for
t
he
volt
age
sa
g
a
nd
swell
durin
g
po
wer
sy
ste
m
ope
rati
on
[2
-
4].
T
he
DV
R
is
util
iz
ed
by
c
ontr
olli
ng
the
vo
lt
ag
e
sou
rce
c
onne
ct
ed
in
series
bet
ween
the
loa
ds
an
d
the
gri
d.
It
is
use
d
to
re
gu
la
te
any
distu
r
bances
that
aff
ect
sensiti
ve
loa
ds
[5
-
7].
In
th
e
li
te
rature,
there
a
re
se
ve
ral
typ
es
of
D
VR
co
ntr
ollers
repor
te
d,
s
uc
h
as
feed
-
f
orwa
r
d
an
d
fee
dbac
k
[8],
fu
zz
y
a
nd a
dapt
ive prop
or
ti
on
al
-
integr
al
-
f
uz
zy
c
on
t
ro
ll
ers
[9].
Sli
din
g
m
ode
c
on
t
ro
l
(SMC)
is
a
c
on
t
ro
l
met
hod
us
e
d
with
the
DV
R
t
o
re
gu
la
te
t
he
vo
lt
age
s
upplied
to
t
he
t
hr
ee
-
ph
ase
loa
d.
SM
C
is
prefe
rr
e
d
in
va
rio
us
nonlinear
c
on
t
ro
l
a
pp
li
cat
io
ns
du
e
to
it
s
fast
res
pons
e
,
easi
er
to
imple
ment,
an
d
r
obust
with
t
he
va
riat
ion
of
the
s
yst
em
pa
rameter
s.
I
n
the
li
te
rat
ur
e
,
the
S
M
C
f
or
the
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
P
ow Elec
& Dri S
ys
t
IS
S
N:
20
88
-
8
694
An
i
mp
r
ove
d m
et
hod
fo
r eff
ic
ie
nt
co
ntr
olli
ng o
f t
he
d
y
namic
vo
lt
age r
est
ore
r to
…
(
Ali
Basi
m
M
ohamme
d
)
1959
DV
R
a
ppli
cat
i
on
is
re
ported
i
n
[
10].
The
me
tho
d
use
s
12
-
s
witc
h,
3
-
phase
vo
lt
age
sou
rce
conve
rter
to
pr
ov
i
de
the
require
d
c
ompe
ns
at
io
n
fo
l
lowing
a
volt
age
distu
rb
a
nce.
Ne
xt,
a
mu
lt
il
evel
S
M
C
co
m
bin
es
a
t
hr
ee
-
phase
inv
e
rter
an
d
th
ree
si
ng
le
-
phas
e
in
ver
te
rs
t
o
i
nject
the
vo
lt
a
ge
c
ompe
ns
at
ion
to
t
he
s
ys
te
m
[11].
The
powe
r
conve
rters
a
re
con
t
ro
ll
ed
by
the
SM
C.
On
t
he
oth
e
r
ha
nd,
the
S
M
C
c
on
t
ro
ls
a
si
ng
le
-
phase
D
VR
by
tun
in
g
the
par
a
mete
rs
of
the
co
ntr
ol
le
r
[
12]
.
I
n
[13],
t
he
SM
C
i
s
util
iz
ed
with
the
DV
R
to
address
the
iss
ue
of
vo
lt
age
sa
g
in
the
s
ys
te
m,
s
pe
ci
fical
ly.
Th
e
par
ti
cl
e
s
wa
rm
op
ti
miza
ti
on
te
ch
nique
is
util
iz
ed
in
[14]
t
o
est
imat
e
the
opti
mu
m
par
a
m
et
ers
of
the
S
M
C
t
o
mit
igate
the
T
HD
of
t
he
volt
age.
T
he
S
M
C
util
iz
ed
i
n
t
his
repor
t
is
base
d
on
the
sync
hrono
us
ref
e
ren
c
e
fr
a
me
to
obta
in
the
D
VR
re
f
eren
ce
volt
age.
The
majo
rity
of
t
he
SM
C
repo
rted
in
the
li
te
ratu
r
e
is
base
d
on
a
var
ia
nt
of
a
li
near
sli
ding
va
riable
wit
h
a
li
near
dif
fer
e
ntiat
or
to
ob
ta
in
t
he
der
i
vative
of
the
e
rror
functi
on.
Althou
gh
it
ha
s
show
n
sat
isf
act
ory
pe
rform
ance
in
t
he
va
rio
us
rep
or
t,
it
s
ap
pl
ic
at
ion
is
li
mit
ed
to
the
pre
sence
of
noise
the
mea
sured
input
sig
nal,
wh
ic
h
is
in
evi
ta
ble
in pract
ic
e.
This
pap
e
r
presents
a
rob
ust
SM
C
te
c
hn
i
qu
e
f
or
D
VR
to
a
ddress
t
he
li
mit
at
ion
of
the
li
near
con
t
ro
ll
er.
T
he
meth
od
is
bas
ed
on
the
a
ppr
ox
im
at
e
cl
assic
al
sli
din
g
m
ode
diff
e
re
ntiat
or
(
ACS
M
D
)
with
the
nonlinea
r
sli
di
ng
va
riable
(NSV).
In
t
his
pa
per,
the
sigm
oi
d
f
unct
ion
is
use
d
to
de
fine
t
he
a
pprop
riat
e
con
t
ro
l
respo
ns
e
base
d
on
t
he
in
put
t
o
mit
igate
t
he
vo
lt
age
disturb
ance
t
hat
occ
urre
d
i
n
the
s
yst
em.
T
he
pro
pose
d
method
is
r
obus
t
a
gainst
t
he
presence
of
noise
in
the
me
asur
e
d
i
nput
si
gn
al
.
Co
ns
e
quently,
t
his
al
lo
ws
t
he
DV
R
to
maint
ai
n
the
vo
lt
age
ma
gn
it
ude
at
the
c
on
sta
nt
va
lue,
minimi
ze
the
ste
ad
y
-
sta
te
erro
r
bound,
a
nd
reduce
the
tot
al
ha
rm
on
i
c
di
stortion
of
t
he
s
ys
te
m.
F
ol
lowing
this
in
tro
du
ct
ory
sec
ti
on
,
the
pro
pose
d
method
ology
of
t
he
ACS
MD
with
NSV
is
di
scusse
d
in
Sec
ti
on
2.
T
his
se
ct
ion
el
ab
or
at
e
s
on
the
ACS
M
D
i
n
detai
l,
the
sel
e
ct
ion
of
t
he
N
SV
meth
od,
t
he
desc
riptio
n
of
the
te
st
s
yst
em
m
odel
,
a
nd
the
perf
ormance
ind
ic
at
or
util
iz
ed
i
n
t
his
st
udy.
Ne
xt,
the
pr
opos
e
d
meth
odol
ogy
is
a
ppli
ed,
a
nd
t
he
re
su
lt
s
a
re
a
naly
zed
i
n
Sect
ion
3. Fina
ll
y,
Secti
on
4
c
on
cl
ud
e
s the
work
pr
e
sente
d
i
n
this
p
a
per.
2.
METHO
DOL
OGY
This
sect
io
n
discusse
s
the
method
ology
pro
po
se
d
i
n
t
his
stu
dy.
T
he
sect
ion
sta
r
ts
with
the
el
aborati
on
of
the
ACS
MD
te
chn
i
qu
e
,
f
ollo
wed
by
the
sel
ect
ion
of
the
N
SV
a
ppr
oach.
The
n,
the
te
st
sy
ste
m
model an
d
t
he per
forma
nce e
valuati
on
meas
ur
e
ment a
re
di
scusse
d.
2.1
Ap
pr
oxim
ate
cl
as
sic
al
sli
din
g
m
od
e
dif
fer
entia
to
r
(
A
CSMD
)
The ASC
M
D
works
by esti
m
at
ing
the
er
r
or
sign
al
as in
(1
).
=
+
(1)
Fr
om
t
he
e
qu
a
ti
on
,
is
the
er
ror
in
the
i
nput
sign
al
,
is
th
e
obser
ve
r
dyna
mic,
is
the
obser
ve
r
sli
din
g
va
riabl
e,
res
pecti
vel
y.
The
obse
rv
e
r
dynamic
is
obta
ined
form
it
s
de
rivati
ve
f
unct
ion
form
ulate
d
i
n
(2).
I
n
(2),
the
gai
n
an
d
ar
e
the
sli
ding
mode
dif
fer
e
ntiat
or
gain,
re
s
pecti
vely
.
T
he
gai
n
a
nd
are
sel
ect
ed
to
for
ce
goes
to
ze
r
o
a
s
>
|
̇
|
.
Co
ns
e
quently,
le
t
th
e
e
sti
mati
on
of
̇
be
come
the
ou
t
pu
t
of
the
fo
ll
owin
g
l
ow
pass fil
te
r
(L
P
F)
as
in (
3)
.
̇
=
−
2
∗
tan
−
1
(
)
(2)
̇
+
=
2
∗
tan
−
1
(
)
(3)
Fr
om
(3),
is
a
ti
me
co
ns
ta
nt
of
the
lo
w
pa
ss
filt
er
(LPF),
an
d
is
the
L
PF
ou
t
pu
t,
res
pecti
vely
.
Eve
ntu
al
ly,
th
e
de
rivati
ve
of
t
he
LPF
ou
t
pu
t
is
re
pr
ese
nte
d
as
in
(4).
T
he
der
i
vative
of
t
he
LPF
ou
t
pu
t
is
the
ou
t
pu
t
of the
AC
SMD met
hod [
15].
̇
=
1
(
−
+
2
∗
tan
−
1
(
)
)
(4)
The
sel
ect
io
n
of
t
he
ti
me
c
onsta
nt
of
the
L
PF
a
nd
the
gai
n
are
very
c
riti
cal
to
the
perf
ormance
of
the
ACSMD
te
chn
i
qu
e
.
In
t
his
st
udy,
thes
e
pa
rameter
s
a
re
set
base
d
on
t
he
st
udy
re
ported
in
[
15].
The
se
par
a
mete
rs
sho
uld
be
sel
ect
ed
su
c
h
t
ha
t
(4)
i
s
minimi
ze
d.
T
her
e
fore,
these
two
par
a
mete
r
s
are
set
s
uch
t
hat
2
is
as
small
as
possible.
I
n
this
study,
is
set
to
0.01,
a
nd
is
s
et
to
100,
res
pe
ct
ively.
I
n
a
ddit
ion
,
sh
ould
be
set
small
eno
ugh t
o
el
imi
nate the
high
-
fr
e
qu
ency te
rm
in
t
h
e input e
rror sign
al
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8
694
In
t J
P
ow
Ele
c
&
Dr
i
S
ys
t
,
V
ol
.
1
1
, N
o.
4
,
D
ecembe
r
2020
:
1958
–
1965
1960
2.2
Sli
ding va
ri
abl
e a
ppr
oach
2.2.1
.
Li
near
PI
D
sli
ding v
ariab
le
The
pr
oport
iona
l,
integral,
a
nd
de
rivati
ve
(PID
)
co
ntr
oller
has
bee
n
util
iz
ed
in
the
var
i
ous
co
ntr
ol
app
li
cat
io
n
in
pr
act
ic
e.
O
ver
90%
of
the
i
ndus
tria
l
process
es
util
iz
e
P
I
D
i
n
th
ei
r
daily
operati
on
[
16,
17]
due
to
it
s
rob
us
tne
ss,
ease
of
mainte
na
nce,
a
nd
simpli
ci
ty
[
18,
19].
The
PID
con
t
ro
ll
er
c
ons
ist
s
of
pro
portion
al
,
integral,
an
d
de
rivati
ve
gains
that
scal
e
the
value
of
er
ror
betwee
n
t
he
input
a
nd
outp
ut
of
the
co
ntr
oller
.
In
the
sli
ding
var
ia
ble
te
chn
i
qu
e
,
t
he
sli
ding
va
riable
base
d
on
t
he
PID
c
ontrolle
r
is
represe
nted usi
ng (5).
=
P
(
)
+
I
∫
(
)
+
D
(
)
0
(5)
In (5)
,
P
,
I
, and
D
r
epr
ese
nt the
pr
oport
ion
al
,
inte
gr
al
,
and
der
i
va
ti
ve
gai
ns
, res
pecti
vely
.
2.2.2
.
Nonli
near
sli
ding va
ri
ab
le
In
t
he
f
ollo
wing it
ems, t
he
no
nlinear
sli
ding
var
ia
bles are p
rop
os
ed
. T
he
sl
iding va
riable
will
co
ntain
a non
li
nea
r
te
r
m which
it
func
ti
on
s t
o
the
er
ror
si
gn
al
.
(
)
=
̇
+
λ
(
)
(6)
Wh
e
re
S(
e
)
is
the
li
nea
r
sli
ding
var
ia
ble,
̇
is
the
li
near
der
i
vative
of
the
e
rror,
λ
is
th
e
sli
ding
var
ia
ble
pa
ra
mete
rs,
(
e
)
is
a
li
near
functi
on
of
e
.
T
he
sli
di
ng
va
riable
be
comes
li
near.
I
n
the
act
ual
sit
uatio
n,
S
(e)
is
not
e
qu
al
to
zer
o
i
n
t
he
sli
ding
mode.
I
nst
ead,
S(
e
)
wil
l
be
hi
gh
l
y
osc
il
la
te
d
an
d
bounde
d
sign
al
s.
In
th
e
f
ollo
wing
sub
sect
ion
s,
t
he
nonlinea
r
sli
ding
va
riable
is
s
uggeste
d
w
here
(
e
)
is
a
nonline
ar
functi
on
of
t
he
.
I
n
a
dd
it
io
n,
the
rob
us
tnes
s
will
be
te
ste
d.
This
will
s
how
the
s
uperio
rity
of
t
he
no
nlin
ear
against
the
li
ne
ar
sli
di
ng
var
i
able.
Eq
uatio
n
(
7)
represe
nts
a
mathe
mati
cal
f
un
ct
io
n
tha
t
has
a
sig
mo
i
d
c
urve
or
S
-
s
ha
pe
d
c
ha
rac
te
risti
c
of
t
he
c
urve.
The
l
og
ist
ic
f
unct
io
n
s
how
n
belo
w
is
the
sta
nd
a
r
d
belo
w
c
hoic
e
for
a
sigm
oid
functi
on [2
0]
.
(
)
=
1
1
+
−
=
1
+
(7)
Wh
e
re
(
)
is
t
he
sli
ding
var
ia
bl
e
of
the
f
unc
ti
on
x,
f
rom
t
he
i
nformat
ion
ab
ove,
t
he
si
gmoid
functi
on
is
m
on
ot
on
ic
a
nd
ha
ve
the
fir
st
de
r
ivati
ve
as
bell
-
sh
a
ped,
it
is
c
on
st
raine
d
by
a
pair
of
horiz
on
ta
l
asym
pto
te
s
as
x→
±
∞.
It
is
conve
x
f
or
va
lues
is
le
ss
tha
n
0,
a
nd
it
is
c
on
ca
ve
f
or
val
ues
m
or
e
tha
n
0.
F
or
these s
pecifica
ti
on
s
, s
ig
mo
i
d f
un
ct
io
n
a
nd it
s
aff
ine
co
mposi
ti
on
s ca
n p
os
se
ss m
ulti
ple opt
ima.
(
)
=
(8)
In
the
prese
nt
w
ork,
the
a
r
ct
an
functi
on
is
us
e
d
in
th
e
co
ns
tr
uctio
n
of
t
he
sli
ding
var
ia
ble.
Accor
dingly,
the slidi
ng v
a
ri
able b
ec
ome
s;
(
e
)
=
̇
+
λ
∗
tan
−
1
(
∗
)
(9)
In
t
his
eq
uatio
n.
S
(
e
)
is
the
sli
ding
va
riable,
α
,
an
d
λ
are
the
sli
ding
va
riable
par
a
mete
rs,
a
nd
e
is
th
e
input
er
r
or
sig
nal.
As
i
n
t
he
pr
e
vious
tw
o
c
ases
of
t
he
sli
di
ng
va
riable,
th
e
ulti
mate
bound
on
the
er
ror
ca
n
be
est
imat
ed
v
i
a Ly
a
puno
v
f
unct
ion as
fo
ll
ows;
V
̇
=
{
−
λ
∗
t
an
−
1
(
α
∗
e
)
+
S
}
∗
sign
(
e
)
≤
−
λ
∗
t
an
−
1
(
α
∗
|
e
|
)
+
ρ
(10)
Wh
e
re
V
̇
is
the
der
i
vative
of
L
yapu
nov
f
unct
ion,
sig
n(
e
)
is
the
sig
nal
f
un
ct
ion
,
a
nd
ρ
is
a
po
sit
ive
const
ant,
t
he ult
imat
e b
ou
nd on th
e
er
ror
(
)
is d
et
ermine
d
as;
|
e
(
t
)
|
≥
1
α
tan
(
ρ
λ
)
,
as
t
→
∞
(11)
Fr
om
t
he
a
bove
ineq
ualit
y,
th
e
ulti
mate
bo
und
on
can
be
adjuste
d
to
a
s
uitable
value
vi
a
a
pro
pe
r
sel
ect
ion
of
t
he
d
esi
gn p
a
rame
te
rs
λ
an
d
.
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
P
ow Elec
& Dri S
ys
t
IS
S
N:
20
88
-
8
694
An
i
mp
r
ove
d m
et
hod
fo
r eff
ic
ie
nt
co
ntr
olli
ng o
f t
he
d
y
namic
vo
lt
age r
est
ore
r to
…
(
Ali
Basi
m
M
ohamme
d
)
1961
2.3
Vo
l
tage sa
g
in
dice
s for per
f
orm
an
ce e
valuat
i
on
In
orde
r
to
e
va
luate
the
perf
ormance
of
th
e
pro
posed
me
thod,
se
ve
ral
volt
age
sa
g
in
di
ces
that
are
typ
ic
al
ly
us
ed
to
deter
mine
t
he
ef
fecti
ve
nes
s
of
t
he
met
hod
to
im
pro
ve
powe
r
qu
al
it
y
a
re
co
ns
id
ere
d
i
n
this
study
[21, 2
2].
The
y
are
li
ste
d i
n
Ta
ble
1.
Table
1.
V
oltage sa
g
i
nd
ic
es
for per
forma
nc
e evaluati
on
V
o
ltag
e sag
ind
ices
Fo
rm
u
la
Para
m
eters
defin
iti
o
n
Detroit Edis
o
n
Sag
Score
(SS)
=
1
−
A
+
B
+
C
3
,
,
are
vo
ltag
e f
o
r
Ph
ase A,
B
,
an
d
C,
r
esp
ectiv
ely
Vo
ltag
e Sag Los
t
Energy
Ind
ex
(VSL
EI
)
=
T
[
1
−
(
)
nom
]
3
.
14
nom
is th
e no
m
in
al vo
ltag
e,
V the
ph
ase v
o
ltag
e,
an
d
T
is th
e
tim
e du
ring
the v
o
ltag
e sag
.
Vo
ltag
e Sag Energ
y
(
)
E
VS
=
∫
[
−
(
(
)
)
]
3.
APPLI
CA
TI
ONS,
RESU
L
TS, AN
D DIS
CUSSIO
NS
3.1.
The mo
deli
ng
of system
and
simul
at
i
on
The
pro
pose
d
sy
ste
m
of
the
D
VR
is
in
ve
sti
gated
by
usi
ng
M
AT
LAB
/Si
mu
li
nk
t
o
s
imulat
e
the
disturba
nces
w
hen
it
occ
ur
s
i
n
a
distrib
utio
n
sy
ste
m
.
The
disturba
nces
c
on
si
der
e
d
in
th
is
stu
dy
a
re
ba
la
nce
d
sag,
un
balance
d
sa
g,
balance
d
s
well
,
a
nd
unbala
nced
s
we
ll
.
The
pa
rame
te
r
s
of
the
te
st
syst
em
model
ar
e
ob
ta
ine
d
i
n
[
23
].
Fi
gure
1
re
presents
t
he
s
ys
t
em
un
der
st
udy.
T
he
s
ys
te
m
consi
sts
of
an
AC
sou
rce
that
feeds
the
tw
o
feed
e
r
s
thr
ough
a
th
ree
-
windin
g
tr
ansfo
rmer.
Ea
ch
feed
e
r
c
on
nected
to
a
wi
nd
i
ng
tra
ns
f
ormer
t
o
su
ppl
y
the
re
quire
d
powe
r
to
dif
fer
e
nt
t
yp
e
s
of
l
oad
s
.
T
he
D
VR
c
onnect
ed
i
n
se
ries
with
the
sec
ond
f
eeders
to miti
gate the
vo
lt
age
d
ist
urb
ance
occurr
ed
in
the
s
ys
te
m
by inject
in
g
a
r
e
qu
i
red v
oltage.
Figure
1. MAT
LAB/Si
mu
li
nk
of the
syst
em
unde
r
stu
dy
3.1.1
.
Ca
se
1: B
alan
ced t
hree
-
p
hase v
olt
ag
e
s
ag
A
balance
d
volt
age
sag
is
a
ppli
ed
to
the
s
yst
em
by
ov
e
rl
oad
i
ng
the
l
oa
d
at
t=
0.1s
un
ti
l
t=
0.
15
s
.
The
n,
the
in
du
ct
ion
m
otor
in
the
sy
ste
m
is
ov
e
rloa
de
d
at
t=
0.
18
5s
unti
l
t=
0.
2s.
Co
ns
e
qu
e
ntly,
t
he
volt
age
amplit
ude
is
re
du
ce
d
i
n
al
l
th
r
ee
phases,
as
de
picte
d
i
n
Fi
gure
2(
a
).
In
the
fig
ur
e,
the
volt
age
is
re
du
ce
d
from
the
nominal
vo
lt
age
to
0.709
6
pu
a
nd
0.612
pu
for
the
tw
o
op
e
rati
ng
sit
ua
ti
on
s,
resp
ect
iv
el
y.
Co
ns
e
qu
e
ntly,
the
D
VR
se
nse
s
this
disturb
ance
a
nd
injec
ts
a
r
e
qu
i
red
volt
age
m
ag
nitu
de
as
sho
wn
in
Fi
gure
2(b
).
As
a
resu
lt
,
t
he
volt
age
a
mp
li
tu
de
at
the
loa
d
si
de
increas
es,
a
s
s
how
n
in
Fig
ur
e
2(c).
F
ollo
wing
the
co
mp
e
nsa
ti
on
,
the
vo
lt
a
ge
i
nc
reases
to
0.9
99
pu
,
0.9
992pu,
and
0.999
2pu
i
n
Ph
a
se
A,
B,
and
C,
resp
ect
i
ve
ly.
In
a
dd
it
io
n,
the
total
harmo
nic
distor
ti
on
(T
H
D)
at
t
he
loa
d
vo
lt
age
be
f
or
e
com
pensat
ion
is
8.7
9.
T
he
TH
D
im
prov
e
s
to
1.41
fo
ll
owin
g
the
com
pensat
ion
of
the
propose
d
D
VR
te
c
hn
i
qu
e
.
The
r
esult
disc
us
ses
in
t
his
st
udy
co
rro
borated
with the
r
es
ult
repor
te
d
in
[
24
].
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8
694
In
t J
P
ow
Ele
c
&
Dr
i
S
ys
t
,
V
ol
.
1
1
, N
o.
4
,
D
ecembe
r
2020
:
1958
–
1965
1962
(a)
(b)
(c)
Figure
2. Sim
ul
at
ion
r
es
ults
f
or b
al
a
nced v
ol
ta
ge
sag
b
ase
d D
VR: (a
)
the
un
c
ompe
ns
at
e
d
loa
d v
oltage,
(b)
t
he
vo
lt
age
inject
s
by DVR,
(c
)
th
e compe
ns
at
ed
load v
oltage
.
3.1.2
.
Ca
se
2:
Unbal
an
ced
volt
age
sa
g
In
this
stu
dy,
t
he
l
oad
is
over
loade
d
at
t=
0.2
s
unti
l
t=
0.3s.
On
l
y
phase
C
is
ap
plied
t
o
si
mu
la
te
the
unbalance
d
volt
age
sag
c
ondit
ion
.
Fo
ll
owi
ng
this
distu
rb
a
nc
e,
the
vo
lt
age
amplit
ude
is
r
edu
ce
d
t
o
0.4
996p
u,
0.899
2pu,
an
d
0.900
7pu
i
n
Phase
A
,
B,
an
d
C,
r
es
pecti
vely
,
as
s
how
n
in
F
igure
3
(a)
.
T
he
n,
t
he
D
VR
de
te
ct
s
the
vo
lt
a
ge
sa
g
a
nd
ra
pid
ly
i
nject
a
pr
op
e
r
mag
nitud
e
t
o
r
egu
la
te
the
vol
ta
ge
at
the
loa
d
side
as
in
Fi
gure
3
(b).
C
on
se
que
ntly,
t
he
volt
age
am
plit
ud
e
a
t
al
l
three
phas
es
is
resto
red
to
0.9
993p
u
,
0.999
3pu
,
1.0
000pu
in
Ph
ase
A
,
B
,
a
nd
C
,
res
pecti
ve
ly.
Fig
ur
e
3(
c
)
sh
ows
the
c
ompen
sat
ed
volt
age
of
t
his
case
study.
A
ddit
io
nally,
the
T
H
D
at
the
loa
d
im
pro
ves
f
rom
15.
78,
be
fore
t
he
c
omp
ensati
on,
to
1.
71
a
fter
t
he
c
ompe
ns
at
io
n
us
i
ng
the
pro
po
se
d D
VR.
(a)
(b)
(c)
Figure
3. Sim
ul
at
ion
r
es
ults
f
or un
balance
d vo
lt
age
sa
g bas
ed DVR:
(a) t
he
unco
mp
e
ns
at
ed
loa
d v
oltage
, (b)
the volt
age
inj
ect
ed
by
D
VR,
(
c)
the c
ompe
ns
at
ed
loa
d vo
l
ta
ge.
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
P
ow Elec
& Dri S
ys
t
IS
S
N:
20
88
-
8
694
An
i
mp
r
ove
d m
et
hod
fo
r eff
ic
ie
nt
co
ntr
olli
ng o
f t
he
d
y
namic
vo
lt
age r
est
ore
r to
…
(
Ali
Basi
m
M
ohamme
d
)
1963
3.1.3
.
Ca
se
3: B
alan
ce three
-
ph
as
e
volt
ag
e
sw
el
l
In
this
case
study,
the
loa
d
i
s
s
udde
nly
tu
r
ned
-
off
t
o
sim
ulate
the
vo
lt
a
ge
swell
distu
r
ban
ce
in
t
he
sy
ste
m.
T
he
volt
age
s
well
oc
cur
s
at
t=
0.1
s
un
ti
l
t=
0.2s
.
Figure
4(a)
sho
w
s
the
volt
age
s
well
that
occur
red
in
the
sy
ste
m
.
T
he
fig
ur
e
s
hows
that
the
volt
age
inc
reases
from
the
nomi
na
l
vo
lt
age
t
o
1.3
98pu
in
al
l
phases.
Fo
ll
owin
g
this
volt
age
s
well
ing
,
the
DV
R
sense
t
his
dif
f
eren
ce
a
nd
inj
ect
a
require
d
volt
age
ma
gn
it
ud
e.
Figure
4(b)
s
hows
t
he
ph
ase
vo
lt
a
ge
injec
te
d
by
the
pro
po
s
ed
DV
R
t
o
com
pensat
e
f
or
t
he
loa
d
vo
lt
age
diff
e
re
nce.
Fig
ur
e
4(c)
re
pre
sents
t
he
vo
lt
age
a
mp
li
tu
de
at
the
loa
d
s
ide
afte
r
c
ompen
sat
ion.
T
he
res
ult
ind
ic
at
es
the
volt
age
at
al
l
phases
im
pro
ve
s
to
0.9
998p
u.
More
ov
e
r,
t
he
TH
D
at
the
l
oad
bus
be
for
e
the
com
pensat
ion i
s 10.85. T
he
c
ompe
ns
at
io
n by
the pr
opos
e
d D
VR im
prov
e
s t
he
T
H
D
to
0.87.
(a)
(b)
(c)
Figure
4. Sim
ul
at
ion
r
es
ults
f
or b
al
a
nce
vo
lt
age s
well
b
ase
d DV
R:
(a) t
he
unco
mp
e
ns
at
e
d
loa
d v
oltage,
(b)
the volt
age
inj
ect
s by DVR,
(c
)
the
compe
nsa
te
load
volt
ag
e.
3.1.4
.
Ca
se
4:
Unbal
an
ced
volt
age
swell
This
case
c
ons
iders
a
n
unbal
anced
volt
age
swell
occ
urred
at
t=
0.
2s
unti
l
t=
0.
3s.
I
n
t
his
operati
n
g
sit
uation,
the
volt
age
at
P
has
e
A
,
B,
an
d
C
inc
reases
to
1.4
08pu,
1.1
46pu,
an
d
1.124
pu,
res
pecti
vel
y.
T
his
resu
lt
is
obse
r
ved
in
Fi
gure
5(a)
.
Subse
quently
,
t
he
D
VR
detect
s
th
e
dist
urban
ce
and
injec
ts
a
require
d
vo
lt
age
mag
nit
ud
e
t
o
mit
igat
e
the
volt
age
di
sturb
a
nce,
a
s
sh
ow
n
in
Fi
gure
5(b
).
Fi
gure
5(
c
)
sho
ws
th
e
load
vo
lt
age
fo
ll
ow
ing
the
co
m
pe
ns
at
io
n
us
in
g
the
pro
posed
D
VR.
I
n
t
he
fig
ur
e
,
t
he
l
oad
volt
age
i
n
Phas
e
A
,
B
,
and
C
inc
rease
s
to
0.9
9
98
pu,
1.000
0pu,
0.9
994p
u,
re
sp
ect
iv
el
y.
Plus
,
t
he
T
HD
at
the
loa
d
bu
s
im
pro
ves
from
11.10 t
o 0.85 a
fter th
e
com
pe
ns
at
io
n.
(a)
(b)
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8
694
In
t J
P
ow
Ele
c
&
Dr
i
S
ys
t
,
V
ol
.
1
1
, N
o.
4
,
D
ecembe
r
2020
:
1958
–
1965
1964
(c)
Figure
5. Sim
ul
at
ion
r
es
ults
f
or un
balance
d vo
lt
age
s
well
base
d DV
R:
(a)
the
unc
ompe
nsa
te
d
loa
d vo
lt
a
ge,
(b)
the
volt
age
injec
te
d by D
V
R, (c
)
the
com
pensat
ed
l
oad
vo
lt
age
.
3.2.
Perfo
r
ma
nce
eva
lu
ati
on
Table
2
summ
arizes
the
perf
ormance
of
th
e
pro
posed
w
ork
i
n
mit
igati
ng
the
volt
age
disturba
nce.
The
pe
r
forma
nc
e
is
evaluated
by
util
iz
ing
the
in
dices
na
med
,
an
d
.
The
resu
lt
s
s
how
that
th
e
ACS
M
D
with
the
Ar
ct
a
n
method
im
pro
ves
the
vo
lt
a
ge
qual
it
y
i
n
te
rm
s
of
,
an
d
.
T
his
impro
veme
nt
i
mp
li
es
t
hat
the
ACS
MD
with
the
A
rctan
me
thod
is
a
ble
to
mit
igate
t
he
s
ys
te
m
volt
age
in
th
e
pr
ese
nce
of the
b
al
ance
d an
d
t
he unbala
nc
ed
vo
lt
age
sa
g.
Table
2.
V
oltage sa
g
i
nd
ic
es
for ACS
M
D
wi
th ar
ct
an
Table
3
ta
bu
la
t
es
the
pe
rform
ance
c
ompa
rison
of
the
pro
pose
d
met
hod
with
t
he
m
et
ho
d
repo
rted
i
n
[23].
T
he
pe
r
forma
nce
is
measu
red
us
in
g
t
he
i
ntegral
ti
me
a
bs
ol
ut
e
er
ror
(ITA
E).
Th
e
distu
rb
a
nces
consi
der
e
d
in
this
study
are
simi
la
r
to
the
cases
discuss
ed
in
the
pr
e
vi
ou
s
sect
io
ns
.
Fr
om
the
ta
bl
e,
the
pro
po
se
d
D
V
R
method
outper
forms
the
method
re
ported
in
[
23]
in
al
l
cases.
The
res
ult
impli
es
that
th
e
pro
po
se
d w
ork
minimiz
es t
he e
rror i
n
c
ompe
ns
at
in
g
the
vol
ta
ge
as c
ompa
r
ed
to
the
meth
od in [
23].
Table
3.
Illustr
at
e a compa
ris
on b
et
ween t
he
r
es
ults in
[23
] wit
h
the
pr
opose
d wor
k ACS
M
D
w
it
h arct
a
n
Op
erating
con
d
itio
n
s
IT
A
E(
DC
)
[23
]
IT
A
E
(
DC)
Balan
ce vo
ltag
e sa
g
1
.62
3
0
.11
1
9
Un
b
alan
ce vo
ltag
e sag
1
.48
7
0
.17
5
2
Balan
ce vo
ltag
e swell
1
.66
8
0
.12
3
8
Un
b
alan
ce vo
ltag
e swell
1
.68
9
0
.07
1
2
7
4.
CONCL
US
I
O
N
In
c
oncl
us
i
on,
this
pa
per
re
ports
a
DV
R
con
t
ro
ll
er
method
us
in
g
the
ACS
M
D
wit
h
the
Ar
ct
a
n
method.
T
he
r
esults
sho
w
th
at
the
pro
pose
d
met
hod
is
a
bl
e
to
co
mp
e
ns
a
te
for
the
volt
age
in
the
te
st
s
ys
te
m
model
unde
r
t
he
bala
nce
d
volt
age
sa
g,
unbalance
d
volt
a
ge
sa
g,
balanc
ed
volt
age
s
w
el
l,
and
unbal
anced
vo
lt
age
s
well
.
F
ollo
wing
t
he
c
ompensati
on,
the
T
H
D
at
the
loa
d
bu
s
is
al
so
im
pro
ve
d.
T
he
co
mpa
rison
analysis
of
the
method
with
t
he
meth
od
re
porte
d
in
the
li
te
ratur
e
has
bee
n
disc
us
se
d
in
this
pap
e
r.
T
he
resu
lt
ind
ic
at
es
t
hat
the
pro
posed
m
et
hod
s
how
s
a
bette
r
perf
or
m
ance
i
n
te
r
ms
of
IT
AE
as
c
ompa
red
to
the
metho
d
repor
te
d
i
n
the
li
te
ratur
e.
T
his
impli
es
t
hat
the
AC
SMD
with
the
Ar
ct
a
n
met
hod
is
a
ble
to
co
mp
e
nsa
te
the
vo
lt
age
un
der
var
i
ou
s
volt
age
d
ist
urba
nces
bet
te
r
as co
m
pared to
the
meth
od d
isc
us
se
d
i
n t
his
pap
e
r.
ACKN
OWLE
DGE
MENTS
The
a
uthor
s
would
li
ke
to
than
k
U
niv
er
sit
i
Tun
H
us
s
ei
n
O
nn
M
al
aysia
(
UT
H
M
),
Johor,
a
n
d
M
inist
r
y
of
Ed
ucati
on
(MOE
)
M
al
aysia
f
or
t
he
a
wa
rd
of
th
e
gra
nt
that
e
na
bled
this
rese
arch
under
gr
a
nt
No.
H20
8.
Vo
ltag
e sag
ind
ices
VSLE
I
(pu
)
E
VS
(p
u)
SS
(pu
)
Fau
lt typ
e
Befo
re
After
Befo
re
After
Befo
re
After
Balan
ce vo
ltag
e sa
g
3
.08
9
6
3
.78
7
6
×
10
-
8
1
2
.64
9
8
1
.14
0
0
×
10
-
4
0
.29
0
4
8
.66
6
7
×
10
-
4
Un
b
alan
ced v
o
ltag
e sag
1
1
.51
7
7
2
.48
1
1
×
10
-
8
2
7
.04
2
1
9
.80
0
0
×
10
-
5
0
.23
3
5
4
.66
6
7
×
10
-
4
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
P
ow Elec
& Dri S
ys
t
IS
S
N:
20
88
-
8
694
An
i
mp
r
ove
d m
et
hod
fo
r eff
ic
ie
nt
co
ntr
olli
ng o
f t
he
d
y
namic
vo
lt
age r
est
ore
r to
…
(
Ali
Basi
m
M
ohamme
d
)
1965
REFERE
NCE
S
[1]
A.
B.
Moha
mme
d,
M.
A
.
M.
Ari
f
f,
and
S.
N.
Ramli,
“Power
qua
li
t
y
im
prov
em
en
t
using
dynam
i
c
v
olt
ag
e
restor
er
in
elec
tr
ical
dist
ribut
ion
sys
te
m
:
An
over
vie
w,
”
Indone
sian
Jou
rnal
of
El
e
ct
ri
c
al
Engi
ne
ering
and
Computer
Sci
en
ce
,
vol
.
17
,
no.
1,
pp.
86
–
93
,
2019
.
[2]
H.
Hafe
z
i
and
R
.
Fara
nd
a,
“Dyn
am
i
c
Volt
age
C
ondit
ione
r
:
A
N
ew
Conce
p
t
for
Smart
Low
-
Volt
age
Distribu
ti
on
Sys
te
ms,”
I
EEE
Tr
ansacti
ons on Power
E
le
c
troni
cs
,
vol
.
33
,
no
.
9
,
pp
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7582
–
7590
,
2018.
[3]
J.
A.
K.
Moham
me
d,
A.
A
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Hus
sein,
and
S.
R
.
Al
-
Sakini
,
“Voltage
disturb
anc
e
mi
ti
g
at
ion
in
Ira
q’s
low
volt
age
distri
buti
on
sys
t
em
,
”
Indone
sia
n
Journal
o
f
E
le
c
tric
al
Engi
ne
ering
and
Com
pute
r
S
cienc
e
,
vol.
17,
no
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1,
pp.
47
–
60
,
2019
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[4]
A.
H.
Abed
,
J.
Rahe
bi
,
H.
Sa
ji
r
,
and
A.
Far
za
m
nia
,
“Protect
ion
of
sensiti
ve
lo
ad
s
from
v
oltages
fluc
tu
at
ions
in
Ira
qi
grids
by
DV
R,
”
2
017
IE
E
E
2nd
Int
ernational
Confe
ren
ce
on
Aut
omat
ic
Control
and
Int
el
li
g
ent
S
yste
ms
(I2CACIS)
,
pp.
1
44
–
149,
2017
.
[5]
A.
Pakhar
ia
an
d
M.
Gupta,
“
Dynami
c
Vol
tage
Restore
r
for
C
Ompensa
ti
o
n
of
Volta
ge
S
ag
and
Sw
el
l
:
a
Li
teratu
r
e
R
evi
e
w,”
In
te
rnationa
l
Journal
of
Ad
v
ance
s
in
Eng
ineering
&
Techno
l
ogy
,
vol.
4,
no
.
1,
pp
.
347
–
355
,
2012.
[6]
D.
V.
Chinm
ay
and
D.
V.
Chait
anya
,
“Opt
im
um
design
of
dyn
a
mi
c
voltage
rest
ore
r
for
vol
ta
ge
sag
mitigation
in
distri
buti
on
ne
t
work,”
In
te
r
national
Journal
of
Powe
r
E
lectroni
cs
and
Dr
ive
sy
stems
(IJ
P
EDS)
,
vol
.
10
,
no
.
3,
p
p
.
1364
-
1372
,
2019.
[7]
D.
Dana
la
kshm
i
,
S.
Bugata,
and
J.
Kohila
,
“A
c
ontrol
strategy
o
n
power
qual
i
ty
im
prove
m
ent
in
consume
r
side
using
custom
po
wer
device
,
”
Ind
onesian
Jour
nal
of
Elec
tric
al
En
gine
ering
and
C
omputer
Scienc
e
,
vol
.
15
,
no.
1
,
pp.
80
–
87
,
2019
.
[8]
P.
T.
Ch
eng,
J
.
M.
Chen
,
an
d
C.
L
.
Ni,
“
Design
of
a
st
at
e
-
f
ee
db
ac
k
co
ntrol
ler
for
seri
es
volt
ag
e
-
sag
com
pensa
tors,
”
I
EE
E
Tr
ansacti
o
ns on
Industry A
ppli
cations
,
vo
l.
45,
n
o
.
1
,
pp
.
26
0
–
267,
2009
.
[9]
P.
S.
Babu
and
N.
Kamaraj,
“
Perform
ance
in
vesti
gation
of
dynam
i
c
voltag
e
restor
er
using
PI
and
fuz
zy
cont
roller,”
In
te
r
nati
onal
Con
fe
re
nce
on
Pow
er,
E
nergy
and
Con
trol
(ICP
EC)
,
pp.
467
–
472,
2013
.
[10]
S.
Biri
c
ik,
H.
Komurc
ugil,
and
M.
B
asu,
“Sl
idi
n
g
mode
con
trol
s
tra
t
egy
for
thr
ee
-
phase
DV
R
employing
twe
lve
-
sw
it
ch
vol
ta
g
e
source
conve
rt
e
r,
”
IECON
201
5
-
41st
Annual
Confe
renc
e
o
f
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