I
nte
rna
t
io
na
l J
o
urna
l o
f
Appl
ied P
o
wer
E
ng
i
neer
ing
(
I
J
AP
E
)
Vo
l.
1
3
,
No
.
4
,
Dece
m
b
er
20
2
4
,
p
p
.
9
8
2
~
9
8
8
I
SS
N:
2252
-
8
7
9
2
,
DOI
:
1
0
.
1
1
5
9
1
/ijap
e
.
v
1
3
.
i
4
.
pp
982
-
988
982
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
a
p
e
.
ia
esco
r
e.
co
m
Power qua
li
ty en
ha
ncement
using
fully inform
e
d pa
rticle
swa
rm o
ptimiza
ti
o
n bas
ed
DSTAT
CO
M
in
distri
but
io
n sy
stems
M
o
g
utha
la
Sh
a
nk
a
r
,
R
.
Sent
hil
K
um
a
r
De
p
a
rtme
n
t
o
f
El
e
c
tri
c
a
l
a
n
d
El
e
c
tro
n
ics
E
n
g
i
n
e
e
rin
g
,
S
a
v
e
e
th
a
En
g
in
e
e
rin
g
Co
ll
e
g
e
(Au
t
o
n
o
m
o
u
s),
An
n
a
Un
iv
e
rsity
,
Ch
e
n
n
a
i,
In
d
a
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Dec
2
6
,
2
0
2
3
R
ev
is
ed
J
u
l 8
,
2
0
2
4
Acc
ep
ted
Au
g
1
5
,
2
0
2
4
To
c
o
m
p
e
n
sa
te
f
o
r
t
h
e
re
a
c
ti
v
e
p
o
we
r,
i
n
v
e
rter
-
b
a
se
d
c
o
n
d
it
i
o
n
e
rs
h
a
v
e
b
e
e
n
u
ti
li
z
e
d
i
n
re
c
e
n
t
y
e
a
rs
d
u
e
to
th
e
ir
fa
ste
r
re
sp
o
n
se
.
Distri
b
u
t
io
n
sta
ti
c
sy
n
c
h
r
o
n
o
u
s
c
o
m
p
e
n
sa
to
r
(
DS
TATCOM
)
h
a
s
b
e
e
n
u
ti
li
z
e
d
t
o
e
n
h
a
n
c
e
p
o
we
r
q
u
a
li
t
y
i
n
p
o
we
r
s
y
ste
m
th
a
t
is
a
n
in
v
e
rter
-
b
a
se
d
d
e
v
ice
th
a
t
is
wid
e
l
y
u
ti
li
z
e
d
.
To
c
o
n
tro
l
th
is
ty
p
e
o
f
e
q
u
i
p
m
e
n
t,
a
p
ro
p
o
rt
io
n
a
l
in
teg
ra
ted
(P
I)
c
o
n
tro
ll
e
r
h
a
s
b
e
e
n
u
ti
li
z
e
d
t
o
c
o
n
tr
o
l
m
o
st
o
f
t
h
e
e
q
u
i
p
m
e
n
t
wi
th
re
sp
e
c
t
to
c
e
rtain
p
a
ra
m
e
ters
.
Th
e
p
e
rfo
rm
a
n
c
e
o
f
th
e
c
o
n
tr
o
ll
e
r
b
a
sic
a
ll
y
d
o
e
s
n
o
t
m
e
e
t
th
e
e
x
p
e
c
tatio
n
s
b
e
c
a
u
se
o
f
th
e
d
y
n
a
m
ics
a
n
d
n
o
n
li
n
e
a
rit
y
o
f
a
sy
ste
m
p
a
ra
m
e
ters
.
In
th
is
p
re
se
n
t
p
a
p
e
r,
a
p
ro
b
a
b
il
isti
c
n
e
u
ra
l
n
e
two
r
k
h
a
s
b
e
e
n
u
se
d
in
a
c
o
n
tro
ll
e
r
with
a
fu
ll
y
in
f
o
r
m
e
d
p
a
rti
c
le
sw
a
rm
o
p
ti
m
iza
ti
o
n
(F
IP
S
O)
a
lg
o
rit
h
m
to
g
e
n
e
ra
te
a
su
it
a
b
le
we
ig
h
t
f
o
r
c
o
n
tro
ll
in
g
th
e
a
x
e
s
o
f
v
a
ri
o
u
s
p
a
ra
m
e
ters
o
f
DST
ATCOMs.
Us
in
g
M
ATLAB/S
im
u
li
n
k
so
ftwa
re
,
sim
u
latio
n
s
we
re
p
e
rfo
rm
e
d
,
a
n
d
t
h
e
re
sp
o
n
se
s
we
re
m
o
n
it
o
re
d
wit
h
p
a
rti
c
u
lar
re
g
a
rd
to
th
e
re
fe
re
n
c
e
re
a
c
ti
v
e
p
a
ra
m
e
ter.
Th
e
re
su
lt
s
a
re
c
o
m
p
a
re
d
.
DST
ATCOM
imp
r
o
v
e
s p
o
we
r
sy
ste
m
d
a
m
p
in
g
.
K
ey
w
o
r
d
s
:
DSTA
T
C
OM
Fu
lly
in
f
o
r
m
e
d
p
ar
ticle
s
war
m
o
p
tim
izatio
n
Neu
r
al
n
etwo
r
k
Po
wer
q
u
ality
Pro
b
ab
ilis
tic
n
eu
r
al
n
etwo
r
k
Pro
p
o
r
tio
n
al
-
in
teg
r
al
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Mo
g
u
th
ala
Sh
an
k
ar
Dep
ar
tm
en
t o
f
E
lectr
ical
an
d
E
lectr
o
n
ics
E
n
g
in
ee
r
i
n
g
,
Sav
e
eth
a
E
n
g
in
ee
r
in
g
C
o
lleg
e
(
A
u
to
n
o
m
o
u
s
)
An
n
a
Un
iv
er
s
ity
C
h
en
n
ai,
T
am
il Na
d
u
,
I
n
d
ia
E
m
ail:
n
n
r
g
s
h
an
k
ar
@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
Nu
m
er
o
u
s
r
esear
ch
er
s
h
a
v
e
lo
o
k
ed
in
to
p
o
wer
q
u
ality
c
o
n
ce
r
n
s
s
u
ch
as
n
eu
tr
al
cu
r
r
en
t
c
o
m
p
en
s
atio
n
,
v
o
ltag
e
s
ag
,
s
wellin
g
,
a
n
d
v
o
l
tag
e
in
s
tab
ilit
y
.
T
h
ese
p
r
o
b
le
m
s
lead
to
a
s
lo
wer
r
esp
o
n
s
e,
lo
wer
p
o
wer
f
lo
w
lim
its
,
an
d
th
e
s
y
s
tem
co
llap
s
e.
All
th
ese
th
in
g
s
wer
e
a
c
o
n
d
itio
n
f
o
r
th
e
d
ev
elo
p
m
en
t
o
f
n
ew
eq
u
i
p
m
en
t
to
im
p
r
o
v
e
th
e
q
u
ality
o
f
elec
tr
ic
ity
,
esp
ec
ially
o
n
th
e
cu
s
to
m
er
'
s
s
id
e.
Po
wer
elec
tr
o
n
ic
d
ev
ice
d
is
tr
ib
u
tio
n
s
tatic
s
y
n
ch
r
o
n
o
u
s
c
o
m
p
en
s
ato
r
(
DS
T
AT
C
OM
)
attem
p
ts
to
r
esto
r
e
p
o
wer
q
u
ality
o
n
th
e
d
is
tr
ib
u
ti
o
n
s
y
s
tem
'
s
s
o
u
r
ce
an
d
lo
ad
s
id
es
[
1
]
.
W
h
en
co
m
p
ar
ed
to
o
th
er
d
ev
ices
u
s
ed
m
eth
o
d
s
s
u
ch
as
d
y
n
am
ic
v
o
lta
g
e
r
esto
r
er
(
DVR
)
,
u
n
if
ied
p
o
wer
-
q
u
ality
co
n
d
iti
o
n
er
(
UPQC
)
,
in
ter
lin
e
p
o
w
er
-
f
lo
w
co
n
tr
o
ller
(
I
PF
C
)
,
DSTA
T
C
OM
o
f
f
er
s
n
u
m
er
o
u
s
ad
v
a
n
tag
es
lik
e
l
o
w
co
s
t,
lo
w
lo
s
s
,
s
ize
is
co
m
p
ac
t,
an
d
less
h
ar
m
o
n
ic
g
en
er
atio
n
.
On
e
o
f
DSTA
T
C
OM
's
u
n
iq
u
e
b
en
ef
i
ts
is
its
ab
il
ity
to
p
r
o
v
id
e
q
u
ick
,
co
n
tin
u
o
u
s
,
an
d
u
n
in
ter
r
u
p
ted
in
d
u
ctiv
e
o
r
ca
p
ac
itiv
e
co
m
p
en
s
atio
n
.
B
ased
o
n
th
e
s
p
ec
if
ie
d
l
o
ad
,
th
e
DSTA
T
C
OM
in
jects
a
s
ig
n
if
ican
t
am
o
u
n
t
o
f
t
h
e
lead
in
g
alo
n
g
with
th
e
lag
g
in
g
co
m
p
e
n
s
atio
n
cu
r
r
en
t
to
m
a
tch
th
e
u
tili
ty
co
n
n
ec
tio
n
'
s
to
tal
d
em
an
d
[2
]
,
[
3]
.
T
h
e
DSTA
T
C
OM
b
eg
an
to
f
u
n
ctio
n
d
y
n
am
ically
in
th
e
r
a
d
ial
d
is
tr
ib
u
tio
n
s
y
s
tem
as
a
r
esu
lt
o
f
th
is
ty
p
e
o
f
in
jectio
n
.
R
ea
ctiv
e
co
m
p
e
n
s
atio
n
h
as
b
ee
n
th
e
p
r
im
ar
y
u
s
e
o
f
th
is
k
in
d
o
f
DSTA
T
C
OM
co
n
tr
o
ller
in
in
d
u
ctio
n
g
en
er
ato
r
s
in
r
ec
en
t
y
ea
r
s
.
T
h
e
co
n
tr
o
l
alg
o
r
ith
m
t
y
p
ically
d
e
ter
m
in
es
DSTA
T
C
OM
co
m
p
li
an
ce
in
ea
ch
g
iv
e
n
ap
p
licatio
n
[4
]
,
[
5]
e
x
p
lain
e
d
DSTA
T
C
OM
co
n
tr
o
l
u
s
in
g
a
f
ix
ed
-
p
ar
a
m
eter
p
r
o
p
o
r
tio
n
al
in
teg
r
al
(
PI
)
c
o
n
tr
o
ller
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
P
o
w
er q
u
a
lity
en
h
a
n
ce
men
t u
s
in
g
fu
lly
in
fo
r
med
p
a
r
ticle
s
w
a
r
m
o
p
timiz
a
tio
n
…
(
Mo
g
u
th
a
la
S
h
a
n
ka
r
)
983
an
d
o
f
f
er
e
d
t
h
r
ee
d
if
f
er
e
n
t
c
o
n
tr
o
l
m
eth
o
d
s
s
u
ch
as
P,
PI,
p
r
o
p
o
r
tio
n
al
in
teg
r
al
d
er
i
v
ativ
e
(
PID
)
f
o
r
p
r
o
d
u
cin
g
r
ef
er
en
ce
cu
r
r
e
n
t
co
m
p
o
n
e
n
ts
[
6
]
.
A
DSTA
T
C
OM
co
n
n
ec
ted
to
a
d
is
tr
ib
u
ted
g
en
er
atio
n
d
is
tr
ib
u
tio
n
n
etwo
r
k
f
ea
tu
r
es
a
n
o
n
lin
ea
r
co
n
tr
o
lle
r
to
co
n
tr
o
l
th
e
g
r
i
d
v
o
ltag
e
u
s
ed
s
elf
-
tu
n
in
g
f
ilter
s
an
d
in
s
tan
tan
eo
u
s
r
ea
ctiv
e
p
o
wer
th
eo
r
y
to
co
n
s
tr
u
ct
a
n
alg
o
r
ith
m
f
o
r
DSTA
T
C
OM
.
S
o
m
e
r
esear
ch
er
s
u
s
ed
it
to
d
a
m
p
en
th
e
s
y
s
tem
in
ad
d
itio
n
to
c
o
n
tr
o
llin
g
th
e
ex
c
h
an
g
e
o
f
r
ea
ctiv
e
p
o
we
r
[7
]
,
[
8]
.
R
ef
er
e
n
ce
v
alu
es
f
o
r
DSTA
T
C
OM
co
n
tr
o
l
a
r
e
o
f
ten
ac
q
u
ir
ed
v
ia
PI
co
n
tr
o
ller
s
,
p
r
im
ar
ily
th
e
‘
d
’
an
d
‘
q
’
ax
is
cu
r
r
en
ts
.
Data
m
in
in
g
is
ty
p
ically
d
o
n
e
in
a
lin
ea
r
co
n
tr
o
ller
,
wh
ich
n
ec
ess
itates
th
e
u
s
e
o
f
a
m
ath
em
ati
ca
l
m
o
d
el.
I
n
th
is
m
o
d
el
,
th
e
v
ar
io
u
s
p
ar
a
m
eter
s
h
av
e
b
ee
n
tu
n
ed
to
p
r
o
d
u
ce
t
h
e
o
p
tim
u
m
o
u
tco
m
es
f
o
r
a
c
er
tain
r
eg
io
n
u
n
d
er
c
o
n
s
tr
ain
e
d
co
n
d
itio
n
s
.
T
h
ese
co
n
tr
o
ller
s
,
wh
ich
wer
e
cr
ea
t
ed
u
s
in
g
a
lin
ea
r
m
ath
em
ati
ca
l
m
o
d
el,
p
er
f
o
r
m
p
o
o
r
ly
i
n
n
o
n
lin
ea
r
s
y
s
tem
d
y
n
am
ics,
m
o
s
tly
d
u
e
to
l
o
ad
d
is
tu
r
b
an
ce
an
d
p
ar
a
m
eter
c
h
a
n
g
es
[
9
]
.
Un
til
n
o
w,
lin
ea
r
ize
d
m
o
d
els
u
tili
ze
d
f
o
r
DSTA
T
C
OM
co
n
tr
o
l
wer
e
als
o
r
e
p
o
r
ted
.
So
m
e
au
th
o
r
s
cr
ea
ted
a
n
o
n
lin
ea
r
c
o
n
tr
o
ller
f
o
r
b
asic
p
o
wer
s
y
s
tem
m
o
d
els u
s
in
g
an
i
n
tr
icate
L
y
a
p
u
n
o
v
tech
n
i
q
u
e,
wh
ic
h
is
n
o
t
ap
p
licab
le
to
all
s
itu
atio
n
s
[
1
0
]
,
[
1
1
]
.
R
ec
en
tly
,
f
u
zz
y
lo
g
ic
an
d
an
ar
tific
ial
n
eu
r
al
n
etwo
r
k
co
n
t
r
o
ll
er
wer
e
u
tili
ze
d
to
co
n
tr
o
l
DSTA
T
C
OM
as
a
s
u
b
s
titu
te
f
o
r
a
g
en
er
al
co
n
tr
o
ller
.
T
h
e
n
ec
ess
ity
an
d
ad
v
an
tag
es
o
f
f
u
zz
y
lo
g
ic
alo
n
g
with
th
e
n
eu
r
al
n
etwo
r
k
-
b
ased
c
o
n
tr
o
ller
s
in
a
g
r
id
s
y
s
tem
wer
e
co
v
er
ed
i
n
.
On
e
s
ig
n
if
ican
t
b
en
ef
it
th
at
wi
ll
d
em
o
n
s
tr
ate
g
o
o
d
r
esp
o
n
s
e
tim
es
is
th
e
co
n
tr
o
lle
r
s
cr
ea
ted
with
th
e
ex
p
e
r
t
s
y
s
tem
d
o
n
o
t
n
ee
d
a
m
ath
em
atic
al
m
o
d
el
[
1
2
]
,
[
1
3
]
.
T
h
is
k
in
d
o
f
co
n
tr
o
ller
is
d
if
f
e
r
en
t
f
r
o
m
th
e
tr
ad
itio
n
al
lin
ea
r
co
n
tr
o
ller
in
th
at
it
allo
ws
f
o
r
a
b
r
o
ad
v
a
r
iety
o
f
s
y
s
tem
o
p
er
atin
g
cir
cu
m
s
tan
c
es,
r
eg
ar
d
less
o
f
task
co
m
p
lex
ity
.
Selectin
g
th
e
co
n
tr
o
ller
'
s
i
n
p
u
ts
th
at
ar
e
tr
u
ly
im
p
o
r
tan
t
m
ig
h
t
im
p
r
o
v
e
p
er
f
o
r
m
an
ce
ev
e
n
f
u
r
t
h
er
;
th
is
to
p
ic
is
co
v
er
ed
in
f
u
r
th
e
r
d
etail
in
th
is
ar
ticle
[
1
4
]
.
C
o
n
s
id
er
in
g
all
th
ese
p
r
o
b
lem
s
,
f
u
lly
in
f
o
r
m
ed
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
FIPSO)
is
s
u
g
g
ested
alo
n
g
with
a
p
r
o
b
a
b
ilis
tic
n
eu
r
al
n
etwo
r
k
(
PNN
)
-
PI
co
n
tr
o
ller
to
co
n
tr
o
l
th
e
DSTA
T
C
OM
'
d
'
an
d
q
ax
es.
PNNs
ap
p
ea
r
to
p
r
o
v
id
e
m
o
r
e
ef
f
ec
tiv
e
s
o
lu
tio
n
s
f
o
r
a
r
a
n
g
e
o
f
co
n
t
r
o
l
is
s
u
es
[
1
5
]
,
[
16]
.
T
h
e
f
ac
t
th
at
PNNs
ca
n
s
o
lv
e
i
n
tr
icate
,
n
o
n
lin
ea
r
,
an
d
m
ath
em
atica
l
p
r
o
b
lem
s
in
r
ea
l
-
wo
r
ld
d
y
n
am
i
ca
l
s
y
s
tem
s
ce
r
tain
ly
d
r
aws
r
e
s
ea
r
ch
er
s
to
em
p
lo
y
th
em
in
co
n
tr
o
ller
d
esig
n
.
Ga
in
in
g
th
e
r
ig
h
t
weig
h
t
an
d
lo
s
in
g
weig
h
t,
h
o
wev
er
,
ar
e
d
if
f
i
cu
lt
task
s
.
W
eig
h
t
ad
ju
s
tm
en
t
ap
p
licatio
n
s
ar
e
p
r
im
ar
ily
b
u
ilt
b
y
h
u
m
an
p
r
o
f
ess
io
n
als
an
d
r
ely
o
n
m
an
y
co
n
tr
o
ller
s
[
1
7
]
.
Ho
wev
er
,
it
tak
es
a
g
r
ea
t
d
ea
l o
f
ex
p
e
r
tis
e,
tim
e,
an
d
p
atien
c
e,
an
d
th
e
tu
n
in
g
an
d
d
esig
n
w
eig
h
t
m
ig
h
t
n
o
t
b
e
id
ea
l.
T
h
e
r
e
h
as
b
ee
n
a
lo
t
o
f
r
esear
ch
o
n
esti
m
atin
g
th
e
ap
p
r
o
p
r
iate
weig
h
t
n
ee
d
ed
f
o
r
co
n
t
r
o
ller
d
esig
n
f
u
lly
in
f
o
r
m
e
d
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
FIPSO)
is
u
s
ed
to
e
x
tr
ac
t
th
e
weig
h
t,
th
is
ap
p
r
o
ac
h
h
as
b
ee
n
u
tili
ze
d
to
p
r
ed
eter
m
in
e
t
h
e
weig
h
t
f
u
n
ct
io
n
o
n
th
e
i
n
p
u
t p
r
o
p
e
r
ties
.
I
n
i
tial
s
ettin
g
s
f
o
r
th
ese
f
u
n
ctio
n
s
ar
e
s
et
in
o
r
d
er
to
ac
co
m
m
o
d
ate
ch
a
n
g
in
g
p
ar
am
eter
s
.
W
h
en
co
m
p
ar
ed
to
o
th
er
alg
o
r
ith
m
s
FIPSO
alg
o
r
ith
m
g
iv
e
b
etter
ac
cu
r
ac
y
an
d
tak
es
less
tim
e,
wh
ic
h
ca
n
b
e
ap
p
licab
le
f
o
r
all
th
e
n
etwo
r
k
s
m
ain
tain
in
g
u
n
iq
u
e
alg
o
r
it
h
m
.
Fu
lly
in
f
o
r
m
ed
PS
O
r
eq
u
ir
es
less
ter
m
in
al
p
a
r
am
eter
d
ata
co
m
p
ar
ed
to
o
th
er
alg
o
r
ith
m
s
.
T
h
e
s
u
g
g
ested
co
n
tr
o
ller
is
p
u
t
in
t
o
p
r
ac
tice,
s
im
u
lated
,
an
d
f
o
u
n
d
to
h
av
e
s
u
p
er
io
r
q
u
alities
th
a
n
th
e
co
n
v
en
tio
n
al
co
n
tr
o
ller
[
1
8
]
,
[
1
9
]
.
T
h
e
wo
r
k
ad
d
r
ess
es
PNN
-
PI,
PNN
FI
P
SO
co
n
tr
o
ller
d
esig
n
,
an
d
m
a
th
em
atica
l
m
o
d
elin
g
o
f
DST
AT
C
OM
in
o
r
d
er
o
f
p
r
ec
ed
en
ce
.
T
h
e
s
ig
n
if
ican
t
in
itiativ
es
th
at
h
av
e
f
u
eled
an
d
g
u
id
ed
p
a
r
ticle
s
war
m
r
esear
ch
,
alo
n
g
with
s
o
m
e
s
ig
n
if
ican
t
n
ew
u
s
es
an
d
av
e
n
u
es.
T
h
e
two
-
s
tep
PS
O
an
d
th
e
PS
O
-
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
in
e
(
PS
O
-
SVM)
,
d
em
o
n
s
tr
ate
th
e
q
u
ic
k
ad
a
p
ta
tio
n
o
f
PS
O
[
2
0
]
.
Stu
n
n
in
g
o
u
tco
m
es
h
av
e
also
b
ee
n
p
r
o
d
u
ce
d
b
y
th
e
PS
O's
in
teg
r
atio
n
an
d
p
r
ac
tical
ap
p
lic
atio
n
with
th
e
in
d
u
s
tr
y
-
s
tan
d
ar
d
m
eth
o
d
.
T
h
e
i
n
er
tia
weig
h
t,
m
u
tatio
n
o
p
er
ato
r
s
,
an
d
s
war
m
s
tar
tu
p
[
2
1
]
.
T
h
is
o
v
er
v
iew'
s
p
r
im
ar
y
b
en
e
f
it
was
em
p
h
asizin
g
h
o
w
cr
u
cial
it
is
t
o
in
tr
o
d
u
ce
s
ev
er
al
m
u
tatio
n
o
p
e
r
ato
r
s
an
d
th
e
in
er
tia
weig
h
t
p
ar
am
eter
in
o
r
d
er
to
en
h
an
ce
PS
O
p
er
f
o
r
m
a
n
ce
[
2
2
]
.
T
h
e
PS
O
alg
o
r
ith
m
,
as
well
as
d
o
in
g
a
th
eo
r
etica
l
ex
am
i
n
atio
n
o
f
th
e
s
y
s
tem
.
T
h
e
n
,
t
h
ey
e
x
am
in
ed
its
cu
r
r
e
n
t
u
s
e
an
d
r
esear
ch
in
e
n
g
in
ee
r
in
g
ap
p
licatio
n
s
,
d
i
s
cr
ete
an
d
p
ar
allel
PS
O
alg
o
r
ith
m
s
,
p
a
r
am
eter
s
elec
t
io
n
,
m
u
lti
-
o
b
jectiv
e
o
p
tim
izatio
n
,
alg
o
r
ith
m
s
tr
u
ct
u
r
e,
an
d
to
p
o
l
o
g
ical
s
tr
u
ctu
r
e
.
Desp
ite
th
e
s
u
cc
ess
f
u
l
ap
p
licatio
n
o
f
PS
O
in
v
ar
io
u
s
d
o
m
ai
n
s
,
th
er
e
ar
e
s
till
ch
allen
g
es
th
at
n
ee
d
to
b
e
ad
d
r
ess
ed
an
d
co
n
s
id
er
ed
as
f
u
tu
r
e
r
esear
ch
d
ir
ec
tio
n
s
[
2
3
]
,
[
24]
.
Ov
er
th
e
p
ast
f
ew
y
ea
r
s
,
PS
O
h
as
g
a
r
n
er
ed
s
ig
n
if
i
ca
n
t
in
ter
est
f
r
o
m
r
esear
ch
e
r
s
an
d
h
as
b
ee
n
a
p
p
lied
in
d
iv
er
s
e
ar
ea
s
[
2
5
]
.
H
o
wev
e
r
,
th
er
e
a
r
e
s
till
cr
itical
p
r
o
b
le
m
s
an
d
is
s
u
es
th
at
p
er
s
is
t
[
2
6
]
,
[
2
7
]
.
T
h
e
r
ef
o
r
e
,
it
is
im
p
er
ativ
e
f
o
r
s
ch
o
lar
s
a
n
d
r
esear
ch
e
r
s
to
d
e
d
icate
m
o
r
e
r
esear
ch
ef
f
o
r
ts
to
war
d
s
o
v
er
co
m
in
g
th
ese
ch
allen
g
es
an
d
is
s
u
es
th
at
co
u
ld
p
o
ten
tially
h
in
d
e
r
th
e
f
u
t
u
r
e
ap
p
licatio
n
o
f
PS
O.
T
h
e
r
esear
ch
co
m
m
u
n
ity
s
h
o
u
ld
f
o
c
u
s
o
n
a
d
d
r
ess
in
g
n
e
w
m
eth
o
d
o
l
o
g
ies f
o
r
c
o
m
p
lex
p
r
o
b
lem
s
[
2
8
]
,
[
2
9
]
.
2.
DST
A
T
CO
M
M
O
D
E
L
L
I
N
G
A
3
MV
AR
DSTA
T
C
OM
h
ad
b
ee
n
co
n
n
ec
ted
in
th
e
p
ar
allel
with
lo
ad
o
n
B
3
to
r
aisi
n
g
a
lo
ad
v
o
ltag
e,
as
d
ep
icted
in
th
e
g
iv
en
Fig
u
r
e
1
.
T
h
e
s
o
u
r
ce
s
o
f
v
o
ltag
e
ar
e
d
ir
ec
tly
co
n
n
ec
ted
t
o
B
1
,
B
2
,
an
d
B
3
th
r
o
u
g
h
a
n
etwo
r
k
o
f
2
1
k
m
f
ee
d
e
r
s
,
wh
ile
th
e
g
e
n
er
ated
en
er
g
y
tr
a
v
el
s
th
r
o
u
g
h
B
1
,
B
2
,
a
n
d
B
3
.
I
n
o
r
d
er
to
c
o
n
n
ec
t
B
2
an
d
B
3
,
a
2
k
m
f
ee
d
er
is
u
tili
ze
d
in
th
is
.
T
h
ey
h
av
e
b
ee
n
c
o
n
n
ec
ted
in
th
e
B
3
v
ia
a
2
5
/0
.
6
s
te
p
-
d
o
wn
d
is
tr
ib
u
tio
n
tr
an
s
f
o
r
m
er
s
o
th
at
b
o
t
h
v
ar
ia
b
le
an
d
f
ix
ed
lo
a
d
s
ca
n
b
e
s
tu
d
ied
.
C
o
n
n
ec
tin
g
a
lo
a
d
esp
ec
ially
a
v
ar
iab
le
lo
a
d
is
m
ea
n
t
to
alter
th
e
v
o
ltag
e
an
d
cu
r
r
en
t
f
lo
win
g
th
r
o
u
g
h
b
u
s
B
3
.
T
h
e
DSTA
T
C
OM
ab
s
o
r
b
s
o
r
g
en
er
ates
r
ea
ctiv
e
p
o
wer
o
n
th
e
B
3
b
u
s
to
r
eg
u
late
v
o
ltag
e.
Usi
n
g
th
e
co
u
p
lin
g
tr
an
s
f
o
r
m
er
'
s
leak
y
r
ea
ctan
ce
to
cr
ea
te
a
s
ec
o
n
d
ar
y
v
o
ltag
e
in
th
e
p
h
ase
h
av
in
g
th
e
p
r
im
a
r
y
v
o
ltag
e,
r
ea
ctiv
e
p
o
wer
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
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7
9
2
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E
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,
Vo
l.
1
3
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4
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Dece
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P
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AB
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C
N
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URA
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WO
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S (
P
NN
s
)
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s
e
a
B
ay
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s
tr
ateg
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n
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d
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.
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PNN
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a
r
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teed
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ata.
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t
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ir
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p
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ed
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n
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et
wo
r
k
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Fig
u
r
e
2
g
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e
d
etai
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ar
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tr
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with
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eig
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(
in
p
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ts
).
T
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s
n
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itab
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it.
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n
ea
ch
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in
g
u
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it,
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atter
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atter
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atter
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t
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licates
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r
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tr
ain
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,
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ad
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o
f
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h
t
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to
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is
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er
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o
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m
ed
.
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n
th
is
wo
r
k
,
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e
tr
ain
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am
p
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d
if
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e
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ased
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th
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o
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ab
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n
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ity
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n
,
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ich
h
as b
ee
n
th
e
b
asic f
u
n
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o
f
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PNN.
A
s
im
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le
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ar
tial d
if
f
er
en
tial f
u
n
ctio
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is
as f
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(
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p
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in
p
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t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
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E
n
g
I
SS
N:
2252
-
8
7
9
2
P
o
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lity
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men
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in
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fu
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in
fo
r
med
p
a
r
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e
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lay
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th
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o
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.
Fig
u
r
e
2
.
Ar
c
h
itectu
r
e
o
f
PNN
4.
F
UL
L
Y
I
NF
O
RM
E
D
P
AR
T
I
CL
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SW
ARM O
P
T
I
M
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Z
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T
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O
N
T
h
e
g
lo
b
al
v
e
r
s
io
n
o
f
th
e
p
ar
t
icle
s
war
m
o
p
tim
izatio
n
is
th
e
f
u
lly
in
f
o
r
m
ed
p
a
r
ticle
s
war
m
(
FIPS
)
.
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ik
e
n
o
r
m
al
PS
O,
th
e
FIPSO a
ls
o
ad
ap
ts
th
e
b
est p
o
s
itio
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o
f
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b
o
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r
h
o
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p
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ticle
as d
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icted
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(
3
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+
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[
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d
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p
a
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i
n
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r
a
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o
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i
s
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t
h
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⊗
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s
t
h
e
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l
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m
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by
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m
e
n
t
v
e
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o
r
m
u
l
t
i
p
l
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a
t
i
o
n
.
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h
e
l
ea
r
n
i
n
g
c
o
e
f
f
i
c
i
e
n
t
a
n
d
c
o
n
s
t
r
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c
t
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o
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c
o
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f
f
ici
e
n
t
k
m
u
s
t
b
e
f
i
x
e
d
a
c
c
o
r
d
i
n
g
t
o
r
e
q
u
i
r
e
m
e
n
ts
r
e
s
p
ec
t
i
v
e
l
y
.
T
h
e
p
o
p
u
l
a
t
i
o
n
s
i
z
e
h
as
t
o
b
e
a
s
s
u
m
e
d
s
u
i
t
a
b
l
y
.
T
h
e
i
n
i
t
ia
l
p
o
s
i
t
i
o
n
o
f
t
h
e
p
a
r
t
i
cl
e
s
i
s
f
o
r
m
e
d
r
a
n
d
o
m
l
y
.
A
g
r
e
a
t
e
r
n
u
m
b
e
r
o
f
it
e
r
a
t
i
o
n
s
i
s
n
ee
d
e
d
f
o
r
h
i
g
h
-
d
i
m
en
s
i
o
n
a
l
o
p
t
i
m
i
z
a
ti
o
n
p
r
o
b
l
e
m
s
.
H
e
r
e
,
t
o
s
o
l
v
e
tw
o
l
o
c
a
t
i
o
n
s
o
f
t
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p
a
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c
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es
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l
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t
h
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n
u
m
b
e
r
o
f
i
t
e
r
a
ti
o
n
s
5.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
5
.
1
.
P
NN
–
P
I
c
o
ntr
o
ller
All
th
at
was
in
v
o
lv
ed
with
th
e
we
ll
-
k
n
o
wn
class
ic
co
n
tr
o
l
s
y
s
tem
wh
ich
is
f
r
eq
u
en
tly
e
m
p
lo
y
ed
i
n
p
lace
o
f
o
th
er
co
n
tr
o
ller
ty
p
e
s
was
a
lin
ea
r
PI
co
n
tr
o
ller
.
Du
e
to
th
e
f
ac
t
th
at
th
is
co
n
tr
o
ller
is
lin
ea
r
,
it
i
s
u
n
s
u
itab
le
f
o
r
a
s
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m
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n
ly
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t
h
at
o
f
th
e
co
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tio
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alg
o
r
ith
m
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o
s
u
m
m
ar
ize
,
th
is
p
ap
er
in
itially
ex
am
in
ed
th
e
ef
f
ec
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o
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m
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d
co
n
clu
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e
d
th
at
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u
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f
o
r
m
s
GA.
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b
s
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n
tly
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e
lim
itatio
n
s
o
f
th
e
s
tan
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ar
d
PS
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wer
e
an
aly
ze
d
.
B
ased
o
n
th
is
a
n
aly
s
is
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a
n
o
v
el
PS
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alg
o
r
ith
m
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lled
F
I
PS
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was
in
tr
o
d
u
ce
d
.
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h
e
ex
p
er
im
en
tal
f
in
d
in
g
s
d
em
o
n
s
tr
ated
th
at
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I
PS
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s
u
r
p
ass
es
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o
th
th
e
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ad
itio
n
al
PS
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an
d
t
h
e
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al
g
o
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ith
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en
ap
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ch
m
a
r
k
f
u
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s
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I
PS
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ex
h
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em
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k
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le
en
h
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ts
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lly
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tify
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tio
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s
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ar
ticu
lar
ly
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o
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ch
allen
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f
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n
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s
.
RE
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R
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NC
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1
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[
3
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S
.
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[
4
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O
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P
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[
5
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T.
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h
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a
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v
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[
6
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M
.
A
.
M
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d
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,
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[
7
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B
.
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h
,
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.
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,
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.
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,
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me
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8
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N
.
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.
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,
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,
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.
[
9
]
S
.
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.
K
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mar,
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n
Pr
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[
1
0
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B
.
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.
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n
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[
2
6
]
V
.
K
o
t
h
a
r
i
,
J.
A
n
u
r
a
d
h
a
,
S
.
S
h
a
h
,
a
n
d
P
.
M
i
t
t
a
l
,
“
A
s
u
r
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p
a
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c
l
e
s
w
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t
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I
n
t
e
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a
t
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o
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n
c
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.
[
2
7
]
M
.
I
mr
a
n
,
R
.
H
a
s
h
i
m,
a
n
d
N
.
E
.
A
.
K
h
a
l
i
d
,
“
A
n
o
v
e
r
v
i
e
w
o
f
p
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
m
i
z
a
t
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v
a
r
i
a
n
t
s,
”
Pr
o
c
e
d
i
a
En
g
i
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ri
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g
,
v
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.
5
3
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p
p
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p
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[
2
8
]
D
.
W
a
n
g
,
D
.
T
a
n
,
a
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d
L
.
Li
u
,
“
P
a
r
t
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c
l
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sw
a
r
m o
p
t
i
mi
z
a
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a
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v
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,
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S
o
f
t
C
o
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p
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6.
[
2
9
]
X
.
R
a
o
a
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d
X
.
Y
a
n
,
“
P
a
r
t
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c
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0
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Wi
r
e
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ss
C
o
m
m
u
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t
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s
a
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M
o
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.
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
Mo
g
u
th
a
l
a
S
h
a
n
k
a
r
h
a
s
re
c
e
iv
e
d
a
B.
Tec
h
.
a
n
d
M
.
Tec
h
.
fr
o
m
JN
TU
Hy
d
e
ra
b
a
d
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n
d
ia,
i
n
2
0
1
2
a
n
d
2
0
1
5
re
sp
e
c
ti
v
e
l
y
,
a
n
d
p
u
rs
u
in
g
a
P
h
.
D.
at
An
n
a
Un
i
v
e
rsity
,
Ch
e
n
n
a
i,
Tam
il
Na
d
u
,
In
d
ia.
He
h
a
s
p
re
se
n
ted
tec
h
n
ica
l
p
a
p
e
rs
in
v
a
rio
u
s
n
a
ti
o
n
a
l
a
n
d
in
tern
a
ti
o
n
a
l
j
o
u
rn
a
ls
a
n
d
c
o
n
fe
re
n
c
e
s
.
His
a
re
a
s
o
f
in
tere
st
in
c
lu
d
e
p
o
we
r
e
lec
tro
n
ics
,
p
o
we
r
q
u
a
li
t
y
,
m
u
lt
i
-
lev
e
l
in
v
e
rters
n
e
u
r
a
l
n
e
two
rk
s
,
a
n
d
fu
z
z
y
l
o
g
ic
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
n
n
r
g
sh
a
n
k
a
r@g
m
a
il
.
c
o
m
.
Dr
.
R
.
S
e
n
th
i
l
K
u
m
a
r
c
u
rre
n
t
ly
is
wo
rk
in
g
a
s
a
p
ro
fe
ss
o
r
in
t
h
e
El
e
c
tri
c
a
l
a
n
d
El
e
c
tro
n
ics
En
g
in
e
e
ri
n
g
De
p
a
rt
m
e
n
t
o
f
S
a
v
e
e
th
a
En
g
i
n
e
e
rin
g
Co
ll
e
g
e
(Au
t
o
n
o
m
o
u
s),
Ch
e
n
n
a
i,
a
n
d
Tam
il
N
a
d
u
.
He
h
a
s
d
o
n
e
B.
E
.
i
n
e
lec
tri
c
a
l
e
n
g
in
e
e
rin
g
fr
o
m
th
e
U
n
i
v
e
rsity
Co
ll
e
g
e
o
f
En
g
in
e
e
rin
g
(g
u
in
d
y
)
a
n
d
a
n
M
.
E
.
a
n
d
P
h
.
D.
fro
m
An
n
a
U
n
iv
e
rsit
y
,
Ch
e
n
n
a
i
,
Tam
il
Na
d
u
,
In
d
ia
.
His
m
a
in
r
e
se
a
rc
h
d
irec
ti
o
n
s
in
c
l
u
d
e
a
rti
fi
c
ial
in
telli
g
e
n
c
e
(n
e
u
ra
l
n
e
two
rk
s,
f
u
z
z
y
lo
g
ic,
g
e
n
e
ti
c
a
lg
o
rit
h
m
,
p
a
rti
c
le
sw
a
rm
o
p
ti
m
iza
ti
o
n
,
a
n
d
imp
e
rialist
c
o
m
p
e
ti
ti
v
e
a
lg
o
r
it
h
m
)
g
ra
v
i
tati
o
n
a
l
se
a
rc
h
a
lg
o
r
it
h
m
,
p
o
we
r
q
u
a
li
ty
,
a
n
d
p
ro
p
o
r
ti
o
n
a
l
-
in
teg
ra
l
c
o
n
tr
o
ll
e
r.
He
h
a
s
p
u
b
li
sh
e
d
2
5
in
ter
n
a
ti
o
n
a
l
j
o
u
r
n
a
l
p
a
p
e
rs,
1
5
i
n
tern
a
ti
o
n
a
l
c
o
n
fe
re
n
c
e
p
a
p
e
rs
,
a
n
d
2
Na
ti
o
n
a
l
Co
n
fe
re
n
c
e
p
a
p
e
rs
a
n
d
a
lso
p
u
b
li
s
h
e
d
a
b
o
o
k
n
a
m
e
d
S
p
e
c
ial
El
e
c
tri
c
a
l
M
a
c
h
i
n
e
s
in
t
h
e
y
e
a
r
2
0
0
9
.
Re
v
iew
e
r
o
f
th
e
b
o
o
k
-
Ba
sic
El
e
c
tri
c
a
l
a
n
d
El
e
c
tro
n
ics
E
n
g
in
e
e
rin
g
–
C
h
a
ru
lath
a
P
u
b
li
c
a
ti
o
n
s
a
n
d
r
e
v
iew
e
r
o
f
t
h
e
J
o
u
r
n
a
l
i
n
In
tern
a
ti
o
n
a
l
Jo
u
rn
a
l
o
f
El
e
c
tri
c
a
l
En
g
i
n
e
e
rin
g
a
n
d
Tec
h
n
o
l
o
g
y
a
n
d
t
h
e
Jo
u
r
n
a
l
of
IET
in
P
o
we
r
El
e
c
tro
n
ics
.
His
a
re
a
s
o
f
r
e
se
a
rc
h
in
tere
st
a
re
re
n
e
wa
b
le
a
n
d
n
o
n
-
re
n
e
wa
b
le
e
n
e
rg
y
so
u
rc
e
s,
p
o
we
r
c
o
n
v
e
rters
,
a
n
d
e
lec
tri
c
a
l
m
a
c
h
in
e
s.
He
is
a
p
ro
fe
ss
io
n
a
l
m
e
m
b
e
r
of
IEI
,
IEE
E,
IS
TE
,
a
n
d
UA
CEE
.
He
is
o
n
e
o
f
th
e
m
e
m
b
e
rs
of
t
h
e
a
d
v
is
o
ry
c
o
m
m
it
tee
fo
r
o
n
e
o
f
th
e
lea
d
in
g
e
n
g
i
n
e
e
rin
g
c
o
ll
e
g
es
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
se
n
t
h
il
k
u
m
a
r@sa
v
e
e
th
a
.
a
c
.
in
.
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