I
nd
o
ne
s
ia
n J
o
urna
l o
f
E
lect
rica
l En
g
ineering
a
nd
Co
m
pu
t
er
Scienc
e
Vo
l.
23
,
No
.
2
,
A
u
g
u
s
t
20
21
,
p
p
.
6
3
3
~
63
8
I
SS
N:
2
5
0
2
-
4
7
5
2
,
DOI
: 1
0
.
1
1
5
9
1
/ijeecs.v
23
.i
2
.
pp
633
-
63
8
633
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
ee
cs.ia
esco
r
e.
co
m
Particle
swa
rm o
ptimiza
tion
tuned
unif
ied
power
f
lo
w
co
ntroller
for
po
wer oscill
a
tion r
e
duction
A
na
nd
a
M
.
H
.
1
,
M
.
R.
S
hiv
a
k
um
a
r
2
1
S
c
h
o
o
l
o
f
El
e
c
tri
c
a
l
a
n
d
El
e
c
tro
n
ics
En
g
i
n
e
e
rin
g
,
REVA Un
i
v
e
rsit
y
/Res
e
a
rc
h
S
c
h
o
lar V.
T
.
U,
I
n
d
ia
2
S
ri
Re
v
a
n
a
S
id
d
e
s
h
wa
ra
In
stit
u
te o
f
Tec
h
n
o
l
o
g
y
,
I
n
d
ia
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Feb
17
,
2
0
2
1
R
ev
is
ed
J
u
n
30
,
2
0
2
1
Acc
ep
ted
J
u
l
7
,
2
0
2
1
On
e
o
f
t
h
e
b
e
st
f
lex
ib
le
AC
tra
n
sm
issio
n
s
y
ste
m
(F
ACTS
)
is
u
n
i
fied
p
o
we
r
flo
w
c
o
n
tr
o
ll
e
r
(UPF
C).
As
it
g
e
ts
m
o
re
b
e
n
e
fit
fro
m
b
o
th
re
a
l
a
n
d
re
a
c
ti
v
e
p
o
we
r
tra
n
sfe
r,
it
is
u
se
d
in
p
o
we
r
sy
ste
m
fo
r
c
o
n
tr
o
ll
i
n
g
t
h
e
t
ra
n
sm
it
ted
p
o
we
r.
Th
e
U
P
F
C
c
o
n
tr
o
ls
th
e
p
o
we
r
o
n
t
h
e
tra
n
sm
issio
n
sid
e
o
f
th
e
p
o
we
r
sy
ste
m
.
Wh
e
n
th
e
re
a
l
a
s
we
ll
a
s
re
a
c
ti
v
e
p
o
we
r
is
se
t
t
h
e
UP
F
C
tri
e
s
t
o
fo
ll
o
w
th
e
c
o
m
m
a
n
d
b
y
u
sin
g
t
h
e
p
ro
p
o
rti
o
n
a
l
a
n
d
in
teg
ra
l
(
PI
)
c
o
n
tro
ll
e
r.
Bu
t
in
s
o
m
e
p
o
we
r
sy
ste
m
s
th
e
P
I
c
o
n
tr
o
ll
e
rs
c
a
n
n
o
t
p
r
o
d
u
c
e
th
e
p
ro
p
e
r
p
o
we
r
d
u
e
to
t
h
e
p
o
we
r
o
sc
il
lati
o
n
s.
Th
e
se
o
sc
il
latio
n
s
a
re
c
re
a
ted
d
u
e
to
P
I
c
o
n
tro
l
ler
p
r
o
p
e
rti
e
s.
I
n
th
is
p
a
p
e
r
th
e
P
I
c
o
n
tr
o
ll
e
r
is
re
p
lac
e
d
with
th
e
p
a
rti
c
le
sw
a
rm
o
p
ti
m
iza
ti
o
n
t
u
n
e
d
P
I
c
o
n
tr
o
ll
e
r
(
P
S
O
-
P
I).
It
m
in
i
m
ize
s
th
e
p
o
we
r
o
sc
il
lati
o
n
s
b
y
u
sin
g
th
e
o
b
jec
ti
v
e
f
u
n
c
ti
o
n
.
Th
e
M
AT
LAB
2
0
1
7
b
is
u
se
d
t
o
d
e
m
o
n
stra
te
th
e
p
o
we
r
tr
a
n
sfe
r
c
u
rv
e
s
a
n
d
th
e
v
o
lt
a
g
e
s.
T
h
e
IEE
E
9
b
u
s sy
ste
m
is
b
e
in
g
u
se
d
a
s a
re
fe
re
n
c
e
sy
ste
m
.
K
ey
w
o
r
d
s
:
FAC
T
S
I
E
E
E
9
b
u
s
Par
ticle
s
war
m
o
p
tim
izatio
n
PI
co
n
tr
o
ller
Po
wer
o
s
cillatio
n
d
am
p
in
g
UPFC
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
:
An
an
d
a
M.
H
Sch
o
o
l o
f
E
lectr
ical
a
n
d
E
lectr
o
n
ics
E
n
g
in
ee
r
i
n
g
R
E
VA
Un
iv
er
s
ity
R
esear
ch
Sch
o
lar
,
V.
T
.
U.
,
I
n
d
ia
E
m
ail: a
n
an
d
m
h
d
v
g
@
g
m
ail.
c
o
m
1.
I
NT
RO
D
UCT
I
O
N
FAC
T
S
d
ev
ices
ar
e
u
s
ed
f
o
r
im
p
r
o
v
em
e
n
t
o
f
th
e
p
o
wer
tr
an
s
f
er
in
t
h
e
p
o
wer
s
y
s
tem
.
I
n
th
at
ty
p
e
UPFC
p
r
o
d
u
ce
s
b
o
th
r
ea
l
an
d
r
ea
ctiv
e
p
o
wer
co
n
tr
o
l
th
r
o
u
g
h
th
e
tr
an
s
m
is
s
io
n
lin
e
[
1
]
.
T
h
er
e
ar
e
m
an
y
ty
p
es
o
f
UPFC
co
m
p
e
n
s
atio
n
lik
e
li
n
e
s
en
d
in
g
e
n
d
/
r
ec
eiv
in
g
e
n
d
an
d
m
id
-
p
o
in
t
co
m
p
en
s
atio
n
s
[
2
]
.
T
h
ese
d
e
v
ices
ar
e
u
s
ed
to
d
am
p
t
h
e
to
r
q
u
e
o
s
cillatio
n
s
in
th
e
g
en
er
ato
r
a
n
ew
co
n
tr
o
l
is
in
tr
o
d
u
ce
d
in
[
3
]
.
T
h
en
th
e
v
o
ltag
e
s
tab
ilit
y
is
d
o
n
e
b
y
[
4
]
with
r
a
d
ial
b
asis
n
eu
r
al
n
etwo
r
k
.
W
ith
s
am
e
s
o
lu
tio
n
r
ed
u
ci
n
g
th
e
i
n
p
u
ts
u
s
ed
ar
e
u
s
ed
in
[
5
]
.
As
well
as
th
e
r
esear
ch
es
to
im
p
r
o
v
e
th
e
ar
tific
ial
in
tellig
en
ce
ar
e
also
d
o
n
e
lik
e
d
ir
ec
t
ad
ap
tiv
e
n
etwo
r
k
f
o
r
tr
ain
in
g
it
with
b
ac
k
p
r
o
p
ag
atio
n
is
ca
r
r
ied
o
u
t
in
[
6
]
an
d
with
f
ee
d
f
o
r
war
d
n
e
u
r
al
n
etwo
r
k
[
7
]
,
[
8
]
ar
e
ca
r
r
ied
o
u
t.
An
d
in
th
e
p
o
wer
s
y
s
tem
t
h
e
im
p
r
o
v
em
en
t
in
tr
a
n
s
ien
t
s
tab
ilit
y
b
y
u
s
in
g
th
e
n
eu
r
al
n
etwo
r
k
is
p
r
o
p
o
s
ed
in
[
9
]
.
An
au
to
m
atic
r
eg
u
latio
n
o
f
th
e
r
ea
ctiv
e
p
o
we
r
in
a
h
y
b
r
id
p
o
wer
s
y
s
tem
h
as
also
b
ee
n
p
r
o
p
o
s
ed
in
[
10
]
.
T
h
e
d
ig
ital
s
ig
n
al
p
e
r
ip
h
er
a
l
in
ter
f
ac
e
co
n
tr
o
ller
(
DSPIC
)
p
r
o
ce
s
s
o
r
is
u
s
ed
f
o
r
r
ea
cti
v
e
p
o
wer
co
m
p
en
s
at
io
n
is
d
ep
icted
in
[
1
1
]
an
d
it
is
im
p
lem
en
ted
with
n
eu
r
al
n
etwo
r
k
.
R
ea
ctiv
e
p
o
wer
co
n
tr
o
l
with
ANN
in
h
y
b
r
id
p
o
wer
g
r
id
is
d
is
cu
s
s
ed
in
[
1
2
]
a
n
d
b
ased
o
n
f
u
zz
y
i
s
d
is
cu
s
s
ed
in
[
1
3
]
.
T
h
e
f
au
lt
lo
ca
tio
n
id
en
tific
a
tio
n
is
d
o
n
e
with
ANN
in
[
1
4
]
.
T
h
er
e
a
r
e
m
an
y
r
esea
r
ch
es
av
ailab
le
in
UPFC
[
1
5
]
-
[
2
4
].
T
h
e
m
u
ltiv
er
s
e
o
p
tim
izatio
n
is
p
r
esen
ted
in
[
2
5
]
f
o
r
p
o
wer
s
y
tem
o
s
cillatio
n
s
tab
ilit
y
.
I
n
th
is
p
ap
er
th
e
PI
is
tu
n
e
d
to
m
in
i
m
ize
th
e
s
tea
d
y
s
tate
er
r
o
r
o
f
th
e
p
o
wer
in
t
h
e
UPFC
co
n
tr
o
l
is
im
p
lem
en
ted
.
T
h
is
r
ed
u
ce
s
th
e
o
s
cillatio
n
s
with
in
th
e
p
o
wer
s
y
s
tem
as th
e
s
ettlin
g
tim
e
is
r
ed
u
ce
d
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
23
,
No
.
2
,
Au
g
u
s
t
20
21
:
633
-
63
8
634
2.
UP
F
C
M
O
DE
L
I
NG
T
h
e
UPFC
co
n
s
is
t
o
f
two
co
n
v
er
ter
s
,
wh
ich
is
s
h
o
wn
in
Fig
u
r
e
1
.
On
e
is
co
n
n
ec
ted
i
n
p
ar
al
lel
an
d
an
o
th
er
o
n
e
is
co
n
n
ec
ted
in
s
er
ies
to
th
e
b
u
s
s
y
s
tem
.
So
,
it
ca
n
ab
le
to
h
an
d
le
th
e
r
ea
l
an
d
r
ea
ctiv
e
p
o
wer
in
d
ec
o
u
p
le
d
way
b
y
u
s
in
g
th
e
co
n
tr
o
l
tech
n
iq
u
es
s
h
o
wn
in
Fig
u
r
e
2
.
T
h
e
co
n
v
er
ter
is
co
n
n
ec
ted
u
s
in
g
th
e
s
er
ies an
d
p
ar
allel
co
n
n
ec
ted
i
s
o
la
ted
tr
an
s
f
o
r
m
er
s
.
Fig
u
r
e
1
.
UPFC
m
o
d
el
Fig
u
r
e
2
.
UPFC
co
n
tr
o
ller
wit
h
PS
O
-
PI
I
n
co
n
tr
o
l
tech
n
iq
u
es
th
e
co
n
tr
o
l
is
d
iv
id
ed
b
y
th
r
ee
.
T
h
ey
ar
e
AB
C
to
DQ0
co
n
v
er
s
io
n
,
s
er
ies
co
n
tr
o
ller
a
n
d
s
h
u
n
t
co
n
tr
o
lle
r
.
T
h
e
AB
C
to
DQ0
tr
an
s
f
o
r
m
atio
n
is
u
s
ed
f
o
r
c
o
n
v
e
r
tin
g
d
ec
o
u
p
lin
g
t
h
e
r
ea
l
an
d
r
ea
ctiv
e
c
o
m
p
o
n
en
t
f
r
o
m
th
e
AB
C
.
T
h
e
s
er
ies
co
n
tr
o
ller
co
m
p
a
r
es
th
e
I
d
q
r
ef
with
th
e
m
ea
s
u
r
ed
I
d
q
m
ea
s
u
r
e
d
.
T
h
is
co
m
p
ar
ed
er
r
o
r
is
g
iv
e
n
to
PI
co
n
tr
o
ller
o
r
as
p
r
o
p
o
s
ed
PS
O
-
PI
co
n
tr
o
ller
.
I
t
is
co
n
v
er
ted
to
Vd
q
r
ef
.
T
h
en
s
h
u
n
t
c
o
n
tr
o
l
ler
tak
es
th
e
ac
tio
n
an
d
it
co
m
p
ar
es
th
is
v
o
ltag
e
with
r
ef
er
en
ce
v
o
ltag
e
th
en
it
co
n
v
er
ts
it
as
cu
r
r
en
t.
So
,
s
er
ies
an
d
s
h
u
n
t
co
n
v
e
r
ter
s
ar
e
co
n
tr
o
llin
g
th
e
v
o
ltag
e
an
d
c
u
r
r
en
t
r
esp
ec
tiv
ely
.
Her
e
th
e
PS
O
-
PI
is
th
e
p
r
o
p
o
s
ed
co
n
v
er
ter
wh
ich
wo
r
k
o
p
ti
m
u
m
co
m
p
ar
ed
t
o
PI
co
n
tr
o
lle
r
.
3.
O
B
J
E
CT
I
V
E
F
UNC
T
I
O
N
Min
im
izatio
n
o
f
Settli
n
g
tim
e
o
f
r
ea
l p
o
wer
,
∑
=
1
(
1
)
W
ith
r
esp
ec
t to
co
n
s
tr
ain
ts
,
≤
≤
(
2
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
P
a
r
ticle
s
w
a
r
m
o
p
timiz
a
tio
n
tu
n
ed
u
n
ified
p
o
w
er flo
w
co
n
tr
o
ller
fo
r
p
o
w
er o
s
cilla
tio
n
…
(
A
n
a
n
d
a
M.
H
)
635
≤
≤
(
3
)
w
h
er
e
T
s
is
th
e
s
ettlin
g
tim
e,
Kp
m
in
an
d
K
p
m
ax
a
r
e
in
d
e
ed
th
e
m
in
im
u
m
an
d
t
h
e
m
ax
im
u
m
p
r
o
p
o
r
tio
n
al
g
ain
s
,
wh
ile
Ki
m
i
n
an
d
Ki
m
ax
ar
e
also
th
e
m
in
im
u
m
a
n
d
m
a
x
im
u
m
I
n
teg
r
al
g
ai
n
s
p
r
o
cu
r
e
d
b
y
e
x
p
er
tis
e
wh
ile
u
s
in
g
a
PI
co
n
t
r
o
ller
.
Par
ticle
s
war
m
o
p
tim
izatio
n
t
ec
h
n
iq
u
e
is
b
ased
o
n
th
e
s
war
m
’
s
f
o
o
d
-
s
ee
k
in
g
b
eh
a
v
io
u
r
[2
6
]
.
T
h
e
lar
g
e
g
r
o
u
p
of
b
ir
d
s
o
r
f
is
h
es
(
p
ar
ticle)
ac
tiv
ely
l
o
o
k
in
g
f
o
r
f
o
o
d
an
d
th
e
b
est
p
a
r
ticle
s
h
ar
in
g
its
p
o
s
itio
n
to
its
n
eig
h
b
o
u
r
h
o
o
d
p
ar
ticle
(
w
h
o
le
p
o
p
u
lace
is
co
n
s
id
er
ed
as
n
eig
h
b
o
u
r
h
o
o
d
p
ar
ticle)
an
d
th
e
d
ata
is
s
h
ar
ed
to
wh
o
le
s
war
m
with
b
est
ar
ea
in
th
e
p
u
r
s
u
it
s
p
ac
e.
Her
e,
f
o
o
d
is
th
e
g
o
al
wo
r
k
,
t
h
e
p
ar
ticl
es
ar
e
th
e
p
o
p
u
lace
an
d
s
war
m
ar
e
th
e
ab
s
o
lu
te
p
o
p
u
lace
in
ea
ch
em
p
h
asis
.
As
P
SO
d
ep
en
d
s
o
n
th
e
co
n
d
u
ct
o
f
th
e
f
o
o
d
s
ea
r
ch
in
a
g
ath
er
in
g
o
f
f
is
h
o
r
b
ee
s
o
r
b
ir
d
s
.
T
h
e
s
ch
em
e
o
f
th
e
alg
o
r
it
h
m
as f
lo
w
ch
ar
t is g
i
v
en
as Fig
u
r
e
3
.
Fig
u
r
e
3
.
Flo
w
ch
a
r
t o
f
PS
O
a
lg
o
r
ith
m
u
s
ed
f
o
r
PI
co
n
tr
o
ller
4.
R
E
SU
L
T
S AN
D
D
I
SCU
SS
I
O
NS
T
h
e
Fig
u
r
e
4
is
th
e
p
r
o
p
o
s
ed
s
tan
d
ar
d
I
E
E
E
9
b
u
s
s
y
s
tem
f
o
r
test
p
o
wer
s
y
s
tem
p
r
o
b
lem
.
T
h
e
I
E
E
E
9
b
u
s
s
y
s
tem
is
co
n
n
ec
te
d
w
ith
UPFC
d
ev
ice.
T
h
e
UPFC
is
co
n
n
ec
te
d
at
t
h
e
b
u
s
n
u
m
b
er
4
.
T
h
e
s
er
ies
co
n
v
er
ter
is
co
n
n
ec
ted
in
s
er
i
es
with
th
e
tr
an
s
m
i
s
s
io
n
lin
e
b
e
twee
n
b
u
s
4
to
b
u
s
6
.
T
h
e
c
o
n
tr
o
ls
f
o
r
b
o
t
h
th
e
co
n
v
er
ter
is
im
p
lem
en
ted
as sh
o
wn
in
th
e
Fig
u
r
e
2
.
T
h
e
s
etp
o
in
t
p
o
wer
is
g
iv
en
a
s
0
.
7
5
p
u
.
o
f
r
ea
l
p
o
wer
f
o
r
U
PF
C
.
I
t
is
in
cr
ea
s
ed
to
0
.
8
p
u
at
5
.
5
s
ec
s
.
T
h
e
to
tal
r
u
n
tim
e
is
1
0
s
ec
s
.
T
h
e
r
ea
ctiv
e
p
o
wer
r
ef
e
r
en
ce
tak
en
is
0
.
3
p
u
.
T
h
e
c
o
m
p
a
r
ativ
e
r
esu
lts
o
f
th
e
PI
co
n
tr
o
ller
a
n
d
PS
O
-
PI
ar
e
p
r
esen
ted
in
th
e
T
ab
le
1
.
T
h
e
PI
co
n
tr
o
ller
tak
es
o
n
ly
2
.
2
5
3
9
e
-
5
s
ec
s
to
r
is
e.
An
d
th
e
PS
O
-
PI
tak
es
o
n
ly
2
.
2
4
5
e
-
5
s
ec
s
.
Acc
o
r
d
in
g
to
th
e
o
b
j
ec
tiv
e
s
et
th
e
s
e
ttli
n
g
tim
e
is
0
.
9
8
0
6
s
ec
s
f
o
r
PI
co
n
tr
o
ller
b
u
t
u
s
in
g
PS
O
-
PI
it
tak
es
o
n
ly
0
.
8
7
2
3
s
ec
s
.
T
h
e
o
th
er
p
a
r
a
m
eter
s
ar
e
as
tab
u
la
ted
in
th
e
T
ab
le
1
,
an
d
it
is
ev
id
en
t
th
at
PS
O
-
PI
p
er
f
o
r
m
an
ce
is
b
etter
.
T
h
e
Fig
u
r
e
5
,
d
ep
icts
th
e
Po
wer
cu
r
v
es
u
s
in
g
PI
co
n
tr
o
ller
in
UPFC
s
y
s
tem
.
T
h
e
Fig
u
r
e
6
,
d
e
p
icts
th
e
Po
wer
cu
r
v
es
u
s
in
g
PS
O
-
PI
co
n
tr
o
ll
er
in
UPFC
d
ev
ice.
Fig
u
r
e
7
,
s
h
o
ws
th
e
C
o
m
p
ar
is
o
n
o
f
PI
an
d
PS
O
-
PI
co
n
tr
o
ller
in
I
E
E
E
9
b
u
s
s
y
s
tem
p
lac
ed
with
UPFC
.
T
h
e
s
et
p
o
in
t is r
ea
ch
ed
in
t
h
e
o
u
t
p
u
t a
s
ex
p
ec
ted
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
23
,
No
.
2
,
Au
g
u
s
t
20
21
:
633
-
63
8
636
Fig
u
r
e
4
.
Pro
p
o
s
ed
b
lo
ck
d
iag
r
am
(
I
E
E
E
-
9
b
u
s
s
y
s
tem
)
T
ab
le
1
.
C
o
m
p
a
r
is
o
n
o
f
m
eth
o
d
s
P
a
r
a
me
t
e
r
PI
P
SO
-
PI
R
i
se
T
i
me
(
s
e
c
)
2
.
2
5
3
9
e
-
05
2
.
2
4
5
0
e
-
05
S
e
t
t
l
i
n
g
T
i
me
(
sec
)
0
.
9
8
0
6
0
.
8
7
2
3
S
e
t
t
l
i
n
g
M
i
n
%
0
.
0
7
6
3
0
.
0
7
6
5
S
e
t
t
l
i
n
g
M
a
x
%
0
.
0
7
6
3
0
.
8
5
4
9
P
e
a
k
(
M
W
)
8
.
6
9
7
9
8
.
6
9
7
9
P
e
a
k
Ti
me
(
s
e
c
)
0
0
.
2
9
3
8
Fig
u
r
e
5
.
Po
wer
c
u
r
v
es o
f
PI
c
o
n
tr
o
ller
in
I
E
E
E
-
9
b
u
s
s
y
s
tem
Fig
u
r
e
6
.
Po
wer
c
u
r
v
es o
f
PS
O
-
PI
co
n
tr
o
ller
i
n
UPFC
in
I
E
E
E
9
b
u
s
s
y
s
tem
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
P
a
r
ticle
s
w
a
r
m
o
p
timiz
a
tio
n
tu
n
ed
u
n
ified
p
o
w
er flo
w
co
n
tr
o
ller
fo
r
p
o
w
er o
s
cilla
tio
n
…
(
A
n
a
n
d
a
M.
H
)
637
Fig
u
r
e
7
.
C
o
m
p
a
r
is
o
n
o
f
PI
an
d
PS
O
-
PI
co
n
tr
o
ller
in
I
E
E
E
9
b
u
s
s
y
s
tem
p
lace
d
with
UPFC
5.
CO
NCLU
SI
O
N
T
h
e
UPFC
is
p
lace
d
in
d
y
n
a
m
ic
I
E
E
E
9
s
im
u
latio
n
m
o
d
el.
T
h
e
s
ettlin
g
tim
e
is
m
in
im
iz
ed
b
y
u
s
in
g
th
e
PS
O
alg
o
r
ith
m
.
T
h
e
co
m
p
ar
ativ
e
an
aly
s
is
o
f
PI
an
d
P
SO
-
PI
co
n
tr
o
l
in
UPF
C
is
i
m
p
lem
en
ted
in
th
is
p
ap
er
.
T
h
e
s
ettlin
g
tim
e
is
m
in
im
ized
in
PS
O
-
PI
co
n
tr
o
ller
.
I
E
E
E
9
b
u
s
s
y
s
tem
s
h
o
ws
th
e
test
r
esu
lts
an
d
th
e
tim
e
d
ata
ar
e
tab
u
lated
.
T
h
e
p
ar
ticle
s
war
m
o
p
tim
izatio
n
tu
n
ed
PI
co
n
t
r
o
ller
(
PS
O
-
PI)
h
elp
s
to
r
ed
u
ce
th
e
po
wer
o
s
cillatio
n
s
m
u
ch
b
etter
an
d
f
aster
.
RE
F
E
R
E
NC
E
S
[1
]
N.
G
.
Hin
g
o
ra
n
i
a
n
d
L.
G
y
u
g
y
i,
Un
d
e
rs
ta
n
d
i
n
g
FA
CT
S
C
o
n
c
e
p
t
s
a
n
d
T
e
c
h
n
o
l
o
g
y
o
f
F
lex
ib
le
A
C
T
ra
n
sm
issio
n
sy
ste
m
,
USA:
Wi
ley
-
IEE
E
P
re
ss
,
2
0
0
0
,
p
p
.
4
5
2
.
[2
]
K.
R.
P
a
d
i
y
a
r
,
F
ACT
S
Co
n
tro
ll
i
n
g
in
p
o
we
r
T
ra
n
sm
issi
o
n
sy
ste
m a
n
d
d
istrib
u
ti
o
n
,
An
sh
a
n
,
Un
i
ted
Kin
g
d
o
m
,
2
0
0
8
.
[3
]
K.
R.
P
a
d
i
y
a
r
a
n
d
R.
K.
Va
rm
a
,
“
Da
m
p
in
g
to
r
q
u
e
a
n
a
ly
sis
o
f
sta
ti
c
VA
R
sy
ste
m
c
o
n
tro
ll
e
rs
,
”
IEE
E
T
ra
n
s
a
c
ti
o
n
s
o
n
P
o
we
r S
y
ste
ms
,
v
o
l.
6
,
n
o
.
2
,
p
p
.
4
5
8
-
4
6
5
,
M
a
y
1
9
9
1
,
d
o
i:
1
0
.
1
1
0
9
/
5
9
.
7
6
6
8
7
.
[4
]
S.
Ha
sh
e
m
i
a
n
d
M
.
R.
Ag
h
a
m
o
h
a
m
m
a
d
i,
“
Wav
e
let
b
a
se
d
fe
a
tu
re
e
x
trac
ti
o
n
o
f
v
o
lt
a
g
e
p
r
o
fil
e
f
o
r
o
n
li
n
e
v
o
lt
a
g
e
sta
b
il
it
y
a
ss
e
ss
m
e
n
t
u
sin
g
RBF
n
e
u
ra
l
n
e
two
r
k
,
”
I
n
ter
n
a
t
io
n
a
l
j
o
u
rn
a
l
o
f
El
e
c
trica
l
p
o
we
r
a
n
d
e
n
e
rg
y
sy
ste
m
,
v
o
l.
4
9
,
p
p
.
8
6
-
9
4
,
Ju
l
.
2
0
1
3
,
d
o
i
:
1
0
.
1
0
1
6
/j
.
i
jep
e
s.2
0
1
2
.
1
2
.
0
1
9
.
[5
]
D.
De
v
ra
j
a
n
d
J.
P
.
Ro
se
ly
n
,
“
On
li
n
e
v
o
l
tag
e
sta
b
il
it
y
a
ss
e
ss
m
e
n
t
u
sin
g
ra
d
ial
b
a
sis
fu
n
c
ti
o
n
n
e
two
rk
m
o
d
e
l
with
re
d
u
c
e
d
i
n
p
u
t
fe
a
tu
re
s,”
I
n
ter
n
a
t
io
n
a
l
j
o
u
r
n
a
l
o
f
p
o
we
r
a
n
d
e
n
e
rg
y
sy
ste
m
,
v
o
l
.
3
3
,
n
o
.
9
,
pp
.
1
5
5
0
-
1
5
5
5
,
2
0
1
1
,
d
o
i:
1
0
.
1
0
1
6
/j
.
ij
e
p
e
s.
2
0
1
1
.
0
6
.
0
0
8
.
[6
]
M
.
Ried
m
il
ler
a
n
d
H.
Bra
u
n
,
“
A
d
irec
t
a
d
a
p
t
iv
e
m
e
th
o
d
fo
r
fa
ste
r
b
a
c
k
p
r
o
p
a
g
a
ti
o
n
lea
rn
i
n
g
:
t
h
e
RP
ROP
a
lg
o
rit
h
m
,
”
IEE
E
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Ne
u
ra
l
Ne
two
rk
s
,
S
a
n
F
ra
n
c
isc
o
,
CA,
USA,
v
o
l.
1
,
1
9
9
3
,
p
p
.
5
8
6
-
591
,
d
o
i:
1
0
.
1
1
0
9
/ICNN.
1
9
9
3
.
2
9
8
6
2
3
.
[7
]
Ba
n
sa
l
R
.
C,
“
Au
to
m
a
ti
c
re
a
c
ti
v
e
p
o
we
r
c
o
n
tr
o
l
o
f
a
u
t
o
n
o
m
o
u
s
h
y
b
rid
p
o
we
r
sy
ste
m
,
”
P
h
D
Th
e
sis,
Ce
n
ter
fo
r
En
e
rg
y
S
t
u
d
ies
,
I
n
d
ia
n
In
st
it
u
te
o
f
Tec
h
n
o
lo
g
y
De
lh
i,
I
n
d
ia,
2
0
0
2
.
[8
]
R.
C.
Ba
n
sa
l,
T.
S
.
Bh
a
tt
i
,
a
n
d
V.
Ku
m
a
r,
“
Re
a
c
ti
v
e
p
o
we
r
c
o
n
tro
l
o
f
a
u
to
n
o
m
o
u
s
win
d
-
d
ies
e
l
h
y
b
ri
d
p
o
we
r
sy
ste
m
s u
sin
g
AN
N,
”
I
n
ter
n
a
t
io
n
a
l
P
o
we
r E
n
g
in
e
e
rin
g
Co
n
fer
e
n
c
e
(IP
EC
2
0
0
7
)
,
S
in
g
a
p
o
re
,
2
0
0
7
,
p
p
.
9
8
2
-
9
8
7
.
[9
]
R.
A.
Ja
y
a
b
a
ra
th
i
a
n
d
N.
B.
D
e
v
a
ra
jan
,
“
AN
N
Ba
se
d
DSP
IC
Co
n
tr
o
ll
e
r
f
o
r
Re
a
c
ti
v
e
P
o
we
r
Co
m
p
e
n
sa
ti
o
n
,
”
Ame
ric
a
n
J
o
u
r
n
a
l
o
f
Ap
p
li
e
d
S
c
ie
n
c
e
s
,
v
o
l
.
4
,
n
o.
7
,
p
p
.
5
0
8
-
5
1
5
,
2
0
0
7
,
d
o
i:
1
0
.
3
8
4
4
/aja
ss
p
.
2
0
0
7
.
5
0
8
.
5
1
5
.
[1
0
]
A.
Ka
ra
m
i,
“
P
o
we
r
sy
ste
m
tran
si
e
n
t
sta
b
il
i
ty
m
a
rg
in
e
stim
a
ti
o
n
u
sin
g
n
e
u
ra
l
n
e
two
r
k
s,”
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
El
e
c
trica
l
Po
we
r &
E
n
e
rg
y
S
y
ste
ms
,
v
o
l
.
3
3
,
n
o
.
4,
p
p
.
9
8
3
-
9
9
1
,
M
a
y
2
0
1
1
,
d
o
i:
1
0
.
1
0
1
6
/j
.
i
jep
e
s.2
0
1
1
.
0
1
.
0
1
2
.
[1
1
]
M
.
T
.
Ha
g
a
n
a
n
d
M
.
B.
M
e
n
h
a
j,
“
Train
i
n
g
fe
e
d
fo
rwa
r
d
n
e
two
rk
s
with
t
h
e
M
a
r
q
u
a
rd
t
a
lg
o
rit
h
m
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Ne
u
ra
l
Ne
two
rk
s
,
v
o
l.
5
,
n
o
.
6
,
p
p
.
9
8
9
-
9
9
3
,
No
v
.
1
9
9
4
,
d
o
i:
1
0
.
1
1
0
9
/
7
2
.
3
2
9
6
9
7
.
[1
2
]
Ju
ra
d
o
,
F
ra
n
c
isc
o
a
n
d
S
a
e
n
z
,
Jo
sé
.
,
“
Ne
u
ro
-
fu
z
z
y
c
o
n
tr
o
l
fo
r
a
u
to
n
o
m
o
u
s
win
d
–
d
ies
e
l
sy
ste
m
s
u
sin
g
b
io
m
a
ss
,
”
Ren
e
wa
b
le E
n
e
rg
y
,
v
o
l.
2
7
,
n
o
.
1
,
p
p
3
9
-
5
6
,
S
e
p
.
2
0
0
2
,
d
o
i
:
1
0
.
1
0
1
6
/S
0
9
6
0
-
1
4
8
1
(
0
1
)
0
0
1
7
0
-
7
.
[1
3
]
A.
P
.
Alv
e
s
d
a
S
il
v
a
,
A.
H.
F
.
In
sfra
n
,
P
.
M
.
d
a
S
il
v
e
ira
,
a
n
d
G
.
Lam
b
e
rt
-
To
rre
s,
“
Ne
u
ra
l
n
e
t
wo
rk
s
f
o
r
fa
u
lt
lo
c
a
ti
o
n
in
su
b
sta
ti
o
n
s,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Po
we
r
De
li
v
e
ry
,
v
o
l.
1
1
,
n
o
.
1
,
p
p
.
2
3
4
-
2
3
9
,
Ja
n
.
1
9
9
6
,
d
o
i:
1
0
.
1
1
0
9
/6
1
.
4
8
4
0
2
1
.
[1
4
]
S
.
A
.
Kir
a
n
m
a
i,
M
.
M
a
n
ju
la
,
a
n
d
V.
R.
S
.
S
a
rm
a
,
“
M
it
ig
a
ti
o
n
o
f
Va
rio
u
s
P
o
we
r
Qu
a
li
t
y
P
ro
b
lem
s
Us
in
g
Un
if
ied
S
e
ries
S
h
u
n
t
Co
m
p
e
n
sa
t
o
r
i
n
P
S
CAD
/E
M
TDC,
”
1
6
th
Na
t
io
n
a
l
P
o
we
r
S
y
ste
ms
Co
n
fer
e
n
c
e
,
v
o
l.
6
,
n
o
.
1
1
,
p
p
.
1
2
7
-
1
4
4
,
1
5
t
h
-
1
7
th
De
c
.
2
0
1
0
.
[1
5
]
V.
M
a
th
a
d
,
F
.
R.
Ba
sa
n
a
g
o
u
d
a
,
a
n
d
S
.
H.
Ja
n
g
a
m
sh
e
tt
i,
“
Vo
lt
a
g
e
Co
n
tr
o
l
a
n
d
P
o
we
r
S
y
ste
m
S
tab
il
it
y
En
h
a
n
c
e
m
e
n
t
u
sin
g
UPF
C
,
”
In
te
rn
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
Ren
e
w
a
b
le
En
e
rg
ies
a
n
d
P
o
we
r
Qu
a
li
ty
(ICRE
PQ’1
4
)
,
v
o
l.
1
,
n
o.
1
2
,
p
p
.
8
7
1
-
8
7
5
,
Ap
r.
2
0
1
4
.
[1
6
]
Qin
g
Yu
,
L.
No
r
u
m
,
T.
U
n
d
e
lan
d
,
a
n
d
S
.
R
o
u
n
d
,
“
I
n
v
e
stig
a
ti
o
n
o
f
d
y
n
a
m
ic
c
o
n
tr
o
ll
e
rs
fo
r
a
u
n
if
ied
p
o
we
r
fl
o
w
c
o
n
tro
ll
e
r,
”
Pro
c
e
e
d
i
n
g
s
o
f
th
e
1
9
9
6
IEE
E
IECON
.
2
2
n
d
I
n
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
In
d
u
stri
a
l
E
lec
tro
n
ics
,
Co
n
tro
l,
a
n
d
In
str
u
me
n
ta
t
io
n
,
Tai
p
e
i,
Taiwa
n
,
1
9
9
6
,
p
p
.
1
7
6
4
-
1
7
6
9
v
o
l
.
3
,
d
o
i:
1
0
.
1
1
0
9
/IE
CON
.
1
9
9
6
.
5
7
0
7
2
9
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
23
,
No
.
2
,
Au
g
u
s
t
20
21
:
633
-
63
8
638
[1
7
]
L.
G
y
u
g
y
i,
C.
D.
S
c
h
a
u
d
e
r,
S
.
L.
Wi
ll
iam
s,
T.
R.
Rietm
a
n
,
D.
R.
T
o
rg
e
rso
n
,
a
n
d
A.
E
d
ris,
“
Th
e
u
n
if
ied
p
o
we
r
fl
o
w
c
o
n
tro
ll
e
r:
a
n
e
w
a
p
p
r
o
a
c
h
t
o
p
o
we
r
tran
sm
issio
n
c
o
n
tro
l,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Po
we
r
De
li
v
e
ry
,
v
o
l.
1
0
,
n
o
.
2
,
p
p
.
1
0
8
5
-
1
0
9
7
,
Ap
r
il
1
9
9
5
,
d
o
i:
1
0
.
1
1
0
9
/6
1
.
4
0
0
8
7
8
.
[1
8
]
M
.
N
o
ro
o
z
ian
,
L.
An
g
q
u
ist,
M
.
G
h
a
n
d
h
a
ri
,
a
n
d
G
.
An
d
e
rss
o
n
,
“
Us
e
o
f
UPF
C
fo
r
o
p
ti
m
a
l
p
o
we
r
flo
w
c
o
n
tr
o
l,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Po
we
r De
l
ive
ry
,
v
o
l.
1
2
,
n
o
.
4
,
p
p
.
1
6
2
9
-
1
6
3
4
,
Oc
t.
1
9
9
7
,
d
o
i:
1
0
.
1
1
0
9
/6
1
.
6
3
4
1
8
3
.
[1
9
]
A.
Ra
i,
“
En
h
a
n
c
e
m
e
n
t
o
f
V
o
lt
a
g
e
S
tab
il
it
y
&
re
a
c
ti
v
e
P
o
we
r
Co
n
tr
o
l
o
f
Distri
b
u
t
io
n
S
y
ste
m
Us
in
g
F
a
c
ts
De
v
ice
s,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
S
c
ien
ti
fi
c
Res
e
a
rc
h
En
g
in
e
e
rin
g
&
T
e
c
h
n
o
lo
g
y
,
v
o
l.
1
,
n
o
.
9
,
p
p
.
0
0
1
-
0
0
5
,
D
e
c
.
2
0
1
2
.
[2
0
]
S
.
Va
ib
h
a
v
Ka
le,
R.
P
.
P
ra
sh
a
n
t
,
a
n
d
R.
Kh
a
tri
,
“
Un
ifi
e
d
P
o
we
r
F
l
o
w
Co
n
tro
ll
e
r
fo
r
P
o
we
r
Q
u
a
li
ty
Im
p
ro
v
e
m
e
n
t,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
Eme
rg
i
n
g
S
c
ien
c
e
a
n
d
En
g
i
n
e
e
rin
g
(IJ
E
S
E),
v
o
l.
1
,
n
o
.
1
0
,
p
p
.
1
-
4
,
A
u
g
.
2
0
1
3
.
[2
1
]
K.
Ra
v
ich
a
n
d
ru
d
u
,
P
.
R
.
Ra
n
i,
P
.
Y
.
B
a
b
u
,
a
n
d
G
.
V.
P
.
A
n
jan
e
y
u
l
u
,
“
Co
m
p
a
riso
n
o
f
S
imu
latio
n
Re
su
lt
s o
f
D
-
F
a
c
ts
&
UPF
C
Us
e
d
fo
r
P
o
we
r
Qu
a
li
t
y
Im
p
r
o
v
e
m
e
n
t,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
S
c
ie
n
ti
fi
c
a
n
d
Res
e
a
rc
h
P
u
b
l
ica
ti
o
n
s,
v
o
l.
3
,
n
o
.
9
,
p
p
.
1
-
5
,
S
e
p
t.
2
0
1
3
.
[2
2
]
G
.
Ka
n
n
a
y
e
ra
m
,
N.
B.
P
ra
k
a
sh
,
R.
M
u
n
iraj
,
a
n
d
T.
S
iv
a
k
u
m
a
r,
“
Op
ti
m
a
l
Tu
n
in
g
o
f
U
P
F
C
Da
m
p
in
g
C
o
n
tr
o
ll
e
r
Us
in
g
S
i
n
g
le
a
n
d
M
u
lt
i
-
O
b
jec
ti
v
e
Ev
o
lu
ti
o
n
a
r
y
Alg
o
rit
h
m
s,”
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
S
c
ien
ti
fi
c
&
T
e
c
h
n
o
l
o
g
y
Res
e
a
rc
h
,
v
o
l.
8
,
n
o
.
1
0
,
p
p
.
3
0
3
1
-
3
0
3
7
,
Oc
t
2
0
1
9
.
[2
3
]
S
.
H
o
c
in
e
a
n
d
L
.
Dja
m
e
l,
“
Op
ti
m
a
l
n
u
m
b
e
r
a
n
d
lo
c
a
ti
o
n
o
f
UPF
C
d
e
v
ice
s
to
e
n
h
e
n
c
e
v
o
lt
a
g
e
p
r
o
fil
e
a
n
d
m
in
imiz
in
g
l
o
ss
e
s
in
e
lec
tri
c
a
l
p
o
we
r
sy
ste
m
s,”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
E
lec
trica
l
a
n
d
C
o
mp
u
t
e
r
En
g
in
e
e
rin
g
(IJ
ECE
)
,
v
o
l.
9
,
n
o
.
5
,
p
p
.
3
9
8
1
-
3
9
9
2
,
Oc
t
2
0
1
9
,
d
o
i:
1
0
.
1
1
5
9
1
/i
jec
e
.
v
9
i
5
.
p
p
3
9
8
1
-
3
9
9
2
.
[2
4
]
An
a
n
d
a
M
.
H.
a
n
d
M.
R
.
S
h
i
v
a
k
u
m
a
r,
“
Dy
n
a
m
ic
p
o
we
r
o
sc
il
latio
n
re
d
u
c
ti
o
n
u
sin
g
P
S
OA
-
P
I
in
UP
F
C,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
I
n
n
o
v
a
ti
v
e
T
e
c
h
n
o
lo
g
y
a
n
d
Ex
p
lo
ri
n
g
E
n
g
in
e
e
rin
g
,
v
o
l.
9
,
n
o
.
2
,
De
c
.
2
0
1
9
,
d
o
i:
1
0
.
3
5
9
4
0
/
ij
it
e
e
.
B6
8
0
9
.
1
2
9
2
1
9
.
[2
5
]
R.
De
v
a
ra
p
a
lli
a
n
d
B.
B
h
a
tt
a
c
h
a
ry
y
a
,
“
P
o
we
r
a
n
d
e
n
e
rg
y
sy
ste
m
o
sc
il
latio
n
d
a
m
p
in
g
u
s
in
g
m
u
l
ti
-
v
e
rse
o
p
ti
m
iza
ti
o
n
,
”
S
N
Ap
p
l.
S
c
i.
,
v
o
l.
3
,
n
o
.
3
,
p
.
3
8
3
,
2
0
2
1
,
d
o
i
:
1
0
.
1
0
0
7
/s4
2
4
5
2
-
0
2
1
-
0
4
3
4
9
-
2
.
[2
6
]
J.
Ke
n
n
e
d
y
a
n
d
R.
Eb
e
rh
a
rt,
“
P
a
rti
c
le
sw
a
rm
o
p
ti
m
iza
ti
o
n
,
”
in
Pro
c
.
1
9
9
5
IEE
E
I
n
t.
Co
n
f.
Ne
u
r
a
l
N
e
two
rk
s
,
v
o
l
.
4
,
p
p
.
1
9
4
2
-
1
9
4
8
,
d
o
i:
1
0
.
1
1
0
9
/ICN
N.1
9
9
5
.
4
8
8
9
6
8
.
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
Ana
n
d
a
M.
H
,
As
sista
n
t
P
r
o
fe
ss
o
r,
S
c
h
o
o
l
o
f
El
e
c
tri
c
a
l
a
n
d
El
e
c
t
ro
n
ics
E
n
g
i
n
e
e
rin
g
,
REVA
Un
iv
e
rsity
.
He
h
o
l
d
s
h
is
B
.
E
in
El
e
c
tri
c
a
l
&
El
e
c
tro
n
ics
En
g
i
n
e
e
rin
g
a
n
d
M
.
Tec
h
in
P
o
we
r
S
y
ste
m
s
&
P
o
we
r
El
e
c
tro
n
ics
.
His
e
m
p
lo
y
m
e
n
t
e
x
p
e
rien
c
e
in
c
lu
d
e
s
6
y
e
a
rs
o
f
i
n
d
u
stry
e
x
p
e
rien
c
e
fro
m
ABB
Lt
d
.
,
DM
-
P
o
we
r
El
e
c
tro
n
ics
a
n
d
8
y
e
a
rs
o
f
tea
c
h
in
g
e
x
p
e
rien
c
e
.
He
is
M
e
m
b
e
r
o
f
IAENG
(In
tern
a
ti
o
n
a
l
As
so
c
iatio
n
o
f
E
n
g
in
e
e
rs)
a
n
d
M
e
m
b
e
r
o
f
IEI
(I
n
stit
u
ti
o
n
o
f
En
g
i
n
e
e
rs
In
d
ia).
His
sp
e
c
ial
fiel
d
s
o
f
in
tere
st
i
n
c
lu
d
e
d
F
ACTS
d
e
v
ice
s
a
n
d
t
h
e
ir
a
p
p
li
c
a
ti
o
n
to
t
h
e
p
o
we
r
s
y
ste
m
,
F
OCS,
S
m
a
rt
G
rid
,
M
icr
o
G
rid
,
G
rid
in
te
g
ra
ti
o
n
o
f
re
n
e
wa
b
le
e
n
e
r
g
y
so
u
rc
e
s.
Dr
.
M
R
S
h
i
v
a
k
u
m
a
r
,
P
ro
fe
ss
o
r
a
n
d
P
r
in
c
ip
a
l
,
S
r
i
Re
v
a
n
a
S
i
d
d
e
sh
wa
ra
In
st
it
u
te
o
f
Tec
h
n
o
l
o
g
y
,
Ba
n
g
a
l
o
re
,
is
a
n
El
e
c
tri
c
a
l
p
o
we
r
En
g
in
e
e
ri
n
g
g
ra
d
u
a
te
fr
o
m
Un
i
v
e
rsity
o
f
M
y
so
re
.
P
o
st
g
ra
d
u
a
te
fro
m
Ba
n
g
a
lo
re
Un
i
v
e
rsity
a
n
d
a
lso
a
P
h
.
D
h
o
ld
e
r
in
El
e
c
tri
c
a
l
En
g
i
n
e
e
rin
g
(
P
o
we
r
S
y
ste
m
s)
fro
m
th
e
sa
m
e
u
n
iv
e
rsity
.
He
h
a
s
m
o
re
th
a
n
Th
re
e
d
e
c
a
d
e
s
o
f
tea
c
h
in
g
e
x
p
e
rien
c
e
a
n
d
g
u
id
e
d
th
e
stu
d
e
n
ts
f
o
r
t
h
e
ir
P
o
st
g
ra
d
u
a
te
a
s
we
ll
a
s
d
o
c
t
o
ra
te
d
e
g
re
e
s.
He
is
a
l
ife
m
e
m
b
e
r
o
f
T
h
e
In
d
ian
S
o
c
iet
y
fo
r
Tec
h
n
ica
l
Ed
u
c
a
ti
o
n
,
A
F
e
ll
o
w
o
f
T
h
e
In
stit
u
t
io
n
o
f
E
n
g
in
e
e
rs
(In
d
ia),
m
e
m
b
e
r
o
f
In
stit
u
t
io
n
o
f
E
n
g
in
e
e
rin
g
a
n
d
Tec
h
n
o
l
o
g
y
M
IE
T
(UK
).
His
fiel
d
o
f
in
tere
st
in
c
l
u
d
e
s
p
o
we
r
sy
ste
m
sta
b
il
it
y
,
F
A
CTS
c
o
n
tr
o
ll
e
rs,
a
n
d
p
o
we
r
e
lec
tro
n
ics
a
p
p
li
c
a
ti
o
n
s.
Evaluation Warning : The document was created with Spire.PDF for Python.