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c
t
e
d
r
es
e
a
r
ch
a
n
d
s
tu
d
i
es
t
o
m
o
d
el
th
e
tu
r
b
in
e
g
o
v
e
r
n
o
r
[
8
]
-
[
1
2
]
.
T
h
is
r
esea
r
ch
p
r
o
p
o
s
es
a
s
tr
u
c
tu
r
e
to
ap
p
l
y
s
y
s
te
m
s
id
en
t
if
ic
atio
n
(
SI
)
m
et
h
o
d
s
to
f
in
d
a
s
i
m
p
li
f
ied
m
o
d
el
o
f
th
r
ee
g
o
v
er
n
o
r
s
i
n
a
s
i
n
g
le
ar
ea
elec
tr
ic
p
o
w
er
s
y
s
te
m
(
S
AEP
S
)
.
T
h
is
p
ap
er
p
r
esen
ts
a
S
A
EP
S
w
it
h
d
i
f
f
er
e
n
t
t
y
p
es o
f
e
lectr
ical
g
e
n
er
atio
n
t
h
at
ar
e:
h
y
d
r
au
li
c
tu
r
b
i
n
e,
s
tea
m
t
u
r
b
in
e
,
an
d
a
s
tea
m
r
eh
ea
t
tu
r
b
in
e.
T
o
d
o
th
is
,
it
w
i
ll
b
e
n
ec
ess
ar
y
to
p
er
f
o
r
m
an
an
a
l
y
t
i
c
r
ed
u
ctio
n
an
d
f
in
d
th
e
m
i
n
i
m
u
m
o
r
d
er
o
f
th
e
s
y
s
te
m
,
t
h
i
s
eq
u
iv
ale
n
t
tr
a
n
s
f
er
f
u
n
ctio
n
w
il
l
m
o
d
el
t
h
e
co
m
p
lete
b
eh
av
io
u
r
o
f
t
h
e
t
h
r
ee
d
ev
ices
i
n
p
a
r
allel.
T
w
o
SI
alg
o
r
ith
m
s
th
a
t
w
ill
b
e
u
s
ed
t
o
th
e
g
e
n
er
ic
elec
tr
ical
s
y
s
te
m
h
av
e
b
ee
n
p
r
o
p
o
s
ed
,
th
ese
alg
o
r
ith
m
s
ar
e
ca
lled
g
en
er
alize
d
p
o
is
s
o
n
m
o
m
en
t
f
u
n
ct
io
n
al
s
(
GP
MF)
an
d
n
u
m
e
r
ic
alg
o
r
ith
m
s
f
o
r
th
e
s
u
b
s
p
ac
e
s
tate
-
s
p
ac
e
(
SS
)
SI
(
NS4
SID
)
,
w
h
ich
w
i
ll b
e
e
x
p
lain
ed
later
.
2.
M
E
T
H
O
D
T
h
e
SI
p
r
o
ce
s
s
is
a
m
et
h
o
d
,
ar
t
an
d
s
cie
n
ce
o
f
s
tr
u
ct
u
r
e
m
a
th
e
m
atica
l
m
o
d
els
o
f
d
y
n
a
m
i
c
s
y
s
te
m
s
tak
i
n
g
th
e
m
ea
s
u
r
e
s
o
f
t
h
e
s
y
s
te
m
s
o
u
tp
u
t
a
n
d
in
p
u
t
s
i
g
n
al
s
[
1
3
]
.
T
h
e
f
o
llo
w
in
g
d
escr
ib
es
th
e
m
et
h
o
d
o
lo
g
y
n
ee
d
ed
to
f
in
d
a
s
im
p
li
f
ied
m
o
d
el
o
f
a
s
in
g
le
ar
ea
p
o
w
er
co
n
tr
o
l,
w
h
er
e
th
er
e
m
a
y
b
e
N
u
n
it
s
w
i
th
d
if
f
er
e
n
t
k
in
d
s
o
f
g
o
v
er
n
o
r
s
.
T
h
e
p
r
o
ce
s
s
o
f
SI
,
in
v
o
lv
e
s
t
h
e
f
o
llo
w
i
n
g
s
tep
s
co
r
r
esp
o
n
d
in
g
f
o
r
th
e
d
ev
elo
p
m
en
t
o
f
t
h
e
p
r
o
p
o
s
ed
m
et
h
o
d
o
lo
g
y
ar
e
d
escr
ib
ed
:
i)
Step
1
:
T
h
e
in
p
u
t
-
o
u
tp
u
t
v
ar
iab
les
o
f
t
h
e
s
et
o
f
N
g
o
v
er
n
o
r
s
o
f
a
n
elec
tr
ic
P
S
ar
e
s
elec
ted
,
th
is
w
il
l
p
r
o
v
id
e
th
e
co
r
r
esp
o
n
d
in
g
in
p
u
t
-
o
u
tp
u
t
d
ata
s
et,
s
o
m
e
d
ata
p
r
o
ce
s
s
in
g
i
s
p
er
f
o
r
m
ed
i
f
n
ec
e
s
s
ar
y
;
ii)
S
tep
2
:
T
o
esti
m
a
te,
th
e
SI
ta
k
es
t
h
e
in
p
u
t
a
n
d
o
u
tp
u
t
d
at
a
an
d
ap
p
lies
t
h
e
id
en
ti
f
icatio
n
al
g
o
r
ith
m
to
f
i
n
d
th
e
s
y
s
te
m
p
ar
a
m
eter
s
t
h
at
s
h
o
w
a
m
i
n
i
m
u
m
er
r
o
r
;
iii)
Ste
p
3
:
T
o
an
aly
ze
t
h
e
p
r
ed
icted
m
o
d
els,
th
e
b
es
t
wa
y
i
s
to
s
i
m
u
late
in
d
ed
icate
d
s
o
f
t
w
ar
e,
f
o
r
t
h
is
ca
s
e
Ma
tla
b
Si
m
u
li
n
k
w
i
ll
b
e
u
s
ed
,
ap
p
ly
i
n
g
th
e
s
a
m
e
i
n
p
u
t
th
at
w
a
s
u
s
ed
to
th
e
o
r
ig
in
al
m
o
d
el
an
d
th
u
s
o
u
tp
u
t
is
o
b
tain
e
d
;
an
d
iv
)
Step
4
:
Fo
r
th
e
v
alid
atio
n
o
f
t
h
e
p
ar
a
m
eter
s
f
o
u
n
d
b
y
th
e
id
e
n
ti
f
i
ca
tio
n
alg
o
r
it
h
m
,
i
t
is
n
ec
ess
ar
y
to
co
m
p
ar
e
t
h
e
o
u
tp
u
t o
b
tain
ed
f
r
o
m
s
tep
4
,
th
en
ca
lc
u
late
t
h
e
esti
m
at
io
n
er
r
o
r
to
s
ee
th
e
p
er
f
o
r
m
a
n
ce
.
2
.
1
.
Sim
pli
f
ied
m
o
dellin
g
T
h
e
p
r
o
ce
d
u
r
e
f
o
r
m
o
d
elin
g
a
s
y
s
te
m
r
eq
u
ir
es,
ta
k
e
t
h
e
m
ea
s
u
r
e
m
en
t
s
o
f
o
u
tp
u
t
an
d
i
n
p
u
t
v
ar
iab
les
f
r
o
m
t
h
e
p
r
i
m
al
S
A
E
P
S
i
n
f
r
eq
u
en
c
y
o
r
ti
m
e
d
o
m
ai
n
a
n
d
th
e
m
o
d
el
s
tr
u
c
tu
r
e
n
ee
d
to
b
e
s
elec
ted
:
tr
an
s
f
er
f
u
n
ctio
n
(T
F
)
o
r
SS
.
T
h
e
SI
u
s
es
t
h
e
o
u
tp
u
t
a
n
d
i
n
p
u
t
m
ea
s
u
r
e
m
e
n
t
o
f
t
h
e
va
r
iab
les
o
f
a
s
y
s
te
m
to
esti
m
ate
th
e
v
alu
e
s
o
f
th
e
ad
ap
tab
le
p
ar
a
m
eter
s
i
n
a
s
p
ec
i
f
y
m
o
d
e
l
fr
a
m
e
.
T
h
e
m
ea
s
u
r
ed
d
ata
m
u
s
t
ad
eq
u
atel
y
r
e
f
lect
th
e
b
eh
a
v
io
r
o
f
e
ac
h
s
y
s
te
m
,
s
in
ce
t
h
e
o
b
tai
n
in
g
o
f
its
p
ar
am
eter
s
d
ep
en
d
s
o
n
t
h
is
,
i
n
m
o
s
t
ca
s
e
s
,
it
d
ep
en
d
s
o
n
th
e
a
m
o
u
n
t
o
f
d
ata.
T
h
er
ef
o
r
e,
it
is
r
eq
u
ier
ed
to
ap
p
ly
in
th
e
f
r
a
m
e
o
f
t
h
e
ca
n
d
id
ate
m
o
d
el
an
esti
m
atio
n
m
et
h
o
d
o
lo
g
y
to
o
b
tei
n
t
h
e
v
alu
e
o
f
t
h
e
ad
j
u
s
tab
le
p
ar
a
m
eter
s
,
th
e
n
e
x
t
s
tep
w
o
u
ld
b
e
to
ev
al
u
ate
t
h
e
esti
m
ated
m
o
d
el
b
y
v
alid
atio
n
.
As
r
ef
er
r
ed
to
a
b
o
v
e
,
th
e
m
o
t
i
v
atio
n
o
f
t
h
is
d
o
cu
m
en
t
i
s
to
di
s
co
v
er
an
eq
u
i
v
alen
t
m
o
d
el
o
f
n
S
A
EP
S
th
at
ca
n
s
u
b
s
tit
u
te
t
h
e
d
i
f
f
er
e
n
t
k
in
d
s
o
f
a
g
o
v
er
n
o
r
t
h
at
t
h
e
ar
ea
co
n
tain
s
.
T
o
d
em
o
n
s
tr
a
te
th
i
s
tech
n
iq
u
e,
a
S
A
EP
S
w
ith
th
r
ee
k
i
n
d
s
o
f
th
e
g
o
v
er
n
o
r
ar
e
p
r
o
p
o
s
ed
,
w
h
ic
h
ar
e:
t
h
e
s
tea
m
t
u
r
b
in
e,
t
h
e
S
tea
m
r
eh
ea
t
t
u
r
b
in
e
an
d
th
e
h
y
d
r
au
l
ic
tu
r
b
in
e
,
F
ig
u
r
e
1
.
Fig
u
r
e
1.
.
S
A
EP
S
w
it
h
a
d
if
f
e
re
n
t
g
e
n
e
ra
ti
o
n
so
u
rc
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
22
,
No
.
3
,
J
u
n
e
2
0
2
1
:
1
2
3
6
-
1
2
4
4
1238
2
.
2
.
Sin
g
le
a
re
a
m
o
del desc
ript
io
n
No
r
m
a
ll
y
,
a
n
is
o
lated
elec
tr
ic
al
ar
ea
,
w
h
er
e
a
g
e
n
er
atin
g
u
n
it o
r
a
g
r
o
u
p
o
f
g
e
n
er
ati
n
g
u
n
i
ts
is
p
lace
d
n
ea
r
b
y
to
d
is
tr
ib
u
te
elec
tr
icit
y
in
th
e
s
a
m
e
ar
ea
i
s
ca
lled
a
S
A
EP
S
.
T
h
er
e
is
n
o
o
th
er
g
e
n
er
ato
r
u
n
i
t
t
h
at
i
s
f
ar
a
w
a
y
,
o
n
l
y
t
h
e
g
e
n
er
ati
n
g
u
n
i
ts
p
r
esen
t
i
n
t
h
at
ar
ea
ar
e
r
esp
o
n
s
ib
le
f
o
r
m
ain
tain
in
g
t
h
e
d
esire
d
f
r
eq
u
en
c
y
i
n
n
o
r
m
al
an
d
ab
n
o
r
m
a
l
co
n
d
iti
o
n
s
[
1
4
]
.
T
h
e
g
en
er
al
g
e
n
er
at
o
r
-
lo
ad
d
y
n
a
m
ic
r
elatio
n
b
etw
ee
n
th
e
f
r
eq
u
e
n
c
y
d
ev
iatio
n
(
Δ
f
)
an
d
t
h
e
in
cr
e
m
e
n
tal
m
is
m
atc
h
p
o
w
er
(
Δ
P
m−Δ
P
L)
i
s
d
e
n
o
ted
as
(
1
)
.
(
)
−
(
)
=
2
(
)
+
(
)
(
1
)
W
h
er
e
Δ
P
m
th
e
m
ec
h
an
ical
p
o
w
er
ch
a
n
g
e
,
Δ
P
L
t
h
e
lo
ad
ch
an
g
e,
Δ
f
i
s
t
h
e
f
r
eq
u
e
n
c
y
d
e
v
i
atio
n
,
D
is
t
h
e
lo
ad
d
am
p
i
n
g
co
ef
f
icie
n
t
an
d
M
t
h
e
in
er
tia
co
n
s
tan
t.
Th
u
s
,
t
h
e
d
a
m
p
in
g
co
ef
f
icie
n
t
i
s
in
g
e
n
er
al
d
ef
in
ed
as
a
p
er
ce
n
t c
h
a
n
g
e
i
n
lo
ad
f
o
r
a
on
e
p
er
ce
n
t
ch
a
n
g
e
i
n
f
r
eq
u
en
c
y
.
Hen
ce
,
a
v
al
u
e
o
f
o
n
e
an
d
a
h
alf
f
o
r
D
i
m
p
l
y
t
h
at
a
on
e
p
er
ce
n
t
c
h
an
g
e
i
n
f
r
eq
u
e
n
c
y
g
i
v
e
r
i
s
e
to
a
o
n
e
an
d
a
h
alf
p
er
ce
n
t
ch
a
n
g
e
i
n
lo
ad
.
Ap
p
ly
i
n
g
t
h
e
L
ap
lace
tr
an
s
f
o
r
m
atio
n
,
it is
d
escr
ib
ed
as (
2
)
.
(
)
(
)
2
(
)
(
)
mL
P
s
P
s
H
s
f
s
D
f
s
−
=
+
(
2
)
I
n
g
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Fu
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1
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I
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N
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esti
m
a
te
th
e
v
alu
e
s
o
f
th
e
p
ar
am
e
ter
s
f
r
o
m
a
s
et
o
f
d
ata.
T
h
er
e
b
y
th
e
f
o
c
u
s
i
n
g
is
also
ca
lled
g
r
a
y
b
o
x
m
o
d
elin
g
.
T
h
e
f
o
llo
w
i
n
g
id
en
ti
f
icatio
n
m
et
h
o
d
s
f
o
r
p
a
r
am
eter
est
i
m
at
io
n
h
a
v
e
b
ee
n
u
s
ed
in
th
i
s
d
o
cu
m
en
t.
3
.
1
.
G
ener
a
lis
ed
po
is
s
o
n
mo
m
ent
f
un
ct
io
na
l
s
(
G
P
M
F
)
C
u
r
r
en
tl
y
t
h
er
e
is
an
alg
o
r
ith
m
to
esti
m
ate
p
ar
a
m
eter
s
th
at
u
s
e
a
g
en
er
alize
d
P
MF
a
p
p
r
o
ac
h
.
T
h
is
alg
o
r
ith
m
i
n
cr
ea
s
es
a
v
ec
to
r
o
f
p
ar
a
m
eter
s
b
y
th
e
s
ize
o
f
th
e
s
y
s
te
m
o
r
d
er
n
ter
m
s
r
elate
d
to
th
e
p
r
eli
m
i
n
ar
y
co
n
d
itio
n
s
.
T
o
esti
m
a
te
b
o
th
ter
m
s
:
p
ar
a
m
eter
s
an
d
s
tate
s
,
th
e
o
b
s
er
v
ab
le
p
h
ase
v
ar
iab
le
f
o
r
m
is
u
s
ed
to
r
ep
r
esen
t
th
e
SS
o
f
a
s
y
s
te
m
.
On
e
o
f
t
h
e
ad
v
an
tag
e
s
o
f
th
is
w
a
y
o
f
r
ep
r
esen
ti
n
g
th
e
o
b
s
er
v
ab
le
p
h
ase
v
ar
iab
le
is
th
at
th
e
d
etails
t
h
at
r
elate
to
th
e
in
itial
co
n
d
itio
n
s
in
th
e
p
ar
am
eter
v
ec
to
r
ar
e
th
e
s
o
-
ca
lled
in
itial
s
tate
s
.
C
o
n
s
eq
u
en
tl
y
,
t
h
ese
s
tates
ar
e
esti
m
a
ted
to
g
eth
er
w
i
th
t
h
e
p
ar
am
e
ter
s
th
at
t
h
e
s
y
s
te
m
h
as.
T
h
u
s
,
ea
ch
s
tate
v
ec
to
r
at
ea
ch
in
s
tan
t
o
f
ti
m
e
af
ter
w
ar
d
s
is
esti
m
ated
at
th
e
s
a
m
e
ti
m
e
as
th
e
p
ar
a
m
e
ter
s
b
y
r
ec
u
r
s
i
v
el
y
ap
p
ly
i
n
g
th
e
i
n
itia
l state
s
th
at
w
er
e
esti
m
ated
[
1
9
]
-
[
2
1
]
.
3
.
2
.
Num
er
ic
a
l
g
o
rit
h
m
s
f
o
r
s
ub
s
pa
ce
s
t
a
t
e
-
s
pa
ce
s
y
s
t
em
i
dentif
ica
t
io
n (
NS4
SI
D)
T
h
e
NS4
SID
f
o
r
m
u
la
ted
b
y
V
an
O
v
er
s
c
h
ee
a
n
d
De
Mo
o
r
,
p
er
f
o
r
m
ca
lc
u
latio
n
s
o
f
p
ar
a
m
e
ter
izatio
n
o
f
th
e
m
o
d
el,
r
eso
lv
i
n
g
f
o
r
th
e
m
atr
ice
s
A
,
B
,
an
d
C
.
T
h
e
alg
o
r
ith
m
i
s
n
o
n
i
ter
ativ
e
an
d
d
o
es
n
o
t
b
e
co
n
d
itio
n
al
o
n
a
p
r
io
r
i
p
ar
am
eter
izatio
n
.
An
ad
v
a
n
ta
g
e
o
f
t
h
is
m
et
h
o
d
is
th
at
a
v
o
id
s
p
r
o
b
le
m
s
s
u
c
h
as
lo
ca
l
m
i
n
i
m
a,
in
it
ial
co
n
d
itio
n
b
ias
an
d
al
w
a
y
s
f
in
d
a
co
n
v
er
g
en
t
s
y
s
te
m
.
T
h
e
SI
is
f
u
n
d
e
d
o
n
s
in
g
u
lar
v
al
u
e
d
ec
o
m
p
o
s
itio
n
an
d
QR
w
h
ic
h
g
u
ar
an
tee
th
at
t
h
e
esti
m
ated
l
in
ea
r
ti
m
e
-
i
n
v
ar
ian
t
m
o
d
el
i
s
s
tab
le.
T
h
e
s
y
s
te
m
o
r
d
er
is
th
e
o
n
l
y
i
n
f
o
r
m
atio
n
r
eq
u
ir
ed
f
o
r
th
e
id
en
ti
f
icatio
n
p
r
o
ce
s
s
[
2
2
]
-
[
2
4
]
.
3
.
3
.
M
o
del pa
ra
m
et
er
s
e
s
t
i
m
a
t
io
n
T
h
e
SI
m
ak
e
a
s
ti
m
a
te
o
f
m
o
d
el
p
ar
am
eter
s
b
y
m
i
n
i
m
izi
n
g
th
e
er
r
o
r
am
o
n
g
th
e
m
o
d
el
o
u
tp
u
t
an
d
th
e
m
ea
s
u
r
ed
r
esp
o
n
s
e.
T
h
u
s
,
th
e
o
u
tp
u
t
y
m
odel
o
f
t
h
e
li
n
ea
r
m
o
d
el
i
s
r
ep
r
esen
ted
b
y
:
(
)
=
(
)
(
8
)
w
h
er
e
T
f
is
t
h
e
tr
as
n
s
f
er
f
u
n
cti
o
n
.
T
h
er
eb
y
to
estab
lis
h
th
e
T
f
,
th
e
alg
o
r
it
m
m
in
i
m
ize
s
th
e
d
i
f
f
er
en
ce
b
et
w
ee
n
th
e
m
ea
s
u
r
ed
o
u
tp
u
t
y
meas
(
t
)
an
d
th
e
m
o
d
el
o
u
tp
u
t
y
model
(
t
)
.
A
w
ei
g
h
ted
n
o
r
m
o
f
t
h
e
er
r
o
r
e(
t
)
,
is
t
h
e
m
i
n
i
m
izatio
n
cr
iter
io
n
,
w
h
er
e:
(
)
=
(
)
−
(
)
(
9
)
(
)
is
o
n
e
o
f
t
h
e
s
u
b
s
eq
u
e
n
t
:
Si
m
u
lated
r
esp
o
n
s
e
(
p
r
ed
icted
r
esp
o
n
s
e
o
f
t
h
e
m
o
d
el
f
o
r
a
g
i
v
en
i
n
p
u
t
u
(
t
)
,
T
f
u
(
t
)
o
f
t
h
e
m
o
d
e
l
f
o
r
a
g
i
v
e
n
i
n
p
u
t
u
(
t
)
a
n
d
p
a
s
t
m
e
a
s
u
r
e
m
e
n
t
s
o
f
o
u
t
p
u
t
(
−
1
)
,
(
−
2
)
,
…
)
.
T
h
er
ef
o
r
e
,
th
e
er
r
o
r
e(
t)
is
ca
lled
p
r
ed
ictio
n
er
r
o
r
o
r
s
i
m
u
l
atio
n
er
r
o
r
.
T
h
e
esti
m
atio
n
al
g
o
r
ith
m
f
iti
n
g
t
h
e
p
ar
am
eter
s
in
t
h
e
m
o
d
el
s
tr
u
ct
u
r
e
T
f
to
ac
h
iev
e
t
h
at
t
h
e
n
o
r
m
o
f
t
h
is
er
r
o
r
is
as s
m
all
as a
ch
iev
ab
le
[
2
5
]
.
4.
SI
M
UL
AT
I
O
N
ST
U
DI
E
S A
ND
RE
S
UL
T
S
T
h
is
s
ec
tio
n
s
h
o
w
s
t
h
e
s
i
m
u
la
tio
n
s
an
d
th
e
r
es
u
lts
,
t
h
e
f
o
llo
w
i
n
g
ca
s
e
ar
e
p
r
o
p
o
s
ed
.
Fig
u
r
e
3
s
h
o
w
s
th
e
in
p
u
t
an
d
o
u
tp
u
t
o
f
th
e
th
r
ee
-
u
n
it
m
o
d
el;
th
e
s
a
m
p
le
ti
m
e
is
0
.
1
m
s
.
T
h
e
Δf
is
u
s
ed
as
in
p
u
t
b
ec
au
s
e
i
n
th
is
v
ar
iab
le
it
is
ap
p
r
o
p
r
iate
d
u
e
to
its
n
at
u
r
e
s
en
s
iti
v
e
to
ch
an
g
e
s
b
y
p
o
w
er
,
an
d
d
is
tu
r
b
a
n
ce
s
,
th
e
s
u
m
o
f
th
e
m
ec
h
a
n
ical
p
o
w
er
s
Pm
w
as
u
s
ed
as
an
o
u
tp
u
t,
b
ec
a
u
s
e
i
t
r
ep
r
esen
ts
t
h
e
r
esp
o
n
s
e
o
f
ea
c
h
o
f
t
h
e
g
o
v
er
n
o
r
s
.
T
h
ese
in
p
u
t
s
an
d
o
u
tp
u
ts
ar
e
s
h
o
w
n
f
o
r
th
e
e
x
p
er
i
m
e
n
t.
An
ex
p
er
i
m
en
t
u
s
in
g
t
h
e
alg
o
r
ith
m
s
N4
SID
an
d
GP
MF,
ex
p
ec
ted
to
v
er
if
y
t
h
e
s
y
s
te
m
o
r
d
er
th
at
p
r
o
d
u
ce
s
th
e
s
m
al
lest
ap
p
r
o
ac
h
er
r
o
r
.
T
h
e
ex
p
er
i
m
en
ts
ch
ar
ac
ter
is
tic
s
ar
e
d
ef
in
ed
in
T
ab
le
2
.
W
h
er
e
ΔP
elec
lo
ad
p
o
w
er
d
is
tu
r
b
an
ce
an
d
ΔP
ref
is
a
r
ef
er
en
ce
lo
ad
p
o
w
er
.
T
h
e
g
r
ap
h
ical
r
esu
lts
f
o
r
ea
ch
ca
s
e
o
f
th
e
e
x
p
er
i
m
en
t
ar
e
s
h
o
w
n
i
n
Fi
g
u
r
e
s
4
to
7
.
E
ac
h
o
f
th
es
e
f
i
g
u
r
es
is
a
ca
s
e
w
h
er
e
i
t
is
p
o
s
s
ib
le
to
o
b
s
er
v
e
m
ea
s
u
r
ed
a
n
d
s
i
m
u
lated
m
o
d
el
o
u
tp
u
t
an
d
m
ea
s
u
r
ed
m
i
n
u
s
s
i
m
u
lated
o
u
tp
u
t.
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ir
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t c
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ea
s
u
r
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d
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i
m
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lated
m
o
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el
o
u
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u
t
a
n
d
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b
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m
ea
s
u
r
ed
m
i
n
u
s
s
i
m
u
lated
o
u
tp
u
t
(
a)
(
b
)
Fig
u
r
e
5
.
E
x
p
er
i
m
en
t
s
ec
o
n
d
c
ase
:
(
a)
m
ea
s
u
r
ed
an
d
s
i
m
u
lat
ed
m
o
d
el
o
u
tp
u
t
an
d
(
b
)
m
ea
s
u
r
ed
m
i
n
u
s
s
i
m
u
lated
o
u
tp
u
t
(
a)
(
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Usi
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ta
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.
RE
F
E
R
E
NC
E
S
[1
]
P
.
P
o
u
r
b
e
ik
a
n
d
J
.
F
e
lt
e
s
,
Dy
n
a
mi
c
M
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ls f
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r T
u
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Go
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n
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IEE
E,
2
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1
3
.
[2
]
A
.
Kh
o
d
a
b
a
k
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sh
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a
n
d
M
.
Ed
ris
i,
“
A
n
e
w
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b
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st P
ID
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a
d
f
re
q
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e
n
c
y
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r
,
”
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n
g
.
Pra
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,
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1
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9
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p
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.
[3
]
Jia
n
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Ch
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,
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i
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H
u
a
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a
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d
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ict
c
o
n
tr
o
l
f
o
r
th
e
h
y
d
ro
tu
rb
i
n
e
g
e
n
e
ra
to
r
se
t,
"
Pro
c
e
e
d
in
g
s
o
f
th
e
2
0
0
3
I
n
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
M
a
c
h
in
e
L
e
a
r
n
in
g
a
n
d
Cy
b
e
rn
e
ti
c
s
(
IEE
E
Ca
t.
N
o
.
0
3
EX
6
9
3
)
,
2
0
0
3
,
p
p
.
5
4
0
-
5
4
3
V
o
l
.
1
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o
i:
1
0
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1
1
0
9
/IC
M
L
C.
2
0
0
3
.
1
2
6
4
5
3
6
.
[4
]
M
.
Dju
k
a
n
o
v
ic,
M
.
No
v
ice
v
ic,
D.
Do
b
rij
e
v
ic,
B.
Ba
b
ic,
D.
J.
S
o
b
a
ji
c
a
n
d
Yo
h
-
Ha
n
P
a
o
,
"
Ne
u
ra
l
-
n
e
t
b
a
se
d
c
o
o
rd
i
n
a
ted
sta
b
il
izi
n
g
c
o
n
tr
o
l
f
o
r
th
e
e
x
c
it
e
r
a
n
d
g
o
v
e
rn
o
r
lo
o
p
s
o
f
lo
w
h
e
a
d
h
y
d
ro
p
o
w
e
r
p
lan
ts,"
in
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
En
e
rg
y
C
o
n
v
e
rs
i
o
n
,
v
o
l.
1
0
,
n
o
.
4
,
p
p
.
7
6
0
-
7
6
7
,
D
e
c
.
1
9
9
5
,
d
o
i:
1
0
.
1
1
0
9
/
6
0
.
4
7
5
8
5
0
.
[5
]
S
.
B.
Cra
ry
a
n
d
J.
B.
M
c
Clu
r
e
,
“
S
u
p
p
lem
e
n
tar
y
Co
n
tro
l
o
f
P
ri
m
e
-
M
o
v
e
r
S
p
e
e
d
G
o
v
e
rn
o
rs,”
T
ra
n
s.
Am.
I
n
st.
El
e
c
tr.
En
g
.
,
v
o
l
.
6
1
,
n
o
.
4
,
p
p
.
2
0
9
-
2
1
4
,
d
o
i:
1
0
.
1
1
0
9
/T
-
A
IEE
.
1
9
4
2
.
5
0
5
8
5
1
4
.
[6
]
F
.
G
o
n
z
a
lez
-
L
o
n
g
a
tt
,
F
.
S
a
n
c
h
e
z
a
n
d
R.
L
e
e
laru
ji
,
"
Un
v
e
il
in
g
th
e
Ch
a
ra
c
ter
o
f
th
e
F
re
q
u
e
n
c
y
in
P
o
w
e
r
S
y
st
e
m
s,"
2
0
1
9
I
EE
E
PE
S
GTD
Gr
a
n
d
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
a
n
d
Exp
o
siti
o
n
Asia
(
GTD
Asia
)
,
2
0
1
9
,
p
p
.
5
7
-
6
2
,
d
o
i:
1
0
.
1
1
0
9
/G
T
D
A
sia
.
2
0
1
9
.
8
7
1
5
9
7
2
.
[7
]
F
.
G
o
n
z
a
lez
-
L
o
n
g
a
tt
,
J.
Ru
e
d
a
,
a
n
d
E.
V
a
z
q
u
e
z
,
“
Ef
f
e
c
t
o
f
F
a
st
Ac
ti
n
g
P
o
w
e
r
Co
n
tr
o
ll
e
r
o
f
Ba
tt
e
r
y
En
e
rg
y
S
t
o
ra
g
e
S
y
st
e
m
s
in
th
e
Un
d
e
r
-
f
re
q
u
e
n
c
y
L
o
a
d
S
h
e
d
d
i
n
g
S
c
h
e
m
e
,
”
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
I
n
n
o
v
a
ti
v
e
S
ma
rt
Gr
id
T
e
c
h
n
o
l
o
g
ies
(
IS
GT
Asia
2
0
1
8
)
,
2
0
1
8
.
[8
]
H.
B.
Ru
u
d
a
n
d
S
.
B
.
F
a
rn
h
a
m
,
“
A
N
e
w
A
u
to
m
a
ti
c
L
o
a
d
Co
n
tro
l
f
o
r
T
u
rb
in
e
G
e
n
e
ra
to
rs,”
T
ra
n
s.
Am.
In
st.
E
le
c
tr.
En
g
.
,
v
o
l.
6
8
,
n
o
.
2
,
p
p
.
1
3
3
7
-
1
3
4
2
,
1
9
4
9
,
d
o
i:
1
0
.
1
1
0
9
/T
-
A
IEE
.
1
9
4
9
.
5
0
6
0
0
9
6
.
[9
]
D.
Ba
b
u
n
sk
i
a
n
d
A
.
T
u
n
e
sk
i,
“
M
o
d
e
ll
i
n
g
a
n
d
d
e
sig
n
o
f
h
y
d
ra
u
li
c
tu
rb
i
n
e
-
G
o
v
e
rn
o
r
sy
ste
m
,
”
I
FA
C
Pro
c
.
V
o
l.
,
2
0
0
3
,
v
o
l.
3
6
,
n
o
.
7
,
p
p
.
2
6
3
–
2
6
7
,
d
o
i
:
1
0
.
1
0
1
6
/S
1
4
7
4
-
6
6
7
0
(1
7
)3
5
8
4
2
-
1
.
[1
0
]
Y.
L
i,
C.
P
e
n
g
,
a
n
d
Z.
Ya
n
g
,
“
S
tea
m
tu
rb
in
e
g
o
v
e
rn
o
r
m
o
d
e
li
n
g
a
n
d
p
a
ra
m
e
ter
s
tes
ti
n
g
f
o
r
p
o
w
e
r
s
y
ste
m
sim
u
latio
n
,
”
Fro
n
t.
E
n
e
rg
y
Po
we
r E
n
g
.
Ch
i
n
a
,
v
o
l.
3
,
p
p
.
1
9
8
-
2
0
3
,
2
0
0
9
,
d
o
i:
1
0
.
1
0
0
7
/s1
1
7
0
8
-
0
0
9
-
0
0
0
4
-
2
.
[1
1
]
M
.
L
.
Ch
a
n
,
R.
D.
Du
n
lo
p
a
n
d
F
.
S
c
h
w
e
p
p
e
,
"
D
y
n
a
m
ic
Eq
u
iv
a
len
ts
f
o
r
A
v
e
ra
g
e
S
y
ste
m
F
re
q
u
e
n
c
y
Be
h
a
v
io
r
F
o
ll
o
w
in
g
M
a
jo
r
Distr
ib
a
n
c
e
s,"
i
n
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
P
o
we
r
Ap
p
a
ra
t
u
s
a
n
d
S
y
ste
ms
,
v
o
l.
P
A
S
-
9
1
,
n
o
.
4
,
p
p
.
1
6
3
7
-
1
6
4
2
,
J
u
ly
1
9
7
2
,
d
o
i
:
1
0
.
1
1
0
9
/T
P
A
S
.
1
9
7
2
.
2
9
3
3
4
0
.
[1
2
]
Y.
Xie
,
H.
Z
h
a
n
g
,
C.
L
i,
a
n
d
H.
S
u
n
,
“
De
v
e
lo
p
m
e
n
t
a
p
p
r
o
a
c
h
o
f
a
p
ro
g
ra
m
m
a
b
le
a
n
d
o
p
e
n
so
f
tw
a
re
p
a
c
k
a
g
e
f
o
r
p
o
w
e
r
s
y
st
e
m
f
re
q
u
e
n
c
y
re
sp
o
n
se
c
a
lcu
latio
n
,
”
Pro
tec
ti
o
n
a
n
d
C
o
n
tro
l
o
f
M
o
d
e
rn
Po
we
r
S
y
ste
ms
,
v
o
l.
2
,
n
o
.
1
8
,
2
0
1
7
,
d
o
i:
1
0
.
1
1
8
6
/s
4
1
6
0
1
-
0
1
7
-
0
0
4
5
-
1
.
[1
3
]
L
.
L
ju
n
g
,
“
P
e
rsp
e
c
ti
v
e
s
o
n
sy
ste
m
id
e
n
ti
f
ica
ti
o
n
,
”
in
An
n
u
a
l
Rev
i
e
ws
in
Co
n
tro
l
,
v
o
l.
3
4
,
n
o
.
1
,
p
p
.
1
-
1
2
,
2
0
1
0
,
d
o
i:
1
0
.
1
0
1
6
/
j.
a
rc
o
n
tr
o
l.
2
0
0
9
.
1
2
.
0
0
1
.
[1
4
]
R.
Um
ra
o
a
n
d
D.
K.
C
h
a
tu
rv
e
d
i
,
“
L
o
a
d
f
re
q
u
e
n
c
y
c
o
n
tr
o
l
u
sin
g
p
o
lar
f
u
z
z
y
c
o
n
tro
ll
e
r,
”
T
ENCON
2
0
1
0
-
2
0
1
0
IEE
E
Reg
i
o
n
1
0
Co
n
fer
e
n
c
e
,
2
0
1
0
,
p
p
.
5
5
7
-
5
6
2
,
d
o
i:
1
0
.
1
1
0
9
/T
ENCON
.
2
0
1
0
.
5
6
8
6
7
4
0
.
[1
5
]
H
.
B
e
v
r
a
n
i
,
“
R
o
b
u
s
t
P
o
w
e
r
S
y
s
t
e
m
F
r
e
q
u
e
n
c
y
C
o
n
t
r
o
l
,
”
i
n
P
o
w
e
r
E
l
e
c
t
r
o
n
i
c
s
a
n
d
P
o
w
e
r
S
y
s
t
e
m
s
,
U
S
A
:
S
p
r
i
n
g
e
r
,
2009.
[1
6
]
L
.
L
ju
n
g
,
S
y
ste
m
Id
e
n
ti
fi
c
a
ti
o
n
:
T
h
e
o
ry
f
o
r
th
e
Us
e
r
.
Div
isio
n
o
f
S
im
o
n
a
n
d
S
c
h
u
ste
r
On
e
L
a
k
e
S
tree
t
Up
p
e
r
S
a
d
d
le Ri
v
e
r,
NJ
,
Un
it
e
d
S
tate
s
:
P
re
n
ti
c
e
-
Ha
ll
,
1
9
9
8
.
[1
7
]
D.
J.
Be
a
ru
p
,
N.
D.
Ev
a
n
s,
a
n
d
M
.
J.
Ch
a
p
p
e
ll
,
“
T
h
e
in
p
u
t
-
o
u
tp
u
t
re
latio
n
s
h
ip
a
p
p
r
o
a
c
h
to
str
u
c
tu
ra
l
id
e
n
ti
f
iab
il
it
y
a
n
a
ly
sis,”
Co
mp
u
ter
M
e
th
o
d
s
a
n
d
Pro
g
ra
ms
i
n
Bi
o
me
d
icin
e
,
v
o
l.
1
0
9
,
n
o
.
2
,
p
p
.
1
7
1
-
181
,
2
0
1
3
,
d
o
i:
1
0
.
1
0
1
6
/
j.
c
m
p
b
.
2
0
1
2
.
1
0
.
0
1
2
.
[1
8
]
T
.
S
o
d
e
rstr
o
m
,
“
On
m
o
d
e
l
str
u
c
tu
re
tes
ti
n
g
in
sy
ste
m
id
e
n
ti
f
ica
ti
o
n
,
”
I
n
t.
J
.
C
o
n
tr
o
l
,
v
o
l.
2
6
,
n
o
.
1
,
p
p
.
1
–
1
8
,
1
9
7
7
,
d
o
i:
1
0
.
1
0
8
0
/0
0
2
0
7
1
7
7
7
0
8
9
2
2
2
8
5
.
[1
9
]
N.
K.
S
in
h
a
a
n
d
G
.
P
.
Ra
o
,
Id
e
n
ti
fi
c
a
ti
o
n
o
f
Co
n
ti
n
u
o
u
s
-
T
ime
S
y
ste
ms
:
M
e
th
o
d
o
l
o
g
y
a
n
d
Co
mp
u
ter
Imp
lem
e
n
ta
ti
o
n
.
S
p
rin
g
e
r
Ne
th
e
rl
a
n
d
s,
2
0
1
2
,
d
o
i:
1
0
.
1
0
0
7
/
9
7
8
-
94
-
011
-
3
5
5
8
-
0
.
[2
0
]
H.
Un
b
e
h
a
u
e
n
a
n
d
G
.
P
.
Ra
o
,
“
A
re
v
ie
w
o
f
id
e
n
ti
f
ica
ti
o
n
i
n
c
o
n
ti
n
u
o
u
s
-
t
im
e
s
y
ste
m
s,”
An
n
u
.
Rev
.
Co
n
tro
l
,
v
o
l.
2
2
,
p
p
.
1
4
5
-
171
,
1
9
9
8
,
d
o
i:
1
0
.
1
0
1
6
/
S
1
3
6
7
-
5
7
8
8
(
9
8
)
0
0
0
1
5
-
7
.
[2
1
]
D.
C.
S
a
h
a
,
V
.
N.
Ba
p
a
t,
a
n
d
B.
K.
Ro
y
,
“
T
h
e
P
o
isso
n
m
o
m
e
n
t
f
u
n
c
ti
o
n
a
l
tec
h
n
i
q
u
e
-
S
o
m
e
n
e
w
r
e
su
lt
s,”
in
Id
e
n
ti
fi
c
a
ti
o
n
o
f
Co
n
ti
n
u
o
u
s
-
T
im
e
S
y
ste
ms
:
M
e
th
o
d
o
lo
g
y
a
n
d
C
o
mp
u
ter
Imp
lem
e
n
ta
ti
o
n
,
N.
K.
S
in
h
a
a
n
d
G
.
P
.
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