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Dec
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24
69
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x
i
m
u
m
m
ec
h
a
n
i
ca
l
p
o
w
er
tr
ac
k
i
n
g
m
et
h
o
d
[
1
7
]
o
r
th
e
ex
tr
e
m
e
s
ee
k
in
g
m
eth
o
d
[
1
8
]
is
d
ep
en
d
ed
o
n
th
e
p
ar
am
eter
s
o
f
th
e
s
y
s
te
m
an
d
m
a
y
b
e
en
tr
ap
p
ed
in
th
e
g
lo
b
al
m
ax
i
m
u
m
.
Am
o
n
g
th
e
ad
ap
tiv
e
h
y
b
r
id
in
tellig
e
n
t
co
n
tr
o
l
[
1
9
]
a
n
d
th
e
ex
p
er
t
co
n
tr
o
l
s
y
s
te
m
[
2
0
]
,
th
e
DE
al
g
o
r
ith
m
[
2
1
]
h
as
r
ec
eiv
ed
t
h
e
m
o
s
t
atten
tio
n
b
ec
au
s
e
o
f
th
e
b
es
t
ef
f
ec
tiv
e
[
2
2
]
an
d
ex
ac
t
tr
ac
k
i
n
g
m
ax
i
m
u
m
p
o
w
er
p
o
in
t
[
2
3
]
.
Un
til
n
o
w
,
t
h
e
DE
al
g
o
r
ith
m
h
a
s
n
ev
er
b
ee
n
i
m
p
le
m
e
n
ted
i
n
P
MSG
w
i
n
d
t
u
r
b
in
e
s
.
F
u
r
t
h
e
r
,
th
e
R
ad
ial
B
asi
s
F
u
n
c
tio
n
Net
w
o
r
k
s
(
R
B
F
NNs)
[
2
4
]
,
[
2
5
]
b
ased
M
PP
T
m
et
h
o
d
is
p
r
o
p
o
s
ed
to
d
esig
n
[
2
6
]
an
d
im
p
le
m
e
n
t
[
2
7
]
f
o
r
PMSG
w
in
d
t
u
r
b
in
e
b
ec
au
s
e
o
f
h
ig
h
p
er
f
o
r
m
a
n
ce
,
ac
cu
r
ac
y
,
a
n
d
co
n
v
er
g
en
ce
.
Mo
r
eo
v
er
,
th
e
d
-
ax
is
s
tato
r
cu
r
r
en
t
co
n
tr
o
l
tec
h
n
iq
u
es
[
2
8
]
s
u
c
h
as
ze
r
o
d
-
a
x
i
s
s
tato
r
cu
r
r
en
t
(
Z
D
C
)
,
u
n
it
y
p
o
w
er
f
ac
to
r
(
UP
F)
an
d
c
o
n
s
tan
t
s
tato
r
f
lu
x
-
li
n
k
a
g
e
(
C
S
FL
)
h
a
v
e
b
ee
n
in
ter
e
s
ted
in
i
m
p
r
o
v
i
n
g
p
er
f
o
r
m
an
ce
an
d
r
ed
u
ce
d
co
s
t
b
ec
au
s
e
o
f
h
ar
d
w
ar
e
less
.
C
u
r
r
en
tl
y
,
th
ese
d
-
ax
is
s
tat
o
r
cu
r
r
en
t
co
n
tr
o
l
tech
n
iq
u
es
h
av
e
o
n
l
y
b
ee
n
ap
p
lied
to
co
n
tr
o
l
f
o
r
t
h
e
m
o
to
r
.
I
n
th
i
s
p
ap
er
,
th
e
s
tu
d
y
ap
p
lies
t
h
es
e
tech
n
iq
u
es
w
i
th
t
h
e
co
r
r
ec
tio
n
to
co
n
tr
o
l
f
o
r
MSC
o
f
P
MSG.
B
ased
o
n
th
e
ac
h
iev
e
d
r
esu
lts
,
th
e
m
ai
n
co
n
tr
ib
u
tio
n
o
f
t
h
i
s
w
o
r
k
ca
n
b
e
o
u
tlin
ed
as
f
o
llo
w
s
;
i)
DE
alg
o
r
ith
m
b
ased
MP
PT
is
p
r
o
p
o
s
ed
f
o
r
P
MSG
w
i
n
d
tu
r
b
i
n
e
;
ii)
d
esi
g
n
a
n
d
i
m
p
le
m
e
n
tat
io
n
o
f
R
B
FNN
f
o
r
th
e
ze
r
o
-
ap
p
r
o
x
i
m
at
io
n
er
r
o
r
o
f
th
e
DE
al
g
o
r
ith
m
b
ased
MPPT
;
iii)
c
o
m
b
in
ed
r
ad
ial
b
asis
f
u
n
ctio
n
n
e
u
r
al
n
et
w
o
r
k
b
ased
MP
PT
m
eth
o
d
an
d
d
ax
is
s
tato
r
cu
r
r
en
t
co
n
tr
o
l
tec
h
n
iq
u
es
(
Z
DC
,
UP
F
an
d
C
SF
L
)
h
av
e
b
e
en
s
u
cc
es
s
f
u
l
ly
ap
p
lied
f
o
r
th
e
co
n
tr
o
l
o
f
th
e
MS
C
o
f
P
MSG
w
i
n
d
tu
r
b
i
n
e.
T
h
i
s
a
r
t
i
c
le
is
o
r
g
an
iz
e
d
as
f
o
l
l
o
w
s
:
s
e
c
ti
o
n
2
i
n
t
e
r
p
r
e
t
s
in
d
e
t
a
i
l
o
f
w
in
d
tu
r
b
in
e
c
o
n
v
e
r
s
i
o
n
p
o
w
er
.
S
e
c
t
i
o
n
3
d
e
s
c
r
i
b
es
th
e
M
PP
T
m
e
th
o
d
.
S
ec
t
i
o
n
4
s
h
o
w
s
t
h
e
s
ta
t
o
r
c
u
r
r
en
t
c
o
n
t
r
o
l
t
e
ch
n
i
q
u
es
.
S
e
c
t
i
o
n
5
p
r
e
s
en
t
s
a
n
d
ex
p
l
a
in
s
th
e
s
im
u
l
at
i
o
n
r
e
s
u
l
ts
.
F
in
a
lly
,
c
o
n
clu
s
i
o
n
s.
2.
DYNA
M
I
C
M
O
DE
L
I
N
G
O
F
P
M
SG
WI
ND
T
URB
I
N
E
SYST
E
M
2
.
1
.
Wind
t
urbin
e
m
o
del
T
h
e
m
ec
h
a
n
ical
o
u
tp
u
t p
o
w
er
o
f
th
e
w
i
n
d
tu
r
b
in
e
i
s
g
iv
e
n
b
y
(
1
)
,
=
1
2
2
(
,
)
3
(
1
)
w
h
er
e
R
is
th
e
tu
r
b
in
e
r
ad
iu
s
(
m
)
,
ρ
is
th
e
air
d
en
s
it
y
(
k
g
/
m
3
)
,
v
w
i
s
th
e
w
in
d
s
p
ee
d
(
m
/s
ec
)
,
C
p
is
th
e
p
o
w
er
co
ef
f
icie
n
t
f
u
n
ctio
n
,
α
is
th
e
ti
p
s
p
ee
d
r
atio
an
d
β
is
th
e
b
lad
e
p
itch
an
g
le.
T
h
e
tip
s
p
ee
d
r
atio
an
d
an
d
p
o
w
er
co
ef
f
icie
n
t a
r
e
ex
p
r
ess
ed
,
=
(
2
)
w
h
er
e
ω
t
r
ep
r
esen
t
an
g
u
lar
s
p
ee
d
o
f
r
o
to
r
(
,
)
=
1
(
2
−
3
−
4
)
(
−
5
)
+
6
(
3
)
w
h
er
e
th
e
ap
p
r
o
x
i
m
a
ted
co
ef
f
i
cien
t v
a
lu
e
s
c
1
–
c
6
ar
e
g
iv
e
n
i
n
T
ab
le
3
.
=
(
1
+
0
.
08
−
0
.
035
1
+
3
)
−
1
(
4
)
T
h
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r
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l
a
t
i
o
n
s
h
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p
b
e
tw
e
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p
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w
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d
w
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d
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p
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d
u
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d
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a
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b
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w
in
d
s
p
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d
d
em
o
n
s
t
r
a
t
es
i
n
F
ig
u
r
e
2
.
T
h
e
t
u
r
b
in
e
p
o
w
e
r
a
t
a
c
e
r
t
a
in
w
in
d
s
p
e
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d
is
p
o
s
s
i
b
l
e
a
t
a
m
a
x
im
u
m
,
w
h
i
ch
is
c
a
ll
e
d
o
p
t
im
u
m
w
in
d
Evaluation Warning : The document was created with Spire.PDF for Python.
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e
c
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a
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im
a
l
t
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r
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e
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h
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t
u
r
b
in
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is
r
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q
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i
r
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d
t
o
o
p
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t
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t
a
n
o
p
t
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al
t
i
p
s
p
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d
r
a
t
i
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f
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m
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u
m
p
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t
c
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b
e
d
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e
b
y
d
r
iv
in
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e
tu
r
b
in
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s
r
o
t
a
t
i
o
n
a
l
s
p
e
e
d
i
n
o
r
d
e
r
t
h
at
i
t
c
o
n
t
in
u
o
u
s
ly
r
o
t
a
t
es
a
t
t
h
e
o
p
t
im
u
m
s
p
ee
d
[
2
]
.
T
h
e
o
p
e
r
a
t
i
o
n
a
l
z
o
n
e
w
i
th
i
n
a
w
in
d
s
p
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e
d
r
an
g
e
th
a
t
i
s
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t
r
i
c
t
e
d
b
e
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e
en
c
o
n
n
e
c
te
d
w
in
d
s
p
e
e
d
(
v
w
c
u
t
-
in
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an
d
d
is
c
o
n
n
e
c
t
e
d
w
in
d
s
p
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e
d
(
v
w
c
u
t
-
out
)
af
f
e
ct
to
t
h
e
c
a
p
tu
r
e
d
w
in
d
p
o
w
e
r
.
O
th
e
r
w
is
e
,
w
in
d
tu
r
b
in
e
s
a
r
e
r
e
q
u
i
r
e
d
t
o
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t
o
p
o
p
e
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at
in
g
a
b
o
v
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o
n
n
e
ct
e
d
w
in
d
s
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d
(
v
w
c
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-
in
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o
r
b
el
o
w
d
i
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c
o
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n
e
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t
e
d
w
in
d
s
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d
(
v
w
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out
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b
e
c
a
u
s
e
o
f
p
r
o
t
e
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t
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co
n
d
i
t
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o
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s
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t
u
r
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e
h
a
s
t
o
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to
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f
o
r
p
r
o
t
e
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t
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o
f
t
h
e
w
in
d
tu
r
b
in
e
a
s
w
e
ll
as
g
en
e
r
a
t
o
r
if
o
u
t
o
f
th
i
s
r
a
n
g
e
.
T
h
e
w
in
d
tu
r
b
in
e'
s
r
at
e
d
p
o
w
e
r
(
P
rated
)
i
s
d
e
t
e
r
m
in
e
d
b
y
th
e
w
in
d
s
p
e
e
d
(
v
r
at
e
d
).
T
h
e
n
,
i
t
c
an
b
e
d
iv
i
d
e
d
i
n
t
o
4
m
a
i
n
r
eg
i
o
n
s
an
d
cl
a
s
s
if
ie
d
as
f
o
l
l
o
w
s
[
9
]
;
i
)
w
in
d
t
u
r
b
in
es
m
u
s
t
b
e
s
t
o
p
p
e
d
an
d
d
i
s
c
o
n
n
e
c
t
e
d
f
r
o
m
th
e
g
r
i
d
t
o
a
v
o
i
d
th
e
g
en
e
r
at
o
r
im
p
l
em
en
ts
in
r
eg
i
o
n
1
an
d
4
,
w
h
ic
h
is
b
e
l
o
w
(
v
w
c
u
t
-
in
)
a
n
d
a
b
o
v
e
(
v
w
c
u
t
-
out
)
;
ii
)
th
e
s
e
co
n
d
r
eg
i
o
n
is
in
b
e
t
w
e
en
(
v
w
cu
t
-
in
)
an
d
(
v
w
r
a
t
e
d
)
w
h
ic
h
a
w
in
d
tu
r
b
in
e
s
c
o
n
t
r
o
l
le
r
im
p
l
em
en
ts
th
e
M
PP
T
m
eth
o
d
b
e
l
o
w
r
at
e
d
w
in
d
s
p
ee
d
t
o
a
c
h
ie
v
e
th
e
o
p
t
im
al
p
o
w
e
r
d
u
r
in
g
th
e
v
a
r
i
a
b
l
e
w
in
d
s
p
e
e
d
;
i
i
i
)
t
h
e
t
h
i
r
d
r
eg
i
o
n
is
in
b
e
t
w
e
en
(
v
w
r
a
t
e
d
)
an
d
(
v
w
c
u
t
-
out
)
w
h
e
r
e
th
e
p
i
t
c
h
c
o
n
t
r
o
l
l
e
r
is
u
s
e
d
t
o
l
im
it
t
h
e
m
ec
h
a
n
i
c
a
l
p
o
w
e
r
g
en
e
r
a
t
io
n
an
d
t
o
k
e
e
p
w
in
d
tu
r
b
in
es
in
s
af
e
o
p
e
r
a
t
i
o
n
.
Turbine
power
(
KW
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MPPT
region
cut
-
in
cut
-
out
Parking
region
Ma
xim
um
pow
er
Rat
ed
-
power
Pitch
-
control
region
rated
Parking
region
Wi
nd
spe
ed
(
m
/
s
)
Fig
u
r
e
2
.
W
in
d
en
er
g
y
co
n
v
er
s
io
n
s
y
s
te
m
o
p
er
atin
g
r
eg
io
n
s
2
.
2
.
P
er
m
a
nent
m
a
g
net
s
y
nc
hro
no
us
g
ener
a
t
o
r
m
o
del
T
h
e
eq
u
iv
alen
t
cir
cu
i
t
m
o
d
el
o
f
th
e
P
MSG
is
d
ep
icted
in
Fig
u
r
e
3
.
I
n
th
e
dq
r
ef
er
en
ce
f
r
a
m
e,
th
e
s
tato
r
v
o
ltag
e
o
f
P
MSG
w
in
d
t
u
r
b
in
e
is
g
i
v
en
b
y
[
3
]
.
I
n
th
i
s
ar
ticle
p
r
esen
t
s
s
u
r
f
ac
e
m
o
u
n
t
ed
alter
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ato
r
.
{
ds
=
ds
+
ds
ds
−
qs
qs
qs
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qs
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qs
qs
−
ds
ds
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(
5
)
W
h
er
e
u
ds
an
d
u
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h
e
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ter
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a
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f
t
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l
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k
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e.
T
h
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ter
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=
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qs
(
6
)
[
]
=
3
2
ds
[
ds
qs
]
+
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2
qs
[
qs
−
ds
]
(
7
)
W
h
er
e
T
e
is
th
e
to
r
q
u
e,
p
is
t
h
e
n
u
m
b
er
o
f
p
o
le
p
air
s
(
a)
(
b
)
Fig
u
r
e
3
.
E
q
u
iv
ale
n
t c
ir
cu
it
m
o
d
el
o
f
th
e
P
MSG:
(
a)
d
-
ax
is
c
ir
cu
it; (
b
)
q
-
ax
i
s
cir
cu
it
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
694
I
n
t J
P
o
w
E
lec
&
Dr
i
S
y
s
t,
Vo
l.
12
,
No
.
4
,
Dec
em
b
er
2021
:
2
4
5
9
–
24
69
2462
3.
M
P
P
T
I
n
o
r
d
er
to
in
cr
ea
s
e
en
er
g
y
c
o
n
v
er
s
io
n
ef
f
icie
n
c
y
in
v
ar
y
i
n
g
t
h
e
s
p
ee
d
,
W
E
C
S
n
ee
d
p
ea
k
p
o
w
er
ex
tr
ac
tio
n
b
ec
a
u
s
e
it
i
s
i
m
p
o
r
tan
t.
T
h
e
MP
P
T
co
n
tr
o
l
tr
ies
to
ac
h
ie
v
e
t
h
e
m
ax
i
m
u
m
p
o
s
s
ib
le
p
o
w
er
at
a
v
w
ce
r
tain
v
al
u
e
o
f
t
h
e
w
i
n
d
.
T
h
e
m
a
x
i
m
u
m
p
o
w
er
p
o
in
t
(
MP
P
)
tr
a
j
ec
to
r
y
d
ep
en
d
s
o
n
th
e
w
i
n
d
s
p
ee
d
.
T
h
e
o
p
er
atio
n
al
zo
n
e
o
f
th
e
MP
PT
co
n
tr
o
l
is
a
p
er
io
d
f
r
o
m
cu
t
-
i
n
w
in
d
s
p
ee
d
to
r
ated
w
i
n
d
s
p
ee
d
,
as
s
ee
n
in
th
e
g
r
ap
h
o
f
t
h
is
c
u
r
v
e
in
Fi
g
u
r
e
2.
3
.
1
.
Co
nv
ent
i
o
na
l
M
P
P
T
m
et
ho
d
I
n
p
ast
y
ea
r
s
,
m
a
n
y
MP
P
T
m
et
h
o
d
s
h
a
ve
b
ee
n
s
t
u
d
ied
an
d
i
m
p
r
o
v
ed
[
2
]
,
[
3
]
.
T
h
er
e
ar
e
m
an
y
d
if
f
er
e
n
t
m
er
its
a
n
d
d
e
m
er
it
s
in
ea
c
h
o
f
t
h
e
m
.
I
n
a
w
a
y
th
at
th
e
m
o
s
t
p
o
p
u
lar
m
et
h
o
d
is
e
m
p
lo
y
ed
th
e
t
ip
s
p
ee
d
r
atio
(
T
S
R
)
tech
n
iq
u
e
[
1
7
]
th
at
u
s
es
(
2
)
.
T
h
u
s
,
th
is
c
o
n
tr
o
l
tech
n
iq
u
e
'
s
o
w
n
f
la
w
i
s
th
at
it
n
ec
ess
itates
th
e
u
s
e
o
f
a
w
i
n
d
-
s
p
ee
d
m
ea
s
u
r
e
m
en
t
g
ad
g
et
a
n
d
th
e
p
r
e
-
d
eter
m
in
ed
v
al
u
e
o
f
t
h
e
b
es
t
tip
s
p
ee
d
r
atio
f
o
r
co
n
v
er
ti
n
g
w
i
n
d
v
elo
cit
y
m
e
asu
r
e
m
en
t
s
in
to
th
e
ir
co
r
r
es
p
o
n
d
in
g
o
p
tim
a
l
s
p
ee
d
r
ef
er
en
ce
[
1
8
]
.
T
h
is
also
in
c
r
ea
s
es t
h
e
co
s
t o
f
t
h
e
s
y
s
te
m
[
1
9
].
3.
2
.
Dif
f
er
ent
ia
l
e
v
o
lutio
n
-
b
a
s
ed
M
P
P
T
Sin
ce
1
9
9
5
,
DE
w
as
ar
g
u
ab
l
y
o
n
e
o
f
t
h
e
f
ir
s
t
tec
h
n
ica
l
p
r
esen
t
b
y
R
.
Sto
r
n
a
n
d
K.
V.
P
r
ice
f
o
r
g
lo
b
al
o
p
tim
izatio
n
o
v
er
co
n
ti
n
u
o
u
s
s
ea
r
c
h
s
p
ac
e
[
2
1
]
,
in
w
h
ich
it
s
co
n
f
ig
u
r
atio
n
w
a
s
o
p
ti
m
al
f
u
n
ctio
n
s
in
a
co
n
tin
u
o
u
s
N
-
d
i
m
e
n
s
io
n
al
r
e
g
io
n
.
E
ac
h
i
n
d
iv
id
u
a
l
i
n
th
e
p
o
p
u
latio
n
is
a
n
N
-
d
i
m
en
s
io
n
al
v
ec
to
r
th
a
t
r
ep
r
esen
ts
a
p
r
o
b
lem
s
o
lu
tio
n
.
DE
d
ep
en
d
s
o
n
tak
in
g
t
h
e
d
is
tin
ctio
n
v
ec
to
r
b
et
w
ee
n
t
w
o
t
y
p
e
s
an
d
in
cl
u
d
in
g
a
s
ca
led
s
o
r
t o
f
th
e
d
is
ti
n
ctio
n
v
ec
to
r
to
a
th
ir
d
in
d
iv
id
u
al
to
m
ak
e
a
n
o
th
er
ap
p
lican
t a
r
r
an
g
e
m
en
t
[
2
2
]
.
T
h
e
p
r
o
ce
s
s
cr
ea
te
s
a
n
e
w
ca
n
d
id
ate
s
o
lu
tio
n
s
u
c
h
as
a
m
u
tan
t
v
ec
to
r
is
cr
ea
ted
b
y
j
o
in
in
g
t
h
r
ee
ar
b
itra
r
ily
c
h
o
s
e
v
ec
to
r
s
f
r
o
m
t
h
e
n
u
m
b
er
o
f
i
n
h
ab
itan
t
s
in
v
ec
to
r
s
b
ar
r
in
g
t
h
e
o
b
jectiv
e
v
ec
to
r
.
T
h
is
co
n
s
o
lid
atin
g
c
y
cle
o
f
th
r
ee
h
ap
h
az
ar
d
l
y
ch
o
s
e
v
ec
to
r
s
to
s
h
ap
e
th
e
m
u
tan
t
v
ec
to
r
an
d
a
m
u
ltip
lier
w
h
ic
h
is
th
e
f
u
n
d
a
m
en
ta
l
b
o
u
n
d
ar
y
o
f
t
h
e
DE
ca
lc
u
lat
io
n
[
2
3
]
.
T
h
is
r
esu
lt
s
i
n
a
m
u
ta
n
t
t
h
at
m
ig
h
t
b
e
ac
ce
p
ted
in
to
t
h
e
p
o
p
u
latio
n
as
a
n
e
w
ca
n
d
id
at
e
s
o
lu
tio
n
.
T
h
er
e
ar
e
t
w
o
g
e
n
er
all
y
u
ti
lized
h
y
b
r
id
tech
n
iq
u
es
i
n
DE
:
b
in
o
m
ial
h
y
b
r
id
an
d
e
x
p
o
n
e
n
tial
h
y
b
r
id
.
T
h
e
f
ittes
t
v
ec
to
r
in
ea
c
h
p
ai
r
is
k
ep
t
f
o
r
t
h
e
n
ex
t
DE
g
en
er
atio
n
,
an
d
t
h
e
lea
s
t
f
it
is
d
is
ca
r
d
ed
.
T
h
e
b
asic
DE
alg
o
r
ith
m
f
o
r
an
N
-
d
i
m
en
s
io
n
al
is
s
u
e
is
d
ep
icted
in
T
a
b
le
1
an
d
th
ese
p
ar
am
eter
s
ar
e
s
i
m
u
lated
i
n
M
A
T
L
A
B
.
T
h
e
f
lo
w
ch
ar
t
f
o
r
DE
a
lg
o
r
ith
m
is
il
lu
s
tr
ated
in
Fi
g
u
r
e
4
.
Initiali
zation
of
an
initial
equilib
rium
state
w
r
1
,
w
r
2
,
w
r
3
,
;
FX
1
,
FX
2
,
FX
3
,
...
Evaluate
the
target
function
and
upd
ate
the
ne
w
eq
uilibrium
state
Upd
at
e
an
d
ca
lc
ul
at
e
ne
w
va
ri
ab
le
(
w
r
-
n
e
w
)
No
Yes
Inpu
t
V
w
=
rand
([
3
,
12
]
,
120
)
Initiali
zation
of
DE
s
pa
ra
met
er
s
Initiali
zation
of
DE
s
in
it
ia
l
pop
ul
at
io
n
w
r
i
=
w
rm
i
n
+
rand
(
w
rm
a
x
-
w
r
m
i
n
)
Check
for
limit
of
variable
(
w
r
)
Stop
Start
Pop
=
w
r
m
i
n
+
rand
(
w
r
m
ax
–
w
r
m
i
n
)
c
he
c
k
s
t
op
condi
t
i
on
Fig
u
r
e
4
.
Flo
w
c
h
ar
t f
o
r
di
f
f
er
e
n
tial e
v
o
lu
tio
n
T
ab
le
1
.
T
h
e
p
ar
am
eter
s
o
f
D
E
D
e
scri
p
t
i
o
n
V
a
l
u
e
P
a
r
t
i
c
l
e
n
u
m
b
e
r
o
f
a
g
e
n
e
r
a
t
i
o
n
,
N
po
p
30
M
a
x
i
m
u
m
n
u
m
b
e
r
o
f
g
e
n
e
r
a
t
i
o
n
s,
i
t
e
r
max
50
C
r
o
sso
v
e
r
p
r
o
b
a
b
i
l
i
t
y
0
.
2
S
c
a
l
i
n
g
f
a
c
t
o
r
l
o
w
e
r
b
o
u
n
d
0
.
2
S
c
a
l
i
n
g
f
a
c
t
o
r
u
p
p
e
r
b
o
u
n
d
0
.
8
3
.
3
.
P
r
o
po
s
ed
t
he
RB
F
NN
ba
s
ed
M
P
P
T
m
et
ho
d
I
n
th
i
s
s
ec
tio
n
i
s
p
r
o
p
o
s
ed
a
m
o
d
el
o
f
s
tr
aig
h
t
f
o
r
w
ar
d
n
eu
r
al
n
et
w
o
r
k
ar
ch
itec
tu
r
e,
w
h
ich
h
as
o
n
l
y
o
n
e
h
id
d
en
la
y
er
an
d
i
s
u
til
ized
in
m
a
n
y
ap
p
licatio
n
ar
ea
s
.
I
t
is
n
a
m
ed
R
ad
ial
B
as
is
F
u
n
ctio
n
Neu
r
al
Net
w
o
r
k
s
(
R
B
FN
N)
.
An
R
B
F
NN
b
ased
o
n
MP
PT
m
et
h
o
d
is
d
esig
n
ed
to
en
ab
le
co
n
tr
o
ll
in
g
MP
PT
w
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
694
I
n
t J
P
o
w
E
lec
&
Dr
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S
y
s
t,
Vo
l.
12
,
No
.
4
,
Dec
em
b
er
2021
:
2
4
5
9
–
24
69
2464
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25
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=
[
w
r
]
o
u
tp
u
t
la
y
er
s
r
esp
ec
tiv
el
y
o
f
t
h
e
R
B
FNN
t
h
at
r
ep
r
esen
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th
e
w
i
n
d
t
u
r
b
in
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r
o
tatio
n
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p
ee
d
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
P
o
w
E
lec
&
Dr
i
S
y
s
t
I
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N:
2
0
8
8
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8
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C
o
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R
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MPP
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(
Tu
a
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2465
4.
d
-
AXIS
ST
AT
O
R
CU
RREN
T
CO
NT
RO
L
T
E
CH
NI
Q
U
E
S
4
.
1
.
Z
D
C
Th
e
Z
DC
is
th
e
m
o
s
t
w
id
el
y
u
tili
ze
d
co
n
tr
o
l
tech
n
iq
u
e
ap
p
lied
to
in
d
u
s
tr
y
b
ec
au
s
e
o
f
its
s
i
m
p
licit
y
[
2
]
.
I
n
o
r
d
e
r
to
i
m
p
le
m
en
t
th
is
co
n
tr
o
l
tech
n
iq
u
e
,
d
-
ax
i
s
s
tato
r
cu
r
r
en
t
is
s
et
to
ze
r
o
.
S
o
,
th
e
r
elatio
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s
h
ip
b
et
w
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n
to
r
q
u
e
an
d
cu
r
r
en
t
ca
n
b
e
lin
ea
r
ized
.
4
.
2
.
UP
F
Un
d
er
th
is
co
n
tr
o
l
la
w
,
t
h
e
p
o
w
er
f
ac
to
r
a
n
g
le
is
al
w
a
y
s
k
e
p
t
at
u
n
it
y
.
T
h
is
r
ea
s
o
n
w
o
u
ld
lead
to
a
co
s
t
ef
f
ec
tiv
e
s
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f
o
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th
e
B
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B
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ter
.
T
h
is
is
o
n
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f
th
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m
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m
p
o
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tan
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en
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te
m
[
3]
.
(
1
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s
h
o
w
n
t
h
i
s
i
m
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le
m
en
tatio
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f
t
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is
co
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o
l la
w
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s
etti
n
g
t
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cti
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p
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w
er
eq
u
a
l
ze
r
o
an
d
illu
s
tr
ated
in
Fig
u
r
e
7
,
as sh
o
w
n
in
(
5
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s
u
b
s
t
itu
tes
in
t
o
(
1
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.
ds
qs
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ds
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0
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1
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d
-
a
xis
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tator
c
urre
nt
c
on
tr
ol
d
-
axis
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axis
CSFL
UPF
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Ո
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b
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b
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b
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RBFNN
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(
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Fig
u
r
e
7
.
P
r
o
p
o
s
ed
M
P
PT
tec
h
n
iq
u
e
an
d
b
lo
ck
d
iag
r
a
m
d
ax
is
s
tato
r
cu
r
r
en
t c
o
n
tr
o
l
ds
=
−
2
+
√
(
2
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2
−
(
qs
)
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(
1
3
)
I
n
(
1
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s
h
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s
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ax
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f
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g
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s
t
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a
in
t
r
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2
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(
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)
4
.
3
.
CSFL
I
n
o
r
d
er
t
o
o
v
er
co
m
e
i
n
cr
ea
s
i
n
g
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l
u
x
lin
k
a
g
e
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s
at
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atio
n
o
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s
tato
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k
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)
w
h
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n
th
e
to
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v
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cr
ea
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ed
,
t
h
e
C
SF
L
m
u
s
t
b
e
ap
p
lied
.
On
e
o
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th
e
m
o
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t
c
h
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ter
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tic
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f
th
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n
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o
l
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h
i
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tead
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f
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g
o
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d
ca
p
ac
it
y
f
ac
to
r
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d
tin
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r
eq
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ir
ed
p
o
w
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n
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ter
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p
ac
it
y
.
I
n
a
s
i
m
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w
a
y
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it
h
i
m
p
le
m
e
n
ti
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t
h
er
d
-
a
x
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s
tato
r
c
u
r
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en
t
co
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tech
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es
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t
h
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a
m
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d
eq
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to
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e
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m
a
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e
n
t
m
ag
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et
f
l
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x
s
h
o
w
n
as
(
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)
.
T
h
is
co
n
tr
o
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tech
n
iq
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e
w
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ll
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it is
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s
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ated
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g
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7
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2
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.
|
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,
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cu
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t
qs
≤
(
1
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I
n
th
is
ca
s
e,
th
e
an
aly
s
is
ca
n
b
e
s
u
m
m
ar
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d
as
t
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a
in
f
ea
t
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r
e
o
f
Z
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co
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tr
o
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is
h
ig
h
co
s
t
u
n
d
er
w
i
n
d
s
p
ee
d
v
ar
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n
s
d
u
e
to
p
o
o
r
ef
f
icien
c
y
an
d
th
e
h
i
g
h
r
ea
cti
v
e
p
o
w
e
r
:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
694
I
n
t J
P
o
w
E
lec
&
Dr
i
S
y
s
t,
Vo
l.
12
,
No
.
4
,
Dec
em
b
er
2021
:
2
4
5
9
–
24
69
2466
T
h
e
m
ai
n
f
ea
t
u
r
e
o
f
UP
F
co
n
t
r
o
l
r
e
d
u
ce
d
th
e
co
s
t
o
f
th
e
p
o
w
er
cir
cu
it
b
ec
au
s
e
o
f
its
s
m
a
ll
s
ize,
th
o
u
g
h
i
t
is
h
i
g
h
p
er
f
o
r
m
an
ce
u
n
d
er
w
i
n
d
s
p
ee
d
v
ar
iatio
n
s
.
T
h
is
is
o
n
e
o
f
th
e
s
i
g
n
if
ican
t
c
o
n
s
id
er
atio
n
s
f
o
r
m
eg
a
w
att
-
le
v
el
w
i
n
d
tu
r
b
in
e
c
ap
ac
it
y
;
A
p
r
o
p
o
s
ed
tech
n
iq
u
e
f
o
r
co
n
tr
o
llin
g
t
h
e
M
SC
o
f
v
ec
to
r
-
co
n
tr
o
lled
P
MSG
w
i
n
d
t
u
r
b
in
e
i
s
C
S
F
L
co
n
tr
o
l
b
ec
au
s
e
o
f
g
o
o
d
ch
ar
ac
ter
is
t
ic
an
d
h
ig
h
p
o
w
er
f
ac
to
r
.
5.
SI
M
UL
AT
I
O
N
R
E
S
UL
T
S
I
n
th
i
s
p
ap
er
,
T
h
e
R
B
FNN
co
n
tr
o
ller
b
ased
MP
PT
m
et
h
o
d
ap
p
lied
to
P
MSG
h
as
b
ee
n
i
m
p
le
m
en
ted
in
M
A
T
L
A
B
u
n
d
er
v
ar
iab
l
e
w
i
n
d
s
p
ee
d
.
I
n
o
r
d
e
r
to
ev
alu
ate
a
n
d
an
al
y
ze
th
e
p
r
o
p
o
s
ed
s
o
lu
tio
n
'
s
p
er
f
o
r
m
a
n
ce
,
R
B
FNN
co
n
tr
o
ller
b
ased
o
n
t
h
e
av
er
a
g
e
a
n
d
s
ta
n
d
ar
d
d
ev
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n
(
S
D)
in
T
ab
le
2
th
at
is
r
elatio
n
s
h
ip
b
et
w
ee
n
th
e
t
u
r
b
in
e
p
o
w
er
s
at
v
ar
iab
le
r
o
to
r
s
p
ee
d
an
d
th
e
n
et
s
u
m
o
f
n
o
d
es
is
1
0
.
W
h
en
t
h
e
er
r
o
r
v
alu
e
r
ea
ch
es
th
e
p
er
m
itted
v
alu
e,
th
e
tr
ain
i
n
g
en
d
s
(
p
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f
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m
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=
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.
0
0
0
0
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o
r
less
o
n
s
r
ea
ch
th
e
allo
w
ab
le
v
al
u
e
(
ep
o
ch
=1
0
0
)
.
T
h
e
p
r
o
ce
s
s
o
f
n
et
w
o
r
k
tr
ai
n
in
g
i
s
d
ep
icted
in
Fig
u
r
e
8
.
T
h
e
n
et
w
o
r
k
tr
ai
n
i
n
g
ch
ar
t
p
r
esen
ts
n
et
w
o
r
k
-
tr
ain
i
n
g
p
r
o
ce
s
s
,
w
h
ic
h
o
cc
u
r
s
1
0
0
t
i
m
es
b
ef
o
r
e
s
to
p
p
in
g
.
Si
m
u
lta
n
eo
u
s
l
y
,
th
e
f
in
e
s
t
tr
ain
i
n
g
r
es
u
lt
s
w
ill
b
e
0
.
0
0
0
1
5
2
6
5
u
s
in
g
th
e
R
B
F
NN
b
lo
ck
tak
e
s
th
e
p
lace
o
f
th
e
o
ld
b
lo
ck
o
f
th
e
MP
PT
alg
o
r
ith
m
a
n
d
is
d
ep
icted
in
Fi
g
u
r
e
7
.
T
ab
le
2
.
Data
o
f
R
B
FNN
S
i
g
n
a
l
1
2
3
4
5
6
7
8
9
10
R
B
F
N
N
A
v
e
r
a
g
e
2
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e
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1
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g
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a
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11
12
13
14
15
16
17
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A
v
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Fig
u
r
e
8
.
Net
w
o
r
k
tr
ai
n
i
n
g
g
r
a
p
h
T
h
e
s
im
u
latio
n
r
esu
lt
s
in
Ma
tl
ab
,
w
h
ic
h
ass
es
s
an
d
co
m
p
ar
e
th
e
s
tr
o
n
g
p
o
in
ts
an
d
w
ea
k
p
o
in
ts
o
f
th
e
p
r
o
p
o
s
ed
s
tato
r
cu
r
r
en
t
co
n
tr
o
l
tech
n
iq
u
es
a
n
d
R
B
FNN
b
ased
o
n
th
e
MP
P
T
m
eth
o
d
.
T
h
e
ef
f
ec
ti
v
e
n
ess
o
f
s
tato
r
cu
r
r
en
t
co
n
tr
o
l
tech
n
iq
u
es
i
s
co
n
s
id
er
ed
u
n
d
er
w
in
d
s
p
ee
d
v
ar
iatio
n
.
T
ab
les
3
an
d
4
lis
t
th
e
P
MSG
w
i
n
d
tu
r
b
in
e
's
p
ar
a
m
eter
s
.
Fi
g
u
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c)
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r
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t;
(
d
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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694
I
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t J
P
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w
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&
Dr
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Vo
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12
,
No
.
4
,
Dec
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2021
:
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er
ter
o
f
p
er
m
a
n
en
t
m
ag
n
et
s
y
n
ch
r
o
n
o
u
s
alter
n
ato
r
is
p
r
ese
n
ted
.
T
h
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
w
as
d
esi
g
n
e
d
an
d
ap
p
lied
s
u
cc
es
s
f
u
ll
y
to
p
er
m
a
n
e
n
t
m
ag
n
et
s
y
n
ch
r
o
n
o
u
s
g
e
n
er
ato
r
w
i
n
d
t
u
r
b
in
es.
T
h
e
s
i
m
u
latio
n
r
esu
lt
s
s
h
o
w
t
h
at
th
e
co
n
tr
o
ller
h
a
s
h
i
g
h
ac
cu
r
ac
y
a
n
d
s
tab
ilit
y
i
n
tr
ac
k
i
n
g
t
h
e
m
a
x
i
m
u
m
p
o
w
er
p
o
in
t
an
d
in
cr
ea
s
es
th
e
p
o
w
er
o
f
p
er
m
a
n
e
n
t
m
ag
n
et
s
y
n
ch
r
o
n
o
u
s
g
en
er
ato
r
w
in
d
t
u
r
b
in
es.
I
n
ad
d
itio
n
,
th
r
ee
d
ax
is
s
tato
r
cu
r
r
en
t,
ze
r
o
d
ax
is
s
tato
r
cu
r
r
en
t,
u
n
i
t
y
p
o
w
er
f
ac
to
r
,
an
d
co
n
s
tan
t
s
tato
r
f
lu
x
-
li
n
k
a
g
e
h
a
v
e
b
ee
n
s
tu
d
ied
.
Gen
er
al
l
y
,
th
e
c
o
n
s
ta
n
t
s
ta
to
r
f
lu
x
-
lin
k
ag
e
m
eth
o
d
ca
n
b
e
r
ed
u
ce
d
co
s
tly
w
it
h
o
u
t
th
e
h
ar
d
w
ar
e.
I
n
f
u
t
u
r
e
w
o
r
k
,
a
lo
w
-
co
s
t
p
r
o
ce
s
s
o
r
-
in
-
t
h
e
-
lo
o
p
p
latf
o
r
m
w
i
ll
b
e
ap
p
lied
to
ex
p
er
im
e
n
tal
v
er
i
f
i
ca
tio
n
o
f
t
h
e
p
r
o
p
o
s
ed
a
p
p
r
o
a
ch
.
ACK
NO
WL
E
D
G
E
M
E
NT
S
T
h
is
r
esear
ch
r
ec
eiv
ed
f
u
n
d
i
n
g
f
r
o
m
t
h
e
I
n
d
u
s
tr
ial
U
n
i
v
er
s
it
y
o
f
Ho
C
h
i M
i
n
h
C
it
y
,
Viet
n
a
m
.
RE
F
E
R
E
NC
E
S
[1
]
V
.
P
e
re
lm
u
ter,
“
Re
n
e
w
a
b
le en
e
rg
y
s
y
ste
m
s: S
im
u
latio
n
w
it
h
S
im
u
li
n
k
a
n
d
S
im
P
o
w
e
rS
y
ste
m
s,”
CRC
Pre
ss
,
2
0
1
6
.
[2
]
V
.
Ya
ra
m
a
su
,
B.
W
u
,
P
.
C
.
S
e
n
,
S
.
Ko
u
r
o
a
n
d
M
.
Na
rim
a
n
i,
“
Hig
h
-
p
o
w
e
r
w
in
d
e
n
e
rg
y
c
o
n
v
e
rsio
n
s
y
ste
m
s:
S
tate
-
of
-
th
e
-
a
rt
a
n
d
e
m
e
rg
in
g
tec
h
n
o
l
o
g
ies
,
”
Pro
c
e
e
d
in
g
s
o
f
th
e
IEE
E
,
v
o
l.
1
0
3
,
n
o
.
5
,
p
p
.
7
4
0
-
7
8
8
,
M
a
y
2
0
1
5
,
d
o
i:
1
0
.
1
1
0
9
/J
P
ROC.
2
0
1
4
.
2
3
7
8
6
9
2
.
[3
]
V
.
Ya
ra
m
a
su
,
a
n
d
Bi
n
W
u
,
“
M
o
d
e
l
p
re
d
ictiv
e
c
o
n
tr
o
l
o
f
w
in
d
e
n
e
rg
y
c
o
n
v
e
rsio
n
sy
ste
m
s,”
W
il
e
y
-
IEE
E
Pre
ss
,
2
0
1
7
.
[4
]
M
.
J.
Du
ra
n
,
F
.
Ba
rre
ro
,
A
.
P
o
z
o
-
Ru
z
,
F
.
G
u
z
m
a
n
,
J.
F
e
rn
a
n
d
e
z
a
n
d
H
.
G
u
z
m
a
n
,
“
Un
d
e
rsta
n
d
i
n
g
P
o
w
e
r
El
e
c
tro
n
ics
a
n
d
El
e
c
tri
c
a
l
M
a
c
h
in
e
s
in
M
u
lt
i
d
isc
ip
li
n
a
ry
W
in
d
En
e
rg
y
Co
n
v
e
rsio
n
S
y
ste
m
Co
u
rse
s,”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Ed
u
c
a
ti
o
n
,
v
o
l.
5
6
,
n
o
.
2
,
p
p
.
1
7
4
-
1
8
2
,
M
a
y
2
0
1
3
,
d
o
i:
1
0
.
1
1
0
9
/T
E.
2
0
1
2
.
2
2
0
7
1
1
9
.
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