Internati
o
nal
Journal of P
o
wer Elect
roni
cs an
d
Drive
S
y
ste
m
(I
JPE
D
S)
V
o
l.
7, N
o
. 1
,
Mar
c
h
20
16
,
pp
. 17
3
~
19
2
I
S
SN
: 208
8-8
6
9
4
1
73
Jo
urn
a
l
h
o
me
pa
ge
: h
ttp
://iaesjo
u
r
na
l.com/
o
n
lin
e/ind
e
x.ph
p
/
IJPEDS
Advan
ced Optimal PSO, Fuzzy a
nd PI Controller with PMSM
and WTGS at 5Hz Side of Genera
tion an
d 50Hz S
i
de of
Grid
Sa
lam Wa
ley
Shneen*
,
Ch
e
n
gx
i
o
n
g
M
a
o
*
*
,
Da
n
Wang**
*
*
School
of
Electrical & Electron
ic Engineering
,
Huaz
hong University
of Scien
c
e
a
nd Technolo
g
y
, Wuhan, Ch
ina
**
,
***School of
Electrical & El
ectronic Eng
i
neer
ing, Huazhong
University
of
Science
and Techn
o
log
y
, Wuhan
,
China
Article Info
A
B
STRAC
T
Article histo
r
y:
Received Sep 23, 2015
Rev
i
sed
Jan 13, 201
6
Accepte
d
Fe
b 1, 2016
To us
e different
control s
y
s
t
em
s
,
like cl
as
s
i
ca
l P
I
controlle
r, Exp
e
rt S
y
s
t
em
Fuzzy
Logic Co
ntroller and optimization PSO
controller. It used to contro
l
for PMSM which worked in the
integra
tion s
y
st
em
to W
i
nd Energ
y
. W
i
nd
energ
y
conten
t
of wind turb
ine
,
PMSM, rectif
i
e
r, DC bus
, inv
e
rter
, f
ilt
er,
load and grid
. In the first step, to
r
un the PMSM
with differen
t
speeds to ge
t
a differ
e
nt frequ
enc
y
to s
e
l
ect
th
e fre
quen
c
y
on the side of a gen
e
ration with
the rated speed.
Second step, solve the ma
thematical equation to use different
values
of wind s
p
eed with s
e
l
ect
ed (
15,20 m/s and less than with more than
15&20m/s). Third step, calcu
l
ation th
e power g
e
neration with
wind speed
(15 m/5 & 20
m/s). Fourth step,
using th
ese component s
y
stem
rectifier
,
DC
bus, inverte
r
, fi
lter
,
load & gri
d
w
ith W
T
GS
& PMSM.
Final step, uses
differen
t
contro
l
s
y
s
t
em
s
,
like
cl
as
s
i
cal P
I
contr
o
ller
,
Exper
t
S
y
s
t
em
F
u
zz
y
Logic con
t
roll
er
and optim
izat
io
n P
S
O
controlle
r with P
M
SM
to anal
yz
e al
l
results after usin
g the sim
u
lation m
ode
l of propo
sed variable speed based on
WECS. The wind turbine is
co
upled
with
PMSM. A closed
loop control
s
y
stem with a PI control, fuzzy
, PSO in the speed loop with curren
t
controll
ers. The
sim
u
lation circ
uits
for PMSM, inverter
, speed
and current
controllers inclu
d
e all r
e
a
listic components of the dr
ive s
y
s
t
em.
These results
als
o
confirm
e
d
that the tr
ans
i
ent torque and
current neve
r
exceed th
e
maximum permi
ssible value.
Keyword:
FLC
PI C
ont
rol
l
e
r
PMSM
PSO
WT
GS
Copyright ©
201
6 Institut
e
o
f
Ad
vanced
Engin
eer
ing and S
c
i
e
nce.
All rights re
se
rve
d
.
Co
rresp
ond
i
ng
Autho
r
:
C
h
e
n
g
x
io
ng M
a
o,
School
of Elec
trical &
El
ect
r
oni
c En
gi
nee
r
i
n
g
,
Hu
azho
ng
Un
iv
ersity of
Scien
ce an
d Tech
no
log
y
,
Wuh
a
n
,
Ch
in
a.
Em
a
il:
cxm
a
o@hu
s
t
.e
du
.cn
1.
INTRODUCTION
The m
o
st
em
ergi
ng
re
ne
wa
bl
e e
n
er
gy
s
o
urce
,
wi
nd e
n
ergy, by m
eans
of power
electronics
is
chan
gi
n
g
fr
om
bei
n
g a
m
i
nor
ene
r
gy
s
o
urce
t
o
be act
i
n
g a
s
an i
m
port
a
nt
po
we
r s
o
u
r
ce i
n
t
h
e
ene
r
gy
s
y
st
em
.
That
wi
n
d
p
o
w
er i
s
al
so get
t
i
ng an a
dde
d
val
u
e i
n
th
e
po
wer system o
p
e
ration
.
T
h
e
powe
r electronics are
changing the
basic c
h
aracte
r
istic of t
h
e
wind turbi
n
e
fr
o
m
bei
ng a
n
e
n
ergy
s
o
urce
t
o
be
an
act
i
v
e
po
we
r
sou
r
ce
[
1
]
.
The
perm
anent
m
a
gnet
sy
nc
hr
on
ous
m
achi
n
e (
P
M
S
M
)
, i
t
has
si
gni
fi
cant
a
d
vant
a
g
es,
at
t
r
a
c
t
i
ng t
h
e
i
n
t
e
rest
of
rese
arche
r
s a
n
d i
n
dust
r
y
f
o
r
use i
n
m
a
ny
ap
pl
i
cat
i
ons,
t
h
at
use
s
pe
rm
anent
m
a
gnet
s
t
o
p
r
o
d
u
ce t
h
e
ai
r ga
p m
a
gnet
i
c
fi
el
d rat
h
e
r
t
h
an
usi
n
g el
e
c
t
r
om
agnet
s
[
2
]
.
The PM
SM
,
wi
t
h
hi
g
h
l
e
v
e
l
ener
gy
pe
r
m
anent
mag
n
e
t m
a
teri
als p
a
rticu
l
arl
y
p
r
ov
i
d
e fast
d
y
n
a
m
i
cs
, efficien
t o
p
e
ration
and
g
ood
co
m
p
atib
ilit
y with
th
e
ap
p
lication
s
bu
t on
ly if th
ey are con
t
ro
lled p
r
op
erly
. Th
e co
n
t
ro
ller is
u
s
ing
to
ov
erco
m
e
th
e n
o
n
lin
earity
problem
of PMSM and als
o
to achieve fas
t
er res
p
onse
[3]. Man
y
in
du
st
rial ap
p
licatio
ns requ
ire
n
e
w
co
n
t
ro
l
t
echni
q
u
es
, t
h
e t
echni
ques
use
d
, a
ppl
i
e
d
i
n
al
l
reg
u
l
a
t
i
on l
o
o
p
s
,
spe
e
d re
g
u
l
a
t
i
on
of
perm
anent
m
a
gne
t
sy
nch
r
o
n
o
u
s
m
achi
n
e (PM
S
M
)
[4]
.
T
h
e devel
opm
ent
of po
we
r el
ect
roni
cs an
d el
ect
ri
c t
echnol
og
y
boos
t
PM
SM
fo
r ext
e
nsi
v
e a
ppl
i
cat
i
ons i
n
m
a
ny
cont
rol
sy
st
em
s. An
d PM
SM
,
whi
c
h are wi
d
e
l
y
used f
o
r sy
st
em
s
and c
ont
rol
de
vi
ces m
i
nut
e ow
ns se
veral
adva
nt
age
s
o
v
e
r ot
he
r m
ach
i
n
es o
n
M
i
l
a
n. Ad
vant
a
g
es
PM
SM
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-86
94
I
J
PED
S
Vo
l. 7,
No
.
1,
Mar
c
h
2
016
: 1
7
3
–
19
2
17
4
include large torque coefficient, and
high efficiency, high
en
erg
y
d
e
n
s
ity, an
d
a torqu
e
m
u
l
tip
lier is s
m
all,
L
o
w
-
in
er
tia
,
lo
w no
is
e
,
an
d h
i
g
h
-
p
er
for
m
a
n
c
e
in
a w
i
de
va
ri
et
y
[5]
.
A
way
c
ont
rol
l
er (
P
I
)
i
n
a
d
d
i
t
i
on t
o
cont
rol
l
e
rs
wi
t
h
i
n
t
e
gral
rel
a
t
i
v
e f
o
rm
ul
at
ed a
n
d
i
m
pl
em
ent
e
d,
u
s
i
n
g s
p
eed
co
nt
r
o
l
m
a
gnet
sy
nc
hr
on
o
u
s
mach
in
e system an
d
a p
e
rman
en
t p
ilo
t p
h
a
se.
Wh
ile
th
e n
e
w strateg
y
p
r
o
m
o
t
es t
r
ad
ition
a
l PI co
n
t
ro
l
per
f
o
r
m
a
nce t
o
a l
a
rge e
x
t
e
nt
,
and
p
r
o
v
es t
o
be a m
ode
l-free ap
pro
ach
com
p
le
tely, it a
l
s
o
k
e
ep
s t
h
e stru
cture
and feat
ure
s
of
a sim
p
l
e
PI cont
rol
l
e
r [
6
]
.
T
h
e use co
ns
ol
e
s
m
ode i
n
st
ead
of Fuzzy
-
P
I c
ont
rol
t
o
im
pr
ove t
h
e
per
f
o
r
m
a
nce of PM
SM
. T
o
cont
rol
t
h
e s
p
ee
d o
f
PM
SM
by
using fuzzy logic (FL
)
ap
proach leads to a
spee
d
cont
rol
t
o
i
m
p
r
o
v
e t
h
e
dy
na
m
i
c behavi
or
of t
h
e PM
SM
sy
st
em
and i
m
m
une di
so
r
d
ers t
o
d
o
w
n
l
o
ad a
n
d
p
a
ram
e
ter v
a
riatio
n
s
[7
,8
]. In
th
e
W
T
GS
syste
m
s an
d
gain
s fro
m
th
e
trad
itio
n
a
l can’t u
s
u
a
lly b
e
set in
proportion-inte
gral (P
I) cont
roller s
p
ee
d large e
n
ough because
of mechanical res
o
nance
.
As a
result
,
per
f
o
r
m
a
nce d
e
gra
d
at
i
o
n a
n
d
spee
d
co
nt
r
o
l
.
F
u
zzy
l
ogi
c c
ont
rol
l
e
r
(F
LC
) f
o
r
use i
n
W
T
GS
sy
st
em
s in
or
de
r
t
o
i
m
prove
t
h
e
pe
rf
orm
a
nce
of
t
h
e s
p
ee
d c
ont
rol
.
Th
e
pr
op
ose
d
FLC
h
a
s bee
n
c
o
m
p
ared
wi
t
h
t
r
a
d
i
t
i
onal
PI
cont
rol
wi
t
h
re
spect
t
o
t
h
e sp
eed of re
sp
o
n
s
e
and dy
nam
i
c l
o
ad t
o
r
que
. S
i
m
u
l
a
t
i
on and
expe
ri
m
e
nt
al
r
e
sul
t
s
have
pr
o
v
ed t
h
at
FLC
was p
r
op
ose
d
i
s
su
pe
ri
or t
o
t
h
e t
r
a
d
i
t
i
onal
PI. T
h
i
s
FLC
can be a
sat
i
s
fact
ory
sol
u
t
i
on
for the
high-pe
r
form
ance m
a
c
h
in
e lifts system
s [9
-11
]
. A
m
o
d
e
rn
way to co
n
t
ro
l th
e speed
of PMSM
u
s
ing
p
a
rticle swarm op
timizatio
n
(PSO) t
o
im
p
r
ov
e t
h
e algor
ithm
p
a
ra
m
e
ters o
b
s
erv
e
r PI-.
Si
m
u
late th
e syste
m
u
n
d
e
r
d
i
fferen
t
op
erating
year co
nd
itio
ns is prep
ared
an
d
th
e ex
p
e
rim
e
n
t
al setu
p.
Use
PSO algo
rith
m
and
opt
i
m
i
zati
on m
a
ke
a po
wer
f
ul
e
n
gi
ne,
wi
t
h
fast
er res
p
o
n
s
e
an
d hi
g
h
e
r
resol
u
t
i
o
n
dy
n
a
m
i
c
and
se
nsi
t
i
v
e
t
o
l
o
ad va
ri
at
i
on [
1
2
,
13]
.
2.
M
O
D
EL FOR A
PMSM DRIV
E
(Fi
g
ure
1
bl
oc
k
di
ag
ram
of a
PM
SM
&
Fi
g
u
r
e2
bl
ock
di
a
g
r
a
m
of a
PM
SM
Dri
v
e)
Th
e co
m
p
lete n
o
n
lin
ear m
o
del o
f
a PMSM
with
ou
t
d
a
m
p
er wi
nd
ing
is as
fo
llows:
vq
= R
i
q
+
pL
qi
q +
s(Ldid +
af
)
(
1
)
vd = Rid +
p
d -
s
L
q
i
q
(
2
)
vd a
nd
vq are
t
h
e d,
q axi
s
v
o
l
t
a
ges, i
d
and i
q
are t
h
e d,
q a
x
i
s
st
at
or cu
rre
nt
s, Ld a
nd L
q
are t
h
e d,q
axis inductanc
e
s, R and
s
are
the stator resistance and in
verter fre
quenc
y
respectively.
af
is
th
e flux
l
i
nkage
d
u
e t
o
t
h
e r
o
t
o
r m
a
gn
et
s l
i
nki
n
g
t
h
e
st
at
or.
The electric t
o
rque:
Te =
3P(
af
iq
+
(L
d
-
L
q
)i
diq
)
/2
(3
)
T
h
e
mo
t
o
r
d
y
n
a
mi
c
s
:
r
r
Jp
B
T
T
L
e
(
4
)
P is the
n
u
m
b
e
r
o
f
po
le
p
a
irs, TL is t
h
e load
t
o
rq
u
e
, B
is th
e
d
a
m
p
in
g
co
efficien
t,
r
is th
e
ro
tor
sp
eed
an
d J th
e m
o
m
e
n
t
o
f
in
ertia. Th
e inv
e
rt
er fr
eq
u
e
n
c
y is related
t
o
th
e ro
tor sp
eed as
fo
llo
ws:
r
s
p
(
5
)
Th
e m
ach
in
e
m
o
d
e
l is n
o
n
lin
ear as it con
t
ain
s
pro
d
u
c
t term
s su
ch
as sp
eed
with
id and
iq
.
No
te t
h
at
r
, id a
n
d iq are
s
t
ate variables
.
During
vector
co
n
t
ro
l, id
is
no
rm
ally fo
rced to
b
e
zero
q
t
q
e
i
K
/2
i
3P
T
af
(
6
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
PED
S
I
S
SN
:
208
8-8
6
9
4
Adv
ance
d
O
p
t
i
m
al
PS
O,
Fu
zz
y
&
PI C
ont
r
o
l
l
e
r Wi
t
h
PM
S
M
&
W
TGS At
5Hz
Si
de
Of
…
(
C
h
e
ngxio
ng M
ao)
17
5
T
L
iq
T
L
-
iq
-
r
-
r
-
+
v
q
Fi
gur
e
1.
Bloc
k
diagram
of a PM
S
M
Fi
gu
re
2.
B
l
ock
di
a
g
ra
m
of a PM
SM
Dri
v
e
3.
SPEED
CONTROL OF PMSM
(Fi
g
ure
3. B
l
o
c
k Di
ag
ram
of Speed C
ont
ro
l
of PM
SM
).
The PM
SM
i
s
usi
n
g co
nt
r
o
l
t
o
sup
p
re
s
s
h
a
rm
o
n
i
c
n
o
i
se to
a lev
e
l. Th
en
,
no
ise to a lev
e
l b
e
l
o
w and
v
i
bratio
n to
m
a
k
e
th
e ro
tatio
n
ev
en qu
ieter.
C
u
r
r
ent
C
u
r
r
e
n
t
C
o
m
m
a
nd
m
easurem
ent
Spee
d m
easur
em
ent
Fi
gu
re
3.
B
l
oc
k
Di
ag
ram
of S
p
eed
C
o
nt
r
o
l
o
f
PM
SM
IGB
T
SP
W
M
i
nve
rt
ers m
a
ke t
h
e r
o
t
a
t
i
o
n
sm
oot
her
wi
t
h
p
r
eci
sel
y
ad
ju
st
i
ng
spee
d
cont
rol
wi
t
h
freq
u
e
n
c
y and
v
o
ltag
e
regu
lat
i
o
n
.
It h
a
s th
e
latest lo
w-no
ise p
o
wer
u
n
its
to
m
a
k
e
th
e ro
tatio
n
ev
en
qu
ieter.
WG
S
has
di
rec
t
ed hi
gh
-s
peed
use
d
(
1
00
o
r
15
0
rpm
)
PM
SM
.
Ene
r
gy
ref
o
rm
i
n
t
h
e
WGS
g
eared
.
3
.
1
.
PI Controller
Mo
deling
In the PI spee
d controller the
m
achine spe
e
d is com
p
ared with th
e re
fe
rence s
p
eed a
n
d the spee
d
erro
r is th
e
n
t
h
sam
p
lin
g
in
terv
al as
ω
e[n] =
ω
r*[
n
]
–
ω
r
[
n
]
(
7
)
The o
u
t
p
ut
o
f
t
h
e speed c
o
nt
r
o
l
l
e
r gi
ves
t
h
e refe
rence
t
o
r
que
. He
nce
t
h
e out
put
o
f
t
h
e speed
co
n
t
ro
ller
at the n
t
h sam
p
lin
g
in
terv
al is
T[n]
=
T[
n-
1]
+ K
p
(
ω
e[n
]
–
ω
e[
n-
1]
) +
Ki
.
ω
e
[
n
]
(
8
)
For
c
onst
a
nt
ai
r
gap
fl
u
x
o
p
er
at
i
on
refe
rence
q
u
ad
rat
u
re a
x
i
s
cu
rre
nt
i
s
gi
v
e
n as
i
q
*
=
T
[
n
]
/
K
t
(
9
)
Th
e lim
i
t
er is u
s
ed
to li
m
i
t
th
e m
a
x
i
m
u
m
v
a
lu
e o
f
ou
tpu
t
of sp
eed con
t
ro
ller. Th
e m
a
x
i
m
u
m
machine rate
d
current a
n
d
de
vice curre
nt
of the
converte
r di
ctate the lim
i
t.
Whe
r
e,
ω
e[n] is spee
d
error at nt
h inst
ant,
ω
r*[n] is the
refe
rence
speed at
nth i
n
sta
n
t
ω
r[n] is the
actual m
achine speed at
nth i
n
sta
n
t,
ω
e
[
n-
1]
is the s
p
ee
d er
r
o
r
at (n
-1
)th
insta
n
t
T[n]
i
s
t
h
e
refe
rence
t
o
r
q
ue at
nt
h
i
n
st
a
n
t
,
T
[
n-
1]
i
s
t
h
e
re
fe
rence
t
o
r
q
ue at
(
n
-
1
)t
h i
n
st
a
n
t
Kp
i
s
p
r
op
o
r
t
i
o
nal
gai
n
of
t
h
e
spee
d c
ont
r
o
l
l
e
r
s
L
R
q
1
p
a
f
k
t
Speed
C
ontr
o
l
Cu
rren
t
Contr
o
l
J
s
B
1
p
a
f
s
L
R
q
1
k
t
J
s
B
1
Lood
Inverter
PMSM
Spee
d
cont
r
o
l
Current
cont
r
o
l
l
e
r
DC
S
p
eed
com
m
and
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-86
94
I
J
PED
S
Vo
l. 7,
No
.
1,
Mar
c
h
2
016
: 1
7
3
–
19
2
17
6
Ki is in
teg
r
al
gain
of t
h
e sp
eed
co
n
t
ro
ller is referen
ce
q
u
adratu
re ax
is cu
rren
t
Kt is torqu
e
con
s
tan
t
3.
2.
Fuz
z
y
L
ogi
c C
o
n
t
r
o
l
l
er
The B
a
si
c c
o
nf
i
g
u
r
at
i
o
n
o
f
a
Fuzzy
L
o
gi
c C
ont
rol
l
e
r
(FLC
) c
onsi
s
t
s
o
f
t
h
e f
o
l
l
o
wi
ng
co
m
ponent
s:
1) Fuzzification
Interface
2)
K
n
o
w
l
e
dge
B
a
se (
K
B
)
3)
Deci
si
o
n
M
a
ki
n
g
L
o
gi
c
4) De
fuzzi
fication
Interface
A
fuzzy c
o
ntroller is a s
p
ecial fuzzy
system that ca
n
be
us
ed as
a
c
ont
rol
l
er com
p
onent
in a cl
ose
d
lo
op
syste
m
. Th
e in
tegratio
n
o
f
a fu
zzy syste
m
in
to
a
cl
osed l
o
o
p
i
s
sh
o
w
n
.
Speci
al
e
m
phasi
s i
s
put
ont
o t
h
e
t
r
ans
f
er beha
v
i
or of fuzzy
cont
rol
l
e
rs
,
w
h
i
c
h
a
r
e
anal
y
zed
usi
ng di
ffe
rent
c
o
n
f
i
g
urat
i
o
ns of
st
anda
r
d
me
m
b
ersh
ip
fun
c
tio
ns. For a PM
m
ach
in
e d
r
iv
e syste
m
wi
th
a fu
ll sp
eed
rang
e, th
e syste
m
will
co
n
s
ist o
f
a
m
achi
n
e, an i
nve
rt
er, c
o
nt
ro
l
l
e
r (co
n
st
ant
t
o
r
que a
nd
fl
u
x
wea
k
eni
n
g ope
rat
i
o
n, ge
n
e
rat
i
on
of re
fe
renc
e
currents
and
PI controller)
3.
3.
Par
t
i
c
l
e
S
w
arm O
p
ti
mi
z
a
ti
on
It is a technique
used t
o
e
x
plore the sea
r
ch
space for
a give
n
proble
m
to find the settings
or
p
a
ram
e
ters requ
ired
to
op
tim
i
ze a p
a
rticu
l
ar o
b
j
ectiv
e.
PSO h
a
s t
w
o
m
a
i
n
con
c
ep
ts: the first is th
ro
ug
h
t
h
e
obs
er
vat
i
on
o
f
hum
an deci
si
o
n
m
a
ki
ng, i
t
w
a
s pr
o
p
o
s
ed t
h
at
hum
ans use
bot
h t
h
ei
r
o
w
n
best
ex
pe
ri
enc
e
an
d
ot
he
rs’
best
e
x
peri
e
n
ce t
o
f
o
r
m
a basi
s of
m
a
ki
n
g
a
deci
si
o
n
, t
o
devel
o
p t
h
e c
once
p
t
s
o
f
i
ndi
vi
d
u
al
l
e
a
r
ni
ng
and c
u
l
t
u
ral
t
r
ansm
i
ssi
on. Th
e secon
d
i
s
t
o
pr
o
pose a si
m
p
l
e
t
h
eo
ry
t
o
e
xpl
ai
n
g
r
o
u
p
b
e
havi
or i
n
nat
u
re, a
n
d
to
po
pu
larize t
h
e th
eo
ry to
create syste
m
s
to
sim
u
late
th
in
g
s
. Th
e b
i
g
g
est ch
aracterist
i
c o
f
PSO is i
n
its
si
m
p
le stru
cture, fast
conv
ergen
ce, and
its ab
ility to
prev
en
t falling
i
n
to
a lo
cal
o
p
tim
u
m
so
lu
tio
n
.
At
th
e
sam
e
t
i
m
e
, PSO i
s
a rand
om
al
gori
t
h
m
wi
th a paral
l
e
l
st
ruct
u
r
e. A
uni
f
o
rm
di
st
ri
but
i
o
n i
s
used t
o
ra
nd
om
l
y
create a particle swarm
.
Each particle
represen
ts a feasib
le
so
lu
tion
to
th
e
p
r
ob
lem
,
th
e particle swarm
r
e
fers
to the individual’s best expe
rience, a
nd t
h
e group’s
be
st experie
n
ce, a
nd l
ogically choos
e
s the m
e
thod
it will
m
o
v
e
itself. After con
tinu
o
u
s
iteratio
n
s
, t
h
e
p
a
rticle
swarm will grav
itate to
ward
s th
e op
t
i
m
u
m
so
lu
tio
n.
4.
WIND T
U
RBINE GE
NERATION SYST
EM
(WTGS) &
MATHE
M
ATICAL MODELING
4.
1. Wind
Tu
r
b
ine
Gener
a
tion Sys
t
em (W
TGS)
W
i
nd
Turb
i
n
e
Gen
e
ration
Syste
m
(W
TGS) is u
s
ed
to
convert ki
netic energy
into electrical energy
.
As wi
nd ca
se
varies, t
h
e e
l
ectrical energy produce
d
fr
om
t
h
e gener
a
t
o
r
needs t
o
be co
n
v
ert
e
d
fo
r
co
nv
en
ien
c
e.
An
i
n
v
e
rter, rectifier, transfo
r
mer a
n
d
filter are
n
e
ed
ed
wit
h
in
the W
i
n
d
Tu
rb
in
e
Gen
e
ratio
n
Syste
m
(W
TGS), in
o
r
d
e
r
for u
tility-g
rad
e
AC po
wer to
b
e
tran
sm
itted
o
v
e
r lo
ng
d
i
stan
ces (Figure 4
)
.
A
tran
sform
e
r
is
u
s
u
a
lly in
stalled
at th
e u
n
d
erm
o
st o
f
th
e
to
wer to
p
r
o
v
i
d
e
vo
ltag
e
d
i
version
fro
m
th
e lo
w
v
o
ltag
e
b
y
t
h
e
wind
turb
in
e, to
m
e
d
i
u
m
/h
ig
h vo
ltag
e
for tran
sit.
Fig
u
r
e
4
.
PMSM
W
i
nd
En
er
gy Co
nv
ersion
Syste
m
Mo
st m
o
d
e
rn
W
i
nd
Turb
in
e Gen
e
ratio
n
Syste
m
(W
TGS) h
a
v
e
in
tellig
en
t feature to
o
b
s
erv
e
and
co
n
t
ro
l th
e syste
m
to
d
i
v
e
rse wind
co
nd
ition
s
. Li
k
e
,
atm
o
sp
heric sen
s
ors d
e
tect
wi
n
d
sp
eed
and
d
i
rectio
n.
Ot
he
r sens
o
r
s obs
er
ve t
h
e st
a
t
us an
d st
re
ngt
h o
f
t
h
e t
u
rbi
n
e part
s t
o
by
pa
ss ru
n-t
o
-
f
ai
l
u
r
e
.
W
i
n
d
t
u
rbi
n
es need
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
PED
S
I
S
SN
:
208
8-8
6
9
4
Adv
ance
d
O
p
t
i
m
al
PS
O,
Fu
zz
y
&
PI C
ont
r
o
l
l
e
r Wi
t
h
PM
S
M
&
W
TGS At
5Hz
Si
de
Of
…
(
C
h
e
ngxio
ng M
ao)
17
7
to
resist ex
treme weath
e
r con
d
ition
s
, su
ch
as sto
r
m
s
an
d
l
i
g
h
t
n
i
n
g
.
In th
ese typ
e
s
o
f
cond
itio
n
s
, it is imp
o
rtan
t
to
ensure th
at
th
e turb
in
e m
o
nito
ring
system
is d
e
sign
ed
to
p
r
ov
id
e
h
i
gh
vo
ltag
e
.
4
.
2
.
Ma
thematica
l
Modeling of Wind Turbines
1
st
E:
Ki
net
i
c
E
n
er
gy
m: To
tal
m
a
ss
Vw:
Th
e v
e
l
o
city o
f
th
e air
p
a
rticles (W
i
n
d Sp
eed)
2
2
1
mV
E
(
1
0
)
2
nd
The air pa
rticles are
m
oving at a sp
eed
(Vw)o
f
th
e particles fo
r a period
o
f
tim
e,
t, can
b
e
rewri
tten
as
fo
llows:
t
V
r
t
V
m
2
(
1
1
)
: th
e air
d
e
n
s
ity
A: th
e
swep
t area of th
e wi
n
d
tu
rb
in
e
ro
t
o
r
r:
t
h
e
radi
us
of
t
h
e wi
nd
t
u
rbi
n
e r
o
t
o
r
3
rd
t
h
e
ki
net
i
c
ener
gy
of t
h
e a
i
r pa
rt
i
c
l
e
s can
be e
x
p
r
esse
d a
s
f
o
l
l
o
ws:
t
V
r
E
3
2
2
1
(
1
3
)
4
th
the act
ual
wind
powe
r at
any insta
n
t of t
i
m
e
can be
re
presente
d as:
3
2
2
1
V
r
t
E
P
wind
(
1
4
)
whe
r
e,
wind
P
, is t
h
e
p
o
t
en
tially av
ailab
l
e p
o
wer in th
e
wind
.
5
th
Th
e relation
s
h
i
p
b
e
t
w
een th
e p
o
wer that is cap
tu
red
b
y
th
e wind
tu
rb
in
e an
d
th
e p
o
t
en
tial m
a
x
i
m
u
m
po
we
r i
n
t
h
e
w
i
nd ca
n
be e
x
pr
essed a
s
f
o
l
l
o
w
s
:
wind
Turbine
p
P
P
C
(
1
5
)
whe
r
e,
Turbine
P
is the mechanical power ca
pt
ured
by th
e win
d
turb
in
e, and
C
p
is th
e p
o
wer co
efficien
t of th
e
wind
turb
in
e
wh
ich
can
b
e
express
e
d
as foll
ows:
1
5
4
3
2
1
6
)
1
(
c
p
e
c
c
c
c
c
C
(
1
6
)
3
1
035
.
0
08
.
0
1
1
(
1
7
)
V
r
m
/
1
(
1
8
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-86
94
I
J
PED
S
Vo
l. 7,
No
.
1,
Mar
c
h
2
016
: 1
7
3
–
19
2
17
8
whe
r
e,
, i
s
t
h
e
bl
ade a
ngl
e a
nd
is th
e tip
sp
eed
ratio
o
f
t
h
e wi
n
d
t
u
rb
ine, wh
ile,
m
, is the
angular spee
d of
t
h
e wind
turbine ge
ne
rat
o
r. The
value
s
of
the coe
fficient
s
(c
1~
c6
)
depe
nd
o
n
t
h
e t
y
pe
of t
h
e
wind
turb
in
e.
3
2
)
,
(
2
1
V
C
r
P
p
Turbine
(
1
9
)
5.
SIMULATION RESULTS
B
y
usi
n
g Si
m
u
l
a
t
i
on m
odel
P
M
SM
& Si
m
u
l
a
t
i
on
of
W
T
G
S
D
r
i
v
e
sy
st
em
by
usi
n
g
PM
S
M
:
5.1.
Simulation model Perm
anent
Ma
gnet
Synchr
on
ous Mac
h
ine (PMSM).
M
odel
o
f
t
h
e s
y
st
em
(Fi
g
u
r
e 5) i
s
veri
fi
e
d
t
h
r
o
ug
h com
put
er sim
u
l
a
t
i
ons usi
n
g t
h
e so
ft
ware pac
k
a
g
e
MATLAB/Simu
lin
k. Su
mm
a
r
izes th
e p
e
rfo
r
m
a
n
ce of
t
h
e
W
T
G
S
, bo
th
i
n
co
m
p
uter
sim
u
latio
n
and
expe
ri
m
e
nt
al
im
pl
em
ent
a
t
i
on. T
h
e
a
n
alyzed
WGS c
onsi
d
ers electrical
dri
v
e
(PMSM
Dri
v
e System
).
Fi
gu
re
5.
Si
m
u
l
a
t
i
on M
o
del
o
f
PM
SM
Dri
v
e converte
r is curre
ntly re
gul
at
ed
SP
WM
vol
t
a
ge so
u
r
ce
i
nve
rt
er
(
CRSPW
M
V
S
I)
direct current
p
o
wer sup
p
l
y. Th
e con
t
ro
ller is u
s
ed
for t
h
e task
to
p
r
ov
id
e
p
o
s
ition
referen
ce track
i
n
g
and
zero
error in
st
eady
st
at
e. C
onst
a
nt
l
o
a
d
i
s
us
ual
f
o
r
WT
GS.
Th
us,
co
n
t
ro
ller
with
p
r
op
ortion
a
l and
i
n
tegral actio
n
(PI) is
use
d
, B
l
oc
k
di
agram
of
PI
C
o
nt
r
o
l
l
e
r i
s
s
h
o
w
n
i
n
Fi
g
u
re
6
.
Fi
gu
re
6.
B
l
oc
k
di
ag
ram
of P
I
C
o
nt
r
o
l
l
e
r
Si
m
u
latio
n
o
f
th
e en
tire syste
m
with
th
e desig
n
e
d
con
t
roller is m
a
d
e
in
th
e Matlab
/
Si
m
u
l
i
n
k
and
gi
ve
n res
u
l
t
s
sho
w
t
h
at
desi
g
n
co
nt
r
o
l
l
e
r
m
eet
s t
h
e requi
r
e
m
e
nt
s com
p
l
e
t
e
l
y
sm
oot
h and pr
eci
se po
si
t
i
on a
n
d
spee
d.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
PED
S
I
S
SN
:
208
8-8
6
9
4
Adv
ance
d
O
p
t
i
m
al
PS
O,
Fu
zz
y
&
PI C
ont
r
o
l
l
e
r Wi
t
h
PM
S
M
&
W
TGS At
5Hz
Si
de
Of
…
(
C
h
e
ngxio
ng M
ao)
17
9
To
v
e
rify th
e
feasib
ility o
f
co
n
t
ro
l, PMSM d
r
i
v
e sim
u
latio
n
m
o
d
e
l
with
con
t
ro
l is
created
and
st
udi
e
d
usi
ng
M
A
TLAB
.
Si
m
u
l
a
t
i
on pa
ra
m
e
t
e
rs:
st
at
or resi
st
ance R
s
= 0.0
1
Ω
, inductance L
d
=
Lq =
0
.
0
183
5H
, f
l
ux
Ψ
= 0
.
4
V.s,
p
a
ir
of po
les p
= 3
,
in
ertia
J =
0
.
0
29k
g.m2
.
Sim
u
latio
n
co
nd
itio
ns: referen
c
e
sp
eed
n =
1
00,15
0 r
a
d
/ s, star
t w
ith
TL = 0N
.m
. Si
m
u
latio
n
resu
lts are p
r
esen
ted
in Figu
re
7-9
speed
is
sh
own
in
Figur
e 7
,
To
rq
ue is sh
ow
n
in
Fi
gu
r
e
8, and
cur
r
en
t is sh
ow
n
i
n
Figu
r
e
9. I
t
is o
b
v
i
ou
s th
at co
rr
ect
r
e
spon
ses to
sp
eed, cur
r
e
n
t
, an
d
torq
u
e
in
a co
n
t
ro
l system
.
U
s
in
g
PI
co
n
t
r
o
l and
Fu
zzy co
n
t
ro
l h
a
s a g
ood
ap
p
lication
for
PMSM driv
e.
At th
e sam
e
time, with
sp
ee
d
ha
ve f
a
st
er
res
p
o
n
se
. R
i
p
p
l
e
of t
o
r
q
ue i
s
ob
vi
o
u
sl
y
red
u
ce
d.
So
t
h
e sy
st
em
perf
o
r
m
a
nce i
s
im
prove
d.
Fi
gu
re
7.
Si
m
u
l
a
t
i
on res
u
l
t
re
spo
n
se
o
f
S
p
ee
d
Fi
gu
re
8.
Si
m
u
l
a
t
i
on res
u
l
t
re
spo
n
se
o
f
T
o
rq
ue
Fi
gu
re
9.
Si
m
u
l
a
t
i
on res
u
l
t
re
spo
n
se
o
f
C
u
r
r
e
nt
5.
2.
Si
mul
a
ti
o
n
o
f
WT
GS w
i
th P
M
S
M
.
To Analysis sim
u
la
tion res
u
lts, There are s
o
m
e
cases to do it as a followi
ng a
n
alysis
W
T
GS By
Usi
n
g PM
SM
(
S
pee
d
,
To
rq
ue,
C
u
r
r
e
n
t
)
a
n
d
(
T
m
(
pu),
W
i
n
d
Spee
d,
V
d
c,
G
r
i
d
V
o
l
t
a
ge a
n
d
Gra
d
C
u
r
r
ent
)
.
First step,
t
o
ru
n t
h
e PM
S
M
wi
t
h
di
ffe
r
e
nt
spee
ds t
o
get
a di
ffe
re
nt
fre
que
ncy
t
o
sel
ect
t
h
e
fre
que
ncy
o
n
t
h
e si
de ge
nerat
i
on wi
t
h
t
h
e
ra
t
e
d spee
d. Th
e si
m
u
latio
n
resu
lt in
th
e tab
l
e (1), it was clearly to
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-86
94
I
J
PED
S
Vo
l. 7,
No
.
1,
Mar
c
h
2
016
: 1
7
3
–
19
2
18
0
get
5
H
z si
de o
f
gene
rat
i
o
n
b
y
usi
n
g rot
a
t
i
o
n
s
p
ee
d 10
0 r
a
d/
sec whi
c
h usi
n
g
t
h
e
si
m
u
l
a
t
i
on
sy
st
em
of
t
h
i
s
work. Sim
u
lati
o
n
Mod
e
l
o
f
PMSM is illu
strated
in
figu
re (5
) wh
ich u
s
i
n
g th
is step.
Tabl
e
1.
PM
S
M
wi
t
h
di
f
f
ere
n
t
s
p
eeds
t
o
ge
t
di
ffe
re
nt
f
r
eq
uency
Rated Speed(rad/s
ec)
Ti
m
e
(sec)
Frequency(H
z
)
50
0.
42
2.
38
100
0.
2
5
200
0.
1
10
1000
0.
02
50
1500
0.
0166
6
60
a) Spee
d
b)
C
u
rre
nt
Fi
gu
re 1
0
. Si
m
u
l
a
t
i
on
M
o
del
of
PM
SM
at
S
p
eed=
1
00
,5
Hz,
a) Spee
d & b) C
u
r
r
ent
a) Spee
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
PED
S
I
S
SN
:
208
8-8
6
9
4
Adv
ance
d
O
p
t
i
m
al
PS
O,
Fu
zz
y
&
PI C
ont
r
o
l
l
e
r Wi
t
h
PM
S
M
&
W
TGS At
5Hz
Si
de
Of
…
(
C
h
e
ngxio
ng M
ao)
18
1
b)
C
u
rre
nt
Fi
gu
re
1
1
.
Si
m
u
l
a
t
i
on M
o
del
of
PM
SM
at
S
p
eed=
2
00
,1
0
H
z, a)
S
p
eed
&
b)
C
u
rre
nt
Second s
t
ep,
s
o
lve t
h
e m
a
thematical equation to
use
diffe
r
ent
values
of
wind s
p
eed wi
th selected
(
1
5
,
20
m
/
s an
d
less t
h
an w
i
t
h
m
o
r
e
th
an
15&20
m
/
s)
.
In t
h
i
s
pa
per
,
we use
d
t
w
o t
y
pes of va
ri
abl
e
and co
nst
a
nt
spee
d. C
o
nst
a
n
t
speed has (
1
5
m
/
s
, 20m
/
s
,
15
&2
0m
/
s
), on
e ho
ur t
h
e spe
e
d was (
15m
/
s
) so o
n
e t
i
m
e
by
usi
n
g (2
0m
/
s
) t
h
e t
h
i
r
d t
i
m
e four h
o
u
rs
be use
d
(1
5&
2
0
m
/
s). For
o
n
e
day
,
we
use
d
vari
abl
e
s
p
eed
wi
t
h
m
o
re t
h
an
(
1
5&
20
m
/
s) so l
e
ss
t
h
a
n
(1
5&
2
0
m
/
s).
Used a sp
ecial
typ
e
to
g
e
t
v
a
ri
ab
le sp
eed wit
h
m
o
re th
an
(15
&
2
0
m
/s) so less th
an
(15
&
20
m
/
s).
We
need a m
a
them
atical equa
tion
by
de
si
g
n
e
d
t
o
t
h
ese
val
u
es.
First, selected
som
e
values li
ke
(15, 20, 20.4
2, 2
0
.38
,
19
.68
,
15
.4
2, 1
5
.38,
14
.98
&
1
4
.68).
Seco
nd
, Am
pl
it
ude &F
req
u
e
n
cy
:
Am
plitude, X
0
= 15m
/
s, X1 =
20m
/
s, S1 =
0.
4
m
/s, S2
=
0
.
2m/s, S3
= 0.02
& S4
=
0
.
00
2
Y
1
=
X
0
+
S
1
+
S
2
+
S
3
+
S
4
(
2
0
)
Y
2
=
X
1
+
S
1
+
S
2
+
S
3
+
S
4
(
2
1
)
Fr
eq
u
e
n
c
y, X0
fo
r
12
ho
ur
s, X
1
fo
r
12
hou
rs,
S1
at 0
.
17
5 h
our
s, S2
at 0
.
5
h
our
s, S3
at 0
.
0
8
hou
r
s
&
S4 at
0.
25
h
o
u
rs
. Si
m
u
l
a
t
i
on m
odel
(
w
i
n
d
spee
d)
of
t
h
is step
is sh
own in
figure (12
)
and
th
e sim
u
latio
n
resu
lts is
shown
in fi
g
u
res
(13).
Fi
gu
re 1
2
. Si
m
u
l
a
t
i
on
m
odel
of
wi
nd
spee
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-86
94
I
J
PED
S
Vo
l. 7,
No
.
1,
Mar
c
h
2
016
: 1
7
3
–
19
2
18
2
0
5
10
15
20
10
15
20
25
Ti
m
e
W
i
nd S
pee
d
W
i
nd
S
peed
(
m
/
s
)
Fi
gu
re
1
3
.
Vari
abl
e
wi
nd
s
p
ee
d
(1
5m
/
s
at
12
Ho
ur
s &
2
0m
/
s
at
1
2
H
o
urs
)
Third step,
C
a
l
c
ul
at
i
on
t
h
e p
o
we
r ge
nerat
i
o
n wi
t
h
wi
n
d
s
p
eed (1
5
m
/
5
& 20
m
/
s).
In
t
h
i
s
st
e
p
, by
usi
n
g
e
q
uat
i
o
n
of
p
o
w
e
r ge
ner
a
t
i
on wi
t
h
ha
v
e
dat
e
of
wi
nd
ener
gy
t
u
rbi
n
e.
By u
s
ing
Parameters an
d op
eratin
g cond
itio
n
s
PMSM,
2
.
0
M
W
,
69
0 V,
9
.
75
H
z
,
Rated
Mech
an
i
cal Pow
e
r 2.0
M
W
Rated
App
a
r
e
nt Pow
e
r 2.241
9 MV
A,
Rated
Po
w
e
r
Facto
r
0
.
89
21
Rated
Ro
tor
Sp
eed 22
.5
r/m
i
n
,
Nu
m
b
er
o
f
Po
le Pairs
26
R
a
t
e
d
M
echa
n
i
cal
Tor
q
ue 84
8
8
2
6
Nm
,
R
a
t
e
d
R
o
t
o
r Fl
ux
Li
n
k
a
g
e 5.
8
2
6
4
(rm
s)
Stator Winding
Resistance 0.821
m
,
d
ax
is Sy
n
c
hr
on
ou
s
In
du
ctan
ce 1
.
57
31
m
H
q
ax
is Sy
n
c
hr
on
ou
s
In
du
ctan
ce 1
.
57
31
m
H
,
W
i
nd
Tu
rb
ine
Ro
to
r Rad
i
u
s
34
m
W
i
n
d
T
u
r
b
i
n
e
Opt
i
m
al
Ti
p Speed
R
a
t
i
o
6.
1
6
,
IGB
T
M
o
dul
at
i
on
Fre
q
uency
1.
5
kHz
1
st
wh
en
th
e wi
n
d
speed is 15m/s
Spee
d
6
.
70
34
15
*
16
.
6
*
26
)
2
(
r
V
p
e
Power
MW
P
P
V
C
r
P
Turbine
Turbine
p
Turbine
00142395
.
3
10
*
00142395
.
3
95
.
3001423
)
15
(
*
4
.
0
*
)
34
(
*
14
.
3
*
225
.
1
*
5
.
0
)
,
(
2
1
6
3
2
3
2
Tor
q
ue
1115770
26
/
6
.
70
95
.
3001423
26
/
Speed
Power
Power
Torque
m
Cur
r
ent
2
nd
wh
en
th
e win
d
sp
eed
is
20m/s
Spee
d
211
.
94
34
20
*
16
.
6
*
26
)
2
(
r
V
p
e
Power
MW
P
P
V
C
r
P
Turbine
Turbine
p
Turbine
1144864
.
7
10
*
1144864
.
7
4
.
7114486
)
20
(
*
4
.
0
*
)
34
(
*
14
.
3
*
225
.
1
*
5
.
0
)
,
(
2
1
6
3
2
3
2
Tor
q
ue
3
.
2831636
26
/
211
.
94
4
.
7114486
26
/
Speed
Power
Power
Torque
m
11
.
3472
2398
.
8
*
26
*
5
.
1
1115770
)
2
)(
2
3
(
r
qs
p
Torque
i
Evaluation Warning : The document was created with Spire.PDF for Python.