Intern
ati
o
n
a
l
Jo
u
r
n
a
l
of
P
o
we
r El
ec
tr
on
i
c
s
an
d D
r
i
v
e
S
y
stem
(I
JPE
D
S)
V
o
l.
11
, N
o
. 2, Jun
e
20
20
, pp
. 10
40
~1
046
I
SSN
:
208
8-8
6
9
4
, D
O
I:
10.
115
91
/i
jp
e
d
s.v
1
1
.i2
.
p
p10
40-
1046
1
0
40
Jo
urn
a
l
h
o
me
pa
ge
: h
t
t
p
:/
/ijpe
d
s.
i
a
e
s
c
o
re.
c
o
m
Optimi
zation of wind
energy conv
ersion systems – an artificial
inte
lligent approach
Yi
ng
Yin
g
Ko
ay
,
Jian
Di
n
g
T
a
n,
Si
a
w
P
a
w
K
o
h
,
K
o
k
He
n
Ch
on
g,
Si
eh
Ki
ong
Ti
o
n
g
,
Ja
n
a
ka
Eka
n
a
yake
Inst
it
ut
e
o
f
Sust
ain
a
ble
Ene
r
g
y
, U
n
iv
e
r
sit
i
Te
na
ga
Na
sio
n
a
l, Ma
la
ysia
A
r
ticle In
fo
A
B
S
T
RAC
T
A
r
tic
le
h
i
st
o
r
y:
Rec
e
i
v
ed
O
c
t
1
8
,
2
019
Rev
i
sed
D
e
c
28
, 20
19
A
c
ce
p
t
ed
Jan
17
, 20
20
Th
e
environ
m
en
tally
friend
l
y
win
d
en
e
r
g
y
co
nv
ers
i
o
n
sy
stem
h
a
s b
e
come
on
e of
th
e
mos
t
stud
ied
b
r
anch
es of
s
u
s
t
ain
a
bl
e
energy
.
Lik
e
many
other
p
o
we
r
ge
n
e
ra
to
r, m
a
xim
u
m
p
o
wer
po
in
t t
r
ac
ki
ng
is a
n
ea
sy
ye
t e
ffe
c
t
i
v
e
wa
y
to
b
o
o
s
t
the
efficie
n
cy of
th
e
co
nv
ers
i
o
n
sy
ste
m
.
In
this
resea
r
ch,
a
mod
i
fie
d
Ele
c
tro
m
ag
net
i
s
m
-lik
e
M
e
chan
is
m Algo
rith
m
(EM
)
is p
r
op
os
ed fo
r
th
e
ma
x
i
mum po
wer
p
o
i
nt
t
r
ac
ki
ng (MPPT
)
sc
he
me
of
a mic
r
o-wi
n
d
e
n
e
r
g
y
con
v
ers
i
on
s
y
s
t
e
m
(
W
ECS
)
.
In
c
o
ntrast
with
th
e
ran
d
o
m
sear
ch
st
eps
u
s
ed
in
a
conventi
onal
E
M
,
modified E
M
i
s
enhanced wit
h
a Split,
Probe,
and
Comp
are (S
PC-
E
M
)
featur
e w
h
i
c
h en
su
re
s
so
lu
tion
s
w
i
th h
i
gh
er
accur
a
c
i
e
s
qu
ick
e
r
b
y
n
o
t
havi
ng
to
scr
u
t
i
n
ize
th
e
sear
ch
i
n
d
e
tai
l
s
a
t
th
e
b
e
gi
nn
i
n
g
stages
of
th
e it
e
r
ations
.
Exp
e
rim
e
nts
a
n
d si
mula
t
i
o
n
s
ar
e carr
i
ed
to
t
e
st
th
e
S
P
C
-EM
in tra
c
k
ing
th
e m
a
xim
u
m p
o
wer
po
int
u
nder
diff
eren
t w
i
n
d
p
r
ofiles
.
Re
sul
t
s i
n
dic
a
te th
a
t
t
h
e
pe
rf
orma
n
c
e
of
the m
o
di
fi
ed EM
showed
si
gnificant
imp
r
ov
emen
t o
v
e
r th
e co
nv
en
tio
n
a
l EM in
th
e b
e
nch
m
arking.
It
can th
us
be
c
o
nc
l
ude
d
t
h
at
ba
se
d o
n
th
e
sim
u
l
a
ti
on
s, the
SPC-E
M
p
e
rfo
rms we
ll
a
s
a
n
MP
P
T
s
c
heme
i
n
a
mi
cro-WEC
S
.
Ke
yw
ords:
Electr
o
magnetism-
Li
ke
M
e
ch
an
i
s
m Alg
o
r
ith
m
M
a
x
i
m
u
m Pow
e
r Po
in
t
Tra
c
ki
ng
S
p
lit-
P
r
ob
e-
C
o
m
p
a
r
e
W
i
nd
En
ergy
Co
nv
e
r
sion
Syst
em
Th
is
is a
n
o
p
en
acces
s a
r
ticle
un
d
e
r the
C
C
B
Y
-SA
licens
e
.
Corres
p
o
n
din
g
A
u
t
h
or:
Jian Ding
Ta
n,
Inst
it
ut
e
of S
u
s
t
a
i
na
ble
E
n
e
r
g
y
,
Uni
v
ersi
t
i
Te
n
a
ga
Na
sio
n
a
l
,
Ja
la
n
Ikr
a
m-U
n
i
t
e
n
, 43
000
Kaj
a
n
g
,
S
e
l
a
ngo
r,
M
a
la
ysi
a
.
Emai
l:
tj
i
a
ndi
n
g
@
u
nit
e
n.e
d
u
.
my
1.
IN
TR
O
DUCTION
F
o
ssil
fue
l
s
ba
se
d p
o
w
e
r ge
n
e
rat
i
on
has al
ways
ra
i
s
e
d
en
vi
ron
m
ent
a
l
c
o
nce
r
ns. R
e
sea
r
che
r
s
a
r
o
u
n
d
th
e
w
o
r
l
d a
r
e
ra
ci
n
g
in s
ear
ch fo
r a
lte
rn
ati
v
e
so
ur
ce
s w
i
t
h
l
e
ss en
v
i
r
o
n
m
en
ta
l i
m
p
a
cts
.
W
i
t
h
it
c
o
me
s
a
r
a
p
i
d
deve
l
o
p
m
ent
o
f
rene
wa
ble
e
n
e
r
g
y
st
ud
i
e
s
[1
-5
].
R
e
ne
wa
ble
e
n
e
r
g
y
ca
n
ge
neral
l
y
be
di
vide
d i
n
t
o
seve
ra
l
maj
o
r
bra
n
c
h
e
s
. Am
o
ng ot
h
e
rs i
s
the
wi
nd e
n
e
r
g
y
.
Wi
nd e
n
e
r
g
y
i
s
kn
o
w
n t
o
b
e
one
of t
h
e
most
envi
ro
nme
n
t
a
l
fri
e
n
d
l
y
an
d
qui
c
k
l
y
de
vel
opi
ng
s
o
u
r
ce
of el
ec
tric
it
y
no
wa
da
y
s
[6
-8].
In
a
wi
n
d
e
n
e
r
gy
con
v
e
r
sio
n
s
y
st
em (WEC
S),
t
h
e o
v
e
r
a
l
l
effi
c
i
e
n
cy is
ge
ne
ral
l
y
t
i
ed t
o
t
h
e abi
l
it
y o
f
t
h
e syste
m
t
o
a
b
stract
maxi
mum out
put
po
wer
at
a
l
l i
n
st
ant
in a
w
i
de
ra
n
g
e
o
f
wi
n
d
spee
d
[9
]
.
In orde
r
t
o
grant
t
h
e
WEC
S
wit
h
maxi
mum
out
p
u
t
po
we
r,
a
ma
xi
mu
m
p
o
we
r poi
nt
t
r
a
c
k
i
n
g
(MP
P
T
)
mec
h
ani
s
m i
s
c
r
uci
a
l
to
bri
n
g
the
t
u
rbi
n
e
t
o
t
h
e
ma
xi
mu
m p
o
w
er
p
o
i
n
t
(M
PP)
for
al
l
wi
n
d
s
p
ee
d
val
u
es.
Ma
ny
M
P
P
T
me
cha
n
i
s
ms
ar
e p
r
o
p
o
sed
in
t
h
e li
t
e
rat
u
re
. Inc
r
e
m
e
n
ta
l
c
o
nduc
ta
nce
(
I
C)
a
l
go
rit
h
m
,
fo
r
inst
a
n
c
e
,
doe
s
not
re
q
u
i
r
e
sens
ors a
n
d d
e
ta
i
l
s on t
h
e
tu
rbi
n
e
an
d
ge
n
e
ra
tor, t
h
us ma
ki
ng
it
mo
re
re
l
i
a
bl
e
a
n
d le
ss e
x
p
e
nsiv
e
[
10-
13
].
H
i
ll c
lim
b
i
ng (H
C) a
l
go
r
i
t
h
m a
p
p
l
i
e
s a
d
i
ff
ere
n
t
str
a
t
e
gy
w
h
i
c
h
re
lie
s h
e
av
ily
o
n
mat
h
emat
ic
al
opt
i
m
i
z
a
t
io
n a
p
p
r
oac
h
t
o
fi
n
d
t
h
e l
o
ca
l
op
t
i
ma of
a
gi
ve
n
fu
nct
i
o
n
[14
-
18
].
In t
h
i
s
me
t
hod, i
f
th
e
cur
r
e
n
t
so
lu
tio
n
is on
th
e
ri
gh
t o
f
t
h
e
be
st
o
p
t
im
a,
th
e
sw
itc
h
i
ng
mov
e
s t
h
e op
e
r
a
tin
g
po
i
n
t t
o
t
h
e
lef
t
,
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J Po
w El
ec
&
Dr
i
S
y
st
IS
SN:
208
8-8
6
9
4
Opt
i
m
i
z
a
t
i
on
o
f
w
i
nd e
n
er
gy
c
onv
e
rsio
n
syst
e
m
s –
an
a
r
t
i
f
i
c
ial
i
n
te
l
l
i
g
ent
a
ppr
o
a
c
h
(Yi
n
g Y
i
ng
K
o
ay)
1
041
maki
n
g
i
t
nea
r
er to the
o
p
t
i
ma
,
a
n
d
vi
ce
versa
.
T
h
e
ge
ne
ra
l
p
l
a
n
o
f
the
HC
i
s
base
d o
n
cha
n
gin
g
a
c
ont
rol
v
a
ri
a
b
l
e
in
a
de
te
r
m
in
ed
s
t
e
p
si
ze
an
d
an
aly
z
e
t
h
e r
e
su
ltin
g
ch
an
ges
in
th
e
ou
tc
ome
,
un
ti
l t
h
er
e
i
s
no
mo
re
i
m
pro
v
e
m
e
n
t
[19
-
21
].
HC
ca
n
be
wi
del
y
fou
n
d
i
n
t
h
e
MP
P
T
st
udie
s
[22
-
25
].
H
o
w
e
ve
r,
i
n
a
ra
pi
d
w
i
n
d
varia
t
i
o
n,
H
C
ca
n b
e
slu
ggi
s
h
an
d
hea
d
in t
h
e w
r
on
g
di
re
c
t
ion t
o
t
h
e
MP
P
[26
]
.
O
t
he
r
MPP
T
a
l
g
o
ri
th
ms for
WEC
S
,
suc
h
a
s
t
h
e pe
rt
u
r
b
and
o
b
ser
v
e
(P
&O
) al
g
o
ri
t
h
m a
i
ms t
o
ma
ximi
ze
the
ge
nerat
e
d p
o
w
e
r
out
put
whi
l
e
c
u
tt
i
n
g
d
o
w
n
t
h
e
re
li
an
c
e
o
n
c
ont
rol
u
n
i
t
s
an
d se
ns
ors
[
27, 28
].
In
thi
s
pa
pe
r,
a
m
odi
fie
d
El
e
c
t
r
oma
g
net
i
sm-Like
Mec
h
a
n
ism
(E
M
)
a
l
g
o
rit
h
m
i
s
pro
pose
d
as
t
h
e
DP
C
M
P
P
T
m
echa
n
is
m of
a
mi
cro
WEC
S
. The
c
ont
rib
u
t
i
on o
f
t
h
is
pape
r
i
s
t
w
o-fol
d
a
nd c
a
n
be s
u
mmari
zed
a
l
o
n
g
th
e l
i
n
e
s a
s
f
o
llow
ed
. Fir
s
t,
a
mod
i
fied
EM
al
go
ri
thm
w
i
th
Sp
lit,
Prob
e
,
and
Co
mp
a
r
e
(S
PC
)
fe
atu
r
e is
p
r
op
o
s
ed
.
W
ith
th
is
f
e
at
ure
,
t
h
is g
l
o
b
a
l
o
p
ti
mi
za
ti
o
n
alg
o
ri
th
m is
enh
a
n
ced
w
i
th
th
e
ab
ility
t
o
fi
nd
so
l
u
ti
o
n
s
w
i
t
h
re
la
tiv
e
l
y h
i
gh
er
ac
cu
rac
i
e
s
in
sh
or
te
r
time
.
S
e
con
d
l
y, th
e mod
i
fi
e
d
EM
is te
ste
d
in
sim
u
la
tion
t
o
tr
ac
k
f
o
r
t
h
e
m
a
x
i
mu
m
pow
er
p
o
i
nt of
a
W
E
CS
.
Th
e p
a
p
e
r is pres
en
t
e
d
in f
i
v
e
c
h
a
p
ter
s
.
Ch
a
p
t
e
r Two
exp
l
a
i
n
s
t
h
e
wo
rk
me
c
h
a
n
is
m o
f
t
h
e
E
M
a
nd t
h
e
det
a
i
l
s o
f
t
h
e
pro
pose
d
mo
di
fi
ca
t
i
on
s.
The
i
m
ple
m
e
n
ta
ti
on
a
nd
desi
g
n
o
f
t
h
e pro
p
o
se
d MP
P
T
me
c
h
a
n
i
s
m
i
s
di
sc
us
sed i
n
C
h
apt
e
r Th
re
e. C
h
ap
t
e
r Fo
ur pre
s
e
n
t
s
t
h
e e
xpe
riment
al
re
sul
t
s
a
n
d
t
h
e
di
scussi
o
n
s
deri
ved.
T
h
e
fi
nal
c
h
apt
e
r
offe
rs
t
h
e
c
onc
l
u
si
o
n
s
d
r
a
w
n
fr
om
th
e
resea
r
ch
.
2.
EL
E
C
TRO
M
A
G
NE
TIS
M
-
L
IKE
ME
C
H
ANI
S
M
AL
G
O
RITH
M
Th
e
EM is
a
p
opu
la
ti
o
n
b
a
sed
op
ti
miz
a
t
i
o
n
m
e
t
hod
pr
opo
sed
by
Bi
r
b
il an
d F
a
ng
[2
9
]
. Th
e
b
a
sic
id
e
a
o
f
t
h
e
EM
is to
imit
ate th
e
a
ttr
a
c
t
i
on
-re
pu
ls
ion
mech
a
n
ism
o
f
ele
c
t
r
o
magn
et
ic
ch
arg
e
s i
n
th
e effo
r
t
to
f
i
nd
th
e
b
e
st g
l
ob
al
op
tim
al s
o
lu
tio
n
in
bo
und
e
d
v
a
ri
ab
les.
Fi
gu
re
1
sh
ow
s an
e
x
a
m
p
l
e
of t
h
e a
t
t
r
a
c
t
io
n
-
r
e
p
u
l
sion
se
a
r
ch
m
ech
an
ism use
d
in
t
h
e
EM
.
F
i
gu
re
1. Tota
l
forc
e e
x
e
r
t
e
d on
Q
a
by
Q
b
and
Q
c
Th
er
e
a
r
e sev
e
r
a
l impo
r
t
an
t op
e
r
a
tio
n
s
in
t
h
e EM
,
i
n
cl
ud
i
n
g
t
h
e
i
n
itia
li
za
tio
n
,
l
o
c
a
l sea
r
c
h
, c
h
a
r
g
e
ca
lc
ula
t
i
on,
fo
rc
e ca
l
c
ul
at
io
n
,
an
d m
o
vem
e
nt
o
f
pa
rt
i
c
l
e
s, a
s
s
h
o
w
n i
n
Fi
gu
re
2.
In t
h
i
s
rese
arc
h
, t
h
e
a
d
ju
st
men
t
p
a
ram
e
te
r
is
t
h
e
ro
tor
sp
ee
d a
l
lo
we
d i
n
t
h
e
w
i
n
d
tur
b
in
e.
In
t
h
e
alg
o
r
i
t
hm,
m
samp
l
e
of
i
n
it
ia
l
parti
c
l
e
s a
r
e
ra
nd
oml
y
pic
k
e
d
from
t
h
e
fe
asi
b
l
e
P
W
M
val
u
e ra
nge
. Ea
c
h
val
u
e
o
f
a
pa
rt
i
c
l
e
i
s
a
s
sume
d
t
o
be
uniformly distri
buted insi
de t
h
e
uppe
r and lowe
r
bound. F
o
r t
h
e
purpose of WECS MP
PT,
t
h
e particle
with
t
h
e
hi
ghe
st
o
u
t
put
p
o
we
r
i
s
m
a
rke
d
a
s
t
h
e be
st
part
i
c
l
e
.
An
EM w
i
th
Sp
lit
,
P
r
ob
e
,
a
n
d
Co
mp
are
(SPC-EM
)
f
e
a
t
u
r
e
is
pr
opo
se
d
i
n
t
h
is r
e
s
ear
ch.
Th
e
SP
C
-
EM
is an
en
h
a
n
c
e
d
v
e
r
s
ion
of
t
h
e EM
wh
ic
h
ha
s th
e
ab
il
ity
t
o
h
it
ac
c
u
ra
t
e
so
l
u
tion
s
w
ith
ou
t
h
e
av
il
y
slo
w
in
g
do
w
n
t
h
e
e
n
t
i
r
e
c
onve
rge
n
c
e
proce
s
s
.
The
l
o
ca
l
sea
r
ch
mec
h
a
n
is
m o
f
a c
o
nve
nt
io
na
l E
M
is repl
a
c
e
d
wi
t
h
t
h
e
SP
C sea
r
ch
proc
ed
u
r
e.
A
t
u
n
i
ng
e
q
uat
i
o
n
i
s
de
si
gne
d
t
o
d
yna
mi
ca
ll
y
reg
u
l
a
t
e
t
h
e
l
e
n
g
t
h
s
of t
h
e
probe
s bas
e
d
on
t
h
e
o
u
tc
o
m
e
s
o
f
e
v
er
y
i
t
e
r
at
i
on, a
s
s
h
o
w
n in
eq
uat
i
o
n (1)
.
_
(1)
In equation
(1),
i
i
ndi
ca
t
e
s th
e
cu
rre
n
t
nu
mb
er of
loc
a
l
se
a
r
c
h
it
erat
i
o
n
wh
i
l
e
_
repr
es
e
n
ts
t
h
e ma
xi
mu
m
n
u
m
b
er
o
f
i
t
e
r
at
i
o
n
.
F
i
gu
r
e
3 e
xpl
a
i
ns t
h
e
de
ci
sio
n
m
a
ki
n
g
proc
ess
of t
h
e
S
P
C
sea
r
ch
mecha
n
ism i
n
t
h
e form of
a
fl
owcha
r
t. T
h
i
s
en
han
ced
S
P
C
-
EM
a
l
go
r
i
thm
is
th
en
e
m
plo
y
e
d
a
s
th
e M
PPT
scheme
o
f
a W
E
CS
,
whi
c
h
i
s
fu
rt
he
r e
xpl
ai
n
e
d in
the
ne
xt
c
h
apt
e
r.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
: 2
088
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6
94
I
n
t
J Po
w El
ec
&
Dr
i
S
y
st
, Vol.
11
,
No
.
2
,
Jun
e
2
020
: 10
40
–
1
0
46
1
042
Fi
gu
re
2. The
f
l
ow
o
f
a c
o
nve
nt
iona
l
EM
a
l
g
o
ri
t
h
m, w
h
ere
a
an
d
b
d
e
no
t
e
th
e
it
er
a
tio
n
numb
e
r
o
f
l
o
ca
l an
d
glo
b
a
l
search
res
p
ec
t
i
v
el
y,
whi
l
e
LS
I
t
e
and
OS
I
t
e
r
e
f
e
r to th
e
p
r
e-d
e
te
rmin
ed
max
i
mum it
er
at
io
n
nu
mbe
r
i
n
l
o
ca
l
and
o
v
e
r
al
l
se
a
r
ch
.
Fi
gu
re
3. The
fl
o
w
o
f
the
p
r
o
p
o
se
d SP
C
-
E
M
,
i
n
whic
h
D
re
prese
n
t
s
t
h
e pa
ra
me
te
r of
a
pa
rti
c
ul
a
r
di
men
s
i
o
n i
n
a
parti
c
ul
a
r
s
o
l
u
t
i
on
a
n
d
λ
de
not
es
the
si
ze
o
f
t
h
e
sea
r
ch
st
e
p
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J Po
w El
ec
&
Dr
i
S
y
st
IS
SN:
208
8-8
6
9
4
Opt
i
m
i
z
a
t
i
on
o
f
w
i
nd e
n
er
gy
c
onv
e
rsio
n
syst
e
m
s –
an
a
r
t
i
f
i
c
ial
i
n
te
l
l
i
g
ent
a
ppr
o
a
c
h
(Yi
n
g Y
i
ng
K
o
ay)
1
043
3.
M
A
X
I
MUM POWER
POI
N
T TR
AC
KIN
G
The
a
i
m
o
f
t
h
e
M
P
PT
sc
he
me
is
t
o
ma
ke
su
re
the
t
u
rbi
n
e
o
p
erat
es
to
p
u
s
h
t
h
e
ma
x
i
mu
m
o
u
t
put
p
o
w
e
r po
s
s
i
b
le
. In
th
is
r
e
search
,
t
h
e
en
h
a
n
ced
SP
C-
EM
is
p
r
op
ose
d
as
th
e
M
P
PT sch
e
me
of
a
W
E
C
S
. Th
e
pro
pose
d
i
m
pl
ement
a
ti
o
n
i
s
a
s
de
pic
t
ed i
n
F
i
gu
re
4.
An
adj
u
st
a
b
l
e
el
ect
ri
c
a
l
loa
d
is
adde
d t
o
c
o
ntrol
t
h
e
spee
d
of
the
tur
b
ine
whe
n
n
e
e
d
ed
. T
h
e
SP
C
-
EM
al
g
o
ri
th
m m
o
nit
o
rs
t
h
e p
o
we
r o
u
t
p
ut
a
n
d el
ect
roni
ca
l
l
y
c
o
n
t
r
o
ls t
h
e
du
mp l
o
a
d
b
y
a
d
j
u
stin
g th
e
pu
lse
-
w
i
d
t
h-
mod
u
l
at
or
(P
WM)
si
gn
a
l
,
wh
ic
h in t
u
rn
co
n
t
ro
l
s
th
e
spee
d
of t
h
e
t
u
rbi
n
e, e
n
s
u
ri
ng
t
h
e
ope
ra
ti
o
n
t
o
pro
duce
t
h
e maxi
m
u
m
p
o
ssi
bl
e o
u
tp
ut
po
we
r.
F
i
gu
re
4. The
pr
opose
d
i
m
pl
ement
a
ti
o
n
of SP
C
-
E
M
as
th
e
MP
PT sc
he
m
e
o
f
t
h
e
WEC
S
.
3.1.
A
l
go
r
i
t
h
m pe
rfo
r
ma
nc
e
t
e
sts
Si
mul
a
t
i
o
ns
are
carri
e
d
o
u
t
t
o
i
n
vest
i
g
at
e t
h
e p
e
r
f
o
r
ma
nc
e
of t
h
e
prop
o
s
ed
MPPT sc
h
e
me
u
nde
r
d
i
f
f
e
ren
t
w
i
nd
p
r
o
f
il
es.
I
n
th
e sim
u
la
tio
ns,
a WECS
w
i
t
h
30
0W
Per
m
an
e
n
t
M
a
gn
et
Sync
h
r
on
ou
s
G
e
n
e
r
a
to
rs
i
s
empl
oye
d
.
T
h
e rat
e
d wi
n
d
spee
d
is
se
t at
12
m/
s.
T
h
e
pe
rf
ormance
o
f
t
h
e pro
pose
d
S
P
C
-E
M
i
s
p
u
t
to
t
e
st
un
de
r t
h
ree
di
ffere
nt wi
nd
pr
ofi
l
e
s
si
m
u
la
te
d
i
n
di
vi
dua
ll
y
,
a
s
sh
o
w
n i
n
F
i
gu
re
5
.
T
h
e
n
, t
o
mi
mic
t
h
e e
v
er
cha
ngi
n
g
w
i
n
d
sp
e
e
d
in t
h
e re
al
wo
rl
d
a
ppl
i
c
at
i
on, t
h
e
si
mu
la
ti
on
o
f
t
h
e
wi
nd
c
h
a
nge
s
fro
m t
h
e
fir
s
t p
r
o
f
i
l
e
t
o
t
h
e sec
o
n
d
, a
nd
the
n
t
o
the
t
h
i
r
d, t
o
fu
rt
her
i
nve
sti
g
a
t
e
i
f
t
h
e p
r
op
ose
d
a
l
go
ri
thm
has t
h
e
a
b
i
l
i
t
y t
o
t
r
ac
k
fo
r
t
h
e MPP wit
h
chan
gi
n
g
wi
n
d
spe
e
d
s.
Fi
gu
re
5.
The
wi
n
d
profil
es
g
e
nerat
e
d
t
o
te
st
the
pro
pose
d
SP
C-E
M
.
Sim
u
la
tion
s
a
r
e c
o
n
d
u
c
te
d in V
B
.Ne
t
sof
t
wa
r
e
w
ith
In
te
l
1
.
6
G
H
z
Co
re i5
p
r
o
c
esso
r,
4G
RAM
and
6
4
-b
it
W
i
ndow
s 7
op
e
r
a
t
i
ng sy
s
t
em. Ten p
a
rt
icl
e
s
are
emp
l
oy
e
d
i
n
t
h
e
SP
C-EM
to tr
ac
k
fo
r t
h
e
M
PP.
To
fu
rt
he
r
st
ud
y
t
h
e im
pro
v
em
ent
ma
de
by
the
m
o
difie
d
a
l
go
rit
h
m, the
pe
rfo
rma
n
ce
o
f
t
h
e
S
P
C
-
EM
is
benc
hma
r
ked
wit
h
t
h
at
o
f
a c
onve
nti
o
na
l
EM. 3
0
i
n
d
i
v
i
dua
l
runs
a
r
e
c
ond
uc
te
d t
o
av
oi
d
st
oc
ha
st
i
c
di
sc
re
pa
nci
e
s
.
The
res
u
l
t
s
are prese
n
t
e
d
in t
h
e
f
o
ll
owi
n
g
c
h
a
p
t
e
r.
4.
R
E
S
U
LTS
AND ANA
LY
S
I
S
Th
e
ex
p
e
r
i
m
e
n
t
s a
r
e
co
nduc
te
d
by
te
sti
n
g
t
h
e p
e
rfor
m
a
n
c
e
of
t
h
e
alg
o
r
i
th
m
s
i
n
tra
c
k
i
n
g
t
h
e
maxi
mum
p
o
w
e
r poi
nt
i
n
t
h
e
si
mula
t
e
d
wi
n
d
p
r
ofi
l
es. T
h
e
resul
t
s
of t
h
e
30 i
ndi
vi
dua
l
runs
are
c
o
m
p
a
r
e
d
i
n
t
h
e for
m
s
of
b
e
st
sol
u
ti
o
n
s,
wo
rst
s
o
lut
i
o
n
s
, a
n
d a
v
era
g
e
solut
i
o
ns.
The
sta
nda
rd
de
vi
a
t
ions
of t
h
e g
a
the
r
e
d
Evaluation Warning : The document was created with Spire.PDF for Python.
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: 2
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I
n
t
J Po
w El
ec
&
Dr
i
S
y
st
, Vol.
11
,
No
.
2
,
Jun
e
2
020
: 10
40
–
1
0
46
1
044
r
e
s
u
lts
a
r
e
a
l
so
ca
lcu
l
a
t
e
d
.
Tab
l
e 1
sho
w
s
th
e
co
mp
a
r
ison
of
th
e r
e
su
lts in
3 r
e
s
p
ec
tiv
e
wi
nd pr
of
ile
s
. Th
e
hi
ghe
st a
v
e
r
a
g
e sol
u
t
i
ons
are
hi
g
h
l
i
ght
e
d
i
n
bol
dfac
e
.
It c
a
n be
o
b
se
rve
d
fro
m
Ta
b
l
e 1 t
h
at
t
h
e p
r
o
p
o
sed
S
P
C
-
EM fo
un
d
hig
h
e
r
out
pu
t
po
we
rs
, w
h
i
c
h
in
d
i
ca
te
s t
h
at
th
e
SP
C
-
EM
man
a
g
e
d to
h
i
t
so
lu
ti
on
s w
i
th
r
e
l
a
ti
v
e
l
y
h
i
g
h
e
r
a
ccur
a
c
i
e
s
.
It
is
als
o
w
o
r
t
h
not
ic
in
g t
h
e
l
a
rge
ga
p
bet
w
e
e
n
t
h
e
best
a
n
d w
o
rst
s
o
l
u
ti
o
n
s
ret
u
rned
by
t
h
e
c
o
n
v
e
n
t
i
ona
l
E
M
. T
h
is
i
n
co
nsist
e
nc
y
i
s
c
a
use
d
by
t
h
e
ra
nd
om st
e
p
s
empl
o
y
e
d
i
n
t
h
e
c
o
n
v
e
n
ti
o
n
al
EM, i
n
whi
c
h the
e
xpl
oi
t
a
t
i
on
of a
solut
i
o
n
c
a
n
not
be
g
u
ara
n
t
e
ed
.
Tabl
e 1.
C
o
mp
a
r
i
s
o
n
of the
s
o
l
u
ti
ons
o
b
t
a
i
n
e
d
a
f
t
e
r 30
in
di
v
i
d
u
a
l
ru
ns.
P
r
of
ile
1
P
r
of
ile
2
P
r
o
f
ile
3
SPC
-EM Be
st
Solut
i
on
200
400
300
Worst
S
o
lutio
n
199.
94
399.
9
299.
91
Av
er
a
g
e Sol
u
tion
199.
97
399.
92
299.
96
S
D
8.
26E-
0
8
2.
74E-
0
7
9.
33E
-08
E
M
Be
st
Solut
i
on
199.
97
399.
96
299.
95
Worst
S
o
lutio
n
196.
01
396.
82
295.
01
Av
er
a
g
e Sol
u
tion
198.
79
398.
09
297.
62
S
D
1.
25E+
0
0
1.
72E+
0
0
1.
64E
+00
The
c
o
n
v
e
r
ge
n
ce proc
esse
s o
f
the
si
m
u
la
ti
on
s are
sa
mpl
e
d
and
co
mpa
r
ed
. F
i
g
u
res
6 (a), (b
), a
nd (c
)
sho
w
t
h
e c
o
mpa
r
i
s
on
of t
h
e
c
o
n
v
erge
nc
e
pe
rfo
r
ma
nces
of t
h
e a
l
go
ri
t
h
ms
unde
r wi
n
d
p
r
o
f
il
e
1,
2
and
3
re
spe
c
t
i
v
el
y. S
e
vera
l
t
h
i
n
gs c
a
n
be
o
b
se
rve
d
from
t
h
e
pl
ot
s.
F
i
rst
,
t
h
e
S
P
C
-E
M ma
na
g
e
d t
o
hit
re
la
ti
vel
y
hi
ghe
r b
e
st
ou
t
put
p
o
we
r.
S
e
c
ondl
y
,
t
h
e
S
P
C
-E
M al
s
o
fou
n
d
t
h
e
fina
l
best
s
o
l
u
ti
o
n
s
rel
a
t
i
v
el
y
qui
cker
.
Obse
rve
t
h
e ra
pid
c
o
n
v
ersi
o
n
o
f
t
h
e S
P
C
-EM a
t
the
be
gi
n
n
in
g p
h
a
s
e
of t
h
e
c
o
n
v
e
r
ge
nce
pr
ocess
e
s. The
con
v
e
n
t
i
onal
E
M
, o
n
t
h
e
othe
r ha
n
d
, fou
n
d
t
h
e
best s
o
lut
i
o
n
s
i
n
rel
a
t
i
ve
l
y
l
a
t
e
r i
t
e
r
at
i
ons
.
It can be
obse
r
ve
d
t
h
a
t
the
prop
ose
d
S
P
C
-
E
M
per
f
o
r
me
d we
l
l
in
t
r
a
c
k
i
n
g
for the
ma
xi
mum
o
u
t
put
po
we
r u
n
d
er
d
i
ffe
re
nt
w
i
nd
profi
l
es.
A
d
o
p
t
i
ng t
h
e
a
d
v
a
nt
a
g
es o
f
q
u
i
c
k
e
r sea
r
c
h
a
nd
hi
g
h
er a
c
c
u
ra
c
i
es, t
h
e
aut
o
mat
i
c
a
l
l
y
a
d
j
u
st
e
d
se
a
r
c
h
st
eps
e
n
a
b
l
e
d
t
h
e S
P
C
-E
M
o
u
t
pe
rfo
r
m al
l
ot
her be
nc
hmar
k
i
ng al
go
ri
thm
s
.
(a
)
(b
)
(c
)
Fi
gu
re
6 (a),
(b
), a
n
d
(c
).
C
o
n
v
erge
nc
e a
n
al
y
s
i
s
of the
al
g
o
ri
t
h
ms
un
der di
f
f
ere
n
t
wi
nd
p
r
ofil
e
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J Po
w El
ec
&
Dr
i
S
y
st
IS
SN:
208
8-8
6
9
4
Opt
i
m
i
z
a
t
i
on
o
f
w
i
nd e
n
er
gy
c
onv
e
rsio
n
syst
e
m
s –
an
a
r
t
i
f
i
c
ial
i
n
te
l
l
i
g
ent
a
ppr
o
a
c
h
(Yi
n
g Y
i
ng
K
o
ay)
1
045
5.
CO
NCL
U
S
I
O
N
In
t
h
i
s
r
e
sear
c
h
,
a
n
S
P
C-
EM g
l
ob
a
l
op
tim
i
z
a
t
i
o
n
a
l
go
r
i
thm is pr
opo
sed
a
s
th
e
M
P
P
T
sc
h
e
m
e
of
a
mic
r
o
-
W
E
CS
.
The
SP
C-E
M
be
g
i
ns t
h
e
loc
a
l
se
arc
h
w
i
t
h
b
i
g st
eps
a
n
d
dy
na
mi
ca
l
l
y t
une
s the
st
e
p
si
ze
as t
h
e
search
m
ove
s
on
. E
x
p
e
rime
n
t
s and
si
mul
a
t
i
ons
are
car
ri
ed
o
u
t
to t
e
st
t
h
e
per
f
ormanc
e
of t
h
e
pro
pose
d
S
P
C
-
EM
i
n
t
r
ac
kin
g
the
maxi
mu
m
p
o
we
r poi
nt un
de
r di
ffe
r
e
n
t wi
nd
p
r
o
f
i
l
e
s. The res
u
l
t
s
i
ndi
ca
te
t
h
at
t
h
e
S
P
C
-
EM
sh
o
w
ed
si
gni
fi
ca
nt
i
m
p
r
o
v
eme
n
t
o
v
e
r
t
h
e
co
n
v
ent
i
on
a
l
E
M
i
n
t
h
e
be
nch
m
ark
i
ng.
It
ca
n t
h
us
be
conc
l
ude
d t
h
at
base
d o
n
t
h
e
s
i
mula
ti
ons
, t
h
e
SP
C
-
E
M
pe
rforms wel
l
as a
n
M
P
PT
sche
me
i
n
a mi
c
r
o
-
WECS
.
In t
i
m
e t
o
c
o
m
e
, t
h
e resea
r
ch
wil
l
move
on
t
o
t
e
st
t
h
e
SP
C-EM
i
n
an a
c
t
ual
WEC
S
.
Impl
eme
n
t
a
t
i
on
of t
h
e
SP
C-E
M
i
n
o
t
her
h
y
b
ri
d
re
ne
wa
bl
e
e
n
e
r
g
y
c
o
nve
rsio
n
syst
ems
i
s
a
l
s
o
w
o
rt
h e
x
pl
ori
n
g
i
n
t
h
e
fut
u
re
e
x
p
a
n
s
i
o
n of t
h
i
s
st
udy
.
A
C
KNOW
LE
D
G
E
M
EN
TS
Th
e au
thor
s
wo
u
l
d
lik
e to tha
n
k
U
n
i
v
e
r
s
i
ti
Te
n
a
g
a
N
a
s
i
ona
l (UNI
TEN
)
fo
r
t
h
e
fu
ll
su
pp
ort
o
f
th
i
s
r
e
s
e
a
r
c
h
un
d
e
r U
N
IIG
and
th
e B
O
LD
in
i
t
ia
tiv
e
.
RE
FERE
NC
E
S
[1]
Liang
R-H
an
d
Liao
J-H
,
"
A
fu
zzy-op
timization
app
r
o
ach
fo
r
g
e
n
e
rat
i
o
n
sc
he
du
li
ng
with wi
nd
a
nd so
la
r e
n
e
r
g
y
systems,"
IEEE
Tr
an
s Power
Sys
t
, vo
l.
2
2
,
16
65-
1
6
7
4
, 200
7
.
[2]
Niko
lo
va S
,
Cau
s
ev
sk
i A, an
d A
l
-S
alay
m
e
h
A
,
"
O
p
t
im
al
op
eratio
n of co
n
v
en
tio
n
a
l po
wer
pl
ants
in
pow
er
sys
t
e
m
with
in
teg
r
a
t
ed
ren
e
wab
l
e en
ergy
sou
r
ces,"
Ener
g
y
Co
nv
ers
Ma
na
g
; 65
: 6
9
7
–70
3.
20
13
[3]
Ba
n
s
a
l
M,
Kh
a
t
od DK,
a
nd Sa
in
i
RP
, "M
od
e
l
i
n
g
and
op
ti
miz
a
t
i
on
of in
te
gra
t
e
d
re
ne
wa
bl
e e
n
e
r
g
y
syste
m
fo
r a rural
site,"
Int
Conf
Re
li
ab Op
ti
m
In
f
Te
c
h
n
o
l
,
25
–8.
2
0
1
4
[4]
Bött
ger D, Götz
M,
Theo
f
i
lid
i
M
,
and
Bru
c
kn
er
T,
"
C
on
tro
l
po
wer pr
o
v
is
io
n wi
t
h
p
o
w
e
r
-
t
o-
h
e
at
pl
ants
in
s
y
st
e
m
s
wit
h
h
i
g
h
sha
r
e
s
o
f
re
n
e
wa
ble
en
e
r
gy
so
urc
e
s
– a
n
i
l
l
u
st
r
a
tiv
e
a
n
alys
is
for G
e
rman
y b
a
sed
on
the
use
o
f
ele
c
tr
ic
b
o
i
l
e
r
s
in
di
st
rict he
at
i
ng
g
r
i
d
s,"
Energy
,
v
o
l
.
8
2
,
pp.
15
7-1
6
7
,
20
15
.
[5]
Gh
os
h S
K
, S
h
a
w
on
M
H
, Rah
m
an A,
an
d
Nath
S
K
, "
W
in
d en
er
g
y
ass
e
ss
m
e
n
t
u
s
in
g weibu
l
l
d
i
s
t
ributio
n
in
co
ast
a
l
areas o
f
Ba
n
g
l
a
des
h
,"
In:
Pro
ceed
in
gs
of th
e 3rd
Intern
atio
na
l Con
f
er
e
n
c
e
on
Developm
en
tal Renewa
b
l
e Ener
gy
T
echn
o
lo
gy
, p
p
.
1
-
6,
20
14.
[6]
Jen
a
D
and Raj
e
n
d
ran
S
,
"
A
rev
i
ew o
f
es
tim
a
tio
n
of effe
ctiv
e win
d
speed
-bas
ed
c
ontrol of wind
t
u
rb
ines
,"
Renew
Su
stain En
erg
y
Rev
, v
o
l
.
4
3
, p
p
.
10
46
-6
2,
20
15.
[7]
Bu
e
h
ri
n
g
IK a
nd
Fre
r
i
s
LL
, "
C
on
tro
l
p
o
l
i
c
i
e
s
fo
r wi
nd
-e
ne
rg
y
c
o
nv
e
r
sio
n
sy
stem
s,
"
I
EE Pr
oc
C Gener
T
r
a
n
s
m
Distrib
,
v
o
l
.
12
8
,
p
p
.
25
3-2
61,
1
9
81
.
[8]
Ho
us
samo
I, L
o
cmen
t F
,
and
S
ech
ilariu
M
,
"
E
x
p
eri
m
ental
a
n
aly
s
is
o
f
i
m
pa
ct
o
f
M
P
P
T
m
e
thod
s
on
en
er
g
y
effic
i
ency
for
p
h
o
tov
o
lta
i
c po
wer
s
y
stems,"
I
n
t
J
Ele
ct
r P
o
w
e
r
En
erg
y
Sys
t
,
vol. 4
6
,
p
p
. 9
8
-1
07,
2
0
13
.
[9]
M
i
rb
agheri
S
Z
, M
e
k
h
ilef
S
,
an
d
M
i
rhas
san
i
S
M
,
"
M
P
P
T with
I
n
c.Cond
me
tho
d
using
co
nv
en
ti
on
al in
terleav
ed
bo
os
t co
nv
erter
,
"
En
erg
y
Pr
oce
d
i
a
,
vo
l.
4
2
,
24
-3
2,
20
13
.
[10]
B
e
n
d
i
b
B
,
B
e
l
m
i
l
i
H
,
a
n
d
K
r
i
m
F
,
"
A
s
u
r
v
e
y
o
f
t
h
e
mo
st us
ed M
P
P
T meth
o
d
s: Con
v
en
tion
al and
adv
a
n
c
e
d
alg
o
rith
ms
app
l
i
e
d fo
r
ph
otov
ol
taics
y
s
t
e
m
s,
"
Re
ne
w
Su
st
ai
n E
n
e
r
g
y
Re
v
, v
o
l
.
4
5
,
p
p
.
63
7-
48
, 2
0
1
5
.
[11]
Soetedjo A, Lomi
A,
a
n
d Mulaya
nt
o
WP, "
M
od
e
l
in
g o
f
win
d
ene
r
gy
sy
ste
m
with
MPPT
c
o
nt
ro
l
,
"
Int Conf Electr
En
g I
n
fo
rm
ati
c
s
,
p
p
. 1-
6, 20
11
.
[12]
Ramos
-
Paja CA
, S
aav
edra-M
on
tes
AJ
, an
d
Aran
g
o
E, "
M
ax
imu
m
po
wer
po
int
tr
acking
in
w
i
n
d
farms
b
y
mean
s
of
a mult
ivariabl
e
algori
thm,
"
Wo
rk E
n
g
Ap
pl
,
p
p
.
1-
6,
20
12
.
[13]
Aga
r
wa
l
V
a
nd Ag
ga
rwa
l
R,
"
A
no
ve
l sc
h
e
me
for
ra
pid
track
in
g
o
f
m
a
x
i
mum
p
o
we
r
po
int i
n
win
d
e
n
e
r
g
y
gen
e
ra
tio
n sys
t
e
m
s
,
"
IEEE T
r
an
s
En
erg
y
Con
ver
s
, v
o
l
.
2
5
, p
p
. 228-3
6
,
2
0
1
0
.
[14]
Kes
r
aoui M
,
Ko
richi
N,
and
B
e
l
k
adi A
,
"
M
axim
u
m
p
o
we
r
point
trac
k
e
r
o
f
wind
energ
y
co
nv
ersio
n
sy
stem,"
Re
ne
w
En
erg
y
, v
o
l. 3
6
,
p
p
.
26
55
-62,
2011
.
[15]
Ab
del-Sala
m M
,
Ahmed
A,
and
A
bdel-S
a
ter
M
,
"M
ax
imu
m
po
w
e
r p
o
int
tra
c
k
i
n
g
fo
r vari
abl
e
sp
e
e
d
grid
co
nne
cte
d
small wi
nd turb
ine,"
In
:
Proc
eed
in
gs
of
th
e
IEE
E
In
ter
nat
io
na
l
E
n
er
gy Co
nfer
enc
e
E
x
hibitio
n
,
pp
.
60
0-6
0
5
,
20
10
.
[16]
Na
hi
d-Al
-Ma
s
o
o
d
Ya
n R a
n
d
S
a
ha
T
K
,
"A ne
w t
o
o
l
t
o
e
s
t
i
m
a
te
m
a
xim
u
m win
d
p
o
we
r p
e
ne
t
r
ati
o
n
le
ve
l:
In
pers
pective
of fr
equ
e
ncy
resp
on
s
e
ad
eq
ua
cy
,"
A
ppl
E
n
e
r
g
y
,
v
o
l.
15
4,
pp.
2
0
9
-2
20, 2
0
1
5
.
[17]
Hi
chem H
,
"
A
Wi
nd
T
u
r
b
in
e
s
e
ns
or
les
s
Au
to
mati
c
C
o
nt
r
o
l S
y
stems
,
An
a
l
ys
is
, M
o
d
e
lli
ng
an
d d
e
velo
p
m
en
t
of
IDA
-
PB
C me
tho
d
,
"
In
tern
atio
na
l Jo
ur
nal o
f
Pow
e
r
El
e
c
troni
c
s a
n
d Dr
ive S
y
stem
, vo
l. 11
, no
.
1
,
20
20
.
[18]
Bou
r
eguig K, "
P
erformanc
e
En
han
cemen
ts
o
f
D
F
IG
Wind
Turbine Us
in
g
F
u
zzy
-
F
eedb
ack Line
a
rizatio
n
Co
nt
rol
l
e
r Aug
m
e
n
te
d
By
H
i
g
h
-Gain Observer,"
Intern
at
io
nal
Jour
na
l of
Po
wer
Ele
c
tro
n
ics
and
Drive Syst
em
(IJP
E
DS)
,
vo
l.
1
1
,
no
. 1
,
2
020
.
[19]
No
ur-Ed
d
ine
TA
RIBA
, Ah
m
e
d
H
a
dd
ou
,
N
a
im
a
Ikken
,
Ab
delh
a
d
i
Bo
ukn
adel
,
an
d Ham
i
d
El
O
m
a
r
i
,
"Co
m
para
tive
stu
d
y
of ne
w M
P
PT
c
o
nt
rol
a
pproa
c
h
e
s
fo
r a
p
hot
ov
ol
tai
c
sy
st
em
,
"
I
n
t
e
rn
at
io
na
l Jo
ur
na
l o
f
Pow
e
r
E
l
e
c
tr
on
i
c
s
a
n
d
Dr
ive S
y
st
em (I
J
P
EDS
)
,
vol
.
1
1
,
no
.
1,
20
20.
[20]
Da
il
i Y, Ga
ub
e
r
t J-P, a
n
d
Ra
h
m
a
n
i L
,
"Im
p
le
men
t
a
t
i
on of a n
e
w ma
x
i
m
u
m
p
o
we
r p
o
i
n
t tra
c
k
i
ng c
ont
rol st
ra
te
gy
fo
r sm
a
ll win
d
ene
r
gy
c
o
nve
rsi
on sy
st
e
m
s
wi
th
out
m
e
c
h
a
n
i
c
al
se
nsors,
"
En
ergy Con
vers
M
ana
g
,
vo
l.
97, pp.
2
98-
30
6, 20
15
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
: 2
088
-8
6
94
I
n
t
J Po
w El
ec
&
Dr
i
S
y
st
, Vol.
11
,
No
.
2
,
Jun
e
2
020
: 10
40
–
1
0
46
1
046
[21]
Wei
C,
Zhan
g
Z, Q
i
ao
W,
and
Qu
L, "
R
e
i
n
f
or
cem
ent
l
e
a
r
ni
ng-b
a
se
d
in
tel
l
i
g
e
n
t
m
a
x
i
m
u
m
po
we
r p
o
in
t
tra
c
ki
n
g
con
t
ro
l fo
r wind
energy
co
nvers
io
n s
y
s
t
ems,"
IE
E
E
Trans
Ind
E
l
ect
r
o
n
,
vo
l. 62
, pp
.
6
3
6
0
-63
7
0
,
2
015
.
[22]
Wu
P
.
T
,
Hun
g
Y.Y
,
and
Lin
Z.P
,
"
I
nt
elligen
t f
o
recast
i
n
g
sy
stem bas
e
d
on
in
te
g
r
ation
of
ele
c
tr
omagn
e
tism-like
mech
anism a
n
d fuzzy
n
e
ura
l
n
e
t
w
o
r
k
,
"
Exp
e
rt
S
y
s
t
em
s w
i
th
Ap
pli
c
at
io
ns
, v
o
l. 4
1
,
pp
.
26
60
-26
7
7
,
20
14
.
[23]
Tan
J.D, Dahari M,
K
oh
S
.
P
,
K
o
ay
Y.Y
,
an
d A
b
e
d
I.A, "A
nalys
i
s
of the Eff
e
c
t
o
f
S
earch S
t
ep S
i
ze
on
the A
ccu
racy
and
Con
v
erg
e
nc
e
P
r
o
p
erties of Ele
c
trom
agn
e
tism-Lik
e
Mech
ani
s
m
A
l
g
o
rithm
,
"
J.
o
f
M
u
lt.-
V
alu
e
d
L
ogic
& S
o
f
t
Com
putin
g
; vo
l.
2
8
,
pp.
42
9-4
41, 20
17
.
[24]
Ku
mar
D
an
d
C
h
att
e
rje
e
K, "
A
r
e
view
of
c
o
nv
en
tio
n
al
and
ad
van
ced
M
P
P
T
alg
o
r
ithms
for
wind
e
n
ergy
s
y
s
t
ems,"
R
e
ne
wa
ble
an
d
S
u
s
t
a
i
n
a
b
l
e
En
ergy
Re
v
i
e
w
s
,
vo
l. 5
5
,
95
7-97
0
,
2
0
16.
[25]
Ga
nj
e
f
a
r
S,
Gh
asse
m
i
AA,
a
n
d
Ah
m
a
di
MM,
"Im
p
rov
i
n
g
e
ffici
enc
y
of t
w
o
-
t
ype m
a
xim
u
m
po
w
e
r p
o
i
n
t tra
c
k
i
ng
meth
od
s of
tip-s
peed
rat
i
o
an
d o
p
t
imum
to
rqu
e
i
n
wind
turb
in
e
s
y
s
t
em us
in
g
a
q
u
a
ntu
m
neur
al
n
e
tw
ork
,
"
Energy
,
vo
l.
67
, pp
. 4
4
4
-
453
, 2
0
1
4
.
[26]
Bi
anchi FD, B
a
t
t
ista
HD,
and Mant
z RJ,
W
i
nd t
u
rbi
n
e
c
o
n
t
rol syst
e
m
s: p
r
in
c
i
ples,
mod
e
ll
in
g an
d ga
in sc
he
d
u
li
ng
des
i
g
n
. 1st
e
d
.
Lo
ndo
n: S
p
ring
er-V
erlag
;
2
0
0
7
.
[27]
T
a
na
ka
T a
n
d
Tou
m
iy
a
T,
"Out
pu
t c
o
n
t
rol b
y
h
i
l
l
-cl
i
m
b
i
ng m
e
th
od fo
r
a sma
l
l-sca
l
e
win
d
p
o
we
r g
e
n
e
rati
ng
system,"
Renew
Ener
gy
,
vol
.
1
2
,
387
-40
0
, 19
97
.
[28]
Datta
R an
d Ra
n
g
an
ath
a
n
V
T
, "
A
metho
d
of
tr
ack
in
g
the
pe
ak
p
o
wer po
in
ts
f
o
r
a
variab
le sp
eed wind
en
erg
y
con
v
ersion
s
y
ste
m
,"
I
E
EE T
r
ans
Energ
y
Con
vers
, v
o
l
.
1
8
, pp
. 16
3
-
1
6
8
,
20
03.
[29]
Bi
rbi
l
S.
I a
n
d
Fa
ng
S
.
C, "Ele
ctro
m
a
gne
t
i
sm-li
k
e
me
c
h
a
n
i
s
m
for
gl
oba
l op
ti
m
i
z
a
t
i
o
n
,
"
Jo
u
r
n
a
l
o
f
Gl
obal
Optimization
,
v
o
l
.
2
5
, p
p
.
26
3
-
282,
20
0
3
.
Evaluation Warning : The document was created with Spire.PDF for Python.