Internati
o
nal
Journal of P
o
wer Elect
roni
cs an
d
Drive
S
y
ste
m
(I
JPE
D
S)
Vol.
6, No. 4, Decem
ber
2015, pp. 888~
896
I
S
SN
: 208
8-8
6
9
4
8
88
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
Utlizati
o
n Cat Swarm Optimizati
on Al
gorithm for Selected
Harmonic Elemination in
Current
Source I
n
vert
er
Hame
d Hossei
nnia, Mor
t
ez
a Fars
adi
Department o
f
Electrical and Co
mputer E
ngin
eer
ing, Urm
i
a
Univ
ers
i
t
y
,
Urm
i
a,
Ir
an
Article Info
A
B
STRAC
T
Article histo
r
y:
Received
J
u
l 15, 2015
Rev
i
sed
O
c
t 19
, 20
15
Accepte
d Nov 5, 2015
The vol
tage
s
ource inv
e
rt
er (VS
I) and Curren
t
s
ource inv
e
rt
er (
C
S
I) are two
ty
p
e
s of tr
aditional power
in
verter
topolog
ies.In th
is paper selectiv
e
harmonic elimin
ation (SHE) Algorithm wa
s im
pe
lem
e
nted to CSI and results
has
been
inv
e
s
t
i
g
ated
. C
a
t s
w
ar
m
(CS
O
) optim
izat
ion is
a n
e
w
m
e
ta-heuris
t
ic
algorithm which
has been used in or
der to tuning switching parameters in
optim
ized
valu
e.Obje
ctiv
e fu
ction
is redu
ction of
tot
a
l
harm
oni
c
distortion(THD)
in inv
e
rters output
curr
ents.All of simulation has been
carri
ed ou
t in
M
a
tl
ab/Software
.
Keyword:
Current s
o
urce
inve
rter
Meta-h
eurestic alg
o
rith
m
Swi
t
c
hi
n
g
pa
ra
m
e
t
e
rs
t
uni
ng
Tot
a
l
ha
rm
oni
c di
st
o
r
t
i
o
n
Copyright ©
201
5 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
:
Ham
e
d Ho
ssei
nni
a,
Depa
rtem
ent of Electrical a
nd Co
m
p
u
t
er
Engin
eer
ing
,
Urm
i
a Un
iv
ersity,
Urm
i
a, Ira
n.
Em
a
il: Ha
m
e
d
.
Ho
sseinn
ia@gmail.co
m
1.
INTRODUCTION
There
are t
w
o types of tra
d
itional power i
nve
rter
t
o
pologies,
Vlotage
source i
nve
rter (VSI)
a
nd
Current s
o
urce
inve
rter
(CSI).T
h
e
voltage
source i
nve
rter produces a
s
p
ecified three-pha
se PWM
voltage
wave
form
for the loa
d
whi
l
e the curre
nt
source i
n
ve
rt
er outputs a
s
p
ecified three
-
pha
se PWM c
u
rrent
wav
e
fo
rm
. Fig
u
r
e
1
sh
ow th
e CSI .th
e
CSI
is ab
le to
inj
e
ct p
o
wer to
t
h
e g
r
id
witho
u
t
an
y add
itio
n
a
l
d
c
/d
c
con
v
e
r
t
e
r, but
l
o
w harm
oni
c i
s
m
a
jor pr
obl
em
i
n
t
h
i
s
ki
n
d
o
f
i
n
vert
e
r
and red
u
ct
i
o
n o
f
t
h
ese harm
oni
c
i
s
ob
ject
o
f
se
ve
ral
researc
h
e
r
s
wo
rk
.I
n a
ddi
t
i
onal
t
h
ese
ha
r
m
oni
cs l
i
m
i
t
e
d
appl
i
cat
i
o
ns o
f
C
S
I i
n
f
r
eq
u
e
ncy
dom
ai
n.C
S
I
d
e
ri
ves i
n
t
h
e
m
e
gawat
t
ran
g
e
are wi
del
y
use
d
i
n
t
h
e i
n
dust
r
y
[
1]
,[
2]
.T
he co
n
v
ent
i
on
al
t
h
ree
pha
se cur
r
e
n
t
sou
r
ce i
n
vert
e
r
has t
h
e def
e
c
t
of i
n
t
r
o
d
u
ci
n
g
i
n
crease
d
l
o
wer
or
der
har
m
oni
cs i
n
t
h
e
out
put
c
u
rr
e
n
t wh
i
c
h
g
i
v
e
r
i
s
e
in
to
lo
s
s
e
s a
n
d
to
rq
u
e
p
u
l
s
a
tio
n in th
e m
ach
in
e.Eli
m
in
atio
n
of l
o
w ord
e
r h
a
rmo
n
i
c is
so
im
p
o
r
tan
t
in CSIs to
av
o
i
d
p
o
s
sib
l
e resonan
ce b
e
t
w
een
t
h
e inp
u
t/ou
t
pu
t
filter cap
acitan
ce and
inpu
t/o
u
t
p
u
t
circu
it ind
u
c
tan
ce.
In t
h
i
s
pa
per
cur
r
ent
s
o
urce
i
nve
rt
er
has
been
i
nve
stiga
t
ed and Select
ed Ha
rm
onic Elim
ination
(SHE) switch
i
n
g
algorith
em
s
h
a
s b
e
en
i
m
p
e
le
m
e
n
t
ed
. Severa
l typ
e
s o
f
switch
i
ng
in
trod
u
c
ed
in
literatu
re are
in
trodu
ced
like: Trap
ezoi
d
al PW
M switching, Selective
Harm
oni
c Eli
m
in
atio
n
(SHE)
and Space
vector
M
o
d
u
lation
(S
VM
) [3]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
PED
S
I
S
SN
:
208
8-8
6
9
4
Utlization
Cat Swar
m Optim
ization (CSO)
Algorithm f
o
r
Se
lected
Har
m
onic .... (Hame
d
Hos
s
einnia)
88
9
Id
S1
S3
S5
S4
S6
S
2
A
B
C
Iw
P
N
Fi
gu
re
1.
C
o
nv
ent
i
onal
C
u
rre
nt
S
o
u
r
ce
In
ve
rt
er
(C
SI
)
Sel
ect
i
v
e ha
rm
oni
c el
i
m
i
n
at
i
on (
S
H
E
) i
s
a
m
e
t
hod t
o
el
i
m
i
n
at
e a num
ber o
f
l
o
w
-
o
r
de
r ha
rm
oni
c i
n
t
h
e i
nve
rt
er P
W
M
cur
r
e
n
t
.
I
t
i
s
a wel
l
-
kno
wn m
e
t
hod f
o
r
gene
rat
i
ng P
W
M
si
gnal
s
t
h
at
can el
im
i
n
at
e l
o
w
or
der
ha
rm
oni
c i
n
s
p
eci
fi
e
d
vol
t
a
ge
or c
u
r
r
ent
wa
vef
o
rm
[
4
]
.
O
n
e
o
f
e
a
sy
way
t
o
h
a
ve
qual
i
f
i
e
d
o
u
t
p
ut
wave
f
o
rm
i
s
t
h
at
el
im
i
n
at
e som
e
l
o
w ha
rm
oni
c.i
f
num
ber
of
pul
se
s pe
r h
a
l
f
cy
cl
e i
s
N
p;
the num
b
er of
angles
th
at i
m
p
l
e
m
en
ted
to h
a
rm
o
n
i
c eli
m
in
atio
n
is
ach
iv
ed
(1):
(1
)
For exam
ple
with fi
ve
pulses pe
r
half
cy
cle, there
are t
w
o indepe
nde
n
t angles,
ᆈ
1
an
d
ᆈ
2
.the t
w
o
swi
t
c
hi
n
g
an
gl
es pr
ovi
de t
w
o de
grees o
f
f
r
eed
om
whi
c
h can be used t
o
ei
t
h
er el
im
i
n
at
e t
w
o harm
oni
c i
n
cu
rren
t or vo
ltag
e
wav
e
fo
rm
.in
th
is p
a
p
e
r cu
rren
t sour
ce in
v
e
rter h
a
s b
e
en
u
tilized
[5
]. Th
e in
v
e
rter
PW
M
cur
r
ent
ca
n
ge
neral
l
y
be
ex
p
r
essed
(
2
):
1
(
)
sin(nwt)
n
n
iw
t
a
(2
)
/2
0
4
a(
)
s
i
n
(
)
(
)
n
iw
t
n
w
t
dw
t
The
fu
rrie
r
c
o
e
fficient a
n
ca
n be fo
u
n
d
f
r
om
(3
)
11
2
2
11
2
2
cos(
)
c
os(
(
))
c
o
s
(
)
c
os(
(
))
...
33
cos(
n
)
c
o
s(
(
)
cos(
),
j
4
36
cos(
)
c
os(
(
))
cos(
)
c
os(
(
))
...
33
c
o
s
(
)
c
os(n(
)
)
c
os(
)
,
j
e
v
en
36
jj
dc
n
jj
nn
n
n
n
n
odd
I
a
n
nn
n
n
nn
(3
)
To el
i
m
i
n
at
e j harm
oni
cs,
j
eq
uat
i
o
n
s
ca
n
be
fo
rm
ul
at
ed by
set
t
i
ng a
n
=0.
1
2
Np
j
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-86
94
I
J
PED
S
Vo
l.
6
,
No
.
4
,
D
ecem
b
er
2
015
:
88
8 – 896
89
0
2.
CAT
SW
AR
M O
P
TIMIZ
A
TIO
N
(
C
S
O
) AL
GO
RITH
M
Cat swarm
algo
rith
m
(CSO)
is b
a
sed
on
th
e b
e
h
a
v
i
o
r
o
f
cats
with
ex
cep
tio
n
a
lly v
i
go
ro
us
v
itality
of
cu
ri
o
s
ity to
ward m
o
v
i
n
g
obj
ects an
d
p
o
s
secin
g
goo
d
h
u
n
ting
sk
ills. Chu
an
d Tsai p
r
op
osed a n
e
w
opt
i
m
i
zati
on al
go
ri
t
h
m
t
h
at
im
i
t
a
t
e
s t
h
e nat
u
ral
beha
vi
o
r
of cat
s.
Eve
n
t
h
o
u
gh cat
s s
p
e
nd m
o
st
of t
h
e
i
r t
i
m
e
restin
g, th
ey always rem
a
in
alert an
d
m
o
ve v
e
ry sl
owly. Th
ese two
ch
aracterictics
o
f
restin
g
with
slow
m
ove
m
e
nt and chasing
with
high s
p
eed
represente
d by
se
eking and traci
ng, res
p
ectivel
y. In CSO, t
h
e
s
e two
m
odes of ope
r
a
t
i
ons are m
a
them
ati
cal
l
y
model
e
d fo
r sol
v
i
n
g com
p
l
e
x opt
i
m
i
zati
on p
r
o
b
l
e
m
s
. These
m
odes
are t
e
rm
ed t
h
e "seeki
n
g an
d
t
r
aci
ng" m
ode
s. A c
o
m
b
i
n
at
i
on
of t
h
e
s
e t
w
o m
odes al
l
o
wes C
S
O has
bet
t
e
r
per
f
o
r
m
a
nce.
Seeki
n
g m
ode has f
o
ur esse
nt
i
a
l
fact
ors:
see
k
i
n
g m
e
m
o
ry
po
ol
(SM
P
), se
eki
n
g ra
nge
of
t
h
e sel
ect
ed
di
m
e
nt
i
on (SR
D
), c
o
unt
s o
f
di
m
e
nt
i
on t
o
chan
ge (C
DC
),
and t
h
e sel
f
p
o
s
i
t
i
on co
nsi
d
e
r
at
i
on (S
PC
).
O
n
ce a
cats goes into tracing m
ode , i
t
m
oves accourding to its
own velocities for
every dim
e
nsions. Eve
r
y cat
has its
own position com
posed of D
dim
e
nti
onse
,
vel
o
cities for each
dim
e
nsi
o
n, a fit
n
ess
value re
prese
n
ti
ng t
h
e
accomm
odation of the cat to the be
nchm
ar
k functiona and a flag to identify we
ther the c
a
t is
in seeking
m
ode
or traci
ng m
o
de. These two
m
odes are dedicated to joi
n
with each
othe
r by mixt
ure ratio (MR). The final
p
o
s
ition
wo
u
l
d
b
e
t
h
e b
e
st p
o
sitio
n
o
f
on
e o
f
th
e
cats [6
].
The com
put
at
i
onal
p
r
oc
ed
ure
of t
h
e pr
o
p
o
s
ed o
p
t
i
m
i
zati
on al
go
ri
t
h
m
i
n
t
h
e form
of fl
owc
h
art
i
s
sho
w
n i
n
Fi
gu
r
e
2.
Whi
c
h
i
s
n
o
w
des
c
ri
be
d i
n
det
a
i
l
?
I.
Ran
d
o
m
ly
in
iti
alize th
e in
itial
set o
f
cats
o
f
size N
pop
,whe
re each cat is of dim
e
ntion D
, Xi={xi
1
,x
i
2
,…,
x
i
D
}
II.
Initialize the velocity of each cat,
i.e., the velocity of cat I in
the D-dim
e
ntional space as Vi= {Vi
1
,Vi
2
,…,
V
i
D
}.
II
I.
Ev
alu
a
te t
h
e
fitn
ess
o
f
each
cat an
d k
e
ep
t
h
e
p
o
s
ition
o
f
th
e
cat th
at h
a
s th
e h
i
g
e
st fitn
ess
v
a
lu
e.
IV.
Acco
r
d
i
n
g t
o
p
a
ram
e
t
e
r
m
i
xi
ng
rat
i
o
(M
R
)
, c
a
t
s
are
ran
d
o
m
l
y
di
st
ri
but
e
d
t
o
see
k
i
n
g a
n
d t
r
aci
n
g
m
odes.
V.
If cat
k i
s
i
n
se
eki
n
g m
ode t
h
en
a)
Create SMP-1
copies
of the
kt
h cat a
n
d re
tain
th
e p
r
esen
t p
o
sitio
n
as on
e
co
p
y
;
b)
For eac
h c
opy
according t
o
C
D
C,
random
l
y
select the dim
e
nsion t
o
be m
u
tated.
c)
For the
dim
e
nsion selecte
d
for each
copy,
ra
ndom
ly add or
subtract the
SRD pe
rce
n
t of
the prese
n
t
val
u
e;
d)
Calculate the fitness value
of all copies and repl
ace orgina
l cat k with the
copy havi
ng best
fitnes
s
val
u
e.
VI.
If cat
k i
s
i
n
t
r
a
c
i
ng m
ode
,t
he
n
a)
Up
dat
e
t
h
e
vel
o
ci
t
y
fo
r e
v
ery
di
m
e
nsi
on
of t
h
e
kt
h cat
:
1
()
;
j
jj
j
kk
k
vw
v
r
G
B
x
b)
Ch
eck if th
e v
e
lo
cities are in th
e
rang
e
o
f
m
a
x
i
m
u
m
v
e
lo
city; in
case th
e new
v
e
lo
city is
o
v
e
r
rang
e,
set it eq
u
a
l t
o
t
h
e m
a
x
i
m
u
m
li
mit
;
c)
Up
dat
e
t
h
e
p
o
s
i
t
i
on f
o
r
eve
r
y
di
m
e
nsi
on
of t
h
e
kt
h cat
:
11
x
j
jj
kk
k
x
v
d)
Co
n
s
t
r
ain
t
h
e
po
sitio
n of th
e cat so
t
h
at it do
esn
’
t ex
ceed
the li
m
i
ts o
f
i
n
terest;
e)
Evaluate the fi
tness of each c
a
t and store the positio
n of the cat that has th
e best fitness value and
com
p
are
the previous global
best v
a
lu
e with th
e cu
rren
t
b
e
st
v
a
lu
e accord
i
n
g
l
y;
f)
Check i
f
the m
a
xim
ux pre
-
s
p
ecified num
b
er of iteratio
ns is
reache
d
, whic
h is used a
s
the
termination
critiatio
n
,
if YES term
in
ate th
e
p
r
og
ram
,
else go
t
o
step.
Because the
im
portance
of
minimizing T
H
D val
u
e,
t
h
e
objective
function is
defi
ne
d as
below
(4)
[7]
:
(4
)
0
..
si
m
t
M
tT
H
D
d
t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
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S
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:
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8-8
6
9
4
Utlization
Cat Swar
m Optim
ization (CSO)
Algorithm f
o
r
Se
lected
Har
m
onic .... (Hame
d
Hos
s
einnia)
89
1
ST
A
R
T
Cre
a
t
e
N
Ca
t
s
I
n
it
ia
l
i
z
e
t
h
e
p
o
s
i
ti
o
n
,
v
e
lo
c
i
ti
e
s
a
n
d
th
e
f
l
a
g
o
f
ever
y
c
a
t
E
v
a
l
u
a
t
e
th
e
c
a
ts
a
c
c
o
r
d
in
g
t
o
th
e
f
i
t
n
e
s
s
f
u
nc
t
i
on
a
n
d
ke
e
p
t
h
e
po
s
i
t
i
o
n
of
t
h
e
c
a
t
,
w
h
i
c
h h
a
s
t
h
e bes
t
f
i
t
n
es
s
val
u
e
C
a
t K
is
i
n
th
e
s
e
e
k
in
g
m
o
d
e
?
A
p
pl
y C
a
t
K
i
n
t
o
t
r
a
c
i
ng
m
o
de
p
r
oc
e
s
s
Ap
p
l
y
Ca
t
K i
n
t
o
S
e
e
k
i
n
g
m
ode
P
r
oc
es
s
R
e
-P
ee
k
N
u
m
b
er
of
C
a
t
s
and s
e
t
t
h
em
i
n
t
o
t
r
ac
i
n
g m
o
de
ac
cor
d
i
n
g t
o
M
R
, a
n
d s
e
t
t
h
e ot
her
s
i
n
t
o
s
e
e
k
i
ng m
ode
NO
Ye
s
EN
D
Fig
u
re
2
.
Cat Swarm
Op
tim
iz
atio
n
(CSO)
Flo
w
ch
art
3.
TUNING SIMULATION
PARAMETERS
In t
h
i
s
pa
per
C
S
O al
g
o
ri
t
h
m
im
pl
em
ent
t
o
t
uni
ng
swi
t
chi
n
g pa
ram
e
ters t
o
m
i
nim
i
ze ob
ject
i
v
e
fu
nct
i
o
n.
O
b
je
ct
i
v
e f
unct
i
o
n
(O
F)
i
s
m
i
nim
i
zat
i
on of
t
o
t
a
l
harm
oni
c
di
st
ort
i
o
n
(T
H
D
).
F
o
r
exam
pl
e f
o
r
redu
ction
THD in
wav
e
fo
rm
with
N
p
=
5
, a
n
d t
o
el
im
i
n
at
e
5t
h a
nd
7t
h
har
m
oni
cs, t
h
e fol
l
owi
n
g t
w
o eq
uat
i
o
n
can be dri
v
e
(5);
11
2
2
11
2
2
3
c
o
s(5
)
c
o
s(5
(
))
c
o
s(5
)
c
o
s(5
(
))
0
33
2
3
co
s
(
7
)
co
s
(
7
(
))
co
s
(
7
)
co
s
(
7
(
)
)
0
33
2
(5
)
In
SH
E al
g
o
ri
t
h
m
m
i
nim
i
zed val
u
e
fo
r T
H
D
i
s
obt
i
o
ne
d
wi
t
h
t
u
ni
n
g
a
n
gl
es i
n
be
st
val
u
e.
I
n
Fi
gu
re
3
num
ber
of si
gn
al
s fo
r el
im
i
n
ati
ng t
w
o
harm
oni
c an
d i
t
s
m
a
n
n
er
has
been
s
h
o
w
n. I
n
Fi
gu
r
e
4 p
r
o
p
o
se
d w
a
y
t
o
g
e
n
e
rating
p
u
l
ses fo
r switch
e
s h
a
s b
e
en
illu
st
rated
[8
],[9
].
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.
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,
D
ecem
b
er
2
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:
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8 – 896
89
2
S1
S2
S3
S4
S5
π
Θ
1
Θ
2
π
/6
π
/3-
Θ
2
π
/3-
Θ
1
π
/2
Fi
gu
re
3.
S
w
i
t
c
hi
n
g
si
gnal
s
f
o
r
5 t
h
an
d
7 t
h
Harm
oni
c El
i
m
i
n
at
i
o
n
OR
Ga
te
An
d
Ga
te
S1
S2
NO
T
An
d
Ga
te
S3
S4
NO
T
S5
Pu
l
s
e
Ge
n
e
r
a
t
i
o
n
Fi
gu
re
4.
Pr
o
p
o
se
d M
e
t
h
od
f
o
r
p
u
l
s
e
gene
ratin
g
in Selective Harm
o
n
i
c Elimin
atio
n
3.
1.
Simula
ti
o
n
Results
Sim
u
l
a
t
i
on wa
s co
nd
uct
e
d wi
t
h
t
h
e c
o
nfi
g
u
r
at
i
on s
h
ow
n i
n
Fi
g
u
re
5.
T
h
e
sim
u
l
a
t
i
on pa
r
a
m
e
t
e
rs are:
I
d
c=6A
, C=40µF, L=1
0
m
H
,
R=1
0
Ω
. Th
e si
m
u
latio
n
resu
lts with
CSO are
sh
o
w
n i
n
Fi
gu
re
6. T
h
i
s
F
i
gu
re
i
n
cl
ude
d
of Li
ne t
o
Li
ne
v
o
l
t
a
ge an
d Loa
d
C
u
rre
nt
an
d
o
u
t
p
ut
cur
r
e
n
t
o
f
I
nve
rt
er (
I
w
)
.
In a
d
di
t
i
onal
FFT
analysis of
I
w
has b
een s
h
o
w
n i
n
Fi
g
u
r
e
7. T
h
i
s
fi
gu
re
pr
o
v
i
n
g C
S
O
al
go
ri
t
h
m
operat
i
on i
n
5
th
and 7
th
h
a
rm
o
n
i
c elimi
n
atio
n wit
h
SHE switch
i
n
g
meth
od
[10
]
,[11
]. Fo
r add
itio
n
a
l ex
am
p
l
e to
pro
v
e
CSO algo
rith
m
ope
rat
i
o
n t
h
i
s
m
e
t
od do
ne i
n
t
h
ree harm
oni
c el
im
i
n
at
i
on (
5
th
,7
th
,11
th
) and
resu
lts h
a
v
e
b
een
illu
strat
e
d
in
Fi
gu
re
8 a
n
d Fi
gu
re
9.
Evaluation Warning : The document was created with Spire.PDF for Python.
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6
9
4
Utlization
Cat Swar
m Optim
ization (CSO)
Algorithm f
o
r
Se
lected
Har
m
onic .... (Hame
d
Hos
s
einnia)
89
3
Id
S
١
S
٣
S
۵
S
۴
S
۶
S
٢
Iw
P
N
Fi
gu
re
5.
Si
m
u
l
a
t
e
d ci
rcuet
Fi
gu
re
6.
Si
m
u
l
a
t
i
on R
e
sul
t
s
f
o
r
Tw
o
Ha
rm
oni
c El
i
m
i
n
at
i
on
(5
t
h
,
7 t
h
),
Loa
d
C
u
rre
nt
(
I
s),
I
n
vert
er
o
u
t
put
Cu
rr
en
t(Iw
)
,
Lin
e
to
Lin
e
Vo
ltag
e
(V
)
Figure
7.
FFT
analysis of (
I
w
)
Evaluation Warning : The document was created with Spire.PDF for Python.
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S
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l.
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,
No
.
4
,
D
ecem
b
er
2
015
:
88
8 – 896
89
4
Fi
gu
re
8.
Si
m
u
l
a
t
i
on R
e
sul
t
s
f
o
r
Th
ree
Harm
oni
c
El
im
i
n
at
ion
(
5
t
h
,
7 t
h
,
1
1
t
h
).
A
.
I
nve
rt
er
out
put
C
u
r
r
e
n
t
(I
w)
b.
L
o
ad
C
u
r
r
ent
(I
s) C
.
L
i
ne t
o
Li
ne
V
o
l
t
a
ge (
V
)
Figure
9.
FFT
analysis of (
Iw
)
R
e
sul
t
s
t
h
at
h
a
s bee
n
ac
hi
ve
d f
o
r
el
im
i
n
at
e di
f
f
ere
n
t
ha
r
m
oni
cs by
im
pl
em
ent
i
on C
S
O wi
t
h
S
H
E
algorithm
,
be s
h
owe
d
.
These
angles
are
optimized
val
u
e
t
h
at
has
bee
n
ac
h
i
ved
wi
t
h
C
S
O
al
go
ri
t
h
m
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
PED
S
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S
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:
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8-8
6
9
4
Utlization
Cat Swar
m Optim
ization (CSO)
Algorithm f
o
r
Se
lected
Har
m
onic .... (Hame
d
Hos
s
einnia)
89
5
Tabl
e
1.
O
p
t
i
m
i
zed Val
u
e
fo
r
swi
t
c
hi
n
g
a
n
gl
e i
n
S
H
E
Al
go
ri
t
h
m
Har
m
onic to be
Eli
m
inated
Switching Angles
ᆈ
1
ᆈ
2
ᆈ
3
5 17.
15
-
-
7 20.
56
-
-
11
23.
75
-
-
13
25.
6
-
-
5,
7 7.
85
14.
2
-
5,
11
13
19.
5
-
5,
13
14.
75
22
-
7,
11
15.
21
19.
45
-
7,
13
16.
23
21
5,
7,
11
2.
42
5.
8
21.
43
7,
11,
13
9.
6
11.
72
24.
13
5,
11,
13
7.
62
10.
82
23.
4
4.
CO
NCL
USI
O
N
As sim
u
latio
n
resu
lt sh
owed
,
b
y
tun
i
ng
selected
ang
l
es in
op
timized
v
a
lu
e, THD
of th
e
o
u
t
p
u
t
cu
rren
t is b
e
tter th
en
arb
itariry ch
o
s
en
v
a
lu
es an
d
qu
ality
o
f
CSI ou
tpu
t
is i
m
p
r
ov
ed.th
i
s v
e
rifies effectiv
en
ess
o
f
th
e Selected Harm
o
n
i
c Elimin
atio
n
(SHE)
with
Ca
t
Swarm
Op
ti
m
i
zat
io
n (CSO).
C
S
O ca
n
be
ap
pl
i
e
d t
o
an
y p
r
ob
lem
w
h
ere
o
p
tim
izat
i
o
n
is
requ
ired
.t
h
e
refore it
can
be ap
pl
i
e
d i
n
m
a
ny
us
age in
powe
r electronic and
p
o
wer m
a
rk
etin
g.th
e co
m
p
aratio
n
of th
e
resu
lts in
th
is
p
a
per with
sim
ilar
work
in
o
t
h
e
r
literatu
re show CSO
alg
o
rith
m
b
e
fit fo
r
op
ti
m
i
zati
o
n issu
es [12
]-[15
].
REFERE
NC
ES
[1]
Mitsu
y
uki H, et al. "A New Cu
rrent Source GTO Inve
rter with Sinusoidal Output Voltage and
Current",
IE
EE
Transactions on
Indus
trial Electronics
, vo
l. 21, p
p
. 1192-1198
, 1
985.
[2]
DEEPAC Ku
mar,
Zakir Husain,
"Estim
ation of Harm
onics
in Three-P
h
as
e and
S
i
x-P
h
as
e Load Circuits
",
IJPEDS,
vol/issue:
5(2), p
p
. 142-152
, 201
4.
[3]
Kwack S
., et a
l
.
,
"An Integrated
Current S
ource I
nvert
er with Re
a
c
tiv
e and Harm
onic P
o
wer Com
p
ens
a
tors
",
IEEE
Tractions on Po
we
r
El
ectr
oni
cs
,
vol/issue: 24(2), 2009.
[4]
AM. Trz
y
n
a
dlo
w
ski, N. Patrici
u
, F. Blaabj
e
rg,
JK. Pe
dersen, “A hy
brid
, Current
-source/voltage-source power
invert
er circu
it”
,
IEE
E
T
r
ans. Po
wer El
ectron
, vo
l/issue: 16
(6), pp
. 866–871
, 2001
.
[5]
Jose R., Espin
o
za, Geza Joos, J
ohan I Guzman, Luis AMoran, Rola
ndo
P. Burgos, “S
elective Harmonic
Elimination
an
d curren
t/voltag
e
con
t
rol
in curre
nt/vo
ltag
e
-source topologies
: A unified approach”,
IE
EE
Transactions on
indus
try electronics,
2001
.
[6]
Kusum
a
latha Y., Obulesh Y., "
H
arm
oni
cs Miti
gation of
Indust
r
ial Moto
r Dr
iv
es with Active
Power Filters in
Cement Plan
t-A
Case Stud
y
"
,
IJ
PEDS
, vo
l/issue: 2(1), pp. 1-8, 20
12.
[7]
Durgasukum
ar
G., MK. Pathak, “THD Reductio
n Perform
ance
of Multi-Lev
e
l Inverter fed Induct
i
on Motor Drive”,
presented
at th
e
India In
tern
ation
a
l Conf
er
en
ce o
n
Power Electro
n
ics (IICPE)
,
20
11.
[8]
Orouskhani M., Mansouri M., Teshnehlab
M., “Average-In
ertia weighted Cat
swarm
optim
izatio
n”, LNCS, Berl
i
n
Heidelb
e
rg: Springer-Verlag
,
pp
. 321– 328
, 2011
.
[9]
J
o
s
é
R. Es
pinoza, et a
l
, "S
ele
c
ti
ve
Harmonic Elimination and Current/Voltage
Control in Curre
nt/Voltag
e
-Sour
ce
Topologies: A U
n
ified
Approach
",
IEEE Transactions on I
ndustrial Electronics,
v
o
l/issue: 4
8
(1), 2
001.
[10]
Abdul Rahiman
Beig, Rangan
a
th
an V., "A
Novel CSI-Fed Induction Motor Driv
e",
IEEE Transactions on
Power
Electronics
, vol/issue: 21(4), pp.
45-49, 2006
.
[11]
Delli Co
lli
V.,
C
a
nce
lli
eve P
., M
a
rigne
tti
F., R
.
Di Stefan
o
,
"Infl
u
ence
of Volt
ag
e and
Current
Source Inv
e
rt
ers
on
Low-power Indu
ction
motors",
I
EEE
Proc-E
le
ctr
i
cal
Power
Appl
., vol/issue: 152(
5), pp
. 1311-132
0, 2005
.
[12]
Hamed, Hosseinnia,
et
al, "Simple Boost Control
Method Optimized
with
Geneti
c Algorithm for Z-Sour
ce
Inverter"
,
J
E
PECS
, vol/issue: 1
(
1), pp
. 32-36
, 20
13.
[13]
Karshenas H.
,
K
o
jori H.
, Dewa
n
S
., “
G
enera
lis
e
d
techn
i
que of s
e
le
ctiv
e harm
oni
c el
im
ination
an
d current
contro
l
in Current Source Inv
e
rter
/Con
verter
”,
I
E
EE tr
ansactions on Power Electronics
, vol/issue: 10(
5), pp. 566
-573,
1995.
[14]
Vázquez N., Ló
pez H., Hern
án
dez C
., Rodr
ígu
ez E., Oros
co
R., Arau
J., "A Grid Connected Current Source
Inverter"
,
I
EEE I
n
ternational
conf
erence on
Clean
Electrical Power
,
pp
. 439
442, 20
09.
[15]
SC. Chu, PW.
Tsai, JS. Pan,
“Cat
swarm opt
imization
”
, in P
R
ICAI 2006:
Trends in Artificial Intelligence,
Springer, pp
. 85
4–858, 2006
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-86
94
I
J
PED
S
Vo
l.
6
,
No
.
4
,
D
ecem
b
er
2
015
:
88
8 – 896
89
6
BIOGRAP
HI
ES
OF AUTH
ORS
Hamed Hosseinnia
was born in Kho
y
, Ir
an in june1988.He r
e
ceived His B.Sc
degree
in Azarb
a
y
j
an
Shahid Madani
university
.
Tabr
iz.
Iran and M.S
c
desgrees(With
honor) in Urmi
a University
, Bo
th in
Electrical Eng
i
n
eering
in 2010
a
nd 2013
res
p
ectively
.
H
e
is curren
t
ly
Phd
student in
Electrical
Engineering at
Urmia University
with fo
cused
on
Optim
izat
ion
and Power s
y
st
em
. His inter
e
sti
ng i
s
FACTS, Power Ele
c
troni
c,
Micr
ogrid Opera
tio
n
and planning
an
d Advanced
pow
er s
y
s
t
em.
Mu
rtaz
a Fars
ad
i
was born in
Kho
y
, Iran
in
September 195
7.
He r
e
ceived
his B.Sc. degr
ee in
Ele
c
tri
cal
Engin
eering
,
M
.
S
c
. d
e
gree in
Ele
c
tri
cal
and Electron
ics Engineer
ing
and Ph.D. degree in
Ele
c
tri
cal
Eng
i
n
eering
(High V
o
ltag
e
) from
M
i
ddle
Eas
t
T
ech
nica
l Univers
i
t
y
(M
ETU),
Ankara,
Turkey
in 1982
, 1984 and 198
9, respectively
.
He is
now an assistant professor in the Electr
ical
Engineering Department of Urmia
Univers
i
t
y
,
Urm
i
a, Iran. Hi
s
m
a
in res
earch
interes
t
s
are
in
high
voltag
e
engin
e
ering, industr
ial
power s
y
stem
s
t
udies and
FACTS, HVDC transmission sy
stems,
DC/AC active
power filters, r
e
newabl
e energ
y
, h
y
br
id and ele
c
tri
cal Veh
i
c
l
es, and new c
ontrol
methods.
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