T
E
L
KO
M
N
I
KA
T
e
lec
om
m
u
n
icat
ion
,
Com
p
u
t
i
n
g,
E
lec
t
r
on
ics
an
d
Cont
r
ol
Vol.
18
,
No.
1
,
F
e
br
ua
r
y
2020
,
pp.
45
6
~
46
4
I
S
S
N:
1693
-
6930,
a
c
c
r
e
dit
e
d
F
ir
s
t
G
r
a
de
by
Ke
me
n
r
is
tekdikti
,
De
c
r
e
e
No:
21/E
/KP
T
/2018
DO
I
:
10.
12928/
T
E
L
KO
M
NI
KA
.
v18i1.
11887
456
Jou
r
n
al
h
omepage
:
ht
tp:
//
jour
nal.
uad
.
ac
.
id/
index
.
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E
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OM
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p
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ac
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an
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am
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k
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h
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Mo
ro
cc
o
Ar
t
icle
I
n
f
o
AB
S
T
RA
CT
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r
ti
c
le
h
is
tor
y
:
R
e
c
e
ived
Nov
24
,
201
8
R
e
vis
e
d
Aug
7
,
20
19
Ac
c
e
pted
Aug
28
,
20
19
T
h
i
s
p
a
p
er
u
s
e
s
a
n
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l
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p
t
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met
h
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as
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h
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ack
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rack
i
n
g
s
earch
o
p
t
i
mi
za
t
i
o
n
a
l
g
o
ri
t
h
m
(IBSA
).
T
h
e
s
t
u
d
y
i
s
co
n
d
u
c
t
ed
fo
r
a
h
y
b
ri
d
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t
a
n
d
-
a
l
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n
e
s
y
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em
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o
s
ed
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f
p
h
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t
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l
t
ai
c
p
an
e
l
(PV
),
w
i
n
d
t
u
r
b
i
n
e
g
en
era
t
o
r
an
d
fu
el
ce
l
l
el
ec
t
ro
l
y
zer
(FC
).
T
o
d
emo
n
s
t
r
at
e
t
h
e
effec
t
i
v
en
e
s
s
o
f
t
h
e
IBS
A
,
fo
u
r
b
e
n
ch
mar
k
fu
n
ct
i
o
n
s
are
u
s
ed
.
T
h
e
re
s
u
l
t
s
h
o
w
s
t
h
e
b
e
t
t
er
e
x
p
l
o
ra
t
i
o
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an
d
ex
p
l
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t
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i
o
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o
f
t
h
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mp
ro
v
ed
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ac
k
t
rac
k
i
n
g
s
earch
o
p
t
i
m
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zat
i
o
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al
g
o
ri
t
h
m
i
n
t
erms
o
f
co
n
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erg
e
n
ce
an
d
s
p
ee
d
fo
r
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y
s
t
em
co
mp
r
i
n
s
i
n
g
PV
p
a
n
el
w
i
n
d
,
t
u
r
b
i
n
e
g
en
era
t
o
r
an
d
fu
e
l
cel
l
.
T
h
e
p
ro
p
o
s
ed
al
g
o
ri
t
h
m
i
s
u
s
e
d
t
o
o
p
t
i
mi
ze
t
h
e
an
n
u
a
l
t
o
t
al
co
s
t
(
A
T
C)
o
f
t
h
e
en
erg
y
p
ro
d
u
ce
d
an
d
fee
d
u
p
t
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e
l
o
a
d
d
ema
n
d
.
T
h
e
eco
n
o
mi
c
ev
a
l
u
a
t
i
o
n
o
f
t
h
e
H
y
b
r
i
d
PV
/
W
i
n
d
/
FC
s
y
s
t
em
i
s
d
o
n
e
t
h
r
o
u
g
h
o
u
t
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rl
y
d
ema
n
d
an
d
d
ai
l
y
w
i
n
d
s
p
ee
d
an
d
i
n
s
u
l
at
i
o
n
.
T
h
e
s
i
mu
l
at
i
o
n
re
s
u
l
t
s
j
u
s
t
i
fy
t
h
e
r
o
b
u
s
t
n
e
s
s
o
f
t
h
e
IBSA
.
K
e
y
w
o
r
d
s
:
F
ue
l
c
e
ll
I
B
S
A
O
pti
mi
z
a
ti
on
P
hotovol
taic
pa
ne
l
W
ind
tur
bine
Th
i
s
i
s
a
n
o
p
en
a
c
ces
s
a
r
t
i
c
l
e
u
n
d
e
r
t
h
e
CC
B
Y
-
SA
l
i
ce
n
s
e
.
C
or
r
e
s
pon
din
g
A
u
th
or
:
J
ihane
Ka
r
ti
te
,
M
oha
mm
e
d
V
Unive
r
s
it
y
in
R
a
ba
t,
Agda
l
R
a
ba
t,
M
or
oc
c
o
.
E
mail:
ka
r
t
it
e
.
ji
ha
ne
@gmail.
c
om
1.
I
NT
RODU
C
T
I
ON
T
he
de
pletion
of
f
os
s
il
f
ue
ls
a
nd
the
incr
e
a
s
ing
e
ne
r
gy
de
mand
ove
r
the
wor
ld,
a
bout
55%
by
2035
[
1]
,
a
r
e
br
ought
mo
r
e
a
tt
e
nti
on
to
g
r
e
e
n
e
ne
r
gy.
T
he
pr
oduc
t
ion
of
e
lec
tr
icity
f
r
om
c
onve
nti
ona
l
s
our
c
e
s
a
f
f
e
c
ts
e
nvir
onment
ba
lanc
e
a
nd
c
a
us
e
s
poll
uti
on
.
T
his
poll
uti
on
a
f
f
e
c
ts
li
f
e
s
a
nd
a
nim
a
ls
.
T
he
powe
r
pr
oduc
e
d
f
r
om
f
os
s
il
f
ue
ls
gives
of
f
ha
r
mf
ul
ga
z
e
s
s
uc
h
a
s
o
xides
of
c
a
r
bon.
T
he
s
e
ga
z
e
s
c
ontr
ibut
e
to
global
wa
r
mi
ng.
L
im
it
e
d
r
e
s
e
r
ve
s
of
f
ue
ls
a
nd
their
uns
table
c
o
s
ts
a
r
e
the
mos
t
im
por
tant
r
e
a
s
ons
f
or
r
e
ne
wa
ble
e
ne
r
gy.
T
he
incr
e
a
s
ing
c
onc
e
r
n
a
bout
e
nvi
r
onmenta
l
poll
ut
ion
a
nd
the
im
pa
c
t
of
tr
a
dit
ional
s
our
c
e
s
ha
s
e
mphas
ize
s
a
ll
c
ou
ntr
ies
f
or
r
e
duc
ing
their
e
mi
s
s
ion.
R
e
ne
wa
ble
e
ne
r
gy
s
our
c
e
s
s
e
e
m
to
be
the
be
s
t
s
olut
ion
f
or
a
s
us
taina
ble
e
lec
tr
if
ica
ti
on.
W
e
c
a
n
ha
ve
the
e
lec
tr
icity
di
r
e
c
tl
y
f
r
om
s
unli
ght
v
ia
P
V
pa
ne
l.
S
olar
e
ne
r
gy
is
one
o
f
t
he
mos
t
pr
omi
s
ing
r
e
ne
wa
ble
e
ne
r
gy
tec
hnol
ogies
:
it
is
c
lea
n
a
nd
a
bunda
nc
e
.
How
e
ve
r
,
the
int
e
r
m
it
tent
na
tur
e
of
thes
e
types
of
e
ne
r
gy
make
s
the
e
ne
r
gy
p
r
oduc
e
d
f
r
o
m
one
r
e
ne
wa
ble
s
our
c
e
unr
e
li
a
ble
[
2,
3]
.
C
oupli
ng
P
V
pa
ne
l
with
a
nother
s
our
c
e
o
f
e
ne
r
gy
s
uc
h
a
s
wind
tur
bine
ge
ne
r
a
tor
c
a
n
r
e
duc
e
s
ig
nif
ica
ntl
y
the
int
e
r
mi
tt
e
nc
e
is
s
ue
.
T
he
e
lec
tr
ic
Hybr
id
r
e
ne
wa
ble
e
ne
r
gy
s
ys
tem
is
l
e
s
s
c
os
tl
y
a
nd
mor
e
r
e
li
a
ble
than
s
ys
tem
with
one
s
our
c
e
[
4,
5
]
.
De
s
igni
ng
a
hyb
r
id
r
e
ne
wa
ble
e
ne
r
gy
s
ys
tem
is
a
dif
f
icult
tas
k,
the
s
izing
o
r
the
nu
mber
of
e
leme
nt
a
nd
the
us
e
d
c
ontr
ol
s
tr
a
tegy
is
ve
r
y
e
s
s
e
nti
a
l,
the
pe
r
f
or
manc
e
of
the
P
V/W
ind/
F
ue
l
c
e
ll
s
ys
tem
c
a
n
be
s
igni
f
ica
ntl
y
inf
luenc
e
d
by
the
pr
opos
e
d
c
ontr
ol
s
tr
a
tegy.
W
ind
tur
bi
ne
ge
ne
r
a
tor
a
nd
P
V
pa
n
e
l
mi
ght
ope
r
a
te
in
the
wa
y
that
they
c
a
n
g
ive
the
maximum
powe
r
to
a
c
hieve
a
high
e
f
f
icie
nc
y
va
lue
[
6]
.
I
n
th
i
s
s
tudy,
the
photovol
taic
(
P
V)
pa
ne
l
a
nd
the
wind
tu
r
bine
ge
ne
r
a
tor
a
r
e
us
e
d
a
s
the
main
s
our
c
e
f
or
the
load
de
mand.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
I
mpr
ov
e
d
bac
k
tr
ac
k
ing
s
e
a
r
c
h
opti
miz
ati
on
algor
it
hm
for
P
V
/W
ind/
F
C
s
y
s
tem
(
J
ihane
K
ar
ti
te)
457
the
f
ue
l
c
e
ll
(
F
C
)
e
lec
tr
olyze
r
is
r
e
qui
r
e
d
a
s
a
s
tor
a
ge
c
a
pa
c
it
y.
T
he
photovo
lt
a
ic
pa
ne
l
(
P
V)
tec
hnolo
gy
is
s
e
e
n
a
s
the
e
a
s
ies
t
r
e
ne
wa
ble
s
our
c
e
due
to
s
e
ve
r
a
l
r
e
a
s
o
ns
:
T
he
s
tudy
of
a
hybr
id
r
e
ne
wa
ble
e
ne
r
gy
s
ys
tem
(
HR
E
S
)
c
oupled
with
hy
dr
oge
n
e
ne
r
gy
is
be
c
a
me
a
n
a
r
e
a
o
f
int
e
r
e
s
t
[
7]
.
T
he
tr
a
dit
ional
s
tor
a
ge
with
c
he
mi
c
a
l
ba
tt
e
r
ies
pr
o
vides
high
di
s
c
ha
r
ging
e
f
f
icie
nc
y
a
nd
high
e
ne
r
gy
s
tor
a
ge
c
a
pa
c
it
y
[
8]
.
T
his
s
ys
tem
pr
ovides
a
n
im
p
r
ove
ment
to
ove
r
c
ome
s
ome
dr
a
wba
c
ks
of
R
E
S
e
s
pe
c
ially
the
int
e
r
mi
tt
e
nc
e
pr
oblem:
the
e
ne
r
gy
s
tor
a
ge
s
ys
tems
a
r
e
a
ble
to
f
e
e
d
load
de
mand
o
r
c
ons
ume
the
pr
oduc
e
d
e
ne
r
gy
f
r
om
r
e
ne
wa
ble
s
our
c
e
s
.
D
ies
e
l
ge
ne
r
a
tor
s
or
f
ue
l
c
e
ll
s
s
e
e
ms
ne
c
e
s
s
a
r
y
in
hybr
id
r
e
ne
wa
ble
e
n
e
r
gy
s
ys
tems
(
HR
E
S
)
by
s
upplyi
ng
the
load
de
mand
whe
n
the
s
tor
a
ge
f
a
c
il
it
ies
a
r
e
e
na
ble
or
e
mpt
y.
T
he
pa
pe
r
pr
e
s
e
nts
I
B
S
A
(
im
pr
ove
d
ba
c
ktr
a
c
king
s
e
a
r
c
h
a
lgor
it
hm
)
t
o
opti
mi
z
e
th
e
a
nnua
l
tot
a
l
c
os
t
(
AT
C
)
f
o
r
photovol
taic
ge
ne
r
a
tor
,
wind
tu
r
bine
ge
ne
r
a
tor
a
nd
f
ue
l
c
e
ll
s
ys
tem
.
2.
HYB
RI
D
RE
NE
W
AB
L
E
E
NE
RGY
S
YST
E
M
P
RE
S
E
NT
AT
I
ON
T
he
s
ys
tem
us
e
d
in
th
is
pa
pe
r
is
a
mul
ti
s
our
c
e
s
ys
tem
c
ompos
e
d
of
hyb
r
id
r
e
ne
wa
ble
e
ne
r
gy
s
our
c
e
s
ys
tem
ba
s
e
d
on
photovol
taic
pa
ne
l,
wind
tu
r
bine
g
e
ne
r
a
tor
a
nd
f
ue
l
c
e
ll
s
e
lec
tr
olyze
r
[
9]
.
T
he
s
tor
a
ge
f
a
c
il
it
ies
a
r
e
us
e
d
to
s
moot
h
out
the
r
e
ne
wa
ble
e
ne
r
gy
f
lu
c
tuation.
B
e
s
ides
,
s
tor
ing
e
lec
tr
icity
in
lar
ge
s
c
a
le
dur
ing
of
f
-
pe
a
k
hour
s
r
e
duc
e
s
igni
f
ica
ntl
y
the
de
pe
nde
nc
e
of
f
os
s
il
e
ne
r
gy
dur
ing
pe
a
k
de
mand.
2.
1.
P
h
ot
ovolt
a
ic
(
P
V)
p
an
e
l
m
od
e
l
T
o
de
ter
mi
ne
the
powe
r
output
f
or
P
V
pa
ne
l
,
tw
o
models
a
r
e
pos
s
ibl
e
:
the
pr
oba
bil
is
ti
c
one
a
nd
the
de
ter
mi
nis
ti
c
one
.
B
oth
a
r
e
ba
s
e
d
on
c
li
matic
da
ta.
I
n
thi
s
s
tudy
we
us
e
the
de
te
r
mi
nis
ti
c
model
to
de
f
ine
the
P
V
powe
r
.
T
he
e
lec
tr
ic
powe
r
is
de
ter
mi
ne
d
d
ir
e
c
tl
y
f
r
om
the
nomi
na
l
powe
r
of
the
P
V
c
e
ll
.
T
his
powe
r
is
inj
e
c
ted
dir
e
c
tl
y
in
the
DC
bus
:
=
∙
co
s
(
1)
w
he
r
e
E
dir
c
is
the
di
r
e
c
t
s
unli
ght
r
e
c
e
ived
by
the
c
oll
e
c
tor
,
θi
s
the
inclination
a
ngle.
=
∙
(
1
+
c
os
2
)
(
2)
E
dif
c
is
the
dif
f
us
e
s
unli
ght
r
e
c
e
ived
by
the
c
oll
e
c
t
or
.
=
(
+
)
∙
(
3)
P
pvc
is
the
nomi
na
l
powe
r
o
f
P
V
pa
ne
l
a
nd
E
n
is
t
he
ins
olation
in
s
tanda
r
d
c
ondit
ions
.
co
s
=
co
s
∙
co
s
(
,
)
+
s
in
Σ
∙
s
in
∙
co
s
Σ
(
4)
β
is
the
a
lt
it
ude
o
f
the
s
un
,
ϕs
is
the
a
z
im
uth
,
ϕc
is
the
c
oll
e
c
tor
a
z
im
uth
a
nd
∑
is
the
inclination
a
ngle
of
the
s
olar
c
oll
e
c
tor
.
s
in
=
co
s
∙
co
s
∙
co
s
+
s
in
∙
s
in
(
5)
L
is
the
latit
ude
of
the
loca
ti
on
,
δ
is
the
s
olar
de
c
li
na
ti
on
a
nd
H
is
the
hour
a
ng
le.
s
in
=
c
os
∙
s
i
n
c
os
(
6)
2.
2.
Win
d
t
u
r
b
in
e
m
o
d
e
l
W
ind
tur
bines
us
e
the
kinetic
e
ne
r
gy
of
wind
s
pe
e
d
.
I
n
th
is
pa
pe
r
the
powe
r
de
li
ve
r
e
d
by
wind
tu
r
bine
ge
ne
r
a
tor
is
modele
d
a
c
c
or
ding
to
wind
s
pe
e
d,
a
s
we
c
a
n
s
e
e
in
F
igu
r
e
1
.
T
he
powe
r
o
utput
of
the
wind
tur
bine
ge
ne
r
a
tor
is
ba
s
e
d
on
wind
s
pe
e
d.
I
t
is
e
xp
r
e
s
s
e
d
by
(
7)
a
s
we
c
a
n
s
e
e
in
(
7
)
:
=
{
0
,
≺
1
2
∙
∙
∙
2
∙
3
,
≤
≺
,
≤
≺
0
≻
(
7)
whe
r
e
Vd
i
s
the
boot
s
pe
e
d,
Vn
is
the
nomi
na
l
s
pe
e
d
a
nd
Vc
is
the
s
hut
down
s
pe
e
d.
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omm
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omput
E
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C
ontr
o
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,
Vol.
18
,
No
.
1
,
F
e
br
ua
r
y
2020
:
45
6
-
46
4
458
F
igur
e
1.
W
ind
tu
r
bine
output
powe
r
2.
3.
F
u
e
l
c
e
ll
m
od
e
l
T
he
r
e
a
r
e
d
if
f
e
r
e
nt
types
of
F
ue
l
c
e
ll
(
F
C
)
;
the
mos
t
us
e
d
f
or
d
is
tr
ibut
e
d
ge
ne
r
a
ti
on
is
the
p
r
oto
n
e
xc
ha
nge
membr
a
ne
(
P
E
M
)
[
10]
.
I
n
thi
s
wor
k,
we
c
ons
ider
P
E
M
F
C
;
it
is
s
tudi
e
d
by
us
ing
the
model
of
the
F
C
s
tac
k.
T
he
output
volt
a
ge
of
the
F
C
Vf
c
c
a
n
be
c
a
lcula
ted
f
r
om
the
volt
a
ge
de
ve
loped
ins
ide
t
he
F
C
.
I
t
is
e
xpr
e
s
s
e
d
by
the
(
8)
:
=
−
−
ℎ
(
8)
w
he
r
e
E
oc
is
the
volt
a
ge
whe
n
the
c
ir
c
uit
is
ope
n,
Va
c
t
is
the
int
e
r
n
volt
a
ge
of
the
F
C
a
nd
Vohm
is
t
he
ohmi
c
volt
a
ge
.
T
he
number
of
hyd
r
oge
n
s
tor
a
ge
tanks
is
de
ter
mi
ne
d
ba
s
e
d
on
the
M
a
na
ge
ment
s
tr
a
tegy
s
howe
d
be
low:
−
if
the
powe
r
ge
ne
r
a
ted
f
r
om
r
e
ne
wa
ble
e
ne
r
gy
s
our
c
e
s
(
P
V/W
ind)
is
g
r
e
a
ter
than
the
load
de
mand,
the
e
lec
tr
olys
e
r
will
be
us
e
d
to
pr
oduc
e
hydr
oge
n.
T
his
hyd
r
oge
n
s
tor
e
d
in
the
tanks
c
a
n
be
c
a
lcula
ted
a
s
f
oll
ows
:
(
)
=
(
−
1
)
+
(
(
)
−
(
)
⁄
)
(
9)
whe
r
e
E
s
tor
is
the
hydr
oge
n
s
tor
e
d
in
the
tanks
,
E
r
e
n
is
the
e
ne
r
gy
pr
oduc
e
d
f
r
om
r
e
ne
wa
ble
s
our
c
e
s
,
E
load
is
the
e
ne
r
gy
load
a
nd
E
f
f
i
n
v
is
the
e
f
f
icie
nc
y
o
f
the
inver
ter
.
−
whe
n
the
e
ne
r
gy
de
mand
of
the
load
is
gr
e
a
te
r
th
a
n
the
e
ne
r
gy
pr
oduc
e
d
by
r
e
ne
wa
ble
e
ne
r
gy
s
ou
r
c
e
s
,
the
F
C
will
be
us
e
d
to
f
e
e
d
up
the
load
[
11]
.
T
h
e
a
mount
of
hydr
oge
n
s
tor
e
d
in
the
tanks
is
c
a
lc
ulate
d
a
s
(
10)
.
(
)
=
(
−
1
)
−
(
(
)
−
(
)
)
_
⁄
(
10)
T
he
c
os
t
of
s
upplyi
ng
the
e
ne
r
gy
de
mand
by
F
C
e
l
e
c
tr
olyze
r
is
de
ter
mi
ne
d
by
the
(
11)
:
=
+
&
_
(
11)
w
he
r
e
C
F
C
is
the
F
C
pu
r
c
ha
s
e
c
os
t,
L
if
e
F
C
is
the
F
C
li
f
e
ti
me
a
nd
C
O
&
M
_
F
C
a
r
e
the
F
C
ope
r
a
ti
on
a
nd
mai
ntena
nc
e
c
os
ts
.
3.
B
AC
K
-
T
RA
CKI
NG
S
E
AR
CH
OP
T
I
M
I
Z
AT
I
O
N
AL
GO
RI
T
HM
(
B
S
A)
B
S
A
is
a
metha
he
ur
is
ti
c
a
lgor
it
hm
,
ba
s
e
d
on
na
t
ur
a
l
or
biol
ogica
l
e
volut
ions
tec
hniques
s
uc
h
a
s
mut
a
ti
on
.
I
t
is
pr
opos
e
d
to
s
olve
c
ons
tr
a
ined
o
pti
mi
z
a
ti
on
pr
oblems
a
nd
ove
r
c
ome
s
ome
dr
a
w
ba
c
ks
of
the
pr
e
vious
e
volut
ionar
y
a
lgor
it
hms
:
e
.
g
.
,
high
s
e
ns
it
ivi
ty
to
the
c
ontr
ol
pa
r
a
mete
r
a
nd
time
-
c
ons
umi
ng
c
omput
a
ti
on
[
12
]
.
B
S
A’
s
s
tr
uc
tur
e
is
s
im
ple;
it
ha
s
a
powe
r
f
ul
global
e
xplor
a
ti
on
a
nd
loca
l
e
xploi
tatio
n
due
to
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
I
mpr
ov
e
d
bac
k
tr
ac
k
ing
s
e
a
r
c
h
opti
miz
ati
on
algor
it
hm
for
P
V
/W
ind/
F
C
s
y
s
tem
(
J
ihane
K
ar
ti
te)
459
c
ontr
oll
ing
the
s
e
a
r
c
h
dir
e
c
ti
on
by
s
c
a
le
f
a
c
t
or
pa
r
a
mete
r
[
13
,
14
]
.
F
igur
e
s
2
(
a
)
a
nd
(
b
)
s
hows
powe
r
a
s
a
f
unc
ti
on
of
c
ur
r
e
nt
a
nd
the
vol
tage
a
s
a
f
unc
ti
on
of
c
ur
r
e
nt
f
or
the
F
C
us
e
d
in
thi
s
s
tudy.
F
ig
ur
e
3
s
hows
the
ge
ne
r
a
l
s
tr
uc
tur
e
of
the
B
S
A
a
lgor
it
hm.
B
S
A
ha
s
f
ive
main
s
teps
:
ini
ti
a
li
z
a
ti
on,
s
e
lec
ti
on
-
I
,
mut
a
ti
on,
c
r
os
s
ove
r
a
nd
s
e
lec
ti
on
-
I
I
[
15
]
.
I
ts
ge
ne
r
a
l
s
tr
uc
tu
r
e
is
de
s
c
r
ibed
in
F
igu
r
e
3
.
F
igur
e
4
s
hows
the
ini
t
i
a
li
z
a
ti
on
pr
oc
e
s
s
of
B
S
A.
(
a)
(
b)
F
ig
ur
e
2
.
(
a
)
P
owe
r
-
c
ur
r
e
nt
(
b
)
Voltage
-
c
ur
r
e
nt
c
ur
ve
s
of
the
F
C
F
igur
e
3.
Ge
ne
r
a
l
s
tr
uc
tur
e
of
B
S
A
F
igur
e
4.
B
S
A’
s
ini
t
ializa
ti
on
−
I
nit
ializa
ti
on
I
n
thi
s
pr
oc
e
s
s
B
S
A
ge
ne
r
a
tes
the
ini
ti
a
l
populatio
n
by
a
uni
f
or
m
dis
tr
ibut
ion
.
−
S
e
lec
ti
on
-
I
B
S
A
de
f
ines
the
Old
population
Old
P
,
whic
h
is
us
e
d
to
c
a
lcula
te
the
s
e
a
r
c
h
dir
e
c
ti
on.
T
he
h
is
tor
ica
l
population
is
ini
ti
a
li
z
e
d
by
(
1
2
)
.
,
=
(
,
)
(
12)
In
e
a
c
h
it
e
r
a
ti
on,
B
S
A
de
ter
mi
ne
Old
P
by
c
o
mpar
ing
tw
o
number
s
ge
ne
r
a
ted
r
a
ndoml
y
a
a
nd
b.
T
his
c
ompar
is
on
is
s
hown
in
(
1
3
)
:
≺
ℎ
=
|
,
▯
(
0
,
1
)
|
(
13)
a
f
ter
de
ter
mi
ning
the
his
tor
ica
l
population
Ol
d
P
,
B
S
A
c
ha
nge
s
the
or
de
r
of
indi
viduals
by
us
ing
the
pe
r
mut
e
f
unc
ti
on
.
Evaluation Warning : The document was created with Spire.PDF for Python.
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S
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:
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E
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T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
,
Vol.
18
,
No
.
1
,
F
e
br
ua
r
y
2020
:
45
6
-
46
4
460
=
(
)
(
14)
−
M
utation
I
n
thi
s
s
tep
B
S
A
ge
ne
r
a
tes
the
ini
ti
a
l
f
or
m
of
tr
ial
population.
M
utant
=
+
∗
(
−
)
(
15)
W
he
r
e
F
is
a
f
unc
ti
on.
I
ts
va
lue
c
ontr
ols
the
a
mpl
i
t
ude
of
the
s
e
a
r
c
h
d
ir
e
c
ti
on.
I
t
is
e
xpr
e
s
s
e
d
by
(
1
6
):
=
5
∗
,
whe
r
e
=
(
0
,
1
)
(
16)
−
C
r
os
s
ove
r
,
(
)
=
1
,
(
1
:
[
∙
∙
∗
∗
]
)
=
1
;
=
(
1
,
2
,
3
,
…
,
)
=
+
(
.
∗
)
.
∗
(
−
)
,
=
∗
(
−
)
+
if
,
be
yond
the
bounda
r
y
.
(
17)
−
S
e
lec
ti
on
I
n
thi
s
s
tep,
the
indi
vidual
with
be
s
t
f
it
ne
s
s
va
lue
i
s
us
e
d
to
r
e
plac
e
the
pr
e
vious
indi
vidual.
4.
I
M
P
ROVE
D
B
AC
KT
RA
CK
I
NG
S
E
AR
CH
OP
T
I
M
I
Z
AT
I
ON
AL
GO
RI
T
HM
(
I
B
S
A)
B
S
A
ha
s
a
r
a
ndom
s
tr
a
tegy
in
de
f
ini
ng
mut
a
ti
on
;
t
he
late
r
int
r
oduc
e
s
c
ha
nge
s
in
indi
vidual
pos
it
ion
.
T
he
mi
x
r
a
te
pa
r
a
mete
r
(
M
)
us
e
d
in
c
r
os
s
ove
r
ope
r
a
tor
c
ontr
ols
the
number
o
f
indi
viduals
that
mut
a
t
e
in
tr
ial
population.
I
n
thi
s
wor
k
the
im
pr
ove
d
ba
c
ktr
a
c
king
s
e
a
r
c
h
opti
mi
z
a
ti
o
n
a
lgor
it
hm
(
I
B
S
A)
pr
e
s
e
nted
by
[
16]
is
us
e
d
to
s
tudy
the
im
pa
c
t
of
us
ing
a
F
C
e
lec
tr
olyze
r
in
a
hybr
id
r
e
ne
wa
ble
e
ne
r
gy
s
ys
tem
e
s
pe
c
ially
in
ter
ms
of
e
ne
r
gy
c
os
t.
T
he
I
B
S
A
is
pr
opos
e
d
to
ove
r
c
ome
s
ome
d
r
a
wba
c
ks
of
the
tr
a
dit
ional
B
S
A
s
uc
h
a
s
the
c
onve
r
ge
nc
e
is
s
ue
[
17
-
19]
.
How
e
ve
r
,
B
S
A
s
hows
a
s
tr
ong
r
obus
tnes
s
in
f
indi
ng
the
be
s
t
c
o
s
t
va
lue;
it
s
wa
y
i
n
s
tor
ing
population
f
r
om
the
pr
e
vious
ge
ne
r
a
ti
on
may
mak
e
it
c
onve
r
ge
ve
r
y
s
lowly
[
20,
21]
.
T
he
s
ys
tem
us
e
d
in
thi
s
s
tudy
is
pr
e
s
e
nte
d
in
F
igur
e
5
.
I
t’
s
c
ompos
e
d
of
P
V
ge
ne
r
a
tor
,
wind
tur
bine
ge
ne
r
a
tor
a
nd
F
ue
l
c
e
ll
s
ys
tem.
T
he
idea
be
hind
the
I
B
S
A
is
de
f
in
ing
a
ne
w
mut
a
nt
ba
s
e
d
on
the
s
c
a
le
f
a
c
tor
va
lue.
T
o
s
e
e
the
e
f
f
e
c
ti
ve
ne
s
s
of
the
I
B
S
A
f
ou
r
be
nc
hmar
k
f
un
c
ti
ons
a
r
e
us
e
d
a
s
s
hown
in
T
a
ble
1
.
T
he
s
im
ulatio
n
r
e
s
ult
s
a
r
e
s
hown
in
F
igu
r
e
6
a
nd
the
s
tatis
ti
c
s
va
lues
a
r
e
s
umm
a
r
ize
d
in
T
a
ble
2
.
F
igur
e
5.
P
V
wind
tur
b
ine
ge
ne
r
a
tor
f
ue
l
c
e
ll
hybr
i
d
r
e
ne
wa
ble
s
ys
tem
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
KA
T
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lec
omm
un
C
omput
E
l
C
ontr
o
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I
mpr
ov
e
d
bac
k
tr
ac
k
ing
s
e
a
r
c
h
opti
miz
ati
on
algor
it
hm
for
P
V
/W
ind/
F
C
s
y
s
tem
(
J
ihane
K
ar
ti
te)
461
T
a
ble
1.
L
ow
-
up
a
nd
dim
e
ns
ion
f
or
the
be
nc
hmar
k
f
unc
ti
ons
ID
N
a
m
e
L
ow
Up
D
F1
A
c
kl
e
y
-
32
20
.
39
20,18
F2
C
r
ie
w
a
nk
-
600
0.2423
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3449
F3
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c
ha
f
f
e
r
-
100
20
.
24
19
.
63
F4
S
he
ke
l
-
32
1
.
824
1
.
643
(
a
)
(
b)
(
c
)
(
d)
F
igur
e
6.
Optim
a
l
c
os
t
va
lue
f
or
(
a
)
F1
,
(
b)
F2
,
(
c
)
F3
a
nd
(
d
)
F
4
us
ing
B
S
A
(
gr
e
e
n
c
ur
ve
)
a
nd
I
B
S
A
(
r
e
d
c
ur
ve
)
4.
1.
Ob
j
e
c
t
ive
f
u
n
c
t
ion
T
he
AT
C
o
f
the
s
ys
tem
c
a
n
be
de
f
ined
a
s
f
ol
lows
:
1
=
.
+
.
+
.
(
18)
whe
r
e
C
p
is
the
tot
a
l
c
os
t
o
f
P
V
ge
ne
r
a
to
r
,
C
w
is
the
tot
a
l
c
os
t
of
wind
tur
bine
ge
ne
r
a
tor
a
nd
C
f
c
is
the
tot
a
l
c
os
t
of
the
f
ue
l
c
e
ll
.
T
he
c
os
t
of
s
upplyi
ng
e
ne
r
gy
with
P
V
ge
ne
r
a
tor
a
nd
wind
tur
bine
ge
ne
r
a
tor
is
de
ter
mi
ne
d
in
[
22]
.
T
he
c
os
t
of
powe
r
p
r
oduc
e
d
f
r
om
F
C
is
de
t
e
r
mi
ne
d
in
(
19)
.
=
+
&
_
(
19)
4.
2.
E
lec
t
r
olyze
r
m
od
e
l
T
he
hydr
oge
n
pr
oduc
ti
on
nh2
r
a
te
is
de
ter
mi
ne
d
b
a
s
e
d
on
F
a
r
a
da
y’
s
law
[
23]
,
it
is
pr
opor
ti
onne
l
to
the
e
lec
tr
ica
l
c
ur
r
e
n
t
ins
ide
the
c
ir
c
uit
[
24
]
.
T
he
nh
2
(
mol
/s
)
is
de
ter
mi
ne
d
in
(
20
)
.
2
=
2
(
20)
whe
r
e
n
F
is
the
F
a
r
a
da
y
e
f
f
icie
nc
y,
n
C
is
the
num
be
r
of
c
e
ll
s
in
s
e
r
ies
i
e
is
the
e
lec
tr
olyze
r
c
ur
r
e
nt
a
nd
F
is
the
F
a
r
a
da
y
c
ons
tant.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
1693
-
6930
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
,
Vol.
18
,
No
.
1
,
F
e
br
ua
r
y
2020
:
45
6
-
46
4
462
5.
S
I
M
UL
AT
I
ON
AN
D
RE
S
UL
T
S
T
he
s
tudi
e
d
s
ys
tem
is
c
ompos
e
d
o
f
P
V
ge
ne
r
a
t
or
,
wind
tur
bine
ge
ne
r
a
tor
a
nd
F
C
e
lec
tr
olyze
r
.
T
he
load
de
mand
is
a
n
AC
load;
a
nd
the
inver
ter
is
us
e
d
with
a
n
e
f
f
icie
nc
y
of
0.
8.
T
he
F
C
is
us
e
d
to
f
e
e
d
up
the
load
in
wor
s
e
c
a
s
e
f
or
R
E
(
r
e
ne
wa
ble
e
ne
r
gy)
.
T
he
s
ys
tem
f
lowc
ha
r
t
is
pr
e
s
e
nted
in
F
igur
e
5.
T
he
us
e
d
s
ys
tem
is
c
ompos
e
d
of
[
25]
:
−
6000
W
p
P
V
ge
ne
r
a
to
r
,
with
a
tot
a
l
a
c
quis
it
ion
c
os
t
of
40000
£.
−
5000
W
wind
tur
bine
ge
ne
r
a
tor
,
with
a
tot
a
l
a
c
quis
it
ion
c
os
t
of
10000£
a
nd
a
n
a
nnua
l
ope
r
a
ti
o
n
a
nd
maintena
nc
e
c
os
t
of
300£.
−
1KW
F
C
,
a
c
quis
it
ion
c
os
t
of
4000£
,
O&
M
c
os
t
of
0
.
2£/h
,
30000
h
e
xpe
c
ted
li
f
e
ti
me,
Nf
c
=
16.
66
KW
h/KgH2
f
o
r
the
nomi
na
l
powe
r
a
n
d
P
mi
n
=
60
W.
−
1KW
e
lec
tr
oly
z
e
r
,
a
c
quis
it
ion
c
os
t
o
f
3200£
,
Ne
yz
=
0.
021KgH
2/KW
h.
−
0.
1Kg
H2
tank
,
a
c
quis
it
ion
c
os
t
o
f
150
£,
O&M
c
os
t
10£/yea
r
,
25
ye
a
r
s
e
xpe
c
ted
li
f
e
ti
me
.
T
he
main
objec
ti
ve
of
thi
s
wor
k
is
to
s
ize
opti
mal
ly
a
hybr
id
P
V/W
ind/
F
C
s
ys
tem
us
ing
I
B
S
A
a
nd
c
ompar
e
the
r
e
s
ult
with
the
B
S
A.
T
he
pr
opos
e
d
m
e
th
od
a
im
s
to
s
a
ti
s
f
y
many
r
e
quir
e
ments
:
−
Optim
ize
the
a
nnua
l
tot
a
l
c
os
t
(
AT
C
)
of
the
s
ys
tem.
−
De
mons
tr
a
te
the
e
f
f
e
c
ti
ve
ne
s
s
of
the
I
B
S
A
c
ompar
e
d
to
the
t
r
a
dit
ional
B
S
A
f
or
s
ys
tem
us
ing
F
ue
l
c
e
l
l.
−
S
tudy
the
in
f
luenc
e
of
the
e
lec
tr
olyze
r
c
ur
r
e
nt
on
t
he
F
a
r
a
da
y
e
f
f
icie
nc
y.
T
a
ble
1
a
nd
T
a
ble
2
s
how
r
e
s
pe
c
ti
ve
ly
the
s
tat
is
ti
c
s
va
lues
a
nd
the
low
-
up
a
nd
dim
e
ns
ion
f
or
the
be
nc
hmar
k
f
unc
ti
ons
.
T
a
ble
2.
S
tatis
ti
c
s
va
lues
f
or
be
nc
hmar
k
f
unc
ti
ons
P
r
obl
e
m
S
ta
ti
s
ti
c
s
B
S
A
I
B
S
A
F1
M
e
a
n
20
.
39
20
.
18
S
td
0.2423
0
.
3449
B
e
s
t
20
.
24
19
.
63
F2
M
e
a
n
1
.
824
1
.
643
S
td
0
.
1014
0
.
093
B
e
s
t
1
.
753
1
.
625
F3
M
e
a
n
0
.
16
0
.
067
S
td
0
.
0573
0
.
1168
B
e
s
t
0
.
1241
0
.
0048
F4
M
e
a
n
-
0
.
010
-
0
.
009
S
td
0
.
0041
0
.
002
B
e
s
t
-
0
.
015
-
0
.
011
5.
1.
Ann
u
al
t
o
t
al
c
os
t
op
t
i
m
izat
ion
of
h
yb
r
id
s
ys
t
e
m
F
igur
e
5
s
hows
the
c
onf
igur
a
ti
on
of
the
Hybr
i
d
r
e
ne
wa
ble
P
V/W
ind/
F
C
s
ys
tem
unde
r
s
tudy.
T
he
pr
opos
e
d
s
tr
uc
tur
e
mee
ts
the
powe
r
de
mand
f
or
is
olate
d
load
loca
ted
in
R
a
ba
t,
M
or
oc
c
o.
F
igur
e
6
plot
s
the
opti
mal
v
a
lue
f
or
the
f
ou
r
be
nc
hmar
k
f
unc
ti
ons
f
or
B
S
A
a
nd
I
B
S
A.
I
n
thi
s
wor
k
the
P
V
ge
ne
r
a
tor
a
nd
wind
tur
bine
ge
ne
r
a
tor
a
r
e
the
pr
im
a
r
y
e
ne
r
gy
s
our
c
e
,
while
f
ue
l
c
e
ll
e
lec
tr
olyze
r
is
us
e
d
a
s
a
ba
c
kup
s
ys
tem.
T
he
opti
mi
z
a
ti
on
method
ba
s
e
d
on
I
B
S
A
(
im
p
r
ov
e
d
ba
c
ktr
a
c
king
s
e
a
r
c
h
opti
mi
z
a
ti
on
a
lgor
it
hm
)
is
us
e
d
to
s
ize
a
nd
de
s
ign
opti
mally
the
hybr
id
r
e
ne
wa
ble
e
ne
r
gy
s
ys
tem.
T
he
pr
ogr
a
m
is
de
ve
loped
on
M
AT
L
AB
s
of
twa
r
e
.
I
B
S
A
opti
mi
z
e
s
the
nu
mber
s
of
P
V
pa
ne
ls
(
Npv)
,
the
number
s
of
wind
tur
bines
(
Nw
)
a
nd
the
number
s
of
F
C
e
lec
tr
olyze
r
(
Nf
c
)
.
T
he
s
e
number
s
a
r
e
include
d
in
the
powe
r
va
lue
of
e
a
c
h
c
om
pone
nt
a
s
s
hown
in
(
18)
.
T
he
I
B
S
A
mus
t
mee
t
the
load
de
mand
with
a
mi
ni
mal
c
os
t
va
lue.
T
he
opti
mal
a
nnua
l
tot
a
l
c
os
t
(
AT
C
)
is
s
hown
in
F
igur
e
7.
T
he
c
u
r
ve
with
gr
e
e
n
c
olor
i
s
f
or
B
S
A
a
nd
the
one
wi
th
r
e
d
c
olo
r
is
f
o
r
I
B
S
A.
T
o
make
a
good
c
ompar
is
on,
we
ha
ve
maintaine
d
the
s
a
me
pa
r
a
mete
r
s
f
or
B
S
A
a
nd
I
B
S
A,
i.
e
.
,
popu
lation
s
ize
a
nd
the
number
of
ge
ne
r
a
ti
on.
T
he
s
im
ulation
pr
oc
e
s
s
is
ini
ti
a
li
z
e
d
by
a
r
a
ndom
va
lue
of
Npv,
Nw
a
nd
Nf
c
.
It
is
de
mons
tr
a
ted
that
the
be
s
t
AT
C
obtaine
d
by
I
B
S
A
is
be
tt
e
r
than
the
va
lue
obtaine
d
by
B
S
A.
T
his
wor
k
s
hows
a
ls
o
the
im
pa
c
t
of
the
e
lec
tr
ol
yz
e
r
c
ur
r
e
nt
on
the
F
a
r
a
da
y
e
f
f
icie
nc
y
F
igur
e
8
.
T
he
F
a
r
a
da
y
e
f
f
icie
nc
y
inc
r
e
a
s
e
s
with
the
a
ugmenta
ti
on
of
the
c
ur
r
e
nt
that
is
mea
ns
a
high
va
lue
f
or
e
lec
tr
olyze
r
c
ur
r
e
nt
gives
a
high
leve
l
of
e
f
f
icie
nc
y.
On
the
other
ha
nd,
the
r
e
ne
wa
bl
e
s
ys
tem
ha
s
de
s
igned
to
f
e
e
d
up
the
load
de
mand.
T
his
c
a
n
be
a
c
hieve
d
t
hr
ough
the
e
lec
tr
olyze
r
c
ur
r
e
nt
whis
h
is
di
r
e
c
tl
y
l
inke
d
to
the
pr
oduc
e
d
hydr
oge
n
.
T
he
leve
l
of
hydr
oge
n
s
tor
e
d
in
the
tank
in
f
luenc
e
s
the
opti
mi
z
a
ti
on
pr
oc
e
s
s
(
the
va
lue
of
AT
C
)
a
nd
then
the
number
of
P
V
pa
ne
ls
,
the
number
of
win
d
tur
bine
a
nd
the
numbe
r
of
F
C
.
T
he
number
o
f
P
V
pa
ne
ls
Npv,
the
number
of
wind
tu
r
bine
ge
ne
r
a
to
r
Nw
a
nd
the
numbe
r
o
f
F
C
Nf
c
opti
mi
z
e
d
by
I
B
S
A
is
s
hown
in
F
igur
e
9.
T
he
opti
mal
s
izing
a
nd
c
os
ts
of
the
Hybr
i
d
P
V/W
ind/
F
C
s
ys
tem
is
a
s
f
oll
ow:
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
I
mpr
ov
e
d
bac
k
tr
ac
k
ing
s
e
a
r
c
h
opti
miz
ati
on
algor
it
hm
for
P
V
/W
ind/
F
C
s
y
s
tem
(
J
ihane
K
ar
ti
te)
463
−
6
KW
of
P
V
−
5
KW
of
W
ind
−
1
KW
of
F
C
with
a
n
Annua
l
T
otal
C
os
ts
(
AT
C
)
of
14562.
17
£.
F
igur
e
7.
Optim
a
l
AT
C
with
B
S
A
(
c
ur
ve
gr
e
e
n)
a
nd
I
B
S
A
(
c
u
r
ve
r
e
d)
F
igur
e
8.
F
a
r
a
da
y
e
f
f
icie
nc
y
-
c
ur
r
e
nt
c
ur
ve
F
igur
e
9.
P
V
number
/
w
ind
tur
bine/F
C
6.
CONC
L
USI
ON
T
his
wor
k
ha
s
us
e
d
a
nove
l
opti
mi
z
a
ti
on
method
ba
s
e
d
on
I
mp
r
ove
d
ba
c
ktr
a
c
king
s
e
a
r
c
h
op
ti
mi
z
a
ti
on
a
lgor
it
h
m
(
B
S
A)
.
T
his
is
the
f
i
r
s
t
ti
me
whe
n
thi
s
ne
w
a
lgor
it
hm
is
us
e
d
to
pe
r
f
or
m
a
tec
hnica
l
opti
mi
z
a
ti
on
f
or
s
ys
tem
c
ompr
omi
s
ing
P
V
pa
ne
ls
,
wind
tur
bine
ge
ne
r
a
tor
s
a
nd
f
ue
l
c
e
ll
(
F
C
)
.
F
ir
s
tl
y,
a
c
ompar
a
ti
ve
s
tudy
is
don
e
ba
s
e
d
on
f
our
be
nc
hmar
k
f
unc
ti
ons
:
a
c
k
ley,
c
r
iew
a
nk
,
s
c
ha
f
f
e
r
a
nd
s
c
he
ke
l
.
T
he
r
e
s
ul
t
s
hows
the
e
f
f
e
c
ti
ve
ne
s
s
of
the
I
B
S
A
a
nd
T
a
ble
1
s
umm
a
r
ize
s
the
s
tatis
ti
c
a
l
va
lue
f
or
the
two
c
ompar
e
d
a
lgor
it
hm
B
S
A
a
nd
I
B
S
A.
I
B
S
A
outper
f
or
ms
B
S
A
in
ter
m
s
of
c
onve
r
ge
nc
e
s
pe
e
d
a
nd
be
s
t
f
it
ne
s
s
va
lue.
S
e
c
ondly,
the
s
ys
tem
unde
r
s
tudy
is
modele
d
th
r
ough
s
e
ve
r
a
l
powe
r
e
qua
ti
ons
then
the
objec
ti
ve
f
unc
ti
on
(
OF)
is
de
f
ined.
W
e
ha
ve
opti
mi
z
e
d
the
OF
us
ing
B
S
A
a
nd
I
B
S
A
,
a
nd
it
c
a
n
be
e
a
s
il
y
s
e
e
n
that
the
I
B
S
A
gives
the
b
e
s
t
AT
C
va
lue.
F
inally,
we
ha
ve
c
onc
luded
that
the
F
a
r
a
da
y
e
f
f
icie
nc
y
inf
luenc
e
s
the
e
lec
tr
olyze
r
c
ur
r
e
nt
a
nd
s
o
the
hydr
oge
n
s
tor
e
d
in
the
tank.
RE
F
E
RE
NC
E
S
[1
]
Si
n
g
h
R
.
an
d
Ban
s
al
R
.
C.
,
“
Rev
i
ew
o
f
H
RE
S
s
b
a
s
ed
o
n
s
t
o
ra
g
e
o
p
t
i
o
n
s
,
s
y
s
t
em
arch
i
t
ec
t
u
re
an
d
o
p
t
i
mi
s
at
i
o
n
cri
t
e
ri
a
an
d
met
h
o
d
o
l
o
g
i
e
s
,”
IE
T
R
e
n
ewa
b
l
e
P
o
wer
G
en
e
r
a
t
i
o
n
,
v
o
l
.
12
,
n
o
.
7
,
p
p
.
7
4
7
-
7
6
0
,
2
0
1
8
.
[2
]
A
d
efara
t
i
T
.
an
d
Ban
s
al
R
.
C.
,
“
In
t
eg
rat
i
o
n
o
f
ren
e
w
ab
l
e
d
i
s
t
ri
b
u
t
e
d
g
en
era
t
o
r
s
i
n
t
o
t
h
e
d
i
s
t
ri
b
u
t
i
o
n
s
y
s
t
em:
a
rev
i
e
w
,”
IE
T
R
en
ew
a
b
l
e
P
o
wer
G
e
n
er
a
t
i
o
n
,
v
o
l
.
10
,
n
o
.
7
,
pp.
873
-
8
8
4
,
2
0
1
6
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
1693
-
6930
T
E
L
KO
M
NI
KA
T
e
lec
omm
un
C
omput
E
l
C
ontr
o
l
,
Vol.
18
,
No
.
1
,
F
e
br
ua
r
y
2020
:
45
6
-
46
4
464
[3
]
Cas
t
a
n
ed
a
M
.
,
et
al
.
,
“
Si
zi
n
g
o
p
t
i
mi
z
at
i
o
n
,
d
y
n
am
i
c
mo
d
el
i
n
g
an
d
en
erg
y
man
ag
eme
n
t
s
t
rat
e
g
i
e
s
o
f
a
s
t
an
d
-
a
l
o
n
e
PV
/
h
y
d
r
o
g
en
/
b
a
t
t
er
y
-
b
a
s
ed
h
y
b
r
i
d
s
y
s
t
em
,”
In
t
er
n
a
t
i
o
n
a
l
j
o
u
r
n
a
l
o
f
h
y
d
r
o
g
e
n
en
er
g
y
,
v
o
l
.
38
,
n
o
.
1
0
,
pp.
3
8
3
0
-
3
8
4
5
,
2
0
1
3
.
[4
]
D
u
f
o
-
L
o
p
ez
R.
,
e
t
al
.
,
“
O
p
t
i
m
i
zat
i
o
n
o
f
co
n
t
r
o
l
s
t
ra
t
eg
i
es
fo
r
s
t
an
d
-
al
o
n
e
re
n
ew
a
b
l
e
en
er
g
y
s
y
s
t
ems
w
i
t
h
h
y
d
ro
g
e
n
s
t
o
r
ag
e
,”
R
e
n
ewa
b
l
e
en
e
r
g
y
,
v
o
l
.
32
,
n
o
.
7
,
p
p
.
1
1
0
2
-
1
1
2
6
,
2
0
0
7
.
[5
]
Bern
al
-
A
g
u
s
t
í
n
J
.
L
.
an
d
D
u
fo
-
L
o
p
ez
R.
,
“
Si
mu
l
at
i
o
n
an
d
o
p
t
i
m
i
zat
i
o
n
o
f
s
t
a
n
d
-
a
l
o
n
e
h
y
b
ri
d
ren
ew
a
b
l
e
en
er
g
y
s
y
s
t
ems
,”
R
e
n
ewa
b
l
e
a
n
d
S
u
s
t
a
i
n
a
b
l
e
E
n
e
r
g
y
R
ev
i
ews
,
v
o
l
.
13
,
n
o
.
8
,
pp.
2
1
1
1
-
2
1
1
8
,
2
0
0
9
.
[6
]
Bas
aran
K
.
,
et
al
.
,
“
E
n
erg
y
man
ag
emen
t
fo
r
o
n
-
g
r
i
d
an
d
o
ff
-
g
ri
d
w
i
n
d
/
PV
an
d
b
a
t
t
er
y
h
y
b
ri
d
s
y
s
t
em
s
,”
IE
T
R
en
ew
a
b
l
e
P
o
we
r
G
e
n
er
a
t
i
o
n
,
v
o
l
.
11
,
n
o
.
5
,
pp.
6
4
2
-
6
4
9
,
2
0
1
6
.
[7
]
Cas
t
a
ñ
ed
a,
M.
,
Fern
án
d
ez,
L
.
M.
,
Sán
ch
ez,
H
.
,
Can
o
,
A
.
,
&
J
u
rad
o
,
F.
,
“
Si
zi
n
g
me
t
h
o
d
s
fo
r
s
t
an
d
-
al
o
n
e
h
y
b
ri
d
s
y
s
t
ems
b
as
e
d
o
n
ren
e
w
ab
l
e
en
er
g
i
e
s
an
d
h
y
d
ro
g
en
,”
2
0
1
2
1
6
th
IE
E
E
M
ed
i
t
e
r
r
a
n
e
a
n
E
l
ec
t
r
o
t
ec
h
n
i
ca
l
Co
n
f
e
r
e
n
ce
,
p
p
.
8
3
2
-
8
3
5
,
2
0
1
2
.
[8
]
Cab
ran
e
Z
.
,
et
al
.
,
“
Bat
t
er
y
an
d
s
u
p
ercap
ac
i
t
o
r
fo
r
p
h
o
t
o
v
o
l
t
a
i
c
en
erg
y
s
t
o
ra
g
e:
a
f
u
zzy
l
o
g
i
c
man
a
g
emen
t
,”
IE
T
R
en
ew
a
b
l
e
P
o
we
r
G
e
n
er
a
t
i
o
n
,
v
o
l
.
11
,
n
o
.
8
,
pp.
1
1
5
7
-
1
1
6
5
,
2
0
1
7
.
[9
]
K
art
i
t
e
J
.
an
d
Ch
er
k
a
o
u
i
M.
,
“
O
p
t
i
m
i
za
t
i
o
n
o
f
h
y
b
r
i
d
re
n
ew
a
b
l
e
en
er
g
y
p
o
w
er
s
y
s
t
em
s
u
s
i
n
g
ev
o
l
u
t
i
o
n
ary
al
g
o
ri
t
h
m
s
,”
5
t
h
In
t
e
r
n
a
t
i
o
n
a
l
Co
n
f
e
r
en
ce
S
y
s
t
e
m
s
a
n
d
Co
n
t
r
o
l
(ICS
C)
,
p
p
.
3
8
3
-
3
8
8
,
2
0
1
6
[1
0
]
W
u
W
.
,
et
al
.
,
“
St
ab
i
l
i
s
ed
co
n
t
ro
l
s
t
ra
t
eg
y
fo
r
PE
M
fu
el
cel
l
an
d
s
u
p
erca
p
aci
t
o
r
p
ro
p
u
l
s
i
o
n
s
y
s
t
em
fo
r
a
ci
t
y
b
u
s
,
”
In
t
e
r
n
a
t
i
o
n
a
l
Jo
u
r
n
a
l
o
f
H
y
d
r
o
g
e
n
E
n
er
g
y
,
v
o
l
.
4
3
,
n
o
.
2
7
,
p
p
.
1
2
3
0
2
-
1
2
3
1
3
,
2
0
1
8
.
[1
1
]
N
el
s
o
n
D
.
B
.
,
et
al
.
,
“
U
n
i
t
s
i
z
i
n
g
an
d
co
s
t
an
a
l
y
s
i
s
o
f
s
t
an
d
-
al
o
n
e
h
y
b
r
i
d
w
i
n
d
/
P
V
/
f
u
el
cel
l
p
o
w
er
g
e
n
erat
i
o
n
s
y
s
t
e
ms
,”
R
en
ew
a
b
l
e
en
er
g
y
,
v
o
l
.
31
,
n
o
.
1
,
pp.
1
6
4
1
-
1
6
5
6
,
2
0
0
6
.
[1
2
]
Ci
v
i
ci
o
g
l
u
P.
,
“
Back
t
rack
i
n
g
s
earc
h
o
p
t
i
mi
za
t
i
o
n
al
g
o
r
i
t
h
m
fo
r
n
u
meri
ca
l
o
p
t
i
mi
za
t
i
o
n
p
r
o
b
l
ems
,
”
A
p
p
l
i
e
d
M
a
t
h
e
m
a
t
i
c
s
a
n
d
Co
m
p
u
t
a
t
i
o
n
,
v
o
l
.
2
1
9
, p
n
o
.
1
5
,
p
p.
8
1
2
1
-
8
1
4
4
,
2
0
1
3
.
[1
3
]
Brév
i
l
l
i
ers
M
.
,
et
a
l
.
,
“
Fas
t
H
y
b
ri
d
BSA
-
DE
-
S
A
A
l
g
o
r
i
t
h
m
o
n
G
PU
,”
In
t
e
r
n
a
t
i
o
n
a
l
Co
n
f
e
r
en
ce
o
n
S
w
a
r
m
In
t
e
l
l
i
g
e
n
ce
B
a
s
ed
O
p
t
i
m
i
z
a
t
i
o
n
,
Sp
r
i
n
g
er,
Ch
am,
p
p
.
75
-
86
,
2
0
1
6
.
[1
4
]
Mo
d
i
r
i
-
D
el
s
h
a
d
M
an
d
Rah
i
m
N
.
A.
,
“
So
l
v
i
n
g
n
o
n
-
co
n
v
e
x
eco
n
o
m
i
c
d
i
s
p
a
t
ch
p
r
o
b
l
em
v
i
a
b
ack
t
rack
i
n
g
s
ea
rch
al
g
o
ri
t
h
m,
”
E
n
er
g
y
,
v
o
l
.
77
,
p
p
.
3
7
2
-
3
8
1
,
2
0
1
4
.
[1
5
]
El
-
Fer
g
an
y
A
.
,
“
O
p
t
i
ma
l
al
l
o
ca
t
i
o
n
o
f
m
u
l
t
i
-
t
y
p
e
d
i
s
t
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t
er
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l
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u
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,
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-
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6
]
K
art
i
t
e
J
.
an
d
Ch
er
k
ao
u
i
M.
,
“
Imp
r
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ack
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rack
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earch
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1
7
.
[1
7
]
L
i
n
J
.
,
“
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p
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D
yn
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cs
,
v
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80
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o
.
1
-
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,
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2
0
9
-
2
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0
1
5
.
[1
8
]
D
u
a
n
H
.
an
d
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u
o
Q
.
,
“
A
d
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p
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m
fo
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d
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mag
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e
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o
me
t
er
o
p
t
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m
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zat
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n
,”
IE
E
E
Tr
a
n
s
a
c
t
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s
o
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M
a
g
n
e
t
i
cs
,
v
o
l
.
50
,
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o
.
1
2
,
pp.
1
-
6
,
2
0
1
4
.
[1
9
]
Brév
i
l
l
i
ers
,
M.
,
A
b
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l
k
af
i
,
O
.
,
L
ep
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t
,
J
.
,
&
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o
u
mg
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ar,
L
.
,
“
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-
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u
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ed
b
ac
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rac
k
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s
earc
h
o
p
t
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mi
za
t
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g
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ri
t
h
m
,”
12
th
In
t
e
r
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t
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C
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vo
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o
n
(E
A
2
0
1
5
),
L
y
o
n
,
Fran
ce
,
2
0
1
5
.
[2
0
]
D
u
b
ey
H
.
M
.
,
et
al
.
,
“
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b
ack
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rack
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ys
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em
s
(ICP
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)
.
2
0
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E
6
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t
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e
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p
.
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-
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0
1
6
[2
1
]
Su
Z
.
,
et
al
.
,
“
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h
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rac
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mi
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mp
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am
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rai
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,”
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r
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co
m
p
u
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,
v
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.
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6
,
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p
.
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4
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0
1
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.
[2
2
]
K
art
i
t
e
J
.
an
d
Ch
er
k
a
o
u
i
M.
,
“
O
p
t
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re
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ew
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ary
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,”
5
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In
t
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(ICS
C),
p
p
.
3
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3
-
3
8
8
,
2
0
1
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.
[2
3
]
Cas
t
a
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ed
a
M
.
,
et
al
.
,
“
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zi
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am
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c
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g
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rat
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d
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PV
/
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a
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ed
h
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b
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d
s
y
s
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em
,”
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t
er
n
a
t
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a
l
j
o
u
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l
o
f
h
y
d
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g
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g
y
,
v
o
l
.
38
,
n
o
.
1
8
,
pp.
3
8
3
0
-
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8
4
5
,
2
0
1
3
.
[2
4
]
K
h
a
n
M
.
J
.
an
d
Iq
b
al
M
.
T.
,
“
D
y
n
ami
c
mo
d
el
i
n
g
an
d
s
i
mu
l
a
t
i
o
n
o
f
a
s
mal
l
w
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n
d
–
fu
e
l
cel
l
h
y
b
r
i
d
en
er
g
y
s
y
s
t
e
m
,”
R
en
ew
a
b
l
e
en
er
g
y
,
v
o
l
.
30
,
n
o
.
3
,
pp.
4
2
1
-
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,
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0
0
5
.
[2
5
]
Mal
ek
i
A
.
an
d
A
s
k
arzad
e
h
A
.
,
“
O
p
t
i
ma
l
s
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zi
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PV
/
w
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n
d
/
d
i
es
e
l
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b
a
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t
o
ra
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fo
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cat
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t
o
an
o
ff
-
g
ri
d
rem
o
t
e
re
g
i
o
n
:
A
cas
e
s
t
u
d
y
o
f
Raf
s
an
j
an
,
Iran
,”
S
u
s
t
a
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n
a
b
l
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E
n
er
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y
Tec
h
n
o
l
o
g
i
es
a
n
d
A
s
s
es
s
m
e
n
t
s
,
vol.
7
,
p
p
.
1
4
7
-
1
5
3
,
2
0
1
4
.
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