Indonesi
an
Journa
l
of El
ect
ri
cal Engineer
ing
an
d
Com
p
ut
er
Scie
nce
Vo
l.
23
,
No.
1
,
Ju
ly
20
21
,
pp.
54
~
6
2
IS
S
N: 25
02
-
4752, DO
I: 10
.11
591
/i
j
eecs
.v
23
.i
1
.
pp
54
-
6
2
54
Journ
al h
om
e
page
:
http:
//
ij
eecs.i
aesc
or
e.c
om
Energy
mana
gement in
co
nn
ect
ed
and disc
onnected mod
e of a
ph
otovo
l
taic syst
em with
a batter
y s
t
orag
e using a
n artifici
al
neural n
etwork t
ec
hn
iqu
e
Ez
z
itou
ni J
ar
mou
ni
1
,
Ahme
d M
ouhsen
2
,
Moham
med L
amhamme
di
3
, a
n
d
Z
akary
a
Benizz
a
4
1,3
Lab
or
at
ory
of Radiat
io
n
-
Ma
tt
er and
I
ns
tr
um
entat
ion
(
RM
I)
,
T
he
Fac
ulty
of S
ci
e
nces a
nd Tec
hnol
og
y,
Hassa
n 1st Uni
ver
sit
y, M
oroc
co
2,4
Lab
or
at
ory
of E
ng
i
neer
i
ng, In
dustria
l M
an
agem
ent an
d I
nnovat
ion (
IMI
I)
,
T
he
Fa
c
ulty
of S
ci
e
nces a
nd
Tech
no
l
og
y,
Hassa
n 1st
U
nive
rsity
, Mo
r
occ
o
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
Ma
r
18
, 202
1
Re
vised
A
pr
28
, 2
021
Accepte
d
Ma
y
1,
2021
In
orde
r
to
red
uce
the
in
conve
n
i
enc
e
resul
ti
ng
fr
om
the
use
of
th
e
tra
di
ti
ona
l
ene
rg
y
source
s
(oil
,
gas
and
c
oal
),
th
e
int
eg
r
at
ion
of
ren
ewa
ble
ener
g
y
source
s
is
among
the
b
et
t
er
solu
ti
ons.
W
it
h
the
i
nte
gra
ti
on
of
g
r
ee
n
ene
r
g
y
source
s,
th
ere
are
sev
eral
str
a
te
gi
es
that
ca
n
be
adopted,
i
ncl
uding
the
combinat
ion
of
cl
e
an
en
erg
y
so
urc
es
(solar
,
wi
nd,
and
b
iomass
)
with
e
ac
h
othe
r,
or
the
co
m
bina
ti
on
of
ren
ewa
ble
source
s
with
conve
nti
on
al
source
s.
In
thi
s
article,
we
f
ocus
on
a
pho
to
volt
aic
s
y
s
te
m
allowing
the
stora
ge
of
en
er
g
y
in
a
batter
y
wit
h
a
coupl
ing
to
the
elec
tri
c
al
gri
d.
In
orde
r
to
o
ver
come
th
e
proble
m
s
rel
at
e
d
to
the
ran
dom
oper
at
ion
tha
t
accom
pani
es
the
use
of
photovol
taic
s
y
s
te
m
s,
we
hav
e
deve
lop
ed
a
con
trol
t
ec
hn
ique
b
ase
d
on
th
e
use
of
art
if
icial
neur
al
n
et
wor
k
te
chno
log
y
.
The
comple
te
s
y
stem
was
designe
d
and
si
m
ula
te
d
on
M
ATLAB
Sim
uli
nk.
Ke
yw
or
d
s
:
Bi
directi
on
al
dc
/dc
Energy m
anage
m
ent
Hybr
i
d gr
i
d
Neural
netw
ork
Photo
vo
lt
ai
c
pa
nel
Re
new
a
ble e
ne
rg
y
So
la
r
b
at
te
ry
This
is an
open
acc
ess arti
cl
e
un
der
the
CC
BY
-
SA
l
ic
ense
.
Corres
pond
in
g
Aut
h
or
:
Ezzi
touni
Jarm
ouni
Lab
or
at
ory
of
Ra
diati
on
-
Ma
tt
er a
nd Instr
ume
ntati
on
(RMI
)
The Fac
ulty
of
Scie
nces a
nd T
echnolo
gy, Ha
ssan 1st
Un
i
ve
rsity
, Mo
r
occ
o
BP:
577, r
oute
de
Ca
sa
blanca
.
Sett
at
, Mo
r
occ
o
E
-
m
ail :
ezzi
tou
ni.
j
a
rm
ou
ni@
gm
ail.co
m
1.
INTROD
U
CTION
Energy
is
a
pr
i
m
or
dial
nee
d
for
al
l
m
ank
ind
.
Howe
ver,
the
real
c
halle
nge
is
faci
ng
t
he
inevita
ble
dep
le
ti
on
of
t
he
world
’s
fo
s
sil
energy
res
our
ces
(o
il
,
gas
a
nd
co
al
).
T
he
sc
ie
nce
has
rece
ntly
turn
e
d
t
o
the
s
o
-
cal
le
d
cl
ean
or
ren
e
wa
ble
en
erg
y
s
ources
[
1
]
,
[
2].
T
he
m
os
t
im
po
rtant
so
urce
of
re
ne
wab
le
e
ne
rg
y
is
that
pro
du
ce
d
by
the
s
un
[
3].
A
ccordin
g
to
i
nt
ern
at
io
nal
re
ne
wab
le
e
nergy
agency
(
IRE
NA
),
t
he
cum
ulati
ve
instal
le
d
capac
it
y
of
s
olar
PV
w
ou
l
d
reach
8
519
G
W,
m
aking
it
the
sec
on
d
la
r
gest
RE
S
(af
te
r
wi
nd)
by
20
50
[4
]
.
H
oweve
r,
m
any
te
chn
ic
al
aspects
of
s
m
art
-
gr
i
ds
are
no
t
ye
t
so
lve
d,
su
ch
as
e
nerg
y
storag
e
inte
grat
ion,
powe
r
sta
bili
ty
, tiel
ine contr
ol,
an
d real
-
ti
m
e
energy m
anag
e
m
ent [
5].
Durin
g
the
m
os
t
unfavo
ur
a
bl
e
per
i
od
s
(abse
nce
of
s
olar
ra
diati
on)
or
at
ni
gh
t,
the
us
e
of
batte
ries
is
necessa
ry
for
a
fu
ll
-
ti
m
e
su
pply
.
Even
in
the
pr
ese
nce
of
of
the
batte
ries
in
phot
ovoltai
c
instal
la
ti
on
s
th
ere
is
al
ways
the
possibil
it
y
of
fal
li
ng
int
o
the
scenari
o,
o
f
the
a
bs
ence
of
the
nom
inal
conditi
ons
"R
andom
op
e
rati
on"
of
s
olar
pan
el
s f
un
ct
ion
,
sy
nchr
onise
d
with
the
stat
e
of
d
isc
ha
r
ge
of
the b
at
te
r
ie
s.
In
this
case
there
will
b
e a
pro
bl
e
m
w
it
h
the
consu
m
er'
s p
owe
r
s
upply ‘C
riti
cal
A
C L
oad’.
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
Ener
gy man
agemen
t i
n
c
onne
ct
ed
an
d disco
nn
ect
e
d m
ode
of
a
p
h
o
t
o
v
o
l
t
a
i
c
…
(
Ezzit
ou
ni
Ja
r
mou
ni
)
55
Ther
e
a
re
se
ve
ral
so
lu
ti
ons
t
ha
t
can
be
a
dopt
ed
in
order
t
o
s
olv
e
this
pro
ble
m
,
a
m
on
g
th
e
m
:
The
com
bi
nation
of
ph
otov
oltai
c
syst
e
m
with
ano
t
her
e
nergy
so
urce.
F
or
ex
a
m
ple,
wind
tu
rb
i
nes,
diesel
gro
up
,
these
s
olu
ti
ons
m
ay
so
lve
the
pro
blem
bu
t
f
or
a
lim
it
ed
tim
e,
are
ther
ef
or
e
unreli
able.
The
m
os
t
widesp
rea
d
an
d
pract
ic
a
l
so
luti
on
in
t
his
ty
pe
of
ca
se
is
to
co
nnect
th
e
instal
la
ti
on
to
the
gr
i
d
[6
]
,
[
7]
.
In
our
work
we
pr
opos
e
a
stud
y
on
a
syst
em
m
ai
nly
co
m
po
se
d
of
a
ph
otovol
ta
ic
pan
el
that
will
ensu
re
th
e
gen
e
rati
on
of
el
e
ct
rici
t
y,
a
batte
ry
to
suppo
rt
the
photov
oltai
c
syst
e
m
in
the
abse
nce
of
no
m
inal
op
erati
ng
co
ndit
ion
s,
and
c
onnecti
on
to
th
e
public
el
ect
ric
it
y
gr
id.
I
n
orde
r
t
o
orga
nise
the
f
un
ct
io
ning
of
these
el
em
ents
between
them
,
a
ne
w
m
anag
em
ent
te
chn
i
qu
e
ba
sed
on
n
e
ural
net
w
orks
will
be
pr
opos
e
d.
This
work
is
s
ubdi
vi
ded
i
nto
thre
e
m
a
i
n
par
ts
orga
nize
d
as
fo
ll
ow
s:
The
first
par
t
exp
la
in
s
the
a
rch
it
ect
ure
of
the
stu
died
syst
e
m
and
the
m
ai
n
com
po
ne
nts.
T
he
sec
ond
pa
rt
is
co
ncerne
d
with
the
m
anag
em
ent
and
super
visio
n
st
rat
egy
ad
opte
d.
T
he
la
s
t
par
t
is
de
dicat
ed
to
the
analy
s
is
and
inter
pr
et
at
ion
of
the
sim
ula
ti
on
res
ults
of
the
stu
die
d
syst
e
m
fo
r
di
ff
e
ren
t
op
e
rati
ng stat
e
s.
Fin
al
ly
,
a co
nclusi
on su
m
m
arizes t
he w
ork
d
e
velo
ped.
2.
PRE
SENT
AT
ION
OF T
HE
STUDIE
D SY
STE
M
In
t
he
face
of
grow
i
ng
ene
rgy
dem
and
,
re
ne
wab
le
e
nergi
es
are
in
vited
to
play
a
deci
sive
r
ole
in
est
ablishin
g
a
su
sta
ina
ble
en
erg
y
strat
e
gy.
The
dev
el
op
m
ent
of
cl
ean
a
nd
re
ne
wab
le
e
nergy
res
ource
s
is
the
best
an
d
safest
way
to
m
eet
t
he
el
ect
rici
ty
need
s
of
dif
fe
re
nt
reg
i
ons
of
t
he
w
or
l
d.
I
n
th
is
par
t
we
will
pr
ese
nt
the
stu
died
sys
tem
,
as
sho
wn
in
Fig
ur
e
1
,
wh
ic
h
is
m
ai
nly
com
po
sed
of
:
A
phot
ovoltai
c
pa
nel
w
hich
will
deliver
a
c
onti
nuous
cu
rr
e
nt
[8
]
.
A
DC/DC
conver
te
r
wit
h
an
MP
PT
“
P
erturb
an
d
obser
ve”
c
on
t
rol
le
r
to
reach
the
po
i
nt
of
the
m
axi
m
um
po
wer
[
9
]
,
[
10]
,
[11]
.
A
s
olar
batte
ry
co
nn
ect
e
d
to
the
bid
irect
io
nal
D
C/
DC
conve
rter
to
en
su
re
the
s
uppl
y
of
el
ect
rici
ty.
A
DC/AC
co
nv
e
rter
to
pro
vi
de
the
AC
vo
l
ta
ge
require
d
f
or
the
crit
ic
al
load.
A
nd
a
co
nnec
ti
on
to
the
public
el
ect
rici
ty
gr
id,
in
or
de
r
to
ens
ur
e
the
s
upply
of
el
ect
rici
ty
t
o
the
consum
ers,
in
the
case
of
a
bse
nce
of
ir
ra
diati
on
f
or
the
phot
ovoltai
c
syst
e
m
,
or
wh
e
n
the
batte
ry
st
at
e
of
charge is le
ss
than 3
0%
. T
he sy
stem
w
as d
s
evelo
ped an
d s
i
m
ul
at
ed
us
in
g t
he
Ma
tl
ab/Si
m
ul
ink
to
ol.
Figure
1.
The
s
tud
ie
d sy
ste
m
arch
it
ect
ure
2.1
.
Bi
-
dire
c
t
iona
l
dc
-
dc c
onver
ters
The
bi
-
directi
onal
DC
-
DC
co
nv
e
rters
are
use
d
w
her
e
the
re
is
a
need
to
im
po
se
power
f
low
in
tw
o
directi
ons
[
12
]
,
[
13]
,
[14]
.
I
n
our
w
ork
bid
i
r
ect
ion
al
DC
-
DC
conver
te
r
is
a
m
ai
n
el
e
m
ent,
b
ecau
se
it
is
go
i
ng
to
en
sure
the
auto
no
m
y
of
operati
on
of
ou
r
syst
em
.
To
m
anag
e
th
e
st
at
e
of
cha
rg
e
“soc”
of
the
ba
tt
ery
a
bid
irect
io
nal
bu
c
k
-
bo
os
t
co
nv
e
rter
will
be
us
ed
to
e
ns
ure
t
he
fl
ow
of
c
urr
e
nt
in
both
di
r
ect
ion
s
(ch
a
rg
e/
discha
rg
e
)
acco
rd
i
ng
to
the
sta
te
o
f
switc
hes
S
1
and
S
2,
whos
e
com
m
and
s
are
generate
d
by
the
neural
net
wor
k
outp
ut
sta
te
s”
zero
or
on
e”
.
Figure
2
s
how
s
the
c
orrespo
nd
i
ng
ci
rcu
it
of
the
c
onve
rter
to
be
us
e
d.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
23
, N
o.
1
,
Ju
ly
20
21
:
54
-
6
2
56
Figure
2
.
Eq
ui
v
al
ent circ
uit o
f
a
bid
irect
i
on
a
l bu
c
k
-
bo
os
t c
onve
rter
3.
SY
STE
M MA
NAGEME
NT
STRA
TE
G
Y
Durin
g
it
s
us
e,
a
batte
ry
placed
in
a
sta
nd
-
a
lon
e
net
wor
k
can
unde
r
go
ei
ther
ov
e
rloa
d
wh
e
n
it
s
so
c
exceed
s
90%
,
or
dee
p
disc
harges
w
hen
i
ts
so
c
decr
eas
es
belo
w
30%
[15
]
,
[
16]
,
[
17
]
.
Ba
se
d
on
these
ind
ic
at
io
ns
we pr
opos
e
a m
anag
em
ent strate
gy for a
hybri
d el
ect
ric n
et
w
ork
in or
de
r
to:
Pr
e
ven
t
dee
p
discha
rg
e
s
an
d
overc
harges
of
the
batte
r
y
and
Ensure
con
ti
nuous
powe
r
sup
ply
fo
r
th
e
consum
er
[
18
]
,
[
19
]
.
This strate
gy c
an be
orga
nised
in
fo
ur
opera
ti
ng
m
od
es
,
as
il
lustrate
d
in
th
e
Fig
ur
e
3
:
Mod
e
1:
“C
ha
r
ge
M
od
e”;
Thi
s
Mo
de
occ
ur
s
wh
e
n
t
he
powe
r
s
upplied
by
the
phot
ovoltai
c
sour
ce
is
gre
at
er
than
t
he powe
r
d
em
and
ed
b
y t
he
loa
d (P
pv >
Pload),
and
bat
te
ry stat
e o
f
cha
rg
e
and les
s
than 3
0%
.
Mod
e
2:
“
Disc
harge
M
od
e”;
This
M
od
e
occ
ur
s
w
he
n
the
powe
r
s
upplied
by
the
phot
ovol
ta
ic
so
urce
is
l
ess
than
t
he powe
r
r
e
qu
ire
d by th
e load an
d batt
ery sta
te
of c
ha
rg
e
, a
nd great
e
r
tha
n 9
0%.
Mod
e
3:
“Neit
her
c
harge
nor
disc
ha
rg
e
M
ode”
or
“C
on
ne
ct
ed
m
od
e”;
This
Mo
de
occ
urs
w
he
n
the
power
su
ppli
ed
by
t
he
phot
ovoltai
c
so
urce
is
le
ss
than
the
powe
r
dem
and
ed
by
t
he
loa
d,
an
d
t
he
batte
ry
sta
te
of
charge
is
al
so
l
ess
than
30%.
The
pu
rpose
of
this
sta
te
is
to
protect
the
bat
te
ry
fr
om
the
de
ep
disc
harge.
In
this
m
od
e,
we
will
ha
ve
the
pro
blem
of
ass
ur
i
ng
the
sup
pl
y
to
the
co
nsu
m
er,
an
d
as
a
conseq
ue
nce
put
a
connecti
on
bet
ween o
ur syst
e
m
an
d
the
publ
ic
elec
tric
g
ri
d.
Mod
e
4:
“
Nei
ther
c
ha
rg
e
nor
disc
harge
Mod
e”;
T
his
sta
te
occurs
wh
e
n
t
he
po
wer
sup
plied
by
th
e
photov
oltai
c
syst
e
m
is
gr
eat
er
tha
n
the
pow
er
dem
and
e
d
by
the
load
an
d
the
batte
ry
sta
t
e
of
cha
rg
e
gre
at
er
than 9
0%. The
pur
po
se
of t
his stat
e is to
prot
ect
the bat
te
ry f
r
om
o
ver
c
hargin
g.
These
op
erati
ng stat
es
‘Mo
de
s’
ca
n be
pr
ese
nted o
n
the
foll
ow
i
ng d
ia
gr
am
.
Figure
3
.
The
diff
e
re
nt syst
em
o
per
at
ing
m
ode
s
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Ener
gy man
agemen
t i
n
c
onne
ct
ed
an
d disco
nn
ect
e
d m
ode
of
a
p
h
o
t
o
v
o
l
t
a
i
c
…
(
Ezzit
ou
ni
Ja
r
mou
ni
)
57
3.1
.
In
tell
ige
nt
m
ana
geme
nt
s
trate
gy
.
The
integ
rati
on
of
ne
w
"
arti
f
ic
ia
l
intelli
gen
ce
"
m
anag
em
e
nt
te
chnolo
gie
s
in
the
el
ect
rical
network
s
is
on
e
of
the
m
ai
n
obj
ec
ti
ve
s
of
our
w
ork
.
In
this
par
t
w
e
will
dev
el
op
a
m
anag
em
ent
m
od
el
based
on
t
he
integrati
on
of
neural
netw
ork
s
in
order
t
o
m
anag
e
the
sy
stem
wh
il
e
resp
ect
ing
t
he
f
our
m
od
es
of
operati
on
m
entioned
a
bo
ve.
W
it
h
this
m
anag
em
ent
t
echn
i
qu
e
we
w
il
l
gain
in
flexib
il
it
y
and
rob
ust
ness
o
f
co
ntr
ol
an
d
we
will
ens
ur
e
the
co
ntinu
it
y
of
el
ect
rici
ty
su
pply
to
the
c
on
s
um
er
and
a
t
the
sa
m
e
time
protect
the
ba
tt
ery
and inc
rease t
he
ir li
fesp
a
n.
Fi
gure
4
il
lustrat
es the st
ru
ct
ur
e
of the
prop
os
e
d neural
netw
ork
m
od
el
.
Figure
4
.
The
s
tructu
re
of
the
pro
po
se
d
a
rtific
ia
l neuron
net
work
3.2
.
The
pr
oposed
m
od
el
A
s
s
how
n
in
F
igure
5,
t
he
pr
opose
d
m
od
el
is
a
ne
ur
al
netw
ork
with
th
ree
inputs
vect
or
s
represe
nting
the
po
wer
ge
ne
rated
by
t
he
phot
ovoltai
c
sys
tem
,
the
batte
r
y
sta
te
of
cha
r
ge
a
nd
the
de
m
and
ed
power
by
t
he
load.
T
he
neural
net
work
outp
ut
co
ns
ist
in
g
of
t
hr
ee
vec
tors
[S1]
an
d
[S
2]
t
o
c
on
t
rol
s
the
bi
-
di
rec
ti
on
a
l
conve
rter,
a
nd
[S3]
to
s
witc
hing
betwee
n
co
nn
ect
e
d
a
nd
disco
nn
ect
e
d
m
od
e.
T
he
dim
ension
s
of
t
he
input/
ou
t
pu
ts
a
re “
1x2000”
for
eac
h vecto
r.
Figure
5
.
The
neural
netw
ork
arc
hitec
ture u
nd
e
r
M
ATL
A
B
4.
SIMULATI
O
N AND
DISC
US
SI
ON OF
THE
R
ES
UL
TS
Af
te
r
t
he
de
vel
op
m
ent
(Choic
e
of
nu
m
ber
of
hidden
la
ye
rs,
nu
m
ber
of
ne
uro
ns
pe
r
la
ye
r,
act
ivati
on
functi
on
an
d
netw
ork
opti
m
iz
at
ion
fu
nc
ti
on
.
)
an
d
the
neu
r
al
netw
ork
sim
ulatio
n
unde
r
Ma
tl
ab
[20],
[21],
[
22
]
,
[23],
[
24]
,
we
ge
ne
rate
the
Sim
uli
nk
file
s,
the
la
tt
er
con
ta
i
ning
al
l
the
inform
a
ti
on
ab
out
our netw
ork
a
nd the
m
anag
em
ent strate
gy
we
h
a
ve
a
dopted
.
4.1.
Tr
aining
of the ne
ural
network
:
In
t
his
pa
rt,
w
e
wil
l
pr
ese
nt
the
dif
fer
e
nt
factors
that
prov
e
t
he
r
o
bustness
a
nd
reli
abili
ty
of
the
con
t
ro
l
syst
em
dev
el
oped
.
F
igure
6
sho
ws
the
num
ber
of
it
erati
ons
a
nd
t
he
ti
m
e
n
eeded
t
o
get
to
the
m
ini
m
u
m
p
os
s
ible err
or
value
(
t
he
con
verge
nce
of the
outp
uts to
the
desir
ed ou
t
pu
ts
).
The
ver
i
ficat
ion
of
the
c
onve
r
gen
ce
of
t
he
le
arn
i
ng
al
gorith
m
is
done
by
t
he
le
ar
ning
c
ur
ve
giv
e
n
in
F
igure
7
,
wh
e
r
e
we
can
see
that
the
value
of
the
error
ta
r
ge
t
is
equ
al
to
1.
3
627
*10
-
8
at
132
ep
oc
hs
,
an
d
this
value
is
ve
ry
enou
gh
t
o
giv
e
a
good
cl
assifi
cat
ion
rate.
T
hi
s
i
m
plies
that
the
netw
ork
pa
ram
et
ers
(w
ei
ght
an
d
bias)
a
re
well
c
al
culat
ed
,
t
hen
the syst
em
m
a
nag
em
ent b
y
ne
ur
al
netw
ork wil
l be
done
i
n a pe
rf
ect
way
[25].
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
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on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
23
, N
o.
1
,
Ju
ly
20
21
:
54
-
6
2
58
Figure
6.
A
NN trai
ning
i
n
M
ATL
AB
/Si
m
ul
ink
Figure
7.
The
s
qu
a
re
d
er
r
or
of
the
ANN
t
rain
ing
with
M
AT
LAB/
S
im
ulink
4.2.
Te
s
ting
of t
he
contr
ol
sy
ste
m in
diffe
rent c
as
es
In
this
sect
io
n,
we
try
to
te
s
t
the
eff
ic
ie
nc
y
of
the
"ne
ur
al
network
"
m
anag
em
ent
syst
e
m
,
un
de
r
diff
e
re
nt
te
st
conditi
ons.
T
o
bette
r
analy
se
the
eff
ic
ie
ncy
and
reli
abili
ty
of
our
co
ntr
ol
syst
e
m
,
w
e
cho
ose
to
assign
values
t
o
the
s
oc
that
are
90%
hi
gh
e
r
or
30%
lowe
r.
In
this
way
we
will
sh
ow
that
if
we
are
a
bove
the
so
c
valu
e
is
90
%,
an
d
the
powe
r
of
the
source
‘
Ppv’
is
higher
tha
n
th
e
ref
ere
nce
va
lue
‘P
L
oad’,
we
will
no
ti
ce
t
hat
the
con
t
ro
l
syst
e
m
will
im
po
se
th
e
batte
ry
t
o
s
w
it
ch
to
non
ch
a
rg
i
ng
m
od
e,
i
n
orde
r
t
o
prote
ct
the
batte
ry from
overc
hargin
g.
In
the
oth
e
r
ca
se
w
he
n
the
lo
wer
pow
er
re
quire
d
by
the
l
oa
d
is
higher
of
the
s
ource,
an
d
the
batte
ry
sta
te
of
cha
rg
e
is
le
ss
than
30%.
T
he
syst
em
i
m
p
os
es
on
the
batte
ry
the
non
-
disc
harg
e
m
od
e
in
ord
er
t
o
protect
the
bat
te
ry
from
deep
discha
rg
e
.
A
nd
at
the
sam
e
tim
e
switc
hes
to
the
co
nnect
ed
m
od
e
in
order
t
o
ens
ur
e
sup
ply t
o
the
cons
um
er.
All t
his
w
e
w
i
ll
p
rese
nt it
in
t
he
th
ree cas
es
belo
w:
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on
esi
a
n
J
E
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c Eng &
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m
p
Sci
IS
S
N:
25
02
-
4752
Ener
gy man
agemen
t i
n
c
onne
ct
ed
an
d disco
nn
ect
e
d m
ode
of
a
p
h
o
t
o
v
o
l
t
a
i
c
…
(
Ezzit
ou
ni
Ja
r
mou
ni
)
59
4.
2.
1.
Cas
e N
1
In
this
case
the
batte
ry
char
ge
m
od
e
is
con
sidered
to
be
95
%
with
var
ia
ble
po
wer
fr
om
the
so
ur
ce.
Fo
r
a
bette
r
analy
s
is
of
al
l
the
gr
aph
s
in
Figu
re
8
,
we
hav
e
cho
sen
to
div
ide
the
analy
sis
into
three
ti
m
e
intervals.
The
first
interval
fr
om
0s
to
3s
:
Du
ring
this
interval
we
see
that
the
po
wer
gen
erated
by
the
ph
oto
vo
lt
ai
c
syst
em
(P
pv
)
is
lower
than
the r
eferen
ce po
wer
(
PLo
ad)
"2
kw
", an
d
that t
he
sta
te
o
f
char
ge
of
the b
at
te
ry is
gr
eat
er
than
90
%.
Ther
efo
re,
we
will
hav
e
the
sta
te
:
S1
=
1,
S2
=
0
and
S3
=
0.
This
is
the
ba
tt
ery
dischar
ge
m
od
e ‘in
o
rd
er to
co
m
pen
sat
e the en
erg
y dem
and
ed
by the co
ns
um
er’
.
The
secon
d
interval
fr
om
3s
to
7s
:
Du
ring
this
interval,
we
see
Pp
v
>
Pload
and
so
c
>
90
%.
Ther
efo
re,
we
will
hav
e
the
sta
te
:
S1
=
0,
S2
=
0
and
S3
=
0.
This
is
the
no
-
char
g
e
and
no
-
dischar
ge
m
od
e
"pr
otect
ion
of
the b
at
te
ry against o
ver
char
gin
g".
The
third
interval
fr
om
7s
to
10
s:
Du
ring
this
interval,
it
sh
ow
s
that
Pp
v
<
PLo
ad,
and
so
c
>
90
%.
Ther
efo
re,
the stat
e p
ro
du
ced is: S1
= 1
, S
2
= 0
an
d
S3
= 0
. Th
is i
s the d
isc
har
ge
m
od
e o
f
the b
at
te
ry.
In
this
case,
there
is
an
auton
om
ou
s
'
hybr
id'
op
erati
on
of
the
syst
em
,
wh
ere
the
po
wer
req
uired
by
the
load
is pr
ov
ided
by the p
ho
tov
oltai
c syst
em
or
the b
at
te
ry
.
Figure
8
.
List
of the
represe
nt
at
ive g
ra
phs
of
of
ca
se
N°
1
4.2.2.
C
as
e
N 2
In
this
case,
w
e
hav
e
co
ns
i
de
red
that
the
sta
te
of
charge
of
the
batte
ry
is
e
qu
al
to
22%
an
d
a
var
ia
bl
e
powe
r
of
t
he
s
ource.
I
n
order
to
bette
r
a
nal
yz
e
al
l
the
gra
ph
s
of
F
ig
ur
e
9
,
we
ha
ve
c
hose
n
to
cl
assi
f
y
it
in
three i
nter
vals:
The
first
inter
val
from
0s
to
3s
:
Durin
g
th
is
interval,
we
see
that
Pp
v
<
PLo
a
d,
an
d
so
c
<
30%.
A
s
a
conseq
ue
nce
of
these
c
onditi
on
s
, w
e
will
ha
ve
the stat
e:
S1
=
0
a
nd
S
2
= 0
,
a
nd
S
3
= 1
,
t
he
c
on
tr
ol
syst
e
m
i
m
po
ses
the
switc
hove
r
to
gri
d
-
c
onnecte
d
m
od
e,
in
or
de
r
to
ensu
re
the
powe
r
dem
and
of
the
co
ns
um
er
and
batte
ry
ch
arg
i
ng
from
th
e
public
el
ect
ric
gr
id
‘In
ord
e
r
to
ens
ure
the
con
ti
nu
ou
s
s
upply
of
the
loa
d
and b
at
te
ry c
ha
rg
e
’.
The
sec
ond
i
nt
erv
al
from
3s
to
7s
:
D
ur
i
ng
this
inter
val,
w
e
noti
ce
due
P
pv
>
PL
oa
d
an
d
s
oc
<
30%.
This
will
giv
e
the
sta
tus:
S1
=
0,
S2
=
0
an
d
S
3
=
0.
As
a
res
ult
of
th
is
case
we
will
hav
e
the
disco
nnect
ed
m
od
e, the
s
uppl
y and
c
ha
rg
i
ng
of the
batte
ry
is do
ne
f
r
om
t
he
s
olar pa
nels
.
The
thi
rd
i
nter
val
f
ro
m
7s
to
10
s:
D
ur
i
ng
t
hi
s
interval,
we
ob
s
er
ve
that
P
pv
<
PL
oa
d,
a
nd
so
c
<
30%
.
I
n
this
case,
switc
h
sta
te
s
will
hav
e
S
1
=
0,
S2
=
1
an
d
S
3
=
1.
As
a
c
on
se
qu
ence
of
this
ca
se,
we
will
have
the
co
nn
ect
e
d
m
od
e
again,
be
cause
the
ba
tt
ery
sta
te
of
charge
is
le
ss
than
30%,
the
batte
r
y
char
ge
a
nd
t
he
powe
r
c
om
pen
sat
ion
require
d by the
ch
a
r
ge i
s don
e
fro
m
the pub
li
c
gr
i
d.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
23
, N
o.
1
,
Ju
ly
20
21
:
54
-
6
2
60
Figure
9
.
List
of the
represe
nt
at
ive g
ra
phs
of case
N°2
4.2.3.
C
as
e
N° 3
The
obj
ect
ive
of
this
stu
dy
is
to
c
ha
racteri
se
the
nor
m
al
op
erati
on
of
the
batte
r
y
away
f
rom
ov
e
rc
harges
an
d
dee
p
disc
harges.
I
n
ord
er
to
char
act
erise
th
is
case,
the
batte
ry
sta
te
of
char
ge
was
assig
ned
a
value
e
qual
to
50%, a
nd the
pow
e
r of t
he so
ur
ce
w
as
k
e
pt
var
ia
ble.
To
a
naly
se this
case, t
he
sim
ulati
on
ti
m
e can
be divi
ded int
o
th
ree
ti
m
e int
erv
al
s a
s s
how
n
in
the
F
ig
ur
e
10
:
-
The
first
inte
rval
sta
rts
fr
om
0s
to
3s
:
Durin
g
t
his
inter
val
it
can
be
seen
that
Pp
v
<
PLoa
d,
an
d
that
th
e
sta
te
of
c
harge
of
the
batte
ry
is
equ
al
t
o
50
%
at
the
sta
rt,
as
a
co
ns
e
qu
e
nce
of
t
hese
c
onditi
ons
we
will
hav
e
the
sta
te
: S1
=
1, a
nd S
2 = 0
a
nd S
3
=
0.
"D
isc
ha
r
ge of
the b
at
te
ry".
-
T
he
seco
nd
inter
val
ra
ng
i
ng
fro
m
3s
to
7s
:
Durin
g
this
interval
it
can
be
seen
that
Ppv
>PLoa
d,
a
nd
si
nce
the
S
OC
is
in
t
he
vicinit
y
of
50%.
T
he
c
ons
equ
e
nce
of
the
se
co
ndit
ion
s
i
s
the
sta
te
:
S
1
=
0,
S
2
=
1
a
nd
S3
=
0. "
batte
r
y char
ge".
-
The
thir
d
inte
r
val
goes
f
ro
m
7s
to
10
s:
Duri
ng
t
his
inter
val
it
can
be
seen
that
Ppv
<PL
oa
d,
a
nd
t
hat
th
e
so
c
is
in
the
vicinit
y
of
50
%
so
the
sta
te
pr
od
uced
is:
S1
=
1,
S2
=
0
and
S
3
=
0.
"D
isc
harge
of
the
batte
ry".
Figure
10
. N
orm
al
o
per
at
in
g:
” cha
rg
e
and
di
scharge”
W
it
h
this
en
e
r
gy m
anag
em
ent tec
hn
iq
ue
, ba
sed o
n
arti
fici
a
l neural
netw
orks,
we wil
l gai
n
in
term
s:
In
te
ll
igent e
ne
r
gy m
anag
em
ent (
reas
onin
g
si
m
il
ar to
hum
an
reas
on
i
ng).
The ro
bustnes
s
of the
contr
ol
syst
e
m
.
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
Ener
gy man
agemen
t i
n
c
onne
ct
ed
an
d disco
nn
ect
e
d m
ode
of
a
p
h
o
t
o
v
o
l
t
a
i
c
…
(
Ezzit
ou
ni
Ja
r
mou
ni
)
61
The
sim
plist
ic
has
t
he
im
ple
m
entat
ion
.
The pr
ote
ct
io
n of t
he batt
ery a
gainst
overc
harge a
nd d
ee
p di
scharge.
Re
du
ci
ng the c
os
t
of
elec
tric
a
l ener
gy, by
usi
ng
t
he photo
volt
ai
c syst
e
m
as m
uch
as
poss
ible.
5.
CONCL
US
I
O
N
To
day
the
pro
du
ct
io
n
of
el
ect
rical
ener
gy
from
so
la
r
ener
gy
is
a
pr
om
i
sing
pr
oj
ect
.
B
ecau
se
so
la
r
energy
is
cl
ea
n,
it
does
not
cause
a
ny
se
ri
ou
s
e
nv
i
ronm
e
ntal
pro
blem
s
com
par
ed
t
o
c
onve
ntion
al
en
erg
y
pro
du
ct
io
n
sou
rces.
D
ue
to
th
e
ran
dom
op
er
at
ion
of
photovo
lt
ai
c
syst
e
m
s,
it
is
necessa
ry
to
store
the
energy
pro
du
ce
d
in
or
der
t
o
use
it
in
the
a
bs
e
nce
of
optim
al
pr
oductio
n
c
ondit
ion
s
.
Ba
tt
eries
offer
a
well
s
tora
ge
so
luti
on. How
e
ver,
the
re
is
al
ways
the possi
bili
ty
that
the
ba
tt
ery
will
be
di
scharged
at
th
e
sam
e
t
i
m
e
wi
th
th
e
abse
nce
of
s
ol
ar
irra
diati
on.
A
c
onnecti
on
t
o
the
public
gri
d
is
a
n
ef
f
ect
ive
so
l
ution,
if
the
syst
em
is
well
m
anag
ed
.
In
th
is
pa
per,
we
ha
ve
pro
po
s
ed
a
new
te
ch
nique
for
el
ect
rical
e
nergy
m
anag
e
m
ent
base
d
on
neural
netw
orks,
i
n
or
der
to
e
nsure
a
con
ti
nu
ous
supp
ly
to
the
c
on
su
m
er
and
to
protect
the
syst
e
m
co
m
po
ne
nts
su
ch
as t
he batt
ery i
n vari
ou
s
ope
r
at
ing
c
onditi
on
s.
ACKN
OWLE
DGE
MENTS
The
a
uthor
s are
v
e
ry m
uch
th
ankf
ul to
t
he u
nan
im
ou
s
rev
ie
wer
s
of t
he pap
er a
nd ed
it
or
of the
j
ou
rn
al
for
t
heir
c
on
st
ru
ct
ive
and h
el
pful c
om
m
ents that im
pr
ov
e
d
the
quali
ty
o
f
t
he pa
per.
REFERE
NCE
S
[1]
N.
L.
Panwar
,
S.
C.
Kaushik,
”
R
e
newa
ble
and
Sus
ta
in
abl
e Ene
rg
y
Revi
ews”,
S
c
ie
n
ce
dire
ct
,
vol.
15
,
pp.
1513
-
1524
,
April
2011.
[2]
S.
Sum
at
hi
and
L.
As
hok
Kum
ar
and
P.
Surekha
,
”
Solar
PV
and
W
ind
Ene
rg
y
Co
nver
sion
S
y
stem
s”,
Inte
rnation
a
l
Publ
ishing
AG
S
wit
zerland
,
2015
.
[3]
M.
Ö.
Arioglu
,
A.
A.
Sela
m
,
S
.
U.
Firat,
“
Renew
abl
e
En
erg
y
S
ourc
es:
Com
par
i
son
of
the
ir
Us
e
and
Respe
ct
iv
e
Polic
ie
s
on
a
Global
Scal
e
”,
in
Busine
ss
Sci
ence
Re
fe
r
enc
e
(
an
imprint
of
IGI
Global)
,
doi
:
10.
40
18/978
-
1
-
522
5
-
0440
-
5.
ch011
.
[4]
IRENA,
“
Future
of
Solar
Photov
olt
aic:
D
epl
o
y
m
ent
,
inve
stm
ent,
te
chno
log
y
,
gr
id
int
egr
at
ion
and
socio
-
ec
onom
i
c
aspe
ct
s”
,
2019
.
[5]
E.
Krem
ers,
P.
Viej
o,
O.
B
ar
ambones,
and
J.
Gonza
l
ez
d
e
Durand,
“
Proceedi
ngs
of
the
2
010
15th
IEEE
Inte
rnational
C
onfe
renc
e
on
Engi
nee
ring
of
C
omplex
Comput
er
Syste
ms
(
IC
ECCS
’10)
”
,
St.
Anne’s
Coll
eg
e,
Univer
sit
y
of
Ox
ford,
UK
,
22
–
26
Marc
h
2010,
pp
.
302
–
311
.
[6
]
V.
Kart
hik
e
y
an,
S.
Raj
ase
k
ar,
V.
Das,
P.
Kar
uppana
n
and
A
.
K.
Singh,
"G
ri
d
-
Connec
t
ed
an
d
Off
-
Grid
Solar
Photovolt
aic
S
y
s
te
m
",
Gr
ee
n
Ener
gy
and
Tec
hnol
ogy
,
do
i:
10.
100
7/978
-
3
-
319
-
501
97
-
0_5.
[7
]
M.
Hafe
ez,
M.
Hari
ri
,
M.
K.
M.
Desa
.
Mu
hamm
ad
Amm
irrul
Atiq
i
Moh
d
.,
“
Za
inuri
Gr
id
-
Connecte
d
P
V
Gene
ration
S
y
stem
Com
pone
nts
and
Challenge
s
”
:
A
R
ev
i
ew
,
En
ergies
2020
,
13(17),
4279
doi
:
10.
3390/e
n1317
4279
.
[8
]
Ham
za
,
H.A.
;
Auw
al
,
Y.M.;
Sharpson,
M.I.
“
Standa
lone
PV
S
y
stem
Design
and
Sizi
ng
f
or
a
Hous
ehol
d
i
n
Gom
be
”
,
Nig
eri
a.
Int
.
J. I
nt
erdisci
p.
R
es.
Inno
v
.
6,
pp
.
96
-
101
,
2
018
.
[9
]
A.
M.
At
al
l
ah,
A.
Y.
Abde
la
z
iz,”
Im
ple
m
en
ta
t
i
on
of
per
turb
an
d
observe
m
ppt
of
pv
s
y
st
em
wi
th
dir
ec
t
control
m
et
hod
using
b
uck
and
buck
boost
conve
r
te
r
s,”
Eme
rging
Tr
ends
in
E
le
c
tric
al
,
E
lectronic
Instrum
ent
ati
o
n
Engi
ne
ering:
An
international J
o
urnal
,
vol
.
1
,
Fe
brua
r
y
2014
.
[10
]
T.
Esra
m
,
P.
L.
Chapman,
”
Com
par
ison o
f
Photovolt
aic
Arra
y
M
axi
m
um
Po
wer
Point
Tra
ck
ing
Te
chn
ique
s,
”
IE
EE
Tr
ansacti
o
ns on Energy
Con
ve
rs
i
on
,
Vol
.
22
,
No.
2,
2007
.
[11
]
N.
Kac
imi,
S.
Grouni,
A.
Idir
,
M.
S.
Bouch
eri
t
,
"N
ew
improved
h
y
br
id
MP
PT
base
d
on
neur
al
n
et
wo
rk
-
m
odel
pre
dictive
cont
rol
-
Ka
lman
fil
ter
for
photov
olt
aic
s
y
s
te
m
",
I
ndonesian
Journ
al
of
E
le
c
tric
a
l
Engi
ne
eri
ng
an
d
Computer
Scien
ce
”
,
Vol
.
20
,
No
.
3
,
pp
.
1230
-
12
41
,
De
ce
m
ber
2
020
.
[12]
A.
Mendoz
a
-
To
rre
s,
N.
Visa
iro
,
”
Sw
it
chi
ng
rul
e
for
a
bidi
r
ec
t
i
onal
DC/DC
co
nver
te
r
in
an
elec
tr
ic
v
ehi
c
le”
i
n
htt
ps://
ww
w.sci
e
nce
dir
ec
t
.
com/sc
ie
nc
e/
ar
ti
c
le/abs/
pii
/S096706611
830594
X Vol.
8
2,
pp
.
108
-
117
,
J
anua
r
y
2019
.
[13
]
B.
L.
Nar
asimhara
ju,
S.P.
Dube
y
,
”
Design
and
ana
l
y
sis
of
cou
ple
d
induc
t
or
bi
dire
c
ti
ona
l
DC
-
DC
conve
rtor
for
high
-
volt
ag
e
d
iv
ersity
appl
i
catio
ns
”
,
in
IET
Pow
er
Elec
troni
cs
V
ol.
7
,
pp
.
998
-
1
007,
Augus
t
201
2.
[14
]
R.
Thumm
a,
V.
V.
S.
K.
Bhaj
ana
,
P.
K.
A
y
la
po
gu,
"D
esign
and
Sim
ula
ti
on
of
a
New
ZVT
Bi
-
dire
ctional
DCD
C
Convert
er
fo
r
Elec
tr
ic
Veh
ic
l
es”
,
Indone
sian
Jou
rnal
of
Elec
tric
a
l
Engi
n
ee
ring
an
d
Computer
Scie
nce
,
Vol.
7
,
No
.
1
,
pp
.
75
-
83
, J
ul
y
2017.
[15]
Za
he
eru
d
din
,
M.
Mana
s
,
”
R
en
ewa
ble
ene
rg
y
m
ana
gement
thr
ough
m
ic
rogrid
ce
ntr
al
con
troller
design:
An
appr
oac
h
to
int
e
gra
te
sol
ar,
wind
and
biomass
wit
h
bat
t
er
y
”
,
IET
Powe
r
Elec
tronic
s
Vol
.
1
,
pp.
15
6
-
163,
Novem
be
r
2015
.
[16
]
A.
Mera
b
et
,
K.
T.
Ahm
ed,
”
Energ
y
Mana
g
emen
t
and
Con
trol
S
y
s
te
m
for
La
bora
to
r
y
Scale
Mi
cro
gr
id
Based
W
ind
-
PV
-
Bat
te
r
y
”
,
in
IET
Powe
r
Elec
t
ronics
V
ol. 8, pp
.
145
-
154
,
Jan
.
2
017
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
23
, N
o.
1
,
Ju
ly
20
21
:
54
-
6
2
62
[17
]
C.
Zha
ng;
L
.
Y.
W
ang,
”
Robust
and
Adapti
ve
Esti
m
at
ion
of
Stat
e
of
Charge
f
or
Li
thi
um
-
Ion
Bat
teries”
,
in
IE
T
Po
wer
E
le
c
troni
cs
Vol.
62,
pp.
4
948
-
4957,
Augu
st 201
5.
[18
]
N.
Maz
i
,
T.
Ala
m
o,
”
En
erg
y
m
a
nage
m
ent
str
ate
gie
s
for
sm
art
gr
ids,”
h
tt
ps:/
/ha
l
.
arc
hiv
es
-
ouver
t
e
s.fr/
tel01472704
,
the
sis,
Mar
ch
20
17.
[19
]
Muhardika
,
S
y
a
fii
,
"D
esign
of
ard
uino
-
base
d
l
oadi
ng
m
ana
ge
m
ent
s
y
stem
to
improve
cont
inu
ity
of
solar
pow
er
suppl
y
",
Indone
s
ian
Journal
of
Elec
tri
cal
Engi
n
eer
ing
and
Compu
te
r Sc
ie
nc
e
,
Vol.
20,
No.
3
,
pp
.
1
677
-
1684
,
2020
.
[20
]
S.
Chen,
Z
.
He
,
”
How
Big
Da
t
a
and
Highper
fo
rm
anc
e
Com
puting
Drive
Br
ai
n
Scie
n
c
e”,
in
Jou
rnal
Pre
-
Proofs
Vol.
4
,
pp
.
381
-
392,
Augus
t
201
9
.
[21
]
S.
Stauba
,
E.
Ka
ramanb,
S.
Ka
y
a
a
and
H.
Kar
ap
Õnara
,
"A
rti
f
ic
i
al
Neura
l
Network
and
Agili
t
y
”
,
S
e
lv
a
Staub
et
al
.
/
Proce
dia
-
So
ci
a
l
and
Be
ha
vi
oral
Scienc
es
,
195
,
p
p.
1477
-
1485
,
2
015
.
[22
]
Raj
ar
aj
an
,
Jag
a
dee
sh.
“
W
hat
is
Multi
lay
er
pe
rce
ptrons
using
bac
kpropa
ga
ti
o
n
al
gorit
hm
,
in
sim
ple
word
s
?
”
-
Quor
a
.
htt
ps://
ww
w.quora
.
com/W
hat
-
isMulti
l
a
y
er
-
per
c
ept
rons
-
using
-
bac
kpropa
g
at
ion
-
al
gori
thm
-
insim
ple
-
words
.
23
Februa
r
y
201
5.
[23
]
N.
Zha
ng
,
S.
Shen
,
A.
Zhou
a
nd
Y.
X
u
,
"Investi
gation
on
Pe
rform
anc
e
of
N
eur
al
Ne
tworks
Us
ing
Quadra
tic
Rel
ative
Err
or
C
ost Func
ti
on",
I
EE
E
access
,
201
6,
doi
:
10
.
1109/
ACCESS
.
2019.
2930520
.
[24
]
H.
Koivo,
”
N
eur
al
n
et
works
:
B
asic
s using
MA
TLA
B
Neura
l
Netw
ork
Tool
box
”, Febr
uar
y
1
,
2008
.
[25
]
F.
Saada
oui,
K.
Mammar,
A,
Haz
za
b
,
“
Modeli
ng
of
photovol
ta
ic
s
y
st
em
with
m
axi
m
u
m
po
w
er
point
tra
ck
in
g
cont
rol
b
y
neur
a
l
net
works
”,
Int
e
rnational
Journal
of
Powe
r
Ele
ct
ronics
and
Dr
iv
e
Syste
m
(
IJP
E
DS)
Vol.
10,
No.
3,
Sep
2019,
pp.
1575
-
1591.
BIOGR
AP
HI
ES OF
A
UTH
ORS
Jarm
oun
i
E
z
z
it
oun
i,
student
,
re
ce
iv
ed
his maste
r
degr
ee
in el
e
ct
r
ic
a
l
engi
ne
eri
ng
from
fac
ul
t
y
of
scie
nce
and
t
ec
hnolog
y
Setta
t,
in
2019,
and
he
is
cur
ren
tly
a
qual
if
ie
d
sec
o
ndar
y
schoo
l
m
at
hemati
cs
tea
che
r,
a
t
the
Mi
nistr
y
of
Nati
on
al
Educat
ion
,
Morocc
o.
His
rese
arc
h
ar
ea
s
inc
lud
e,
sm
art
grid,
ren
ewa
b
l
e
ene
rg
y
and
ar
t
ifi
cial
intelligen
ce
.
L
abor
a
tor
y
of
Radi
at
ion
-
Matt
er
and
Inst
rum
ent
at
ion
(R
MI),
The
Facult
y
of
Sci
enc
es
and
Te
chno
log
y,
Hass
an
1st
Univer
sit
y
,
Morocc
o.
BP
:
577,
r
oute
d
e
C
asa
blanca
.
Set
ta
t
,
Mor
occ
o.
Ah
me
d
Mouhs
e
n,
recei
ved
his
Ph.D.
degr
e
e
in
El
e
ct
roni
cs
from
the
Univ
ersity
of
Bordea
ux
,
Franc
e,
in
1992
,
and
he
is
cur
ren
tly
a
Profess
or
at
the
Elec
tr
ical
Engi
n
ee
ring
Depa
rtment
,
Facul
t
y
of
Science
s
and
Techn
ologi
es,
Hass
an
I
Univer
sit
y
,
S
et
t
at
,
Morocc
o
.
His
rese
arc
h
in
te
r
est
foc
uses
on
embedde
d
sy
stems
,
wire
le
ss
comm
unic
at
ions
and
informati
on
te
chnol
og
y
.
La
bora
toi
re
d’I
ngéni
er
ie
,
de
Mana
gement
In
dustrie
l
et
d’In
novat
ion
(
LIMI
I)
Faculté´
des
Scie
nc
es
et
tech
nique
s
(FS
T)
Hass
an
First
Univ
ersit
é
BP
:
577
,
route
d
e
C
asa
b
la
n
c
a.
Se
ttat,
Morocc
o.
Mohame
d
Lam
hamd
i
,
holds
a
(
2008)
in
m
ateri
a
ls
and
te
chno
log
y
of
e
lectr
oni
cs
component
s
from
Paul
Sabat
i
er
Univer
sit
y
To
ulouse
Franc
e
.
A
fte
r
four
y
e
ars’
r
ese
arc
h
engi
n
ee
r
Grand
Gap
Rec
tifier
proj
ec
t
at
STMicroe
l
ectroni
cs
&
GREMA
N
-
Univer
sity
of
Tours.
in
Novem
ber
2011
he
has
bee
n
an
assistant
profe
ss
or
at
nationa
l
sc
hool
of
appl
i
ed
scie
nc
e
khourib
ga
Morocc
o,
where
he
be
ca
m
e
th
e
t
ec
hni
cal
m
ana
ger
of
the
El
e
ct
roni
cs
Sign
al
s
and
S
y
stems
(ESS)
group.
in
Janua
r
y
2018
,
he
joi
n
ed
th
e
fa
cul
t
y
of
s
ci
en
ce
and
technolog
y
i
n
Sett
a
t,
Moroc
c
o,
where
h
e
bec
ame
m
ember
of
the
RMI
La
bora
tor
y
(Ra
y
on
nement
-
Matière
&
Instrum
ent
at
i
on).
Curre
nt
rese
arc
h
topi
cs
inc
lud
e,
MEMS
sensors
for
RF
appl
icat
ions,
m
at
er
ia
ls
sci
ences,
intell
ige
nt
s
y
stems
and energ
y
.
Z
akary
a
BENIZZ
A,
was
born
in
KENITRA,
Morocc
o,
in
198
5.
He
is
Ph.D.
ca
ndidate
in
th
e
Facul
t
y
of
Scie
n
ce
s
and
Te
chno
l
og
y
,
Hass
an
firs
t
Univer
sit
y
,
Morocc
o.
He
is
the
Data
Center
responsible
in
u
nive
rsit
y
Hass
an
1st
Sett
at
Moro
c
co
since
2010
,
h
e
recei
ved
the
Master
degr
e
e
in
S
y
stem
and
Network
from
Univer
sit
y
Hass
an
first,
Settat,
Moroc
co.
Mem
ber
of
Engi
ne
eri
ng,
Ind
ustria
l
Mana
g
ement and
Innov
at
i
on
(IMII) Labor
at
or
y
.
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