I
n
t
e
r
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at
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al
Jou
r
n
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of
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lec
t
r
ical
an
d
Com
p
u
t
e
r
E
n
gin
e
e
r
in
g
(
I
JE
CE
)
Vol.
16
,
No.
5
,
Oc
tober
20
26
,
pp
.
2282
~
2293
I
S
S
N:
2088
-
8708
,
DO
I
:
10
.
11591/i
jec
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.
v
16
i
5
.
pp
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282
-
2293
2282
Jou
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C
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Abde
lm
a
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M
im
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S
ys
tems
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M
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a
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C
omp
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nts
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R
e
s
e
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c
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Gr
oup,
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bor
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pe
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a
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c
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ials
(
L
ASM
AR
)
,
Highe
r
S
c
hool
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T
e
c
hnology
M
e
kne
s
,
M
oulay
I
s
mail
Unive
r
s
it
y
of
M
e
kne
s
M
e
kne
s
50000,
M
or
oc
c
o
E
mail:
a
bde
l.
mi
mouni
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du.
umi
.
a
c
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ma
1.
I
NT
RODU
C
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T
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a
pid
global
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towa
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gy
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s
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tanc
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P
V)
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ys
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ploym
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ls
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c
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de
mi
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ti
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s
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a
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h
[
1]
,
[
2]
.
W
it
h
the
incr
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s
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mphas
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s
on
incor
por
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hings
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I
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ba
s
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ta
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[
3]
–
[
7]
.
How
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be
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P
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Evaluation Warning : The document was created with Spire.PDF for Python.
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I
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2088
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8708
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A
bde
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2283
de
mons
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ti
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a
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odule
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tempe
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tur
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[
8]
,
[
9
]
.
C
onve
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M
P
P
T
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lgor
i
thm
s
li
ke
the
popular
pe
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b
a
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obs
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r
ve
(
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&O)
method
make
im
pleme
ntation
s
im
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e
s
ult
in
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lator
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mi
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[
10
]
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[
11
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I
ntelli
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P
P
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methods
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uc
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a
s
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[
12
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[
13]
.
T
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pe
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if
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t
maximum
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point
s
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,
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,
a
nd
tot
a
l
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f
f
icie
nc
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T
he
s
e
va
lues
c
a
n
be
obtaine
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with
r
e
s
pe
c
t
to
I
-
V
a
nd
P
-
V
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ur
ve
s
be
ha
vior
on
I
r
r
a
dianc
e
a
s
we
ll
a
s
tempe
r
a
tu
r
e
f
a
c
tor
s
.
T
he
r
e
f
or
e
,
ther
e
is
a
ne
e
d
to
plo
t
thes
e
c
u
r
ve
s
to
de
ter
mi
ne
thes
e
s
pe
c
if
ic
va
lues
[
14]
,
[
15]
.
F
ur
ther
mor
e
,
ther
e
ha
s
be
e
n
a
pa
r
a
digm
s
hif
t
withi
n
the
I
o
T
tec
hnology
c
onc
e
r
ning
e
ne
r
gy
moni
tor
ing
a
nd
mana
ge
ment
[
16
]
–
[
18]
.
T
he
in
c
or
por
a
ti
on
of
I
o
T
in
to
photovol
taic
s
ys
tems
pr
ovides
a
ugmente
d
f
unc
ti
ona
li
ti
e
s
,
s
uc
h
a
s
r
e
a
l
-
ti
me
moni
tor
ing,
int
e
ll
igent
e
ne
r
gy
mete
r
s
,
r
e
mot
e
c
ontr
ol
mec
ha
nis
ms
,
a
nomaly
de
tec
ti
on,
powe
r
pr
oduc
ti
o
n
f
or
e
c
a
s
ti
ng,
a
nd
pr
e
ve
ntative
maintena
nc
e
.
I
o
T
s
ys
tem
s
c
ompr
is
e
va
r
ied
c
omponents
,
including
da
ta
a
c
qui
s
it
ion
a
nd
tr
a
ns
mi
s
s
ion
modul
e
s
li
ke
Ar
duino
,
E
S
P
32,
a
nd
R
a
s
pbe
r
r
y
P
i
a
nd
li
gh
twe
ight
c
omm
unica
ti
on
pr
o
tocols
,
s
uc
h
a
s
M
QT
T
a
nd
HT
T
P
c
omm
unica
ti
o
n,
a
long
with
c
loud
platf
o
r
ms
,
s
uc
h
a
s
T
hingS
pe
a
k,
T
hings
B
oa
r
d,
a
nd
Node
-
R
E
D
[
19]
–
[
22]
.
T
he
int
e
gr
a
ti
on
o
f
e
ne
r
gy
mana
ge
ment
us
ing
r
e
ne
wa
bles
a
nd
I
oT
tec
hnology
pr
ovides
a
unique
oppor
tuni
ty
to
e
mpl
oy
mul
ti
d
is
c
ipl
inar
y
idea
s
withi
n
e
duc
a
ti
ona
l
s
tudi
e
s
,
int
e
gr
a
ti
ng
e
lec
tr
onics
,
e
ne
r
gy
mana
ge
ment,
a
nd
c
omm
unica
ti
on
tec
hnology
int
o
a
c
c
e
s
s
ibl
e
a
nd
low
-
c
os
t
pr
otot
ype
s
.
De
s
pit
e
the
a
va
il
a
bil
it
y
of
s
e
ve
r
a
l
low
-
c
os
t
P
V
moni
tor
ing
s
y
s
tems
,
mos
t
e
xis
ti
ng
platf
or
ms
e
it
he
r
f
oc
us
s
olely
on
da
ta
a
c
quis
it
ion
without
r
e
a
l
-
ti
me
c
ontr
ol
c
a
pa
bil
it
ies
or
im
pleme
nt
M
P
P
T
a
lgor
it
h
ms
without
int
e
gr
a
ted
I
oT
moni
tor
ing.
F
ur
the
r
mor
e
,
f
e
w
s
tudi
e
s
pr
ovide
e
x
pe
r
im
e
ntal
c
ompar
is
ons
of
c
las
s
ica
l
a
nd
int
e
ll
ige
nt
M
P
P
T
tec
hniques
unde
r
s
a
me
ope
r
a
ti
ng
c
ondit
ions
on
the
s
a
me
e
mbedde
d
platf
or
m.
T
o
a
ddr
e
s
s
thes
e
li
mi
tations
,
thi
s
wor
k
pr
opos
e
s
a
unif
ied
e
mbedde
d
a
r
c
hit
e
c
tur
e
int
e
gr
a
ti
ng
r
e
a
l
-
ti
me
M
P
P
T
c
ontr
ol
,
high
-
r
e
s
olut
ion
s
e
ns
ing,
a
nd
I
o
T
-
ba
s
e
d
moni
tor
ing
.
Unl
ike
p
r
e
vio
us
s
tudi
e
s
,
the
pr
opos
e
d
s
ys
tem
e
na
bles
di
r
e
c
t
e
xp
e
r
im
e
ntal
c
ompar
is
on
be
twe
e
n
P
&O
a
nd
F
L
C
a
lgor
it
h
ms
un
de
r
identica
l
ha
r
dwa
r
e
a
nd
e
nvir
onmenta
l
c
ondit
io
ns
.
T
he
s
tudy
a
im
s
to
de
s
ign,
im
pleme
nt,
a
nd
va
li
d
a
te
a
n
e
duc
a
ti
ona
l
pr
otot
ype
that
int
e
gr
a
tes
I
oT
-
ba
s
e
d
P
V
e
ne
r
gy
moni
to
r
ing
a
nd
M
P
P
T
c
ontr
ol
us
ing
low
-
c
os
t
ha
r
dwa
r
e
a
nd
ope
n
-
s
our
c
e
s
of
twa
r
e
.
C
ons
tr
uc
ted
us
ing
a
mi
c
r
oc
ontr
oll
e
r
(
E
S
P
32)
,
the
pr
opos
e
d
s
ys
tem
c
ombi
ne
s
M
P
P
T
a
lgor
it
hm
wi
th
r
e
a
l
-
ti
me
da
ta
a
c
quis
it
ion
thr
ough
I
NA
219
s
e
ns
or
s
to
c
on
tr
ol
a
DC
-
DC
boos
t
c
onve
r
ter
,
a
s
we
ll
a
s
wir
e
l
e
s
s
da
ta
tr
a
ns
mi
s
s
ion
to
a
da
s
hboa
r
d
via
the
M
QT
T
p
r
otoc
ol.
T
his
pr
otot
ype
of
f
e
r
s
a
n
int
e
r
a
c
ti
ve
a
nd
r
e
pli
c
a
ble
tool
f
or
s
tudents
a
nd
r
e
s
e
a
r
c
he
r
s
to
obs
e
r
ve
P
V
pe
r
f
or
manc
e
,
c
ompar
e
a
nd
e
va
luate
M
P
P
T
methods
,
a
nd
vis
ua
li
z
e
e
ne
r
gy
f
low
dyna
mi
c
s
in
r
e
a
l
-
ti
me.
I
n
a
ddit
ion,
th
e
s
ugge
s
ted
pr
otot
ype
f
a
c
il
it
a
tes
on
-
de
vice
tr
a
c
ing
of
P
-
V
a
nd
I
-
V
c
ur
ve
s
us
ing
duty
c
yc
le
modul
a
ti
on
a
nd
p
lot
ti
ng
the
r
e
s
ult
s
on
M
AT
L
AB
.
T
hr
ough
th
is
e
du
c
a
ti
ona
l
pr
otot
ype
,
lea
r
ne
r
s
ga
in
d
ir
e
c
t
e
xpos
ur
e
to
vit
a
l
t
e
c
hnica
l
knowle
dge
,
including
s
e
ns
or
int
e
r
f
a
c
ing,
P
W
M
-
ba
s
e
d
c
ontr
ol,
c
loud
c
omm
unica
ti
on,
a
nd
e
ne
r
gy
e
f
f
icie
nc
y
a
na
lys
is
,
f
os
ter
ing
both
theor
e
ti
c
a
l
unde
r
s
tanding
a
nd
pr
a
c
ti
c
a
l
c
ompete
nc
e
.
T
his
wor
k
c
ontr
ibut
e
s
to
the
f
ield
o
f
e
mbedde
d
s
ys
tem
lea
r
ning
a
nd
r
e
ne
wa
ble
e
ne
r
gy
e
duc
a
ti
on
in
ke
y
wa
ys
:
i)
E
duc
a
ti
ona
l
a
c
c
e
s
s
ibi
li
ty:
C
r
e
a
ti
ng
a
n
inexpe
ns
ive
P
V
moni
tor
ing
a
nd
c
ontr
ol
s
ys
te
m
us
ing
ope
n
-
s
our
c
e
ha
r
dwa
r
e
(
E
S
P
32,
I
NA
219,
Ar
duino
I
DE
,
a
nd
T
hings
B
oa
r
d)
;
ii
)
P
e
da
gogica
l
i
ntegr
a
t
ion:
An
e
xa
mpl
e
of
how
da
ta
a
c
quis
it
ion,
c
ontr
ol
a
lgo
r
i
thm
s
,
a
nd
c
omm
unica
ti
on
-
ba
s
e
d
I
oT
int
e
gr
a
ti
on
c
a
n
be
int
e
gr
a
ted
int
o
a
s
ingl
e
pr
otot
ype
f
or
tea
c
hing
pur
pos
e
s
;
ii
i)
P
r
a
c
ti
c
a
l
d
e
mons
tr
a
ti
on:
An
e
xpe
r
im
e
ntal
c
ompar
is
on
of
c
las
s
ica
l
M
P
P
T
methods
a
nd
int
e
ll
igent
methods
us
ing
the
s
a
me
platf
or
m,
whic
h
wou
ld
a
ll
ow
s
tudents
to
moni
tor
r
e
a
l
-
ti
me
de
c
is
ions
of
a
lgo
r
it
hms
;
a
nd
iv)
S
c
a
lable
f
r
a
mew
or
k:
T
his
e
xpe
r
im
e
ntal
c
onf
igur
a
ti
on
is
a
ls
o
s
c
a
lable
f
o
r
us
e
in
c
las
s
r
oom
e
xpe
r
im
e
nts
,
r
e
s
e
a
r
c
h
pr
ojec
ts
,
a
s
we
ll
a
s
in
I
oT
wor
ks
hops
f
or
pr
ojec
ts
r
e
late
d
to
r
e
ne
wa
ble
e
ne
r
gy
c
onc
e
pts
in
the
c
ontext
o
f
S
mar
t
G
r
id.
2.
S
YST
E
M
OVE
RV
I
E
W
2.
1.
E
d
u
c
at
ion
al
d
e
s
ign
c
on
c
e
p
t
T
he
pr
o
tot
ype
wa
s
c
onc
e
ived
a
s
a
p
r
a
c
ti
c
a
l
lea
r
nin
g
platf
o
r
m
that
b
r
idges
theor
e
ti
c
a
l
c
onc
e
pts
of
P
V
e
ne
r
gy
c
onve
r
s
ion
with
r
e
a
l
-
wor
ld
im
pleme
ntati
on.
I
t
wa
s
buil
t
to
he
lp
s
tudents
unde
r
s
tand
h
ow
da
ta
a
c
quis
it
ion,
c
ontr
ol
a
lgo
r
it
hms
,
a
nd
c
omm
unica
ti
o
n
pr
otocols
int
e
r
a
c
t
wi
thi
n
a
c
ompl
e
te
P
V
moni
to
r
ing
a
nd
c
ontr
ol
s
ys
tem.
T
he
s
e
tup
wa
s
de
s
igned
f
or
e
a
s
y
r
e
pli
c
a
ti
on
in
a
c
a
de
mi
c
labs
or
c
las
s
r
oom
de
mon
s
tr
a
ti
ons
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2088
-
8708
I
nt
J
E
lec
&
C
omp
E
ng
,
Vol
.
16
,
No.
5
,
Oc
tober
20
26
:
2282
-
2293
2284
us
ing
inexpe
ns
ive
a
nd
wide
ly
a
v
a
il
a
ble
c
ompon
e
nts
.
T
he
pr
otot
ype
is
c
a
pa
ble
of
taking
lea
r
ne
r
s
out
of
s
im
ulation
s
of
twa
r
e
to
e
xpe
r
im
e
ntation
a
t
a
leve
l
invol
ving
ha
r
dwa
r
e
c
omponents
,
r
e
s
ult
ing
in
i
nc
r
e
a
s
e
d
unde
r
s
tanding
of
s
ys
tem
be
ha
vior
a
nd
c
ontr
ol
r
e
s
pons
e
unde
r
c
ha
nging
s
olar
c
ondit
ions
.
2.
2.
S
ys
t
e
m
a
r
c
h
it
e
c
t
u
r
e
T
he
ove
r
a
ll
s
ys
tem
a
r
c
hit
e
c
tur
e
pr
ovides
a
c
o
mpl
e
te,
c
los
e
d
-
loop
e
duc
a
ti
ona
l
s
e
tup
that
li
nks
ha
r
dwa
r
e
c
ontr
ol,
da
ta
a
c
quis
it
ion,
a
nd
I
oT
mon
it
or
ing.
I
t
e
na
bles
us
e
r
s
to
vis
ua
li
z
e
the
be
ha
vio
r
of
P
V
s
ys
tems
unde
r
va
r
ying
ir
r
a
dianc
e
c
ondit
ions
whil
e
s
im
ult
a
ne
ous
ly
obs
e
r
ving
the
e
f
f
e
c
t
of
dif
f
e
r
e
nt
M
P
P
T
s
tr
a
tegie
s
on
e
ne
r
gy
e
f
f
icie
nc
y
a
nd
c
onve
r
ter
pe
r
f
or
manc
e
.
T
he
pr
opos
e
d
s
ys
tem
c
ons
is
ts
of
a
DC
-
DC
boos
t
c
onve
r
ter
whic
h
c
onne
c
ts
a
t
the
input
with
a
phot
ovolt
a
ic
s
our
c
e
a
nd
a
load
a
t
the
output
.
T
he
c
on
ve
r
ter
is
c
ontr
oll
e
d
by
a
c
ontr
ol
a
nd
moni
tor
unit
.
T
his
uni
t
is
divi
de
d
int
o
th
r
e
e
leve
ls
:
da
ta
a
c
quis
it
ion
leve
l,
whic
h
c
oll
e
c
ts
e
lec
tr
ica
l
pa
r
a
mete
r
s
in
r
e
a
l
ti
me
thr
o
ugh
high
pr
e
c
is
ion
I
NA
219
s
e
ns
or
s
,
c
ontr
ol
le
ve
l
that
im
pleme
nts
the
M
P
P
T
a
lgor
it
hms
to
a
djus
t
the
du
ty
c
yc
le
f
or
e
xt
r
a
c
ti
ng
the
maximum
powe
r
,
while
the
I
o
T
c
omm
unica
ti
on
int
e
r
f
a
c
e
moni
tor
s
the
s
ys
tem
p
e
r
f
or
manc
e
.
All
thes
e
leve
ls
a
r
e
ha
ndled
by
a
low
-
c
os
t
mi
c
r
oc
ontr
oll
e
r
E
S
P
32.
T
he
E
S
P
32
a
ls
o
s
uppor
ts
on
-
de
vice
tr
a
c
ing
of
I
-
V
a
nd
P
-
V
c
ur
ve
s
c
omm
uni
c
a
te
with
a
laptop
to
log
a
nd
plot
s
e
r
ial
da
ta
v
ia
M
AT
L
AB
e
nvir
onment.
I
n
a
ddi
ti
on,
the
E
S
P
32
is
c
onne
c
ted
to
a
Wi
-
F
i
ne
twor
k
to
e
na
ble
c
omm
unica
ti
on
with
the
I
oT
s
e
r
ve
r
us
ing
the
M
QT
T
p
r
otocol.
F
igur
e
1
pr
e
s
e
nts
the
pr
opos
e
d
s
ys
tem
a
r
c
hit
e
c
tur
e
block
diagr
a
m.
F
igur
e
1.
T
he
pr
opos
e
d
a
r
c
hit
e
c
tur
e
b
lock
diagr
a
m
a
nd
c
ir
c
uit
diagr
a
m
o
f
the
pr
otot
ype
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
E
lec
&
C
omp
E
ng
I
S
S
N:
2088
-
8708
L
ow
-
c
os
t
e
duc
ati
onal
pr
otot
y
pe
for
I
o
T
-
bas
e
d
P
V
e
ne
r
gy
monitor
ing
…
(
A
bde
lmalek
M
imouni
)
2285
3.
I
M
P
L
E
M
E
NT
E
D
HARD
WAR
E
COM
P
ONE
NT
S
A
ha
r
dwa
r
e
a
r
c
hit
e
c
tur
a
l
de
s
ign
f
o
r
the
pr
otot
y
pe
is
ne
e
de
d
to
s
tr
ike
a
ba
lanc
e
be
twe
e
n
s
pe
e
d,
c
ompl
e
xit
y,
a
nd
c
os
t
e
f
f
e
c
ti
ve
ne
s
s
.
F
igur
e
1
s
hows
the
c
ir
c
uit
diagr
a
m
of
the
pr
otot
ype
,
whic
h
is
de
s
igned
by
c
ombi
ning
a
s
olar
pa
ne
l,
de
ve
loped
DC
-
DC
boos
t
c
onve
r
ter
,
E
S
P
32
modul
e
,
a
nd
two
c
ur
r
e
nt
-
volt
a
ge
s
e
ns
or
s
f
r
om
I
NA
219.
All
the
c
omponents
ha
ve
be
e
n
c
ho
s
e
n
to
make
them
low
in
c
os
t,
e
a
s
il
y
a
va
il
a
ble,
a
n
d
s
im
ple
to
im
pleme
nt
f
or
tea
c
hing.
T
he
P
V
s
our
c
e
is
a
polycr
ys
talli
ne
s
olar
pa
ne
l
of
6
V,
8
W
,
that
s
uppli
e
s
the
de
s
igned
boa
r
d
input
.
T
his
input
is
c
onne
c
ted
to
a
non
-
i
s
olate
d
boos
t
c
o
nve
r
ter
that
incr
e
a
s
e
s
the
volt
a
ge
to
mee
t
the
r
e
qu
ir
e
ments
of
the
load
while
maintaining
maximum
powe
r
thr
ough
M
P
P
T
c
ontr
ol
.
As
s
hown
in
F
igur
e
2,
t
he
boos
t
c
onve
r
ter
c
ir
c
uit
c
ons
is
ts
of
a
n
inducto
r
(
200
µ
H
)
,
a
n
I
R
F
Z
44
M
OSF
E
T
,
a
S
c
hott
ky
Diode
(
1N58
22)
,
a
nd
c
a
pa
c
it
or
s
(
two
e
lec
tr
olyt
ic
c
a
pa
c
it
or
s
of
100
µ
F
)
.
All
of
them
ha
ve
be
e
n
de
s
igned
to
pr
ovide
les
s
s
witching
los
s
,
s
maller
output
r
ipp
le,
a
s
we
ll
a
s
s
table
dyna
mi
c
pe
r
f
or
manc
e
in
c
ha
nging
e
nvir
onmenta
l
c
ond
it
ions
,
a
s
de
s
c
r
ibed
in
[
23]
.
I
n
(
1
)
a
nd
(
2)
,
r
e
s
pe
c
ti
ve
ly,
the
v
a
lues
of
inductor
a
nd
c
a
pa
c
it
or
a
r
e
given.
=
(
1)
=
(
2)
W
he
r
e
∆
a
nd
∆
a
r
e
the
c
u
r
r
e
nt
a
nd
volt
a
ge
r
ippl
e
,
r
e
s
pe
c
ti
ve
ly,
is
the
duty
c
yc
le,
is
the
s
witching
f
r
e
que
nc
y.
I
n
a
ddit
ion
to
the
c
omponent
s
e
lec
ti
on,
the
e
f
f
icie
n
c
y
of
the
DC
–
DC
boos
t
c
onve
r
ter
plays
a
c
r
it
ica
l
r
ole
in
the
ove
r
a
ll
s
ys
tem
pe
r
f
or
manc
e
.
C
onve
r
te
r
e
f
f
icie
nc
y
c
a
n
be
e
xpr
e
s
s
e
d
a
s
(
3)
:
=
(
3)
whe
r
e
a
nd
r
e
pr
e
s
e
nt
the
output
a
nd
input
powe
r
of
the
c
onve
r
ter
,
r
e
s
pe
c
ti
ve
ly.
T
he
major
s
our
c
e
s
of
los
s
in
the
c
onve
r
te
r
a
r
e
the
s
witching
los
s
e
s
in
the
M
OSF
E
T
,
c
onduc
ti
on
los
s
e
s
in
the
indu
c
tor
a
nd
c
a
pa
c
it
or
s
,
a
nd
f
or
wa
r
d
volt
a
ge
d
r
op
a
c
r
os
s
the
diode.
T
he
s
e
lec
ted
c
omponents
we
r
e
c
hos
e
n
to
mi
nim
ize
thes
e
los
s
e
s
while
maintaining
low
c
os
t
a
nd
e
a
s
e
o
f
im
pleme
ntation.
I
n
pa
r
ti
c
ula
r
,
the
us
e
of
a
S
c
hott
ky
diode
r
e
duc
e
s
c
onduc
ti
on
los
s
e
s
,
while
the
s
e
lec
ted
s
witc
hing
f
r
e
que
nc
y
of
20
kHz
pr
ov
ides
a
c
ompr
omi
s
e
be
twe
e
n
e
f
f
icie
nc
y
a
nd
dyna
mi
c
r
e
s
pons
e
.
T
his
de
s
ign
a
p
pr
oa
c
h
e
ns
ur
e
s
s
table
ope
r
a
ti
on
unde
r
va
r
ying
ir
r
a
dianc
e
c
ondit
ions
while
r
e
maining
s
uit
a
ble
f
or
e
duc
a
ti
ona
l
a
nd
e
xpe
r
im
e
ntal
a
ppli
c
a
ti
ons
.
E
S
P
32
is
a
low
-
c
os
t
mi
c
r
oc
ontr
oll
e
r
,
whic
h
f
e
a
t
ur
e
s
a
dua
l
-
c
or
e
pr
oc
e
s
s
or
,
int
e
gr
a
ted
W
i
-
F
i
a
nd
B
luetooth
c
onne
c
ti
vit
y,
a
nd
mul
ti
ple
P
W
M
c
ha
nne
ls
[
24]
.
T
he
s
e
c
a
pa
bil
it
ies
make
it
s
uit
a
ble
f
or
r
e
a
l
-
ti
me
c
ontr
ol
a
nd
I
o
T
da
ta
c
omm
unica
ti
on
withi
n
a
c
o
mpac
t
a
nd
low
-
c
os
t
platf
or
m.
T
wo
high
-
pr
e
c
is
ion
I
NA
219
s
e
ns
or
s
a
r
e
us
e
d
to
mea
s
ur
e
c
ur
r
e
nt
a
nd
volt
a
ge
on
both
the
input
a
nd
output
s
ides
o
f
the
c
onve
r
t
e
r
.
E
a
c
h
s
e
ns
or
c
omm
unica
tes
with
the
E
S
P
32
thr
ough
th
e
I
2C
int
e
r
f
a
c
e
,
with
unique
a
ddr
e
s
s
e
s
(
0
×
40
a
nd
0
×
44)
a
s
s
igned
to
pr
e
ve
nt
da
ta
ove
r
lap.
T
he
s
e
ns
or
s
p
r
ovide
c
a
li
br
a
ted
mea
s
ur
e
ments
of
c
ur
r
e
nt
,
vol
tage
,
a
nd
powe
r
,
e
na
bli
ng
a
c
c
ur
a
te
mon
it
or
ing
of
s
ys
tem
pe
r
f
or
manc
e
a
nd
a
lgor
i
thm
e
f
f
icie
nc
y
.
F
igur
e
2.
E
qu
ivale
nt
c
ir
c
uit
of
a
DC
-
DC
boos
t
c
onve
r
ter
4.
S
OF
T
WAR
E
I
M
P
L
E
M
E
N
T
AT
I
ON
AN
D
CON
T
ROL
S
T
RA
T
E
GY
4.
1.
S
ys
t
e
m
p
r
ogr
am
m
i
n
g
e
n
viron
m
e
n
t
T
he
s
of
twa
r
e
f
r
a
mew
or
k
ha
s
be
e
n
de
s
igned
us
ing
the
Ar
duino
int
e
gr
a
ted
de
ve
lopm
e
nt
e
nvir
onment
(
I
DE
)
,
whic
h
p
r
ovides
a
c
onve
nient
platf
or
m
f
o
r
wr
it
ing
c
ode
to
de
bug
the
E
S
P
32
mi
c
r
oc
ontr
o
ll
e
r
.
T
he
E
S
P
32
is
p
r
ogr
a
mm
e
d
us
ing
C
+
+
ba
s
e
d
ope
n
-
s
our
c
e
li
br
a
r
ies
to
im
pleme
nt
Algo
r
it
hm
1,
including
r
e
a
l
-
ti
me
da
ta
c
oll
e
c
ti
on
f
r
om
the
ha
ndli
ng
I
NA
219
s
e
ns
or
s
,
r
unning
the
M
P
P
T
c
ontr
ol
a
lgor
it
hms
f
or
a
djus
ti
ng
duty
c
yc
le
to
ge
ne
r
a
te
the
P
W
M
s
ignal,
a
s
we
ll
a
s
uploading
da
ta
to
the
moni
tor
ing
da
s
hboa
r
d
via
M
QT
T
c
omm
unica
ti
on
pr
otocols
.
S
e
r
ial
c
omm
unica
ti
o
n
with
M
AT
L
AB
e
na
bli
ng
loca
l
da
ta
a
c
quis
it
ion
a
nd
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2088
-
8708
I
nt
J
E
lec
&
C
omp
E
ng
,
Vol
.
16
,
No.
5
,
Oc
tober
20
26
:
2282
-
2293
2286
vis
ua
li
z
a
ti
on
dur
ing
tes
ti
ng
o
r
tr
a
c
ing
the
P
-
V
a
nd
I
-
V
c
ur
ve
s
of
the
P
V
modul
e
to
e
na
ble
s
tudents
to
moni
tor
how
a
lgor
it
hms
r
e
s
pond
to
di
f
f
e
r
e
nt
ir
r
a
dianc
e
leve
ls
.
All
c
ont
r
ol
a
lgo
r
it
hms
we
r
e
r
u
n
in
r
e
a
l
ti
me
,
a
l
ong
wit
h
a
n
o
pti
mi
z
e
d
s
a
m
pli
ng
pe
r
iod
t
o
e
ns
ur
e
that
t
he
s
ys
tem
is
r
e
s
po
ns
ive
wi
thou
t
ove
r
loa
ding
the
mi
c
r
oc
o
ntr
o
ll
e
r
.
Algor
it
hm
1
.
Algo
r
it
hm
i
mpl
e
mente
d
on
E
S
P
32
Include libraries, define and initialize variables and objects;
Check sensors communication;
Connect to Wi
-
Fi network;
Connect to the MQTT broker;
Loop
function
Data_Reading function:
V_pv, I_pv, P_pv ← V, I, P values → INA219 sensor;
V_load, I_load, P_load ← V, I, P values → INA219 sensor;
MPPT_Algorithm function:
if
P_O
then
P_O algorithm;
end
if
FLC
then
FLC algorithm;
end
if
I
-
V_P
-
V_Tracer
then
Duty_Cycle Sweeping;
end
if
publish time
then
if
failed to connected
then
Reconnect function;
end
Publish data to the MQTT broker;
end
Wire transmission of data;
end
4.
2.
P
e
r
t
u
r
b
an
d
ob
s
e
r
ve
algorit
h
m
T
he
pe
r
tur
b
a
nd
obs
e
r
ve
(
P
&O)
a
lgo
r
it
hm
wa
s
im
pleme
nted
a
s
the
ba
s
e
li
ne
M
P
P
T
tec
hnique
be
c
a
us
e
of
it
s
s
im
pli
c
it
y
a
nd
wide
us
e
in
e
duc
a
ti
ona
l
a
nd
indus
tr
ial
a
ppli
c
a
ti
ons
.
T
he
a
lgor
it
hm
w
or
ks
by
pe
r
iodi
c
a
ll
y
pe
r
tur
bing
the
c
onve
r
ter
’
s
duty
c
yc
le
a
nd
obs
e
r
ving
the
r
e
s
ult
ing
c
ha
nge
in
output
powe
r
.
I
f
the
powe
r
incr
e
a
s
e
s
a
f
ter
the
pe
r
tu
r
ba
ti
on,
the
a
djus
t
ment
c
onti
nue
s
in
the
s
a
me
di
r
e
c
ti
on;
i
f
it
de
c
r
e
a
s
e
s
,
the
pe
r
tur
ba
ti
on
dir
e
c
ti
on
is
r
e
ve
r
s
e
d.
T
his
it
e
r
a
ti
ve
pr
oc
e
s
s
e
na
ble
s
the
s
y
s
tem
to
tr
a
c
k
the
maximum
powe
r
point
(
M
P
P
)
but
c
a
n
lea
d
to
s
mall
os
c
il
lations
a
r
ound
it
dur
ing
s
tea
dy
-
s
tate
c
ondit
ions
[
25]
,
[
26]
.
F
igur
e
3
pr
e
s
e
nts
the
P
&O
a
lgor
it
hm
logi
c
,
whic
h
c
onti
nu
ous
ly
mea
s
ur
e
s
the
P
V
volt
a
ge
a
nd
c
u
r
r
e
nt,
c
om
putes
the
ins
tanta
ne
ous
powe
r
,
a
nd
upda
tes
the
P
W
M
duty
c
yc
le
ge
ne
r
a
ted
with
a
20
kHz
s
witching
f
r
e
que
nc
y.
F
igur
e
3.
P
&O
a
lgor
it
hm
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
E
lec
&
C
omp
E
ng
I
S
S
N:
2088
-
8708
L
ow
-
c
os
t
e
duc
ati
onal
pr
otot
y
pe
for
I
o
T
-
bas
e
d
P
V
e
ne
r
gy
monitor
ing
…
(
A
bde
lmalek
M
imouni
)
2287
4.
3.
F
u
z
z
y
logi
c
c
on
t
r
ol
(
F
L
C)
As
a
s
uppleme
nt
to
the
c
las
s
ica
l
method,
the
F
L
C
a
lgor
it
hm
wa
s
a
ls
o
de
ve
loped
to
de
mons
tr
a
te
a
n
int
e
ll
igent
M
P
P
T
pr
oc
e
dur
e
that
doe
s
not
r
e
qui
r
e
a
mathe
matica
l
model
o
f
the
P
V
s
ys
tem.
T
he
c
ontr
ol
a
lgor
it
hm
take
s
2
input
pa
r
a
mete
r
s
,
e
r
r
or
(
)
a
nd
c
ha
nge
in
e
r
r
or
(
)
,
whic
h
a
r
e
de
f
ined
a
s
the
s
lope
a
nd
the
va
r
iabili
ty
o
f
the
P
-
V
c
ha
r
a
c
ter
is
ti
c
s
o
f
the
P
V
mo
dule.
T
he
c
ont
r
ol
a
lgo
r
it
hm
then
p
r
oduc
e
s
the
ou
tp
ut
(
)
,
whic
h
is
the
c
ha
nge
in
the
duty
c
yc
le.
E
qua
ti
ons
(
4
)
a
nd
(
5
)
s
how
the
de
f
in
it
ion
e
xpr
e
s
s
ion
of
the
inp
uts
(
)
a
nd
(
)
with
s
a
mpl
ing
ti
mes
k
[
13]
,
[
27
]
.
(
)
=
(
)
−
(
−
1
)
(
)
−
(
−
1
)
(
4)
(
)
=
(
)
−
(
−
1
)
(
5)
whe
r
e
(
)
a
nd
(
)
a
r
e
r
e
s
pe
c
ti
ve
ly
the
powe
r
a
nd
the
volt
a
ge
of
the
P
V
pa
ne
l.
T
he
f
uz
z
y
c
ontr
ol
pr
oc
e
s
s
c
ons
is
ts
of
thr
e
e
main
s
t
a
ge
s
:
f
uz
z
if
ica
ti
on,
inf
e
r
e
nc
e
,
a
nd
de
f
uz
z
if
ica
ti
on,
a
s
pr
e
s
e
nted
in
F
igur
e
4.
Dur
ing
f
uz
z
if
ica
ti
on,
th
e
input
va
r
iable
s
a
nd
a
r
e
c
onve
r
ted
int
o
li
ngui
s
ti
c
va
r
iable
s
us
ing
f
ive
tr
iangula
r
membe
r
s
hip
f
unc
t
ions
:
ne
ga
ti
ve
big
(
NB
)
,
ne
ga
ti
ve
s
mall
(
NS)
,
z
e
r
o
(
Z
E
)
,
pos
it
ive
s
mall
(
P
S
)
,
a
nd
pos
it
ive
big
(
P
B
)
.
T
he
s
e
membe
r
s
hip
f
unc
ti
ons
we
r
e
s
e
lec
ted
to
pr
ovide
a
ba
lanc
e
be
twe
e
n
c
ontr
ol
r
e
s
olut
ion
a
nd
c
omput
a
ti
ona
l
e
f
f
i
c
ienc
y
s
uit
a
ble
f
or
r
e
a
l
-
ti
me
im
pleme
ntation
on
th
e
E
S
P
32
.
T
he
inf
e
r
e
nc
e
e
ngine
is
ba
s
e
d
on
the
M
a
mdani
me
thod
a
nd
e
mpl
oys
a
r
ule
ba
s
e
c
ompos
e
d
of
25
r
ules
.
T
he
s
e
r
ules
a
r
e
de
s
igned
to
r
e
f
lec
t
the
nonli
ne
a
r
be
ha
vior
of
the
P
V
s
ys
tem
a
nd
to
guide
the
ope
r
a
ti
ng
poin
t
towa
r
d
the
M
P
P
.
E
a
c
h
r
ule
de
f
ines
the
r
e
lations
hip
be
twe
e
n
the
input
s
(
,
)
a
nd
the
output
(
)
,
e
na
bli
ng
a
da
pti
ve
a
djus
tm
e
nt
of
the
duty
c
yc
le
unde
r
c
ha
n
ging
c
ondit
ions
.
F
inally
,
the
de
f
uz
z
if
ica
ti
on
s
tage
us
e
s
the
c
e
ntr
oid
(
c
e
nter
of
gr
a
vit
y
)
method
to
c
onve
r
t
th
e
a
ggr
e
ga
ted
f
uz
z
y
output
int
o
a
c
r
is
p
c
ont
r
ol
s
ig
na
l.
T
his
method
e
ns
ur
e
s
s
moot
h
tr
a
ns
it
ions
in
the
duty
c
yc
l
e
a
nd
c
ontr
ibut
e
s
to
r
e
duc
ing
os
c
il
lations
a
r
ound
th
e
M
P
P
.
F
igur
e
4.
F
uz
z
y
logi
c
c
ontr
ol
s
tr
a
tegy
4.
4.
Dat
a
Ac
q
u
is
it
ion
an
d
I
oT
in
t
e
gr
at
ion
I
n
a
ddit
ion
to
the
c
ont
r
ol
logi
c
,
the
E
S
P
32
c
onti
n
uous
ly
c
oll
e
c
ts
volt
a
ge
a
nd
c
ur
r
e
nt
f
r
o
m
both
the
P
V
input
a
nd
c
onve
r
ter
ou
tput
,
then
c
omput
e
s
powe
r
a
nd
duty
c
yc
le
va
lues
.
T
he
E
S
P
32
c
omm
unic
a
ti
on
with
a
laptop
pr
ovides
loca
l
r
e
a
l
-
ti
me
da
ta
vis
ua
li
z
a
ti
on
a
nd
s
tor
a
ge
in
ti
mes
tampe
d
C
S
V
f
i
les
f
or
s
ubs
e
que
nt
a
na
lys
is
us
ing
the
M
AT
L
AB
e
nvir
onment.
T
he
s
e
e
na
ble
a
n
a
c
quis
it
ion
r
outi
ne
f
or
on
-
de
vice
tr
a
c
in
g
of
P
-
V
a
nd
I
-
V
c
u
r
ve
s
by
incr
e
menta
ll
y
s
we
e
ping
the
c
onve
r
ter
du
ty
c
yc
le
f
r
om
0
to
0.
95
;
thi
s
r
outi
ne
c
a
n
be
ini
ti
a
ted
with
a
s
e
lec
ti
on
s
witch.
T
he
E
S
P
32
c
on
ne
c
ts
to
a
W
i
-
F
i
ne
twor
k
a
nd
tr
a
ns
mi
ts
J
S
ON
-
f
o
r
matted
mea
s
ur
e
ments
tele
metr
y
to
the
T
hings
B
oa
r
d
platf
o
r
m
us
ing
M
QT
T
pr
otocol
.
T
hings
B
oa
r
d
is
a
n
ope
n
-
s
our
c
e
I
oT
platf
or
m
tha
t
s
uppor
ts
de
vice
c
onne
c
ti
vit
y,
da
ta
a
c
quis
it
ion,
pr
oc
e
s
s
ing,
vis
ua
li
z
a
ti
on,
r
ule
-
ba
s
e
d
a
utom
a
ti
on,
a
nd
de
vice
mana
ge
ment
[
28]
.
I
t
a
ll
ows
c
omm
unica
ti
on
thr
ough
wide
ly
us
e
d
I
oT
pr
otocols
s
uc
h
a
s
M
QT
T
,
C
oAP,
a
nd
HT
T
P
,
a
nd
c
a
n
ope
r
a
te
wi
th
S
QL
,
No
S
QL
,
or
hybr
id
da
taba
s
e
a
r
c
hit
e
c
tur
e
s
.
T
he
platf
o
r
m
is
a
v
a
il
a
ble
in
thr
e
e
de
ploym
e
nt
opti
ons
:
the
f
ul
ly
ope
n
-
s
our
c
e
C
omm
unit
y
E
dit
ion
,
the
f
e
a
tur
e
-
r
ich
P
r
of
e
s
s
ional
E
dit
ion
,
a
nd
a
c
loud
-
ba
s
e
d
platf
or
m
-
as
-
a
-
s
e
r
vice
ve
r
s
ion.
I
n
the
pr
e
s
e
nt
wor
k
,
the
C
omm
unit
y
E
d
it
ion
wa
s
a
dopted
f
or
im
pleme
nti
ng
the
moni
tor
ing
int
e
r
f
a
c
e
.
T
his
e
dit
ion
pr
ovides
ti
me
-
s
e
r
ies
plot
s
a
nd
la
s
t
va
lue
c
a
r
ds
f
or
quick
s
tatus
c
he
c
ks
,
with
widge
ts
that
s
uppor
t
z
oomi
ng,
r
a
nge
s
e
lec
ti
on,
a
nd
e
xpor
t
o
f
his
tor
ica
l
da
ta
f
or
pos
t
-
lab
a
na
lys
is
.
T
he
f
r
a
mew
or
k
de
ve
loped
uti
li
z
ing
the
M
QT
T
c
omm
unica
ti
on
pr
otocol
f
o
r
d
a
ta
tr
a
ns
mi
s
s
ion
hinges
on
the
publi
s
h
-
s
ubs
c
r
ibe
model,
in
whic
h
the
E
S
P
32
a
c
ts
a
s
the
publi
s
he
r
a
nd
the
de
s
igned
da
s
hboa
r
d
on
the
T
hings
B
oa
r
d
platf
or
m
s
e
r
v
e
s
a
s
the
s
ubs
c
r
iber
,
a
s
s
hown
in
F
igur
e
5.
T
he
r
e
a
l
-
ti
me
a
na
lys
is
e
na
ble
s
the
lea
r
ne
r
s
to
tr
a
c
k
the
dyna
mi
c
va
r
iation
of
s
ys
tem
va
r
iable
s
,
unde
r
s
tand
tr
e
nds
,
a
nd
a
na
lyz
e
the
pe
r
f
or
manc
e
of
a
lgor
it
h
ms
thr
ough
the
d
e
s
igned
da
s
hboa
r
d.
T
he
de
s
igned
f
r
a
mew
or
k
e
nha
nc
e
s
c
r
uc
ial
lea
r
ning
c
onc
e
pts
r
e
late
d
to
da
ta
a
c
quis
it
ion,
c
omm
unica
ti
on
pr
otocols
,
a
nd
vis
ua
li
z
a
ti
on
on
c
lo
ud
platf
or
ms
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2088
-
8708
I
nt
J
E
lec
&
C
omp
E
ng
,
Vol
.
16
,
No.
5
,
Oc
tober
20
26
:
2282
-
2293
2288
F
igur
e
5.
M
QT
T
c
omm
unica
ti
on
p
r
otocol
a
r
c
hit
e
c
t
ur
e
5.
E
XP
E
RI
M
E
NT
AL
S
E
T
UP
F
igur
e
6
pr
e
s
e
nts
the
e
xpe
r
im
e
ntal
va
li
da
ti
on
s
e
tup
of
the
pr
opos
e
d
s
ys
tem.
T
he
pr
otot
ype
wa
s
e
va
luate
d
unde
r
na
tur
a
l
s
unli
ght
us
ing
a
c
ompac
t
be
nc
h
that
include
s
the
P
V
modul
e
,
c
us
tom
DC
-
DC
boos
t
c
onve
r
ter
,
va
r
iable
r
e
s
is
ti
ve
load,
a
s
we
ll
a
s
the
E
S
P
32
mi
c
r
oc
ont
r
oll
e
r
a
nd
I
NA
219
s
e
ns
or
s
a
t
the
c
ontr
ol
-
s
e
ns
ing
boa
r
d.
E
va
luation
mea
s
ur
e
ment
e
quipm
e
nt
c
ompr
is
e
d
a
digi
tal
mul
ti
mete
r
,
a
n
os
c
il
los
c
ope
f
or
wa
ve
f
or
m
ins
pe
c
ti
on,
a
nd
lux
mete
r
f
or
c
ontextu
a
li
z
ing
ope
r
a
ti
ng
c
ondit
ions
.
S
e
r
ial
loggi
ng
to
M
AT
L
AB
s
uppor
ted
gr
ound
-
tr
uth
vis
ua
li
z
a
ti
on
a
longs
ide
th
e
I
o
T
da
s
hboa
r
d.
T
o
ke
e
p
the
de
s
ign
r
e
pr
oduc
ibl
e
f
or
lab
c
our
s
e
s
,
the
c
us
tom
boos
t
s
tage
us
e
d
wide
ly
a
va
il
a
ble
pa
r
ts
:
a
S
c
hott
ky
diode
(
1N5822)
,
a
200
µ
H
i
nduc
tor
,
two
100
µ
F
e
lec
tr
olyt
ics
,
a
nd
a
low
-
R
ds
(
on)
M
OSF
E
T
(
I
R
F
Z
44)
.
T
his
s
e
lec
ti
on
pr
ovides
low
r
i
pple
a
nd
s
table
tr
a
ns
ient
be
ha
vior
a
t
modes
t
c
os
t,
a
ppr
opr
iate
f
or
s
tudent
buil
ds
.
T
a
ble
1
s
umm
a
r
ize
s
the
e
xpe
r
im
e
ntal
c
ondit
ions
.
F
igur
e
6.
E
xpe
r
im
e
ntal
va
li
da
ti
on
s
e
tup
of
the
pr
o
pos
e
d
s
ys
tem
T
a
ble
1.
E
xpe
r
i
menta
l
c
ondit
ions
P
a
r
a
me
te
r
V
a
lu
e
P
V
pa
ne
l
6V
/
8W
I
r
r
a
di
a
nc
e
N
a
tu
r
a
l
s
unl
ig
ht
(
~
600
–
900 W
/m
²)
T
e
mpe
r
a
tu
r
e
A
mbi
e
nt
(
~
25
–
30°C
)
S
a
mpl
in
g t
im
e
100 ms
S
w
it
c
hi
ng f
r
e
que
nc
y
20 kHz
L
oa
d
V
a
r
ia
bl
e
r
e
s
is
ti
ve
D
ur
a
ti
on
~
15
–
20 mi
n pe
r
t
e
s
t
6.
RE
S
UL
T
S
AN
D
DI
S
CU
S
S
I
ON
I
n
the
c
ur
r
e
nt
c
onf
igu
r
a
ti
on,
the
I
-
V
a
nd
P
-
V
c
ha
r
a
c
ter
is
ti
c
s
a
r
e
ge
ne
r
a
ted
by
va
r
ying
the
c
onve
r
ter
’
s
duty
c
yc
le
with
the
P
V
pa
ne
l
s
ti
ll
a
tt
a
c
he
d
to
th
e
boos
t
c
onve
r
ter
.
T
he
r
e
s
ult
ing
c
ha
r
a
c
ter
is
ti
c
s
,
s
hown
in
F
igur
e
7
(
a
)
,
we
r
e
r
e
c
or
de
d
unde
r
the
e
xpe
r
im
e
nta
l
tes
t
c
ondit
ions
a
nd
us
e
d
to
identi
f
y
the
maximu
m
powe
r
point
,
whic
h
wa
s
late
r
a
dopted
a
s
a
r
e
f
e
r
e
nc
e
f
o
r
e
va
luating
the
M
P
P
T
a
lgor
it
hms
.
Ove
r
a
ll
,
the
c
u
r
ve
s
f
oll
ow
the
typi
c
a
l
be
ha
vior
of
a
photovol
taic
modul
e
,
wit
h
a
n
e
xtende
d
qua
s
i
-
c
ons
tant
c
ur
r
e
nt
r
e
gion
f
oll
owe
d
by
a
c
lea
r
kne
e
point
.
B
a
s
e
d
on
th
e
I
–
V
c
u
r
ve
,
the
s
hor
t
-
c
ir
c
uit
c
u
r
r
e
nt
wa
s
e
s
ti
ma
ted
to
be
a
pp
r
o
xim
a
te
ly
1.
5
–
1
.
55
A
,
w
he
r
e
a
s
the
c
ur
r
e
nt
a
pp
r
oa
c
he
d
z
e
r
o
a
t
a
n
o
pe
n
-
c
i
r
c
ui
t
vo
lt
a
ge
of
a
bou
t
6
.
5
–
7
V
.
T
he
c
or
r
e
s
pond
ing
P
–
V
c
ur
ve
pr
e
s
e
n
ts
a
s
ing
le
a
nd
we
l
l
-
de
f
in
e
d
maxi
mum
a
r
ou
nd
≈
5
V
a
nd
≈
1
.
34
A
,
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
E
lec
&
C
omp
E
ng
I
S
S
N:
2088
-
8708
L
ow
-
c
os
t
e
duc
ati
onal
pr
otot
y
pe
for
I
o
T
-
bas
e
d
P
V
e
ne
r
gy
monitor
ing
…
(
A
bde
lmalek
M
imouni
)
2289
yield
ing
≈
6
.
7
W
.
How
e
ve
r
,
thi
s
c
ha
r
a
c
ter
iza
ti
on
method
ha
s
a
n
inher
e
nt
li
mi
tation:
be
c
a
us
e
the
s
w
e
e
p
wa
s
pe
r
f
or
med
thr
ough
duty
-
c
yc
le
va
r
iation
while
the
pa
ne
l
r
e
maine
d
c
oupled
to
the
boos
t
c
onve
r
ter
,
the
tr
ue
ter
mi
na
l
ope
r
a
ti
ng
li
mi
ts
of
the
P
V
modul
e
c
o
uld
not
be
f
ull
y
r
e
a
c
he
d.
T
he
r
e
f
or
e
,
I
s
c
a
nd
Voc
we
r
e
de
ter
mi
ne
d
s
e
pa
r
a
tely
thr
ough
indepe
nde
nt
mea
s
ur
e
ments
.
T
he
M
P
P
T
i
mpl
e
menta
ti
on
r
e
s
ult
s
we
r
e
logge
d
a
nd
a
na
lyze
d
in
M
AT
L
AB
unde
r
identica
l
ir
r
a
dianc
e
a
nd
load
c
ondit
ions
.
F
igur
e
7(
b)
p
r
e
s
e
nts
a
c
ompar
is
on
of
the
duty
c
yc
les
c
omput
e
d
on
the
E
S
P
32
f
or
the
F
L
C
a
nd
the
P
&O
method.
B
e
c
a
us
e
the
duty
c
yc
le
gove
r
ns
e
ne
r
gy
t
r
a
ns
f
e
r
in
the
boos
t
c
onv
e
r
ter
,
it
s
tempor
a
l
be
ha
vior
r
e
f
lec
ts
e
a
c
h
c
ontr
oll
e
r
’
s
a
bil
i
ty
to
tr
a
c
k
the
M
P
P
in
r
e
a
l
ti
me.
T
he
F
L
C
s
e
tt
les
mor
e
r
a
pidl
y
a
nd
maintains
a
mar
ke
dly
s
maller
s
tea
dy
-
s
tate
os
c
il
lation,
indi
c
a
ti
ng
f
a
s
ter
c
onve
r
ge
nc
e
a
nd
lowe
r
r
ippl
e
.
B
y
c
ontr
a
s
t,
P
&O
e
xhibi
ts
pe
r
s
is
tent
pe
r
tur
ba
ti
on
c
yc
les
,
whic
h
c
a
n
r
e
duc
e
e
ne
r
gy
e
f
f
icie
nc
y
a
nd
incr
e
a
s
e
c
umul
a
ti
ve
s
witching
s
tr
e
s
s
on
the
powe
r
s
tage
.
(
a
)
(
b)
F
igur
e
7.
E
xpe
r
im
e
ntal
(
a
)
I
-
V
a
nd
P
-
V
c
ha
r
a
c
ter
is
ti
c
s
,
a
nd
(
b
)
duty
c
yc
le
c
ompar
is
on
T
o
qua
nti
tatively
e
va
luate
the
pe
r
f
or
manc
e
of
t
he
im
pleme
nted
M
P
P
T
a
lgor
it
hms
,
s
e
ve
r
a
l
ke
y
pe
r
f
or
manc
e
met
r
ics
we
r
e
de
f
ined.
T
he
tr
a
c
king
e
f
f
icie
nc
y
(
)
is
e
xpr
e
s
s
e
d
a
s
the
r
a
ti
o
be
twe
e
n
t
he
e
xtr
a
c
ted
powe
r
a
nd
the
theor
e
ti
c
a
l
maximum
po
we
r
a
va
il
a
ble
f
r
om
the
P
V
modul
e
(
6)
a
nd
the
s
tea
dy
-
s
tate
r
ippl
e
wa
s
c
ons
ider
e
d
to
a
s
s
e
s
s
the
s
tabili
ty
of
the
c
ontr
ol
a
lgor
it
hm
a
r
ound
the
M
P
P
,
de
f
ined
in
(
7
)
.
=
(
6)
=
−
×
100
(
7)
whe
r
e
r
e
pr
e
s
e
nts
the
mea
s
ur
e
d
output
powe
r
unde
r
M
P
P
T
ope
r
a
ti
on
a
nd
c
or
r
e
s
ponds
to
the
maximum
powe
r
obtaine
d
f
r
om
the
I
-
V/P
-
V
c
ur
ve
tr
a
c
ing.
F
igur
e
8
(
a
)
s
hows
that
both
methods
a
djus
t
the
P
V
output
volt
a
ge
.
F
L
C
maintains
the
ope
r
a
ti
ng
point
ne
a
r
the
M
P
P
with
lowe
r
r
ippl
e
a
nd
high
e
r
s
tabili
ty.
F
igu
r
e
8(
b
)
pr
e
s
e
nts
the
output
pow
e
r
.
P
&O
int
r
oduc
e
s
lar
ge
r
f
luctua
ti
ons
ne
a
r
the
M
P
P
,
whil
e
F
L
C
r
e
a
c
he
s
s
tea
dy
ope
r
a
ti
on
f
a
s
ter
a
nd
de
li
ve
r
s
a
mo
r
e
c
onti
nuous
powe
r
pr
of
il
e
.
F
L
C
yields
s
tr
onge
r
pe
r
f
or
manc
e
be
c
a
us
e
it
li
mi
ts
los
s
e
s
a
nd
s
uppor
ts
unif
or
m
e
ne
r
gy
e
xtr
a
c
ti
on
.
T
he
r
e
s
ult
s
indi
c
a
te
that
F
L
C
pr
ovides
h
igher
pr
e
c
is
ion
a
r
ound
the
M
P
P
.
T
he
F
L
C
a
lgor
it
hm
mana
ge
d
to
a
tt
a
in
a
n
a
ve
r
a
ge
e
f
f
icie
nc
y
of
t
r
a
c
king
o
f
84
%
,
whic
h
is
much
higher
than
the
P
&O
a
lgor
it
hm’
s
82.
5
%
.
I
n
a
ddit
ion,
f
r
om
the
r
e
s
ult
,
th
e
F
L
C
de
mons
tr
a
ted
a
n
a
ve
r
a
ge
powe
r
ga
in
of
1.
5%
.
T
he
s
tea
dy
s
tate
r
ippl
e
is
a
nother
mea
s
ur
e
of
the
s
tabili
ty
of
the
c
ont
r
ol
s
c
he
mes
.
T
he
P
&O
a
lgor
it
hm
ha
s
a
r
ippl
e
of
a
bout
1.
8
%
,
whe
r
e
a
s
the
F
L
C
method
ha
s
a
r
ippl
e
of
jus
t
0.
5
%
,
ind
ica
ti
ng
be
tt
e
r
s
tabili
ty
a
nd
les
s
os
c
il
lations
a
r
ound
the
M
P
P
.
M
P
P
T
tr
a
c
king
e
f
f
icie
nc
ies
r
e
por
ted
in
the
l
it
e
r
a
tur
e
a
r
e
mo
r
e
than
90%
in
c
ontr
oll
e
d
lab
c
ondit
ions
us
ing
high
-
pr
e
c
is
ion
s
e
ns
or
s
a
nd
s
table
s
our
c
e
s
of
i
r
r
a
dianc
e
[
8]
,
[
29]
,
[
30]
.
I
n
c
ontr
a
s
t,
the
r
e
s
ult
s
r
e
po
r
ted
in
our
pa
pe
r
(
82
.
5%
f
or
P
&O
a
nd
84%
f
o
r
F
L
C
)
a
r
e
lowe
r
due
to
the
l
ow
-
c
os
t
e
mbedde
d
platf
or
m
us
e
d,
the
ve
r
y
s
mall
r
e
s
olut
io
n
of
the
I
NA
219
s
e
ns
or
s
,
a
nd
ir
r
a
dianc
e
a
nd
tem
pe
r
a
tur
e
nor
maliza
ti
on
in
outdoo
r
e
xpe
r
i
ments
.
F
ur
ther
,
th
e
r
e
a
l
-
wor
ld
e
nvi
r
onment
p
r
e
s
e
nts
va
r
iabili
ty
that
is
o
f
ten
not
pr
e
s
e
nt
in
c
ontr
oll
e
d
s
ys
tems
.
De
s
pit
e
thes
e
c
ons
tr
a
int
s
,
the
p
r
opos
e
d
s
ys
tem
pr
ovides
c
ons
is
tent
a
nd
r
e
li
a
ble
c
ompar
a
ti
ve
r
e
s
ult
s
,
de
mons
tr
a
ti
ng
the
e
f
f
e
c
ti
ve
ne
s
s
of
the
F
L
C
a
lgor
it
hm
in
im
pr
oving
s
tabili
ty
a
nd
e
ne
r
gy
e
xtr
a
c
ti
on
withi
n
a
pr
a
c
ti
c
a
l
a
nd
low
-
c
os
t
im
pleme
ntation
f
r
a
mew
or
k
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2088
-
8708
I
nt
J
E
lec
&
C
omp
E
ng
,
Vol
.
16
,
No.
5
,
Oc
tober
20
26
:
2282
-
2293
2290
B
y
e
xe
c
uti
ng
both
a
lgor
it
hms
on
the
s
a
me
plat
f
or
m,
the
s
tudents
will
be
a
ble
to
c
ompar
e
a
nd
c
ontr
a
s
t
the
pe
r
f
or
manc
e
s
unde
r
s
im
il
a
r
c
ondit
ion
s
.
S
pe
c
if
ica
ll
y,
they
will
be
a
ble
to
obs
e
r
ve
a
nd
s
tudy
the
manne
r
in
whic
h
F
L
C
he
lps
in
r
e
duc
ing
s
tea
dy
-
s
tate
os
c
il
lations
,
e
nha
nc
e
s
the
r
a
te
of
c
onve
r
ge
nc
e
,
a
nd
s
us
tains
s
upe
r
ior
pe
r
f
o
r
manc
e
s
unde
r
s
udde
n
c
ha
nge
s
in
i
r
r
a
dianc
e
.
T
he
int
e
gr
a
t
ion
o
f
I
o
T
f
unc
ti
ona
li
ti
e
s
e
na
bles
r
e
a
l
-
ti
me
s
upe
r
vis
ion,
a
nomaly
de
tec
ti
on,
a
nd
pr
e
ve
nti
ve
maintena
nc
e
,
ther
e
by
e
nha
nc
ing
op
e
r
a
ti
ona
l
e
f
f
icie
nc
y
a
nd
c
ontr
ibu
ti
ng
to
longer
s
ys
tem
li
f
e
ti
me
thr
ough
mor
e
e
f
f
e
c
ti
ve
e
ne
r
gy
mana
ge
ment.
F
igur
e
9
il
lus
tr
a
tes
the
de
ve
loped
c
us
tom
da
s
hboa
r
d,
whi
c
h
pr
ovides
a
c
ompl
e
te
vis
ua
li
z
a
ti
on
int
e
r
f
a
c
e
,
i
nc
ludi
ng
time
-
s
e
r
ies
c
ha
r
ts
f
or
volt
a
ge
,
powe
r
,
c
ur
r
e
nt
,
a
n
d
duty
c
yc
le
mea
s
ur
e
ments
a
nd
c
a
r
ds
dis
playing
the
late
s
t
va
lues
of
the
moni
tor
e
d
pa
r
a
mete
r
s
.
B
y
inco
r
por
a
ti
ng
thi
s
I
o
T
laye
r
,
the
e
xpe
r
im
e
ntal
pr
ot
otype
is
tr
a
ns
f
or
med
int
o
a
n
int
e
ll
igent
moni
to
r
ing
platf
o
r
m
that
a
ll
ows
s
tudents
to
obs
e
r
ve
,
a
na
lyze
,
a
nd
int
e
r
a
c
t
with
s
ys
tem
be
ha
vior
in
r
e
a
l
t
im
e
.
(
a
)
(
b)
F
igur
e
8.
P
&O
a
nd
F
L
C
a
lgor
it
hm
e
xpe
r
im
e
ntal
r
e
s
ult
s
:
(
a
)
volt
a
ge
c
ompar
is
on
a
nd
(
b)
powe
r
c
ompar
is
on
F
igur
e
9.
M
onit
or
ing
da
s
hboa
r
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
E
lec
&
C
omp
E
ng
I
S
S
N:
2088
-
8708
L
ow
-
c
os
t
e
duc
ati
onal
pr
otot
y
pe
for
I
o
T
-
bas
e
d
P
V
e
ne
r
gy
monitor
ing
…
(
A
bde
lmalek
M
imouni
)
2291
T
he
va
li
d
a
ti
o
n
s
e
tu
p
us
e
s
a
l
ow
-
c
os
t
,
ope
n
-
s
our
c
e
plat
f
or
m
t
ha
t
b
r
i
ngs
to
ge
the
r
P
V
da
ta
a
c
qu
is
it
ion
,
M
P
P
T
c
on
tr
o
l
,
a
nd
I
o
T
-
ba
s
e
d
mon
it
o
r
in
g.
S
t
ude
n
t
s
c
a
n
view
r
e
a
l
-
ti
m
e
I
–
V
a
n
d
P
–
V
mea
s
u
r
e
me
nts
,
a
nd
t
he
s
ys
tem
inc
ludes
bo
th
P
&O
a
nd
F
L
C
M
P
P
T
metho
ds
to
a
ll
ow
s
t
r
a
igh
tf
or
wa
r
d
c
ompa
r
is
on
of
the
ir
pe
r
f
or
manc
e
.
A
de
d
ica
ted
I
o
T
lay
e
r
ha
ndles
c
on
ti
nuous
mo
nit
o
r
i
ng
a
nd
da
ta
lo
ggi
ng
wi
thou
t
dis
r
u
pti
ng
the
c
ont
r
ol
loop
.
B
e
c
a
us
e
the
p
r
oto
type
r
e
li
e
s
on
c
om
monl
y
a
va
i
lable
ha
r
dwa
r
e
a
n
d
ope
n
-
s
our
c
e
too
ls
,
it
is
e
a
s
y
t
o
r
e
p
r
oduc
e
a
nd
wo
r
ks
we
ll
f
or
labo
r
a
t
or
y
c
ou
r
s
e
s
a
n
d
pr
o
jec
t
-
ba
s
e
d
lea
r
ning
.
H
owe
ve
r
,
a
t
t
he
a
c
qu
is
it
i
on
s
tage
,
thi
s
im
p
leme
n
tati
on
us
e
s
s
e
ns
or
s
tha
t
c
a
n
on
ly
w
or
k
on
a
s
mal
l
-
s
c
a
le
P
V
s
ys
te
m
,
wh
ich
is
a
li
mi
t
i
ng
f
a
c
to
r
dur
i
ng
va
li
da
t
ion
on
hig
he
r
powe
r
s
c
e
na
r
ios
.
T
he
i
mpl
e
me
ntat
ion
doe
s
no
t
i
nc
lu
de
i
r
r
a
dia
ti
o
n
a
n
d
t
e
mper
a
tu
r
e
s
e
ns
or
s
,
whi
c
h
play
c
r
uc
ial
pa
r
ts
dur
ing
no
r
ma
li
z
a
ti
on
p
r
oc
e
s
s
e
s
on
P
-
V
a
nd
I
-
V
c
ur
v
e
s
to
a
s
s
e
s
s
M
P
P
T
r
e
s
ult
s
on
va
r
ying
ope
r
a
t
ing
c
ond
it
i
ons
.
I
mp
r
ove
m
e
nts
on
f
utu
r
e
i
mpl
e
men
tati
ons
c
ou
ld
incl
ude
s
c
a
li
n
g
up
thi
s
s
ys
tem
to
hi
ghe
r
c
a
pa
c
it
ies
whi
le
inco
r
po
r
a
t
ing
o
th
e
r
powe
r
s
our
c
e
s
t
o
f
a
c
i
li
tate
mi
c
r
o
-
g
r
id
va
li
d
a
ti
o
n.
7.
CONC
L
USI
ON
T
h
is
s
t
ud
y
de
s
c
r
ib
e
d
t
he
de
s
i
gn
,
de
ve
lo
pm
e
n
t
,
a
n
d
e
xp
e
r
i
men
ta
l
va
l
ida
t
io
n
of
a
l
ow
-
c
os
t
,
ope
n
-
s
o
u
r
c
e
p
r
ot
o
ty
pe
tha
t
in
te
g
r
a
t
e
s
P
V
s
e
ns
in
g
,
M
P
P
T
c
o
ntr
o
l
,
a
nd
I
o
T
mo
ni
to
r
in
g
o
n
a
n
E
S
P
32
wi
t
h
d
ua
l
I
N
A2
19
m
e
a
s
u
r
e
men
t
.
T
h
e
p
la
tf
o
r
m
e
na
bl
e
s
t
he
c
on
t
r
o
l
,
s
e
ns
in
g
,
a
n
d
m
on
i
to
r
in
g
o
f
da
ta
.
T
his
p
r
o
vi
de
s
r
a
pi
d
t
r
a
c
i
ng
of
I
-
V
a
nd
P
-
V
c
u
r
ve
s
,
s
im
ul
ta
ne
o
us
c
om
pa
r
is
o
n
a
nd
e
va
lu
a
t
io
n
o
f
P
&
O
a
nd
f
uz
z
y
M
P
P
T
c
on
t
r
o
l
.
I
n
a
d
di
t
io
n
,
t
he
I
o
T
i
nt
e
g
r
a
ti
on
a
ll
ows
r
e
a
l
-
t
im
e
v
is
u
a
l
iza
t
io
n
b
y
a
d
e
s
i
gn
e
d
da
s
hb
oa
r
d
o
n
the
T
h
in
gs
B
o
a
r
d
pl
a
t
f
o
r
m
,
e
na
bl
in
g
p
e
r
c
e
pt
io
n
a
n
d
r
e
p
r
od
uc
t
i
on
o
f
a
bs
t
r
a
c
t
c
onc
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p
ts
i
n
b
o
th
p
owe
r
e
lec
t
r
o
n
ics
a
n
d
da
ta
a
c
qu
is
it
io
n
.
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he
p
r
o
t
ot
yp
e
’
s
e
xp
e
r
i
men
ta
l
v
a
l
id
a
t
i
on
u
nd
e
r
na
tu
r
a
l
s
un
li
gh
t
e
xh
ib
i
te
d
f
a
s
t
a
n
d
s
ta
b
le
t
r
a
c
i
ng
a
n
d
e
v
i
de
n
t
c
on
t
r
o
l
d
is
ti
nc
t
io
ns
,
w
he
r
e
t
he
f
uz
z
y
M
P
P
T
c
on
tr
o
l
im
p
r
o
ve
d
bo
th
r
i
pp
le
a
nd
f
a
s
t
r
e
s
po
ns
e
t
im
e
s
c
o
mp
a
r
e
d
w
it
h
P
&O
o
n
th
e
s
a
me
a
r
c
h
it
e
c
t
u
r
e
.
T
he
p
r
o
pos
e
d
s
ys
t
e
m
p
r
o
to
ty
pe
,
a
p
a
r
t
f
r
o
m
f
il
li
ng
t
he
e
x
is
t
in
g
ga
p
be
tw
e
e
n
m
on
it
o
r
i
ng
a
n
d
c
on
t
r
o
l
l
a
y
e
r
s
of
P
V
s
ys
te
ms
,
is
c
a
p
a
b
le
a
n
d
us
e
f
ul
i
n
de
m
o
ns
t
r
a
t
in
g
th
e
f
e
a
s
i
bi
li
t
y
of
i
n
teg
r
a
t
in
g
a
d
va
n
c
e
d
c
o
nt
r
ol
a
lg
o
r
i
th
ms
a
n
d
I
o
T
p
la
t
f
o
r
ms
on
r
e
s
o
u
r
c
e
-
c
ons
t
r
a
ine
d
a
r
c
h
it
e
c
tu
r
e
s
.
B
e
yo
nd
i
ts
e
du
c
a
ti
on
a
l
va
l
ue
,
th
e
p
r
op
os
e
d
s
ys
t
e
m
o
f
f
e
r
s
a
s
c
a
l
a
b
le
f
r
a
mew
o
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k
f
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r
a
p
id
p
r
o
to
t
yp
in
g
o
f
s
ma
r
t
P
V
m
on
i
to
r
in
g
s
ys
te
ms
.
F
u
tu
r
e
w
o
r
k
wi
ll
f
o
c
us
o
n
in
te
g
r
a
ti
ng
e
nv
i
r
o
nme
n
ta
l
s
e
ns
o
r
s
,
im
p
r
o
v
in
g
mea
s
u
r
e
me
nt
a
c
c
u
r
a
c
y
,
a
n
d
i
nc
o
r
po
r
a
t
in
g
a
dv
a
nc
e
d
M
P
P
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te
c
h
ni
qu
e
s
s
uc
h
a
s
hy
b
r
i
d
a
nd
mac
hi
ne
lea
r
ni
n
g
-
ba
s
e
d
a
pp
r
oa
c
he
s
.
AC
KNOWL
E
DGM
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N
T
S
T
he
f
i
r
s
t
a
uthor
is
g
r
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tef
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f
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the
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uppor
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b
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Na
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C
e
nter
f
or
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c
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ic
a
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c
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R
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s
e
a
r
c
h
(
C
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)
in
the
f
r
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mew
or
k
of
the
"
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his
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C
:
C
onc
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pt
ua
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a
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M
:
M
e
th
odol
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So
:
So
f
twa
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Va
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Fo
:
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nve
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:
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CONF
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Author
s
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tate
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DA
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