I
nte
rna
t
io
na
l J
o
urna
l o
f
Appl
ied P
o
wer
E
ng
i
neer
ing
(
I
J
AP
E
)
Vo
l.
1
4
,
No
.
1
,
Ma
r
ch
20
2
5
,
p
p
.
2
0
2
~
2
1
1
I
SS
N:
2252
-
8
7
9
2
,
DOI
:
1
0
.
1
1
5
9
1
/ijap
e
.
v
1
4
.
i
1
.
pp
202
-
211
202
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
a
p
e
.
ia
esco
r
e.
co
m
O
ptimi
za
tion a
nd
ma
na
g
ement of
s
o
la
r and wind p
r
o
duction for
sta
nda
lo
ne micro
g
rid:
a
Mo
ro
ccan
cas
e study
M
o
ha
m
ed
E
l H
a
f
y
dy
,
Yo
us
s
ef
O
ub
a
il,
M
o
ha
m
ed
B
eny
di
r,
L
a
ho
us
s
i
ne
E
lm
a
hn
i,
E
lm
o
uta
wa
k
il Ala
o
ui M
y
Ra
chid
La
b
o
r
a
t
o
r
y
o
f
E
n
g
i
n
e
e
r
i
n
g
S
c
i
e
n
c
e
s
a
n
d
E
n
e
r
g
y
M
a
n
a
g
e
me
n
t
(
LA
S
I
M
E)
,
I
b
n
Z
o
h
r
U
n
i
v
e
r
s
i
t
y
N
a
t
i
o
n
a
l
S
c
h
o
o
l
o
f
A
p
p
l
i
e
d
S
c
i
e
n
c
e
s
,
A
g
a
d
i
r
,
M
o
r
o
c
c
o
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
J
u
n
9
,
2
0
2
4
R
ev
is
ed
Au
g
2
4
,
2
0
2
4
Acc
ep
ted
Oct
2
3
,
2
0
2
4
Th
e
i
n
c
re
a
sin
g
d
e
m
a
n
d
fo
r
su
st
a
in
a
b
le
a
n
d
e
fficie
n
t
e
n
e
r
g
y
so
l
u
ti
o
n
s
h
a
s
p
ro
m
p
te
d
e
x
ten
siv
e
re
se
a
rc
h
in
t
o
o
p
ti
m
izi
n
g
re
n
e
wa
b
le
e
n
e
rg
y
so
u
rc
e
s
in
m
icro
g
rid
s
y
ste
m
s.
Th
is
p
a
p
e
r
fo
c
u
se
s
o
n
o
p
t
imiz
in
g
re
n
e
wa
b
le
e
n
e
rg
y
so
u
rc
e
s
with
i
n
a
sta
n
d
a
l
o
n
e
m
icro
g
rid
u
si
n
g
pa
rt
icle
sw
a
rm
o
p
ti
m
iza
ti
o
n
(P
S
O)
a
s
th
e
so
le
a
lg
o
rit
h
m
.
Th
e
m
icro
g
ri
d
m
o
d
e
l
p
ro
p
o
se
d
in
teg
ra
tes
p
h
o
to
v
o
lt
a
ic
(P
V)
,
wi
n
d
,
b
a
tt
e
ry
sto
ra
g
e
,
a
n
d
se
rv
e
s
a
lo
a
d
re
p
re
se
n
ted
b
y
a
n
a
g
ricu
lt
u
ra
l
firm.
Re
a
l
-
wo
rl
d
d
a
t
a
fro
m
Ag
d
z
in
Ou
a
rz
a
z
a
te,
M
o
ro
c
c
o
,
is
u
ti
li
z
e
d
fo
r
a
n
a
l
y
sis.
Th
e
p
rima
ry
o
b
jec
ti
v
e
is
to
m
in
imiz
e
e
x
c
e
ss
p
ro
d
u
c
ti
o
n
fro
m
P
V
a
n
d
win
d
so
u
rc
e
s
wh
e
n
th
e
b
a
tt
e
ry
re
a
c
h
e
s
fu
ll
c
h
a
rg
e
.
Th
is
re
se
a
rc
h
a
d
d
re
ss
e
s th
e
in
c
re
a
sin
g
d
e
m
a
n
d
fo
r
su
sta
i
n
a
b
le en
e
rg
y
so
lu
ti
o
n
s b
y
e
m
p
h
a
siz
in
g
a
sin
g
le
o
p
ti
m
iza
ti
o
n
tec
h
n
iq
u
e
,
P
S
O,
f
o
r
a
c
h
iev
in
g
a
b
a
lan
c
e
d
a
n
d
e
fficie
n
t
e
n
e
rg
y
g
e
n
e
ra
ti
o
n
sy
ste
m
.
Th
e
stu
d
y
a
ims
to
c
l
o
se
ly
a
li
g
n
e
n
e
rg
y
p
ro
d
u
c
ti
o
n
wit
h
l
o
a
d
d
e
m
a
n
d
t
o
re
d
u
c
e
wa
sta
g
e
a
n
d
e
n
s
u
re
a
re
li
a
b
l
e
e
n
e
rg
y
su
p
p
l
y
with
i
n
th
e
m
icro
g
rid
.
Th
e
e
v
a
l
u
a
ti
o
n
is
c
o
n
d
u
c
ted
b
a
se
d
o
n
th
e
a
b
il
it
y
o
f
th
e
P
S
O
a
lg
o
rit
h
m
to
d
imi
n
ish
th
e
g
a
p
b
e
twe
e
n
to
t
a
l
e
n
e
rg
y
p
ro
d
u
c
ti
o
n
a
n
d
l
o
a
d
d
e
m
a
n
d
.
T
h
e
u
se
o
f
th
e
P
S
O
a
lg
o
rit
h
m
re
su
lt
e
d
i
n
a
3
0
%
re
d
u
c
ti
o
n
in
e
x
c
e
ss
e
n
e
rg
y
,
e
ffe
c
ti
v
e
ly
m
it
ig
a
ti
n
g
u
n
n
e
c
e
ss
a
ry
e
n
e
r
g
y
wa
sta
g
e
wh
e
n
th
e
b
a
tt
e
ry
is
fu
ll
y
c
h
a
rg
e
d
.
Th
is
o
u
tco
m
e
h
i
g
h
li
g
h
ts
t
h
e
a
lg
o
rit
h
m
'
s
c
a
p
a
c
it
y
t
o
a
d
a
p
t
a
n
d
o
p
ti
m
ize
e
n
e
rg
y
p
ro
d
u
c
ti
o
n
fr
o
m
p
rima
ry
so
u
rc
e
s to
p
re
c
ise
ly
a
li
g
n
wit
h
t
h
e
sp
e
c
ifi
c
re
q
u
irem
e
n
ts o
f
th
e
lo
a
d
.
K
ey
w
o
r
d
s
:
E
n
er
g
y
m
an
ag
e
m
en
t
E
n
h
an
ce
d
p
o
wer
Mic
r
o
g
r
id
Op
tim
izatio
n
Par
ticle
s
war
m
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Mo
h
am
ed
E
l H
af
y
d
y
L
ab
o
r
ato
r
y
o
f
E
n
g
i
n
ee
r
in
g
Scien
ce
s
an
d
E
n
e
r
g
y
Ma
n
ag
em
e
n
t (
L
ASI
ME
)
I
b
n
Z
o
h
r
Un
i
v
er
s
ity
Natio
n
al
Sch
o
o
l o
f
a
p
p
lied
Scien
ce
s
Ag
ad
ir
,
Mo
r
o
cc
o
E
m
ail:
m
o
h
am
ed
.
elh
af
y
d
y
@
ed
u
.
u
iz.
ac
.
m
a
1.
I
NT
RO
D
UCT
I
O
N
Mic
r
o
g
r
id
s
ar
e
s
elf
-
s
u
f
f
icien
t
au
to
n
o
m
o
u
s
elec
tr
ical
s
y
s
tem
s
d
esig
n
ed
to
s
u
p
p
l
y
p
o
wer
to
r
em
o
te
lo
ca
tio
n
s
,
cr
itical
in
f
r
astru
ctu
r
e,
an
d
is
o
lated
c
o
m
m
u
n
ities
n
o
t
ea
s
ily
co
n
n
ec
ted
to
t
h
e
m
ain
elec
tr
ical
g
r
i
d
.
T
h
ey
co
n
s
is
t
o
f
v
ar
io
u
s
en
er
g
y
s
o
u
r
ce
s
lik
e
b
atte
r
ies,
win
d
tu
r
b
in
es,
s
o
lar
p
an
els,
an
d
b
ac
k
u
p
g
en
er
at
o
r
s
,
alo
n
g
with
e
n
er
g
y
m
an
a
g
em
e
n
t
an
d
co
n
tr
o
l
tech
n
o
lo
g
ies
[
1
]
.
E
m
er
g
in
g
as
a
n
in
n
o
v
ativ
e
s
o
lu
tio
n
f
o
r
en
er
g
y
n
ee
d
s
in
r
em
o
te
an
d
u
n
d
er
s
er
v
ed
ar
ea
s
,
m
icr
o
g
r
id
s
e
n
ab
le
t
h
e
u
s
e
o
f
r
en
ewa
b
le
en
er
g
y
,
r
ed
u
cin
g
r
elian
ce
o
n
f
o
s
s
il
f
u
els
,
an
d
o
f
f
er
in
g
a
s
u
s
tain
ab
le
alter
n
ativ
e
to
t
r
ad
i
tio
n
al
g
r
i
d
s
[
2
]
.
T
h
ey
ar
e
p
ar
ticu
lar
ly
u
s
ef
u
l
f
o
r
p
o
wer
in
g
r
e
m
o
te
co
m
m
u
n
itie
s
,
ess
en
tial
f
ac
il
ities
lik
e
h
o
s
p
itals
an
d
d
ata
ce
n
ter
s
,
p
r
o
v
i
d
in
g
en
er
g
y
d
u
r
in
g
em
er
g
en
cies,
an
d
lo
wer
i
n
g
en
er
g
y
co
s
ts
in
r
u
r
al
r
eg
io
n
s
[
3
]
.
As
a
r
esu
lt,
m
icr
o
g
r
id
s
ar
e
g
ain
in
g
tr
ac
tio
n
in
ar
ea
s
with
h
ig
h
e
n
er
g
y
p
r
ices,
lim
ited
in
f
r
astru
ctu
r
e,
o
r
u
n
s
tab
le
elec
tr
ical
n
etwo
r
k
s
,
m
a
k
in
g
th
e
m
a
cr
u
cial
f
o
cu
s
f
o
r
r
esear
ch
in
e
n
er
g
y
tech
n
o
lo
g
y
an
d
p
o
licy
[
4
]
.
B
en
e
f
its
o
f
m
icr
o
g
r
id
s
in
clu
d
e
im
p
r
o
v
ed
p
o
we
r
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
Op
timiz
a
tio
n
a
n
d
ma
n
a
g
eme
n
t o
f so
la
r
a
n
d
w
in
d
p
r
o
d
u
ctio
n
fo
r
…
(
Mo
h
a
med
E
l H
a
fyd
y
)
203
q
u
ality
,
r
eliab
ilit
y
,
an
d
co
s
t
s
av
in
g
s
f
o
r
r
em
o
te
ar
ea
s
.
T
h
e
y
en
h
a
n
ce
en
e
r
g
y
s
ec
u
r
ity
b
y
p
r
o
v
id
in
g
b
ac
k
u
p
p
o
wer
d
u
r
in
g
o
u
tag
es
an
d
co
n
tr
ib
u
te
to
clim
ate
c
h
an
g
e
m
i
tig
atio
n
b
y
r
ed
u
ci
n
g
f
o
s
s
il
f
u
el
d
ep
en
d
e
n
cy
a
n
d
g
r
ee
n
h
o
u
s
e
g
as
em
is
s
io
n
s
[
5
]
.
On
g
o
i
n
g
ef
f
o
r
ts
aim
to
im
p
r
o
v
e
m
icr
o
g
r
id
d
esig
n
,
m
an
ag
em
en
t,
an
d
in
teg
r
atio
n
o
f
r
en
ewa
b
le
en
e
r
g
y
s
o
u
r
ce
s
th
r
o
u
g
h
a
d
v
an
ce
d
en
er
g
y
m
an
a
g
em
en
t
s
y
s
te
m
s
,
en
er
g
y
s
to
r
a
g
e
s
o
lu
tio
n
s
,
an
d
g
r
id
-
f
o
r
m
i
n
g
te
ch
n
o
lo
g
ies to
b
o
o
s
t e
f
f
icien
cy
an
d
r
ed
u
ce
co
s
ts
[
6
]
.
Pre
v
iew
s
tu
d
y
[
7
]
,
a
m
ix
ed
-
in
teg
er
lin
ea
r
p
r
o
g
r
a
m
m
in
g
(
MI
L
P)
m
o
d
el
is
in
tr
o
d
u
ce
d
t
o
o
p
tim
ize
en
er
g
y
a
n
d
r
eser
v
e
m
an
ag
e
m
en
t
in
an
in
d
ep
en
d
en
t
m
icr
o
g
r
id
p
o
wer
ed
b
y
r
e
n
ewa
b
le
s
o
u
r
ce
s
,
ai
m
in
g
to
m
in
im
ize
co
s
ts
wh
ile
ad
d
r
ess
in
g
en
er
g
y
p
r
o
d
u
ctio
n
u
n
ce
r
tain
ties
.
Simi
lar
ly
,
[
8
]
u
s
es
a
g
en
etic
al
g
o
r
ith
m
to
m
i
n
im
ize
o
v
er
all
co
s
t
s
an
d
in
c
o
r
p
o
r
ates
d
em
an
d
r
esp
o
n
s
e
in
a
m
icr
o
g
r
id
s
ettin
g
.
Pre
v
iew
s
tu
d
y
[
9
]
,
b
o
th
g
e
n
etic
alg
o
r
ith
m
a
n
d
p
a
r
ticle
s
war
m
o
p
tim
izatio
n
(
PS
O)
ar
e
ap
p
lie
d
to
ac
h
ie
v
e
an
o
p
tim
al
c
o
n
f
i
g
u
r
atio
n
f
o
r
a
g
r
id
-
co
n
n
ec
ted
h
y
b
r
id
s
y
s
tem
,
with
a
f
o
cu
s
o
n
co
s
t
m
in
im
izatio
n
.
T
h
e
s
tu
d
y
i
n
[
1
0
]
u
s
es
g
en
etic
alg
o
r
ith
m
s
an
d
p
ar
ticle
s
wa
r
m
o
p
tim
izatio
n
to
o
p
tim
ize
th
e
s
izin
g
o
f
r
en
ewa
b
le
g
en
er
atio
n
u
n
its
in
an
is
o
lated
m
icr
o
g
r
id
,
co
n
s
id
er
in
g
c
o
s
t
an
d
p
ea
k
d
em
an
d
co
n
s
tr
ain
ts
.
Acc
o
r
d
in
g
to
[
1
1
]
,
MA
T
L
AB
/Si
m
u
lin
k
an
d
p
ar
t
icle
s
war
m
o
p
tim
izatio
n
ar
e
u
s
ed
to
d
em
o
n
s
tr
ate
ef
f
icien
t
p
o
wer
f
l
o
w
in
a
d
iv
e
r
s
e
m
icr
o
g
r
id
m
o
d
el,
lead
in
g
to
s
ig
n
if
ican
t
tr
an
s
m
is
s
io
n
lo
s
s
r
ed
u
ctio
n
d
u
r
in
g
b
atter
y
ch
a
r
g
in
g
an
d
d
is
ch
ar
g
i
n
g
.
B
en
y
d
ir
et
a
l.
[
1
2
]
h
as
tac
k
led
a
cr
u
cial
is
s
u
e
in
m
icr
o
g
r
id
o
p
tim
izatio
n
b
y
co
n
ce
n
tr
atin
g
o
n
th
e
e
f
f
icien
t
allo
ca
tio
n
o
f
en
e
r
g
y
f
r
o
m
r
e
n
ewa
b
le
s
o
u
r
ce
s
to
m
ee
t
lo
ad
d
em
an
d
a
n
d
r
ed
u
ce
en
er
g
y
wastag
e,
e
m
p
lo
y
i
n
g
p
a
r
ticle
s
war
m
o
p
tim
izatio
n
an
d
g
en
etic
alg
o
r
ith
m
tech
n
iq
u
es [
1
3
]
.
T
h
is
s
tu
d
y
m
ak
es
a
u
n
iq
u
e
co
n
tr
ib
u
tio
n
in
o
r
d
er
to
o
p
tim
iz
e
th
e
p
o
wer
p
r
o
d
u
ctio
n
in
m
ic
r
o
g
r
id
s
b
y
co
n
ce
n
tr
atin
g
o
n
th
e
ef
f
icien
t
allo
ca
tio
n
o
f
en
er
g
y
f
r
o
m
r
e
n
ewa
b
le
s
o
u
r
ce
s
to
m
in
im
ize
en
er
g
y
waste
an
d
m
ee
t
lo
ad
d
em
an
d
.
Un
lik
e
p
r
e
v
i
o
u
s
r
esear
ch
,
wh
ich
f
o
cu
s
es
m
ain
ly
o
n
co
s
t
m
in
im
izatio
n
a
n
d
o
p
tim
al
s
izin
g
,
o
u
r
s
tu
d
y
ad
d
r
ess
es
th
e
cr
itical
is
s
u
e
o
f
av
o
id
i
n
g
u
n
n
ec
ess
ar
y
en
er
g
y
s
u
r
p
lu
s
.
B
y
e
v
alu
atin
g
o
n
ly
,
th
e
p
er
f
o
r
m
an
ce
o
f
PS
O,
we
em
p
h
asize
its
ef
f
ec
tiv
en
ess
in
ac
h
iev
in
g
o
p
tim
al
en
e
r
g
y
u
tili
za
tio
n
.
Utilizin
g
r
ea
l
-
wo
r
ld
d
ata
f
r
o
m
A
g
d
z
i
n
Ou
a
r
za
za
te,
Mo
r
o
cc
an
r
eg
io
n
wit
h
s
ig
n
if
ican
t
s
o
lar
a
n
d
win
d
p
o
ten
tial
[
1
4
]
.
T
h
is
r
esear
ch
ex
ten
d
s
b
ey
o
n
d
co
n
v
en
tio
n
al
o
p
tim
izatio
n
m
eth
o
d
s
,
o
f
f
e
r
in
g
in
s
ig
h
ts
in
to
ef
f
e
ctiv
e
s
tr
ateg
ies
f
o
r
im
p
r
o
v
in
g
m
icr
o
g
r
id
o
p
er
atio
n
an
d
m
ax
im
izin
g
r
en
ewa
b
le
e
n
er
g
y
u
s
e
wh
ile
m
in
im
izin
g
w
aste [
1
5
]
.
T
h
is
p
ap
er
is
s
tr
u
ctu
r
ed
as
f
o
llo
ws:
i)
S
ec
tio
n
1
,
w
e
p
r
esen
t
th
e
p
r
o
p
o
s
ed
m
ic
r
o
g
r
i
d
an
d
its
co
m
p
o
n
en
ts
,
in
clu
d
in
g
p
h
o
to
v
o
ltaic
(
PV)
an
d
win
d
s
o
u
r
ce
s
,
b
atter
y
s
to
r
ag
e,
an
d
th
e
lo
ad
r
ep
r
esen
ted
b
y
a
n
ag
r
icu
ltu
r
al
f
ir
m
;
ii)
Sectio
n
2
o
f
f
er
s
an
o
v
er
v
iew
o
f
p
ar
ti
cle
s
war
m
o
p
tim
izatio
n
(
PS
O)
,
p
r
o
v
id
in
g
r
ea
d
er
s
with
a
clea
r
u
n
d
er
s
tan
d
in
g
o
f
th
e
alg
o
r
ith
m
'
s
p
r
in
cip
les
an
d
m
ec
h
a
n
is
m
s
;
iii)
Sectio
n
3
,
we
p
r
esen
t
t
h
e
s
im
u
latio
n
r
esu
lts
d
er
iv
ed
f
r
o
m
th
e
im
p
lem
en
tatio
n
o
f
PS
O
in
o
u
r
m
icr
o
g
r
id
s
y
s
tem
.
T
h
i
s
s
ec
tio
n
s
h
o
wca
s
e
s
th
e
p
r
ac
tical
im
p
licatio
n
s
o
f
em
p
lo
y
in
g
PS
O
to
o
p
tim
iz
e
p
o
wer
p
r
o
d
u
ctio
n
,
s
p
ec
if
ically
ad
d
r
ess
in
g
th
e
r
ed
u
ctio
n
o
f
ex
c
ess
en
er
g
y
w
h
en
th
e
b
atter
y
is
f
u
lly
ch
ar
g
ed
;
Fin
all
y
i
v
)
Sectio
n
4
,
in
t
h
e
co
n
clu
s
io
n
,
we
s
u
m
m
ar
ize
th
e
k
ey
f
in
d
in
g
s
an
d
lim
itatio
n
s
o
f
o
u
r
s
tu
d
y
,
e
m
p
h
asizin
g
th
e
ef
f
ec
tiv
e
n
ess
o
f
PS
O
in
en
h
an
cin
g
m
icr
o
g
r
id
o
p
er
atio
n
an
d
r
en
e
wab
le
en
er
g
y
u
tili
za
tio
n
wh
ile
m
in
im
izin
g
wastef
u
ln
ess
.
2.
T
H
E
P
RO
P
O
SE
D
M
E
T
H
O
D
T
h
e
m
icr
o
g
r
i
d
s
tu
d
ied
in
th
i
s
p
ap
er
in
clu
d
es
p
h
o
to
v
o
ltaic
p
an
els
an
d
win
d
tu
r
b
in
es
as
th
e
m
ain
r
en
ewa
b
le
en
er
g
y
s
o
u
r
ce
s
,
with
a
b
atter
y
s
to
r
ag
e
s
y
s
tem
s
h
o
wn
in
Fig
u
r
e
1
.
T
h
is
s
tan
d
alo
n
e
m
icr
o
g
r
id
is
d
esig
n
ed
to
m
ee
t
th
e
e
n
er
g
y
n
ee
d
s
o
f
a
n
ag
r
icu
ltu
r
al
f
ir
m
in
Ag
d
z,
M
o
r
o
cc
o
.
I
t
p
r
o
v
id
e
s
a
r
eliab
le
en
er
g
y
s
u
p
p
ly
u
s
in
g
t
h
e
ar
ea
'
s
av
ailab
le
s
o
lar
an
d
win
d
r
eso
u
r
ce
s
.
Fig
u
r
e
1
.
Mic
r
o
g
r
id
s
tu
d
ied
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
9
2
I
n
t J Ap
p
l Po
wer
E
n
g
,
Vo
l.
1
4
,
No
.
1
,
Ma
r
ch
20
2
5
:
202
-
2
1
1
204
I
n
th
is
s
tu
d
y
,
o
u
r
atten
tio
n
i
s
n
o
t
d
ir
ec
te
d
to
war
d
s
t
h
e
c
o
n
v
er
ter
s
a
n
d
p
o
wer
elec
tr
o
n
ics
o
f
th
e
m
icr
o
g
r
id
.
I
n
s
tead
,
o
u
r
p
r
im
a
r
y
f
o
c
u
s
lies
in
th
e
m
an
a
g
em
en
t
an
d
o
p
tim
izatio
n
o
f
p
o
we
r
p
r
o
d
u
ctio
n
f
r
o
m
r
en
ewa
b
le
en
er
g
y
s
o
u
r
ce
s
.
T
a
b
le
1
p
r
esen
ts
th
e
m
ic
r
o
g
r
i
d
p
ar
am
eter
s
.
T
ab
le
1
.
Mic
r
o
g
r
id
p
ar
am
eter
s
C
o
m
p
o
n
e
n
t
s
P
a
r
a
me
t
e
r
s
V
a
l
u
e
s
P
h
o
t
o
v
o
l
t
a
i
c
R
a
t
e
d
ma
x
p
o
w
e
r
2
7
9
W
C
u
r
r
e
n
t
a
t
P
ma
x
8
.
5
9
A
V
o
l
t
a
g
e
a
t
P
m
a
x
3
1
.
4
4
V
S
h
o
r
t
c
i
r
c
u
i
t
c
u
r
r
e
n
t
9
.
0
3
V
O
p
e
n
c
i
r
c
u
i
t
v
o
l
t
a
g
e
3
8
.
4
5
V
O
p
e
r
a
t
i
n
g
t
e
mp
e
r
a
t
u
r
e
r
a
n
g
e
-
4
5
+
8
5
°C
C
e
l
l
t
e
c
h
n
o
l
o
g
y
P
o
l
y
c
r
y
st
a
l
l
i
n
e
W
i
n
d
t
u
r
b
i
n
e
R
a
t
e
d
ma
x
p
o
w
e
r
1
5
k
W
B
l
a
d
e
r
a
d
i
u
s
R
2
m
M
u
l
t
i
p
l
i
c
a
t
i
o
n
r
a
t
i
o
G
2
A
i
r
d
e
n
s
i
t
y
1
.
2
5
/
²
B
a
t
t
e
r
y
Ref
A
P
C
N
EW
1
5
0
-
1
2
G
EL
V
o
l
t
a
g
e
r
e
g
u
l
a
t
i
o
n
f
o
r
f
l
o
a
t
i
n
g
u
s
e
1
3
.
5
V
–
1
3
.
8
V
I
n
i
t
i
a
l
c
u
r
r
e
n
t
45
A
C
a
p
a
c
i
t
y
50
Ah
2
.
1
.
P
r
o
po
s
ed
m
a
na
g
e
m
ent
s
t
ra
t
eg
y
T
h
e
p
r
o
p
o
s
ed
m
an
ag
em
en
t
s
tr
ateg
y
f
o
r
en
er
g
y
f
lo
w
in
th
e
s
tan
d
alo
n
e
m
icr
o
g
r
id
is
b
ased
o
n
r
eg
u
latin
g
th
e
e
n
er
g
y
f
lo
w
a
cc
o
r
d
in
g
to
th
e
lev
el
o
f
th
e
b
atter
y
.
T
h
is
s
tr
ateg
y
en
s
u
r
es
th
at
th
e
en
er
g
y
g
en
er
ated
b
y
th
e
PV
s
y
s
tem
an
d
th
e
win
d
tu
r
b
in
e
is
s
to
r
ed
i
n
th
e
b
atter
y
d
u
r
in
g
p
er
io
d
s
o
f
lo
w
d
em
an
d
an
d
is
u
s
ed
to
s
u
p
p
ly
p
o
wer
d
u
r
in
g
p
er
io
d
s
o
f
h
ig
h
d
em
a
n
d
o
r
w
h
en
r
en
ewa
b
le
e
n
er
g
y
s
o
u
r
ce
s
ar
e
n
o
t
av
ailab
le.
T
h
e
p
r
o
p
o
s
ed
s
tr
ateg
y
'
s
o
b
je
ctiv
e
is
to
o
p
tim
ize
th
e
u
ti
li
za
tio
n
o
f
r
en
ewa
b
le
en
er
g
y
s
o
u
r
ce
s
wh
ile
also
g
u
ar
an
teein
g
th
e
p
r
o
tectio
n
o
f
th
e
b
atter
ies f
r
o
m
a
n
y
d
am
ag
e
[
1
6
]
.
B
alan
cin
g
p
o
wer
in
th
e
m
icr
o
g
r
id
is
ess
en
tial,
esp
ec
ially
u
n
d
er
v
a
r
y
in
g
p
o
wer
g
e
n
er
atio
n
f
r
o
m
r
en
ewa
b
le
s
o
u
r
ce
s
.
Ov
er
ch
ar
g
in
g
o
r
ex
ce
s
s
iv
e
d
is
ch
ar
g
in
g
o
f
b
atter
ies
is
a
m
ajo
r
ca
u
s
e
o
f
b
atter
y
ex
p
lo
s
io
n
s
.
T
h
er
ef
o
r
e,
c
o
n
t
r
o
llin
g
th
e
b
atter
y
'
s
s
tate
o
f
ch
ar
g
e
(
SOC
)
is
cr
u
cial
f
o
r
s
af
e
o
p
er
atio
n
s
.
I
n
th
is
s
tu
d
y
,
we
u
s
e
SOC
v
alu
es
in
o
u
r
en
er
g
y
m
an
ag
em
en
t
s
tr
ateg
y
.
Fig
u
r
e
2
illu
s
tr
ates
th
e
en
er
g
y
m
a
n
ag
em
en
t
a
p
p
r
o
ac
h
em
p
lo
y
ed
,
wh
ich
is
b
ased
o
n
SOC
,
th
e
p
o
wer
p
r
o
d
u
ce
d
,
an
d
th
e
p
o
wer
d
e
m
an
d
e
d
[
1
7
]
.
T
h
e
s
y
s
tem
o
p
er
ates
in
f
iv
e
m
o
d
es:
Mo
d
e
1
ch
ar
g
es
th
e
b
atter
ies
wh
ile
m
ee
tin
g
f
ir
m
d
em
an
d
wh
en
r
en
ewa
b
le
en
er
g
y
(
PV
an
d
win
d
)
is
s
u
f
f
icien
t.
Mo
d
e
2
u
s
es
b
atter
y
p
o
wer
to
co
m
p
en
s
ate
f
o
r
s
h
o
r
tf
alls
wh
en
r
e
n
ewa
b
le
en
er
g
y
is
in
ad
eq
u
ate
.
Mo
d
e
3
r
elies
e
n
tire
ly
o
n
b
atter
y
p
o
we
r
wh
en
n
o
r
en
ewa
b
le
en
er
g
y
is
av
ailab
le.
Mo
d
e
4
d
is
co
n
n
ec
ts
f
u
lly
ch
ar
g
ed
b
att
er
ies
to
p
r
o
tect
th
em
wh
en
r
e
n
ewa
b
le
en
er
g
y
is
ab
u
n
d
a
n
t.
Mo
d
e
5
d
is
co
n
n
ec
ts
th
e
f
ir
m
wh
e
n
n
o
r
en
ewa
b
le
e
n
er
g
y
is
p
r
o
d
u
ce
d
,
a
n
d
th
e
b
at
ter
i
es a
r
e
n
o
t c
h
ar
g
in
g
[
1
8
]
.
Fig
u
r
e
2
.
Flo
w
ch
a
r
t o
f
t
h
e
en
er
g
y
f
l
o
w
r
eg
u
latio
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
Op
timiz
a
tio
n
a
n
d
ma
n
a
g
eme
n
t o
f so
la
r
a
n
d
w
in
d
p
r
o
d
u
ctio
n
fo
r
…
(
Mo
h
a
med
E
l H
a
fyd
y
)
205
2
.
2
.
P
a
rt
icle
s
wa
rm
o
ptim
iz
a
t
io
n (
P
SO
)
Par
ticle
s
war
m
o
p
tim
izatio
n
(
PS
O)
is
a
n
atu
r
e
-
in
s
p
ir
ed
alg
o
r
ith
m
th
at
m
im
ics
p
ar
ticle
b
eh
av
io
r
in
a
s
ea
r
ch
s
p
ac
e
to
f
in
d
o
p
tim
al
s
o
lu
tio
n
s
,
with
p
ar
ticles
ad
ju
s
tin
g
p
o
s
itio
n
s
b
ased
o
n
p
er
s
o
n
al
an
d
g
lo
b
al
b
est
-
k
n
o
wn
p
o
s
itio
n
s
[
1
9
]
.
T
h
e
alg
o
r
ith
m
u
p
d
ates
ea
ch
p
ar
ticle'
s
v
elo
city
b
y
c
o
n
s
id
er
in
g
t
h
e
b
e
s
t
s
o
lu
tio
n
s
at
b
o
th
in
d
iv
id
u
al
a
n
d
g
l
o
b
al
lev
els,
in
f
lu
en
ce
d
b
y
two
c
o
ef
f
icien
t
s
,
1
an
d
2
,
wh
ich
r
ep
r
esen
t
tr
u
s
t
in
p
er
s
o
n
al
ex
p
er
ien
ce
an
d
co
llectiv
e
in
f
o
r
m
atio
n
,
r
esp
ec
tiv
ely
.
T
h
ese
c
o
ef
f
icien
ts
,
co
m
b
in
e
d
with
r
an
d
o
m
v
alu
es
1
an
d
2
,
in
tr
o
d
u
ce
s
to
ch
asti
c
ef
f
ec
ts
f
r
o
m
co
g
n
itiv
e
an
d
s
o
cial
b
eh
a
v
io
r
s
[
1
2
]
.
(
+
1
)
=
(
)
+
1
1
(
−
)
+
2
2
(
−
)
(
1
)
T
h
e
s
ec
o
n
d
eq
u
atio
n
u
p
d
ates
th
e
p
o
s
itio
n
,
with
ea
ch
p
a
r
ticle
m
o
d
if
y
in
g
its
lo
ca
tio
n
b
a
s
ed
o
n
th
e
r
ec
en
tly
d
eter
m
in
ed
v
elo
city
.
+
1
=
+
+
1
(
2
)
T
h
e
p
ar
am
eter
s
o
f
p
o
s
itio
n
an
d
v
elo
city
a
r
e
in
ter
d
ep
en
d
en
t;
th
e
v
elo
city
is
in
f
lu
e
n
c
ed
b
y
th
e
p
o
s
itio
n
,
an
d
th
e
p
o
s
itio
n
is
in
f
lu
en
ce
d
b
y
th
e
v
elo
city
[
2
0
]
.
W
e
ca
n
illu
s
tr
ate
th
e
m
o
v
in
g
p
ar
ticle
in
Fig
u
r
e
3.
I
n
th
is
s
tu
d
y
,
we
u
s
e
PS
O
to
o
p
tim
ize
p
o
wer
p
r
o
d
u
ctio
n
f
r
o
m
r
en
ewa
b
le
s
o
u
r
ce
s
,
m
atc
h
in
g
p
o
wer
g
e
n
er
atio
n
with
f
ir
m
d
em
a
n
d
in
o
u
r
s
y
s
te
m
[
2
1
]
.
T
ab
le
2
p
r
esen
ts
th
e
P
SO p
ar
am
eter
s
em
p
lo
y
e
d
in
o
u
r
s
tu
d
y
.
Fig
u
r
e
4
p
r
esen
ts
th
e
PS
O
f
lo
wch
ar
t
o
f
a
p
r
o
ce
s
s
.
T
h
e
a
lg
o
r
ith
m
b
eg
in
s
b
y
in
itializin
g
p
ar
ticles
wi
th
r
an
d
o
m
p
o
s
itio
n
s
an
d
v
elo
cit
ies
with
in
a
s
ea
r
ch
s
p
ac
e.
E
ac
h
p
ar
ticle'
s
f
itn
ess
is
th
en
ev
alu
ated
u
s
in
g
a
p
r
ed
ef
in
e
d
f
itn
ess
f
u
n
ctio
n
[
2
2
]
.
T
h
e
p
ar
ticles'
v
elo
cities
a
n
d
p
o
s
itio
n
s
ar
e
u
p
d
ated
b
ase
d
o
n
th
eir
p
er
s
o
n
al
b
est
(
pb
e
s
t
)
an
d
th
e
g
lo
b
al
b
est
(
gb
e
s
t
)
s
o
lu
tio
n
s
f
o
u
n
d
.
T
h
is
iter
ativ
e
p
r
o
ce
s
s
co
n
tin
u
es
u
n
til
th
e
co
n
v
er
g
en
ce
o
f
th
e
f
itn
ess
v
al
u
e
to
ze
r
o
an
d
r
ea
ch
es
th
e
m
a
x
im
u
m
n
u
m
b
er
o
f
iter
atio
n
s
[
2
3
]
.
Fig
u
r
e
3
.
Mo
v
in
g
p
ar
ticles
T
ab
le
2
.
PS
O
p
ar
am
eter
s
P
a
r
a
me
t
e
r
s
V
a
l
u
e
S
w
a
r
m si
z
e
3
0
0
M
a
x
i
m
u
m
i
t
e
r
a
t
i
o
n
s
1
0
0
2
.
3
.
F
i
t
nes
s
f
un
ct
io
n
T
h
e
o
b
jectiv
e
f
u
n
ctio
n
(
f
itn
ess
)
u
s
ed
in
th
is
s
tu
d
y
f
o
r
PS
O
al
g
o
r
ith
m
ca
n
b
e
e
x
p
r
ess
ed
as
(
3
)
.
(
)
=
∑
φ
|
P
g
,
i
−
P
d
,
i
|
24
i
=
1
(
3
)
Acc
o
r
d
in
g
t
o
0
3
0
)
,
(
x
)
r
ep
r
esen
ts
th
e
f
itn
ess
s
co
r
e
o
f
a
s
o
lu
tio
n
,
wh
er
e
P
g
,
i
is
th
e
to
tal
p
o
wer
g
en
er
ated
b
y
r
en
ewa
b
le
s
o
u
r
ce
s
an
d
P
d
,
i
is
th
e
p
o
wer
d
em
a
n
d
f
o
r
ea
ch
h
o
u
r
i
f
r
o
m
1
to
2
4
.
T
h
e
weig
h
t
φ
in
d
icate
s
th
e
im
p
o
r
tan
ce
o
f
m
atch
in
g
p
o
we
r
g
en
er
atio
n
with
d
em
an
d
,
with
h
ig
h
er
weig
h
ts
r
ed
u
cin
g
d
ev
iatio
n
s
.
T
h
is
f
itn
ess
f
u
n
ctio
n
ev
al
u
ates
PS
O
s
o
lu
ti
o
n
s
b
y
m
ea
s
u
r
in
g
th
e
d
i
f
f
er
en
ce
b
etwe
en
g
en
er
ated
p
o
wer
an
d
d
em
an
d
o
v
er
2
4
h
o
u
r
s
,
s
u
m
m
in
g
th
e
ab
s
o
lu
te
d
if
f
er
en
ce
s
f
o
r
ea
c
h
h
o
u
r
.
T
h
e
PS
O
alg
o
r
ith
m
iter
ativ
ely
s
ee
k
s
to
m
in
im
ize
th
is
fi
tn
ess
v
alu
e
to
war
d
s
ze
r
o
,
o
p
tim
izin
g
p
o
wer
d
is
tr
ib
u
tio
n
to
clo
s
ely
alig
n
g
en
er
ati
o
n
with
d
em
an
d
an
d
m
in
im
ize
s
u
r
p
lu
s
o
r
d
ef
icit
[
2
4
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
9
2
I
n
t J Ap
p
l Po
wer
E
n
g
,
Vo
l.
1
4
,
No
.
1
,
Ma
r
ch
20
2
5
:
202
-
2
1
1
206
Fig
u
r
e
4
.
Flo
wch
ar
t
o
f
PS
O
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
I
n
th
is
s
ec
tio
n
,
we
p
e
r
f
o
r
m
a
co
m
p
r
eh
e
n
s
iv
e
an
aly
s
is
o
f
t
h
e
o
u
tco
m
e
s
o
b
tain
ed
f
r
o
m
ap
p
ly
in
g
o
u
r
PS
O
m
eth
o
d
.
W
e
b
eg
in
b
y
p
r
esen
tin
g
th
e
p
r
o
f
iles
o
f
ir
r
a
d
ian
ce
an
d
win
d
s
p
ee
d
with
in
th
e
h
is
to
r
ical
er
a
r
ef
er
r
ed
to
as
Ag
d
ez
,
s
itu
ated
in
Ou
ar
za
za
te,
Mo
r
o
cc
o
.
Fo
llo
win
g
th
is
,
we
s
h
o
wca
s
e
th
e
g
en
er
ated
o
u
tp
u
t
o
f
b
o
th
p
h
o
to
v
o
ltaic
s
y
s
tem
s
an
d
win
d
tu
r
b
in
es
o
v
er
a
s
p
an
o
f
f
iv
e
d
a
y
s
,
as
d
ep
icted
in
Fig
u
r
e
5
[
2
5
]
.
Fig
u
r
e
6
s
h
o
ws
th
e
p
o
wer
c
o
n
s
u
m
p
tio
n
p
r
o
f
ile
f
o
r
a
f
ar
m
in
g
estab
l
is
h
m
en
t
in
A
g
d
ez
o
v
er
f
iv
e
c
o
n
s
ec
u
tiv
e
d
ay
s
.
I
t
clea
r
ly
s
h
o
ws
wh
en
th
e
ag
r
ic
u
ltu
r
al
f
ir
m
’
s
elec
tr
icity
d
e
m
a
n
d
p
e
ak
ed
at
6
.
5
k
W
an
d
wh
en
it
d
r
o
p
p
ed
t
o
as
lo
w
as
1
k
W
.
T
h
is
g
r
ap
h
p
r
o
v
id
es
v
alu
a
b
le
in
s
ig
h
ts
in
t
o
th
e
f
ir
m
'
s
en
er
g
y
co
n
s
u
m
p
tio
n
p
atter
n
s
,
h
elp
i
n
g
to
id
en
tify
p
ea
k
u
s
ag
e
p
er
io
d
s
an
d
en
ab
lin
g
m
o
r
e
ef
f
icien
t
en
er
g
y
m
an
ag
e
m
en
t
s
tr
ateg
ies.
Fig
u
r
e
7
s
h
o
ws
th
e
p
o
wer
f
lo
w
with
in
t
h
e
m
icr
o
g
r
id
.
T
h
e
p
r
o
p
o
s
ed
m
an
ag
e
m
en
t
s
tr
ateg
y
s
u
cc
ess
f
u
lly
m
an
ag
ed
th
e
p
o
wer
f
lo
w
o
v
e
r
5
d
ay
s
.
T
h
e
m
ax
im
u
m
PV
p
o
wer
r
ea
c
h
ed
1
0
k
W
,
an
d
th
e
win
d
tu
r
b
in
e
p
r
o
d
u
ce
d
u
p
t
o
1
4
k
W
.
Ho
we
v
er
,
at
tim
es
d
u
r
in
g
th
e
d
ay
,
th
e
co
m
b
i
n
ed
p
o
wer
f
r
o
m
th
e
s
e
s
o
u
r
ce
s
f
ell
b
el
o
w
th
e
f
ir
m
'
s
d
em
an
d
.
I
n
s
u
c
h
ca
s
es,
th
e
b
atter
ies
s
u
p
p
lied
th
e
n
ec
ess
ar
y
p
o
we
r
,
in
d
icate
d
b
y
t
h
e
n
eg
ativ
e
b
atte
r
y
p
o
wer
v
alu
e,
m
ea
n
i
n
g
th
e
p
o
wer
f
lo
we
d
f
r
o
m
th
e
b
atter
ies to
th
e
lo
ad
.
Fig
u
r
e
5
.
W
in
d
s
p
ee
d
an
d
i
r
r
a
d
ian
ce
p
r
o
f
ile
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
Op
timiz
a
tio
n
a
n
d
ma
n
a
g
eme
n
t o
f so
la
r
a
n
d
w
in
d
p
r
o
d
u
ctio
n
fo
r
…
(
Mo
h
a
med
E
l H
a
fyd
y
)
207
Fig
u
r
e
6
.
L
o
ad
p
r
o
f
ile
Fig
u
r
e
7
.
Po
wer
f
lo
w
in
th
e
m
icr
o
g
r
id
I
n
Fi
g
u
r
e
8
,
t
h
e
c
o
m
p
ar
is
o
n
b
et
we
en
to
tal
p
r
o
d
u
cti
o
n
a
n
d
lo
ad
d
em
an
d
is
p
r
ese
n
te
d
.
I
t
b
e
co
m
es
ev
i
d
en
t
t
h
at
t
h
e
m
ic
r
o
g
r
id
e
x
h
ib
i
ts
n
o
t
a
b
le
in
s
ta
n
c
es
o
f
p
o
w
er
s
u
r
p
lu
s
a
n
d
s
h
o
r
ta
g
e
o
v
er
ti
m
e
.
O
u
r
al
g
o
r
it
h
m
,
in
c
o
r
p
o
r
a
ti
n
g
p
ar
ticl
e
s
wa
r
m
o
p
ti
m
i
za
t
io
n
(
PS
O
)
,
is
d
esi
g
n
ed
t
o
a
d
d
r
ess
a
n
d
o
p
t
im
ize
th
is
is
s
u
e
.
T
h
e
o
u
t
co
m
es
o
f
t
h
is
o
p
ti
m
iz
ati
o
n
p
r
o
c
ess
a
r
e
i
ll
u
s
t
r
at
e
d
i
n
Fi
g
u
r
e
9
,
r
e
v
e
ali
n
g
h
o
w
th
e
a
lg
o
r
it
h
m
e
f
f
ec
tiv
el
y
m
iti
g
a
tes
t
h
e
p
o
we
r
s
u
r
p
l
u
s
a
n
d
s
h
o
r
ta
g
e
p
r
o
b
le
m
s
.
Fi
g
u
r
e
1
0
ill
u
s
t
r
a
tes
t
h
e
s
u
cc
ess
o
f
p
a
r
t
icl
e
s
w
a
r
m
o
p
ti
m
iz
ati
o
n
(
PS
O
)
in
o
p
ti
m
i
zi
n
g
p
o
we
r
p
r
o
d
u
ct
i
o
n
wi
th
in
a
m
i
cr
o
g
r
i
d
,
p
ar
tic
u
la
r
l
y
in
m
a
n
a
g
i
n
g
b
at
te
r
y
p
er
f
o
r
m
a
n
c
e.
B
e
f
o
r
e
o
p
ti
m
iz
ati
o
n
,
i
n
s
t
an
ce
s
o
f
p
o
w
er
p
r
o
d
u
cti
o
n
s
u
r
p
ass
i
n
g
d
em
a
n
d
l
e
d
to
t
h
e
b
at
te
r
y
,
r
ea
ch
i
n
g
h
ig
h
p
o
we
r
le
v
els
1
4
k
W
.
Ho
we
v
e
r
,
af
te
r
o
p
t
i
m
iz
ati
o
n
,
t
h
is
e
x
ce
s
s
p
o
we
r
was
e
f
f
ec
t
iv
el
y
r
e
d
u
ce
d
,
r
esu
lti
n
g
i
n
t
h
e
b
att
er
y
o
p
e
r
at
in
g
at
a
m
o
r
e
ef
f
i
cie
n
t
8
k
W
.
T
h
ese
r
esu
lts
ca
n
b
en
ef
it
t
h
e
b
at
te
r
y
i
n
s
e
v
e
r
al
wa
y
s
.
Fi
r
s
tl
y
,
t
h
e
o
p
ti
m
iz
ati
o
n
p
r
o
c
ess
e
n
s
u
r
es
t
h
at
t
h
e
b
at
te
r
y
o
p
er
ates
wit
h
i
n
a
m
o
r
e
co
n
t
r
o
ll
ed
a
n
d
e
f
f
ici
e
n
t
r
a
n
g
e
o
f
p
o
w
e
r
,
s
p
e
ci
f
ic
all
y
r
ed
u
ce
d
f
r
o
m
1
4
t
o
8
k
W
.
T
h
is
o
p
ti
m
iz
ati
o
n
h
el
p
s
p
r
e
v
e
n
t
e
x
t
r
e
m
e
c
h
ar
g
i
n
g
an
d
d
is
c
h
ar
g
i
n
g
cy
cles
,
wh
ic
h
ca
n
c
o
n
t
r
i
b
u
te
t
o
a
lo
n
g
e
r
li
f
es
p
a
n
f
o
r
t
h
e
b
att
er
y
.
S
ec
o
n
d
l
y
,
b
y
a
v
o
i
d
i
n
g
e
x
ce
s
s
i
v
e
p
o
we
r
le
v
e
ls
th
a
t
e
x
c
ee
d
d
e
m
a
n
d
,
t
h
e
b
att
e
r
y
is
s
u
b
j
ec
t
e
d
t
o
less
s
t
r
ess
a
n
d
s
tr
ai
n
.
F
ig
u
r
e
1
1
s
u
m
m
a
r
i
ze
s
t
h
e
co
m
p
a
r
is
o
n
b
et
we
en
t
h
e
t
o
t
al
p
r
o
d
u
c
ti
o
n
w
ith
t
h
e
p
o
we
r
b
a
tte
r
y
b
ef
o
r
e
a
n
d
af
te
r
o
p
ti
m
i
za
t
io
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
9
2
I
n
t J Ap
p
l Po
wer
E
n
g
,
Vo
l.
1
4
,
No
.
1
,
Ma
r
ch
20
2
5
:
202
-
2
1
1
208
(
a)
(
b
)
Fig
u
r
e
8
.
T
o
tal
p
r
o
d
u
ctio
n
:
(
a)
an
d
th
e
e
x
ce
s
s
/s
h
o
r
tag
e
p
o
we
r
an
d
(
b
)
b
ef
o
r
e
o
p
tim
izatio
n
(
a)
(
b
)
Fig
u
r
e
9
.
T
o
tal
p
r
o
d
u
ctio
n
:
(
a)
an
d
th
e
e
x
ce
s
s
/s
h
o
r
tag
e
p
o
we
r
an
d
(
b
)
af
te
r
o
p
tim
izatio
n
Fig
u
r
e
1
0
.
T
o
tal
p
r
o
d
u
ctio
n
an
d
b
atter
y
p
o
wer
b
ef
o
r
e
an
d
a
f
ter
o
p
tim
izatio
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
Op
timiz
a
tio
n
a
n
d
ma
n
a
g
eme
n
t o
f so
la
r
a
n
d
w
in
d
p
r
o
d
u
ctio
n
fo
r
…
(
Mo
h
a
med
E
l H
a
fyd
y
)
209
Fig
u
r
e
1
1
.
Su
m
m
ar
y
o
f
c
o
m
p
a
r
is
o
n
b
ef
o
r
e
an
d
af
ter
o
p
tim
iz
atio
n
4.
CO
NCLU
SI
O
N
I
n
co
n
clu
s
io
n
,
th
is
s
tu
d
y
d
e
m
o
n
s
tr
ates
th
e
ef
f
ec
tiv
en
ess
o
f
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
PS
O)
in
en
h
an
cin
g
o
u
r
m
icr
o
g
r
id
s
y
s
te
m
.
Prio
r
to
o
p
tim
izatio
n
,
p
o
w
er
g
en
e
r
atio
n
f
r
o
m
s
o
lar
p
an
el
s
an
d
win
d
tu
r
b
in
es
ex
h
ib
ited
s
ig
n
if
ican
t
f
lu
ctu
ati
o
n
s
,
r
esu
ltin
g
in
i
n
ef
f
icien
cie
s
an
d
a
co
m
b
in
ed
3
5
%
wastag
e
an
d
s
h
o
r
tag
e
o
f
to
tal
p
o
wer
g
en
er
ated
.
T
h
e
ap
p
licatio
n
o
f
th
e
PS
O
alg
o
r
ith
m
s
u
b
s
tan
tially
im
p
r
o
v
ed
th
e
s
y
s
tem
b
y
alig
n
in
g
p
o
wer
g
en
e
r
atio
n
m
o
r
e
clo
s
ely
with
ac
tu
al
elec
tr
icity
d
em
an
d
.
Po
s
t
-
o
p
tim
izatio
n
,
th
e
p
o
wer
r
an
g
e
was
r
ed
u
ce
d
to
1
3
-
1
5
k
ilo
watts,
r
ed
u
cin
g
in
ef
f
icien
cies
to
ar
o
u
n
d
1
0
%
o
f
t
h
e
to
tal
p
o
wer
g
e
n
er
ated
.
M
o
r
eo
v
e
r
,
th
e
o
p
tim
izatio
n
p
o
s
itiv
ely
im
p
ac
ted
th
e
b
atter
y
'
s
life
s
p
an
b
y
p
r
ev
en
tin
g
ex
tr
em
e
ch
ar
g
in
g
an
d
d
is
ch
ar
g
in
g
cy
cles,
co
n
tr
ib
u
tin
g
to
th
e
o
v
er
all
s
u
s
tain
ab
ilit
y
o
f
th
e
e
n
er
g
y
s
y
s
tem
.
T
h
e
p
ap
er
'
s
co
n
tr
ib
u
tio
n
lies
in
s
u
cc
ess
f
u
lly
ad
d
r
ess
in
g
p
o
wer
im
b
alan
ce
ch
allen
g
es,
en
h
an
c
in
g
ef
f
icien
cy
,
an
d
p
r
o
m
o
tin
g
s
u
s
tain
ab
le
en
er
g
y
u
s
e.
Ho
wev
er
,
th
er
e
a
r
e
s
o
m
e
lim
itatio
n
s
to
th
is
wo
r
k
th
at
ca
n
b
e
ad
d
r
ess
ed
in
f
u
tu
r
e
r
esear
ch
.
T
h
e
s
tu
d
y
f
o
cu
s
es
s
o
lely
o
n
th
e
PSO
alg
o
r
ith
m
,
p
o
ten
tially
o
v
er
lo
o
k
in
g
o
th
e
r
o
p
tim
izatio
n
tech
n
iq
u
es
th
at
co
u
ld
y
iel
d
b
etter
o
r
m
o
r
e
r
o
b
u
s
t
r
esu
lts
in
d
if
f
er
e
n
t
s
ce
n
ar
io
s
.
T
h
e
ef
f
ec
tiv
en
ess
o
f
th
e
PS
O
alg
o
r
i
th
m
was
ev
alu
ated
b
ased
o
n
s
p
ec
i
f
ic
d
ata
s
ets
f
o
r
s
o
lar
an
d
win
d
p
o
wer
g
en
er
at
io
n
,
an
d
its
p
er
f
o
r
m
an
ce
m
a
y
v
ar
y
with
d
if
f
e
r
en
t
d
ata
in
p
u
ts
o
r
u
n
d
er
d
if
f
er
e
n
t
en
v
ir
o
n
m
en
tal
co
n
d
itio
n
s
.
O
v
er
all,
th
is
s
tu
d
y
g
iv
es
a
s
tr
o
n
g
s
tar
tin
g
p
o
i
n
t
f
o
r
im
p
r
o
v
in
g
m
icr
o
g
r
id
o
p
tim
iza
tio
n
,
p
r
o
v
id
in
g
u
s
ef
u
l
in
s
ig
h
ts
an
d
p
a
v
in
g
th
e
way
f
o
r
f
u
t
u
r
e
ad
v
an
ce
m
e
n
ts
in
en
er
g
y
m
an
ag
em
e
n
t a
n
d
s
u
s
tain
ab
ilit
y
.
RE
F
E
R
E
NC
E
S
[
1
]
S
.
A
h
ma
d
,
M
.
S
h
a
f
i
u
l
l
a
h
,
C
.
B
.
A
h
me
d
,
a
n
d
M
.
A
l
o
w
a
i
f
e
e
r
,
“
A
R
e
v
i
e
w
o
f
M
i
c
r
o
g
r
i
d
E
n
e
r
g
y
M
a
n
a
g
e
m
e
n
t
a
n
d
C
o
n
t
r
o
l
S
t
r
a
t
e
g
i
e
s,
”
I
E
EE
A
c
c
e
ss
,
v
o
l
.
1
1
,
p
p
.
2
1
7
2
9
–
2
1
7
5
7
,
2
0
2
3
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
ESS
.
2
0
2
3
.
3
2
4
8
5
1
1
.
[
2
]
K
.
G
a
o
,
T.
W
a
n
g
,
C
.
H
a
n
,
J
.
X
i
e
,
Y
.
M
a
,
a
n
d
R
.
P
e
n
g
,
“
A
R
e
v
i
e
w
o
f
O
p
t
i
mi
z
a
t
i
o
n
o
f
M
i
c
r
o
g
r
i
d
O
p
e
r
a
t
i
o
n
,
”
E
n
e
rg
i
e
s
,
v
o
l
.
1
4
,
n
o
.
1
0
,
p
.
2
8
4
2
,
M
a
y
2
0
2
1
,
d
o
i
:
1
0
.
3
3
9
0
/
e
n
1
4
1
0
2
8
4
2
.
[
3
]
M
.
K
h
a
r
r
i
c
h
,
L.
A
b
u
a
l
i
g
a
h
,
S
.
K
a
me
l
,
H
.
A
b
d
El
-
S
a
t
t
a
r
,
a
n
d
M
.
T
o
st
a
d
o
-
V
é
l
i
z
,
“
A
n
I
mp
r
o
v
e
d
A
r
i
t
h
m
e
t
i
c
O
p
t
i
m
i
z
a
t
i
o
n
A
l
g
o
r
i
t
h
m
f
o
r
d
e
si
g
n
o
f
a
m
i
c
r
o
g
r
i
d
w
i
t
h
e
n
e
r
g
y
st
o
r
a
g
e
s
y
st
e
m:
C
a
se
s
t
u
d
y
o
f
E
l
K
h
a
r
g
a
O
a
s
i
s,
E
g
y
p
t
,
”
J
o
u
r
n
a
l
o
f
E
n
e
r
g
y
S
t
o
r
a
g
e
,
v
o
l
.
5
1
,
p
.
1
0
4
3
4
3
,
J
u
l
.
2
0
2
2
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
st
.
2
0
2
2
.
1
0
4
3
4
3
.
[
4
]
S
.
A
.
S
h
e
z
a
n
e
t
a
l
.
,
“
E
v
a
l
u
a
t
i
o
n
o
f
D
i
f
f
e
r
e
n
t
O
p
t
i
mi
z
a
t
i
o
n
Te
c
h
n
i
q
u
e
s
a
n
d
C
o
n
t
r
o
l
S
t
r
a
t
e
g
i
e
s
o
f
H
y
b
r
i
d
M
i
c
r
o
g
r
i
d
:
A
R
e
v
i
e
w
,
”
En
e
r
g
i
e
s
,
v
o
l
.
1
6
,
n
o
.
4
,
p
.
1
7
9
2
,
F
e
b
.
2
0
2
3
,
d
o
i
:
1
0
.
3
3
9
0
/
e
n
1
6
0
4
1
7
9
2
.
[
5
]
M
.
F
.
I
s
h
r
a
q
u
e
,
A
.
R
a
h
ma
n
,
S
.
A
.
S
h
e
z
a
n
,
a
n
d
S
.
M
.
M
u
y
e
e
n
,
“
G
r
i
d
C
o
n
n
e
c
t
e
d
M
i
c
r
o
g
r
i
d
O
p
t
i
m
i
z
a
t
i
o
n
a
n
d
C
o
n
t
r
o
l
f
o
r
a
C
o
a
s
t
a
l
I
sl
a
n
d
i
n
t
h
e
I
n
d
i
a
n
O
c
e
a
n
,
”
S
u
st
a
i
n
a
b
i
l
i
t
y
,
v
o
l
.
1
4
,
n
o
.
2
4
,
p
.
1
6
6
9
7
,
D
e
c
.
2
0
2
2
,
d
o
i
:
1
0
.
3
3
9
0
/
su
1
4
2
4
1
6
6
9
7
.
[
6
]
A
.
A
l
l
o
u
h
i
,
S
.
R
e
h
m
a
n
,
a
n
d
M
.
K
r
a
r
t
i
,
“
R
o
l
e
o
f
e
n
e
r
g
y
e
f
f
i
c
i
e
n
c
y
m
e
a
su
r
e
s
a
n
d
h
y
b
r
i
d
P
V
/
b
i
o
mass
p
o
w
e
r
g
e
n
e
r
a
t
i
o
n
i
n
d
e
s
i
g
n
i
n
g
1
0
0
%
e
l
e
c
t
r
i
c
r
u
r
a
l
h
o
u
ses
:
A
c
a
se
s
t
u
d
y
i
n
M
o
r
o
c
c
o
,
”
E
n
e
r
g
y
a
n
d
B
u
i
l
d
i
n
g
s
,
v
o
l
.
2
3
6
,
p
.
1
1
0
7
7
0
,
A
p
r
.
2
0
2
1
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
n
b
u
i
l
d
.
2
0
2
1
.
1
1
0
7
7
0
.
[
7
]
B
.
E
.
B
a
r
k
o
u
k
i
e
t
a
l
.
,
“
A
n
E
c
o
n
o
mi
c
D
i
sp
a
t
c
h
f
o
r
a
S
h
a
r
e
d
En
e
r
g
y
S
t
o
r
a
g
e
S
y
st
e
m
U
si
n
g
M
I
LP
O
p
t
i
mi
z
a
t
i
o
n
:
A
C
a
s
e
S
t
u
d
y
o
f
a
M
o
r
o
c
c
a
n
M
i
c
r
o
g
r
i
d
,
”
E
n
e
r
g
i
e
s
,
v
o
l
.
1
6
,
n
o
.
1
2
,
p
.
4
6
0
1
,
Ju
n
.
2
0
2
3
,
d
o
i
:
1
0
.
3
3
9
0
/
e
n
1
6
1
2
4
6
0
1
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
9
2
I
n
t J Ap
p
l Po
wer
E
n
g
,
Vo
l.
1
4
,
No
.
1
,
Ma
r
ch
20
2
5
:
202
-
2
1
1
210
[
8
]
H
.
A
l
l
o
u
h
i
,
A
.
A
l
l
o
u
h
i
,
K
.
M
.
A
l
m
o
h
a
mm
a
d
i
,
A
.
H
a
mr
a
n
i
,
a
n
d
A
.
Ja
mi
l
,
“
H
y
b
r
i
d
r
e
n
e
w
a
b
l
e
e
n
e
r
g
y
s
y
st
e
m
f
o
r
su
s
t
a
i
n
a
b
l
e
r
e
si
d
e
n
t
i
a
l
b
u
i
l
d
i
n
g
s
b
a
se
d
o
n
S
o
l
a
r
D
i
sh
S
t
i
r
l
i
n
g
a
n
d
w
i
n
d
Tu
r
b
i
n
e
w
i
t
h
h
y
d
r
o
g
e
n
p
r
o
d
u
c
t
i
o
n
,
”
E
n
e
r
g
y
C
o
n
v
e
rsi
o
n
a
n
d
Ma
n
a
g
e
m
e
n
t
,
v
o
l
.
2
7
0
,
p
.
1
1
6
2
6
1
,
O
c
t
.
2
0
2
2
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
n
c
o
n
ma
n
.
2
0
2
2
.
1
1
6
2
6
1
.
[
9
]
S
.
P
r
a
k
a
s
h
a
n
d
K
.
B
o
o
p
a
t
h
y
,
“
H
i
g
h
sp
e
e
d
B
LD
C
m
o
t
o
r
f
o
r
g
r
i
d
t
i
e
d
P
V
b
a
se
d
EV
s
y
st
e
m
u
s
i
n
g
h
y
b
r
i
d
P
S
O
-
sp
o
t
t
e
d
h
y
e
n
a
o
p
t
i
m
i
z
e
d
P
I
c
o
n
t
r
o
l
l
e
r
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
A
p
p
l
i
e
d
P
o
w
e
r
E
n
g
i
n
e
e
ri
n
g
,
v
o
l
.
1
3
,
n
o
.
3
,
p
p
.
7
6
8
–
7
8
2
,
S
e
p
.
2
0
2
4
,
d
o
i
:
1
0
.
1
1
5
9
1
/
i
j
a
p
e
.
v
1
3
.
i
3
.
p
p
7
6
8
-
7
8
2
.
[
1
0
]
R
.
M
o
u
a
c
h
i
,
M
.
A
.
Ja
l
l
a
l
,
F
.
G
h
a
r
n
a
t
i
,
a
n
d
M
.
R
a
o
u
f
i
,
“
M
u
l
t
i
o
b
j
e
c
t
i
v
e
S
i
z
i
n
g
o
f
a
n
A
u
t
o
n
o
m
o
u
s
H
y
b
r
i
d
M
i
c
r
o
g
r
i
d
U
si
n
g
a
M
u
l
t
i
m
o
d
a
l
D
e
l
a
y
e
d
P
S
O
A
l
g
o
r
i
t
h
m
:
A
C
a
se
S
t
u
d
y
o
f
a
F
i
sh
i
n
g
V
i
l
l
a
g
e
,
”
C
o
m
p
u
t
a
t
i
o
n
a
l
I
n
t
e
l
l
i
g
e
n
c
e
a
n
d
N
e
u
ro
s
c
i
e
n
c
e
,
v
o
l
.
2
0
2
0
,
p
p
.
1
–
1
8
,
A
u
g
.
2
0
2
0
,
d
o
i
:
1
0
.
1
1
5
5
/
2
0
2
0
/
8
8
9
4
0
9
4
.
[
1
1
]
A
.
E
i
d
a
n
d
M
.
A
b
d
e
l
-
A
k
h
e
r
,
“
P
o
w
e
r
L
o
ss
R
e
d
u
c
t
i
o
n
u
s
i
n
g
A
d
a
p
t
i
v
e
P
S
O
i
n
U
n
b
a
l
a
n
c
e
d
D
i
st
r
i
b
u
t
i
o
n
N
e
t
w
o
r
k
s,”
i
n
2
0
1
9
2
1
st
I
n
t
e
r
n
a
t
i
o
n
a
l
Mi
d
d
l
e
E
a
st
P
o
w
e
r
S
y
st
e
m
s
C
o
n
f
e
re
n
c
e
(
ME
P
C
O
N
)
,
D
e
c
.
2
0
1
9
,
p
p
.
6
7
5
–
6
8
0
,
d
o
i
:
1
0
.
1
1
0
9
/
M
EPCO
N
4
7
4
3
1
.
2
0
1
9
.
9
0
0
7
9
8
6
.
[
1
2
]
M
.
B
e
n
y
d
i
r
e
t
a
l
.
,
“
E
n
h
a
n
c
i
n
g
m
i
c
r
o
g
r
i
d
p
r
o
d
u
c
t
i
o
n
t
h
r
o
u
g
h
p
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
m
i
z
a
t
i
o
n
a
n
d
g
e
n
e
t
i
c
a
l
g
o
r
i
t
h
m,
”
I
AE
S
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
Ar
t
i
f
i
c
i
a
l
I
n
t
e
l
l
i
g
e
n
c
e
,
v
o
l
.
1
3
,
n
o
.
3
,
p
p
.
3
6
4
4
–
3
6
5
6
,
S
e
p
.
2
0
2
4
,
d
o
i
:
1
0
.
1
1
5
9
1
/
i
j
a
i
.
v
1
3
.
i
3
.
p
p
3
6
4
4
-
3
6
5
6
.
[
1
3
]
M
.
S
.
A
l
a
m,
F
.
S
.
A
l
-
I
sm
a
i
l
,
S
.
M
.
R
a
h
ma
n
,
M
.
S
h
a
f
i
u
l
l
a
h
,
a
n
d
M
.
A
.
H
o
ssa
i
n
,
“
P
l
a
n
n
i
n
g
a
n
d
p
r
o
t
e
c
t
i
o
n
o
f
D
C
m
i
c
r
o
g
r
i
d
:
A
c
r
i
t
i
c
a
l
r
e
v
i
e
w
o
n
r
e
c
e
n
t
d
e
v
e
l
o
p
me
n
t
s,”
En
g
i
n
e
e
ri
n
g
S
c
i
e
n
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
,
a
n
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
,
v
o
l
.
4
1
,
p
.
1
0
1
4
0
4
,
M
a
y
2
0
2
3
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
j
e
s
t
c
h
.
2
0
2
3
.
1
0
1
4
0
4
.
[
1
4
]
S
.
F
a
k
i
h
,
M
.
T.
M
a
b
r
o
u
k
,
M
.
B
a
t
t
o
n
-
H
u
b
e
r
t
,
a
n
d
B
.
L
a
c
a
r
r
i
e
r
e
,
“
B
i
-
l
e
v
e
l
a
n
d
m
u
l
t
i
-
o
b
j
e
c
t
i
v
e
o
p
t
i
mi
z
a
t
i
o
n
o
f
r
e
n
e
w
a
b
l
e
e
n
e
r
g
y
so
u
r
c
e
s
a
n
d
st
o
r
a
g
e
p
l
a
n
n
i
n
g
t
o
su
p
p
o
r
t
e
x
i
st
i
n
g
o
v
e
r
l
o
a
d
e
d
e
l
e
c
t
r
i
c
i
t
y
g
r
i
d
s,
”
En
e
rg
y
Re
p
o
r
t
s
,
v
o
l
.
1
0
,
p
p
.
1
4
5
0
–
1
4
6
6
,
N
o
v
.
2
0
2
3
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
g
y
r
.
2
0
2
3
.
0
8
.
0
1
5
.
[
1
5
]
E.
S
a
r
k
e
r
,
M
.
S
e
y
e
d
ma
h
mo
u
d
i
a
n
,
E.
Jame
i
,
B
.
H
o
r
a
n
,
a
n
d
A
.
S
t
o
j
c
e
v
s
k
i
,
“
O
p
t
i
ma
l
ma
n
a
g
e
me
n
t
o
f
h
o
me
l
o
a
d
s
w
i
t
h
r
e
n
e
w
a
b
l
e
e
n
e
r
g
y
i
n
t
e
g
r
a
t
i
o
n
a
n
d
d
e
ma
n
d
r
e
s
p
o
n
se
st
r
a
t
e
g
y
,
”
E
n
e
r
g
y
,
v
o
l
.
2
1
0
,
p
.
1
1
8
6
0
2
,
N
o
v
.
2
0
2
0
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
n
e
r
g
y
.
2
0
2
0
.
1
1
8
6
0
2
.
[
1
6
]
J.
G
a
r
c
í
a
F
e
r
r
e
r
o
e
t
a
l
.
,
“
M
o
d
e
l
i
n
g
a
s
o
l
a
r
p
r
e
ss
u
r
i
z
e
d
v
o
l
u
m
e
t
r
i
c
r
e
c
e
i
v
e
r
i
n
t
e
g
r
a
t
e
d
i
n
a
p
a
r
a
b
o
l
i
c
d
i
s
h
:
O
f
f
-
d
e
si
g
n
h
e
a
t
t
r
a
n
sf
e
r
s
,
t
e
m
p
e
r
a
t
u
r
e
s,
a
n
d
e
f
f
i
c
i
e
n
c
i
e
s,”
En
e
r
g
y
C
o
n
v
e
rs
i
o
n
a
n
d
Ma
n
a
g
e
m
e
n
t
,
v
o
l
.
2
9
3
,
p
.
1
1
7
4
3
6
,
O
c
t
.
2
0
2
3
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
n
c
o
n
ma
n
.
2
0
2
3
.
1
1
7
4
3
6
.
[
1
7
]
J.
T.
M
a
r
o
k
o
,
D
.
K
.
M
u
r
a
g
e
,
a
n
d
P
.
K
.
H
i
n
g
a
,
“
Lo
a
d
sh
e
d
d
i
n
g
i
n
i
s
l
a
n
d
e
d
m
i
c
r
o
g
r
i
d
u
s
i
n
g
f
u
z
z
y
l
i
n
e
a
r
p
r
o
g
r
a
mm
i
n
g
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
rn
a
l
o
f
A
p
p
l
i
e
d
Po
w
e
r
E
n
g
i
n
e
e
r
i
n
g
,
v
o
l
.
1
3
,
n
o
.
3
,
p
p
.
6
3
7
–
6
4
4
,
S
e
p
.
2
0
2
4
,
d
o
i
:
1
0
.
1
1
5
9
1
/
i
j
a
p
e
.
v
1
3
.
i
3
.
p
p
6
3
7
-
6
4
4
.
[
1
8
]
Y
.
A
c
h
o
u
r
,
A
.
O
u
a
mm
i
,
a
n
d
D
.
Z
e
j
l
i
,
“
M
o
d
e
l
P
r
e
d
i
c
t
i
v
e
C
o
n
t
r
o
l
B
a
s
e
d
D
e
man
d
R
e
sp
o
n
se
S
c
h
e
m
e
f
o
r
P
e
a
k
D
e
man
d
R
e
d
u
c
t
i
o
n
i
n
a
S
m
a
r
t
C
a
m
p
u
s I
n
t
e
g
r
a
t
e
d
M
i
c
r
o
g
r
i
d
,
”
IE
E
E
A
c
c
e
ss
,
v
o
l
.
9
,
p
p
.
1
6
2
7
6
5
–
1
6
2
7
7
8
,
2
0
2
1
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
ES
S
.
2
0
2
1
.
3
1
3
2
8
9
5
.
[
1
9
]
M
.
E
.
S
h
a
y
a
n
,
G
.
N
a
j
a
f
i
,
B
.
G
h
o
b
a
d
i
a
n
,
S
.
G
o
r
j
i
a
n
,
R
.
M
a
mat
,
a
n
d
M
.
F
.
G
h
a
z
a
l
i
,
“
M
u
l
t
i
-
m
i
c
r
o
g
r
i
d
o
p
t
i
mi
z
a
t
i
o
n
a
n
d
e
n
e
r
g
y
man
a
g
e
me
n
t
u
n
d
e
r
b
o
o
st
v
o
l
t
a
g
e
c
o
n
v
e
r
t
e
r
w
i
t
h
M
a
r
k
o
v
p
r
e
d
i
c
t
i
o
n
c
h
a
i
n
a
n
d
d
y
n
a
mi
c
d
e
c
i
s
i
o
n
a
l
g
o
r
i
t
h
m
,
”
Re
n
e
w
a
b
l
e
En
e
rg
y
,
v
o
l
.
2
0
1
,
p
p
.
1
7
9
–
1
8
9
,
D
e
c
.
2
0
2
2
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
r
e
n
e
n
e
.
2
0
2
2
.
1
1
.
0
0
6
.
[
2
0
]
T.
Ç
a
r
k
ı
t
a
n
d
M
.
A
l
ç
ı
,
“
C
o
m
p
a
r
i
so
n
o
f
t
h
e
p
e
r
f
o
r
ma
n
c
e
s
o
f
h
e
u
r
i
s
t
i
c
o
p
t
i
mi
z
a
t
i
o
n
a
l
g
o
r
i
t
h
ms
P
S
O
,
A
B
C
a
n
d
G
A
f
o
r
p
a
r
a
me
t
e
r
e
st
i
mat
i
o
n
i
n
t
h
e
d
i
sc
h
a
r
g
e
p
r
o
c
e
sses
o
f
L
i
-
N
M
C
b
a
t
t
e
r
y
,
”
J
o
u
r
n
a
l
o
f
E
n
e
r
g
y
S
y
st
e
m
s
,
v
o
l
.
6
,
n
o
.
3
,
p
p
.
3
8
7
–
4
0
0
,
S
e
p
.
2
0
2
2
,
d
o
i
:
1
0
.
3
0
5
2
1
/
j
e
s
.
1
0
9
4
1
0
6
.
[
2
1
]
D
.
R
e
k
i
o
u
a
,
S
.
B
e
n
s
mai
l
,
C
.
S
e
r
i
r
,
a
n
d
T
.
R
e
k
i
o
u
a
,
“
P
o
w
e
r
s
u
p
e
r
v
i
si
o
n
o
f
a
n
a
u
t
o
n
o
m
o
u
s
p
h
o
t
o
v
o
l
t
a
i
c
/
w
i
n
d
t
u
r
b
i
n
e
/
b
a
t
t
e
r
y
sy
st
e
m
w
i
t
h
M
P
P
T
u
s
i
n
g
a
d
a
p
t
a
t
i
v
e
f
u
z
z
y
l
o
g
i
c
c
o
n
t
r
o
l
l
e
r
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
rn
a
l
o
f
Ap
p
l
i
e
d
P
o
w
e
r
En
g
i
n
e
e
ri
n
g
,
v
o
l
.
1
2
,
n
o
.
1
,
p
p
.
9
0
–
1
0
1
,
M
a
r
.
2
0
2
3
,
d
o
i
:
1
0
.
1
1
5
9
1
/
i
j
a
p
e
.
v
1
2
.
i
1
.
p
p
9
0
-
1
0
1
.
[
2
2
]
S
.
D
o
r
a
h
a
k
i
,
R
.
D
a
s
h
t
i
,
a
n
d
H
.
R
.
S
h
a
k
e
r
,
“
O
p
t
i
ma
l
e
n
e
r
g
y
ma
n
a
g
e
m
e
n
t
i
n
t
h
e
smar
t
mi
c
r
o
g
r
i
d
c
o
n
si
d
e
r
i
n
g
t
h
e
e
l
e
c
t
r
i
c
a
l
e
n
e
r
g
y
st
o
r
a
g
e
s
y
st
e
m
a
n
d
t
h
e
d
e
m
a
n
d
-
si
d
e
e
n
e
r
g
y
e
f
f
i
c
i
e
n
c
y
p
r
o
g
r
a
m,”
J
o
u
rn
a
l
o
f
E
n
e
r
g
y
S
t
o
ra
g
e
,
v
o
l
.
2
8
,
p
.
1
0
1
2
2
9
,
A
p
r
.
2
0
2
0
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
s
t
.
2
0
2
0
.
1
0
1
2
2
9
.
[
2
3
]
A
.
O
u
a
mm
i
,
Y
.
A
c
h
o
u
r
,
D
.
Ze
j
l
i
,
a
n
d
H
.
D
a
g
d
o
u
g
u
i
,
“
S
u
p
e
r
v
i
so
r
y
M
o
d
e
l
P
r
e
d
i
c
t
i
v
e
C
o
n
t
r
o
l
f
o
r
O
p
t
i
m
a
l
E
n
e
r
g
y
M
a
n
a
g
e
me
n
t
o
f
N
e
t
w
o
r
k
e
d
S
mart
G
r
e
e
n
h
o
u
s
e
s
I
n
t
e
g
r
a
t
e
d
M
i
c
r
o
g
r
i
d
,
”
I
EEE
T
r
a
n
sa
c
t
i
o
n
s
o
n
Au
t
o
m
a
t
i
o
n
S
c
i
e
n
c
e
a
n
d
E
n
g
i
n
e
e
ri
n
g
,
v
o
l
.
1
7
,
n
o
.
1
,
p
p
.
1
1
7
–
1
2
8
,
J
a
n
.
2
0
2
0
,
d
o
i
:
1
0
.
1
1
0
9
/
TA
S
E.
2
0
1
9
.
2
9
1
0
7
5
6
.
[
2
4
]
S
.
S
a
n
k
a
r
a
n
a
n
t
h
,
M
.
K
a
r
t
h
i
g
a
,
S
.
E.
,
S
.
S
.
,
a
n
d
D
.
P
.
B
a
v
i
r
i
set
t
i
,
“
A
I
-
e
n
a
b
l
e
d
m
e
t
a
h
e
u
r
i
st
i
c
o
p
t
i
m
i
z
a
t
i
o
n
f
o
r
p
r
e
d
i
c
t
i
v
e
man
a
g
e
me
n
t
o
f
r
e
n
e
w
a
b
l
e
e
n
e
r
g
y
p
r
o
d
u
c
t
i
o
n
i
n
sm
a
r
t
g
r
i
d
s,”
E
n
e
rg
y
Re
p
o
rt
s
,
v
o
l
.
1
0
,
p
p
.
1
2
9
9
–
1
3
1
2
,
N
o
v
.
2
0
2
3
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
g
y
r
.
2
0
2
3
.
0
8
.
0
0
5
.
[
2
5
]
M
.
K
h
a
r
r
i
c
h
e
t
a
l
.
,
“
D
e
v
e
l
o
p
e
d
A
p
p
r
o
a
c
h
B
a
se
d
o
n
E
q
u
i
l
i
b
r
i
u
m
O
p
t
i
m
i
z
e
r
f
o
r
O
p
t
i
ma
l
D
e
s
i
g
n
o
f
H
y
b
r
i
d
P
V
/
W
i
n
d
/
D
i
e
s
e
l
/
B
a
t
t
e
r
y
M
i
c
r
o
g
r
i
d
i
n
D
a
k
h
l
a
,
M
o
r
o
c
c
o
,
”
I
EEE
Ac
c
e
ss
,
v
o
l
.
9
,
p
p
.
1
3
6
5
5
–
1
3
6
7
0
,
2
0
2
1
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
ESS
.
2
0
2
1
.
3
0
5
1
5
7
3
.
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
Mo
h
a
m
e
d
El
H
a
fy
d
y
wa
s
b
o
r
n
i
n
Zag
o
ra
,
M
o
ro
c
c
o
in
1
9
8
2
.
He
re
c
e
iv
e
d
a
M
a
ste
r’s
d
e
g
re
e
in
p
ro
c
e
ss
a
n
d
a
n
a
ly
sis
fo
r
a
ir
q
u
a
li
t
y
trea
tme
n
t
f
ro
m
th
e
F
a
c
u
lt
y
o
f
S
c
ie
n
c
e
,
Ib
n
Zo
h
r
Un
i
v
e
rsity
,
A
g
a
d
ir
M
o
ro
c
c
o
.
He
is
c
u
rre
n
tl
y
p
u
rs
u
in
g
a
Ph
.
D
.
d
e
g
re
e
in
th
e
Lab
o
ra
to
r
y
o
f
En
g
i
n
e
e
rin
g
S
c
ien
c
e
s a
n
d
En
e
rg
y
wit
h
t
h
e
Na
ti
o
n
a
l
S
c
h
o
o
l
o
f
Ap
p
li
e
d
S
c
ien
c
e
s
,
Ib
n
Zo
h
r
Un
iv
e
rsity
,
Ag
a
d
ir
M
o
ro
c
c
o
.
His
re
se
a
rc
h
in
tere
st
is
a
rti
ficia
l
i
n
telli
g
e
n
c
e
fo
r
m
icro
g
rid
m
a
n
a
g
e
m
e
n
t.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
m
o
h
a
m
e
d
.
e
l
h
a
fy
d
y
@e
d
u
.
u
iz.ac
.
m
a
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
Op
timiz
a
tio
n
a
n
d
ma
n
a
g
eme
n
t o
f so
la
r
a
n
d
w
in
d
p
r
o
d
u
ctio
n
fo
r
…
(
Mo
h
a
med
E
l H
a
fyd
y
)
211
Yo
u
ss
e
f
O
u
b
a
il
wa
s
b
o
rn
in
Ag
a
d
ir,
M
o
r
o
c
c
o
,
i
n
1
9
9
4
.
He
h
o
ld
s
a
d
o
c
to
ra
te
in
e
lec
tri
c
a
l
e
n
g
in
e
e
rin
g
,
a
u
t
o
m
a
ti
o
n
,
a
n
d
re
n
e
wa
b
le
e
n
e
rg
y
.
He
e
a
rn
e
d
h
is
e
n
g
i
n
e
e
rin
g
d
e
g
re
e
in
in
d
u
strial
e
n
g
in
e
e
rin
g
in
2
0
1
7
fr
o
m
th
e
Éco
le
Na
ti
o
n
a
le
d
e
s
S
c
i
e
n
c
e
s
Ap
p
li
q
u
é
s,
Ib
n
Zo
h
r
Un
iv
e
rsity
,
Ag
a
d
ir,
M
o
r
o
c
c
o
.
His
re
se
a
rc
h
fo
c
u
se
s
o
n
a
rti
f
icia
l
in
telli
g
e
n
c
e
a
n
d
ro
b
u
st
c
o
n
tro
ll
e
rs
fo
r
th
e
in
te
g
ra
ti
o
n
o
f
re
n
e
wa
b
le
e
n
e
rg
ies
with
in
m
icro
g
rid
t
o
p
o
lo
g
ies
.
He
c
a
n
b
e
c
o
n
tac
ted
at
e
m
a
il
:
y
o
u
ss
e
f.
o
u
b
a
il
@e
d
u
.
u
iz.ac
.
m
a
.
Be
n
y
d
ir
M
o
h
a
m
e
d
re
c
e
iv
e
d
h
is
P
h
.
D
.
c
a
n
d
id
a
te
a
n
d
s
u
b
stit
u
te
tea
c
h
e
r
sp
e
c
ializin
g
in
El
e
c
tri
c
a
l
En
g
in
e
e
rin
g
a
t
th
e
Hig
h
S
c
h
o
o
l
o
f
Te
c
h
n
o
l
o
g
ies
in
Ag
a
d
ir
(ES
T
Ag
a
d
ir),
o
r
ig
i
n
a
tes
fro
m
Ag
a
d
ir
,
M
o
r
o
c
c
o
.
His
re
se
a
rc
h
,
in
teg
r
a
l
to
h
is
n
a
ti
o
n
a
l
d
o
c
t
o
ra
l
th
e
sis,
is
p
rima
ril
y
fo
c
u
se
d
o
n
re
n
e
wa
b
le
e
n
e
r
g
y
,
e
n
g
i
n
e
e
rin
g
sc
ien
c
e
,
a
n
d
e
n
e
rg
y
m
a
n
a
g
e
m
e
n
t
.
He
c
a
n
b
e
c
o
n
tac
ted
at
e
m
a
il
:
m
o
h
a
m
e
d
.
b
e
n
y
d
ir@ed
u
.
u
iz.ac
.
m
a
.
Elm
a
h
n
i
L
a
h
o
u
ss
in
e
Ph
.
D
.
in
El
e
c
tri
c
a
l
En
g
in
e
e
rin
g
a
n
d
Re
n
e
wa
b
le
En
e
r
g
y
.
Wi
n
n
e
r
o
f
ENS
E
T
Ra
b
a
t
i
n
1
9
9
3
.
M
e
m
b
e
r
o
f
th
e
La
b
o
ra
to
r
y
o
f
M
a
teria
ls
a
n
d
Re
n
e
wa
b
le
En
e
rg
y
(RM
EL
)
,
P
r
o
fe
ss
o
r
a
t
t
h
e
F
a
c
u
lt
y
o
f
S
c
ien
c
e
,
Ib
n
Zo
h
r
Un
i
v
e
rsity
,
A
g
a
d
ir.
His
re
se
a
rc
h
is
fo
c
u
se
d
o
n
S
m
a
rt
G
rid
,
e
lec
tri
c
v
e
h
icle
s,
d
e
m
a
n
d
re
sp
o
n
se
,
e
n
e
rg
y
e
fficie
n
c
y
,
re
n
e
wa
b
le
e
n
e
rg
y
in
te
g
ra
ti
o
n
,
e
n
e
rg
y
sto
ra
g
e
,
a
n
d
d
istr
ib
u
ted
re
so
u
rc
e
s.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
l.
e
lma
h
n
i@u
iz.ac
.
m
a.
Elm
o
u
t
a
wa
k
il
Ala
o
u
i
M
y
Ra
c
h
id
re
c
e
iv
e
d
h
is
P
h
.
D
.
a
t
th
e
Un
iv
e
rsit
y
Ib
n
Zo
h
r
Ag
a
d
ir,
M
o
ro
c
c
o
,
wi
th
a
Ba
c
h
e
l
o
r
in
E
lec
tro
n
ics
ENS
ET
,
Ra
b
a
t
a
n
d
M
a
ste
rs
in
In
d
u
str
ial
En
g
i
n
e
e
rin
g
a
t
t
h
e
ENS
A
Ag
a
d
ir.
His
d
o
c
to
ra
l
t
h
e
sis
fo
c
u
se
d
o
n
t
h
e
De
fe
n
siv
e
S
o
ftwa
re
p
ro
c
e
ss
o
rs.
P
e
rm
a
n
e
n
t
m
e
m
b
e
r
in
E
n
g
i
n
e
e
rin
g
S
c
ien
c
e
s
La
b
o
ra
to
ry
a
n
d
E
n
e
rg
y
M
a
n
a
g
e
m
e
n
t
.
Re
sp
o
n
sib
le
o
f
th
e
In
d
u
strial
S
y
st
e
m
s
Op
ti
m
iza
ti
o
n
Re
se
a
rc
h
Tea
m
.
Ag
a
d
ir,
M
o
ro
c
c
o
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
r
.
a
lao
u
i@
u
iz.ac
.
m
a
.
Evaluation Warning : The document was created with Spire.PDF for Python.