Indonesian J
ournal of Ele
c
trical Engin
eering and
Computer Sci
e
nce
Vol. 1, No. 3,
March 20
16, pp. 543 ~ 5
5
5
DOI: 10.115
9
1
/ijeecs.v1.i3.pp54
3-5
5
5
543
Re
cei
v
ed
De
cem
ber 1
3
, 2015; Re
vi
sed
Febr
uary 19,
2016; Accept
ed Feb
r
ua
ry
28, 2016
Advanced Optimal for Power-Electronic Syst
ems for
the Grid Integration of Energy Sources
Salam Waley
Shneen
Schoo
l of Elect
r
ical & Electro
n
i
c Engi
neer
in
g, Huazh
o
n
g
Uni
v
ersit
y
of Sci
e
n
c
e and T
e
chno
log
y
/ W
uhan,
Chin
a
Electromec
han
ical En
gin
eeri
n
g Dep
a
rtment,
Univers
i
t
y
of
T
e
chn
o
lo
g
y
/Bag
hda
d,
Iraq
e-mail: salam_w
a
ley
73@y
a
hoo.com
A
b
st
r
a
ct
Ren
e
w
able
a
n
d
cle
a
n
e
nerg
i
es lik
e
a p
hoto
v
oltaic (P
V) e
n
e
rgy
and
w
i
nd
ener
gy (W
E), they c
a
n
contrib
u
te in d
e
creas
ing the
electric e
nergy
cos
t. Energy storage is n
e
c
e
ssary in PV and W
E
hybri
d
system w
i
th th
e vari
abl
e n
a
tu
re. A hybri
d
sy
stem (PV,
WE
and
di
esel), it
uses th
e ai
m
of mi
ni
mi
z
i
n
g
th
e
total cost and
ensur
ing th
e e
nergy av
ail
a
b
l
e. In this
pape
r, the mod
e
li
n
g
and cost a
n
a
lysis of a hyb
r
id
system (PV, WE and d
i
ese
l
) consi
deri
ng thre
e types syste
m
s: First, diesel
w
i
th a hybrid s
ystem. Seco
nd
,
dies
el an
d batt
e
ry w
i
th a hybrid system. Thir
d, grid
, battery and hy
brid syst
em. In co
mp
ari
s
on to all types
,
for cost a
n
a
l
ys
is, a
mathe
m
atical
mod
e
l
hav
e i
n
trod
uced
fo
r eac
h typ
e
. T
here
are
tw
o p
a
rts of this
w
o
r
k
.
First by Homer
softw
are, it ha
s been us
ed to
find the syst
e
m
feasi
b
i
lity an
d cond
uct the econ
o
m
ic an
al
ysis
.
Se
co
nd
b
y
Ma
tl
a
b
sim
u
l
a
ti
on
,
th
i
s
pa
pe
r in
cl
ud
e
s
sta
t
us
of
g
r
id i
n
tegr
atio
n i
n
o
ne
day
thro
ugh
tw
enty fou
r
.
T
he p
o
w
e
r ge
nerati
on
by w
i
nd tur
b
in
e, th
e ch
ang
e
of
w
i
nd sp
eed
w
h
ich
effect on
valu
es
of po
w
e
r
gen
eratio
n. T
he pow
er g
ener
ation
by
sol
a
r cell, the ch
an
g
e
of temper
at
u
r
e an
d rad
i
atio
n w
h
ich effect
i
n
valu
es of pow
e
r
gen
eratio
n. T
he b
a
ttery ba
n
k
, it uses to
en
ergy stora
ge a
nd it is
k
eep
in
g
the en
ergy to
us
e
it in next time
s w
hen the energy g
ener
ati
on not en
ou
g
h
to run the l
oads. T
he pre
s
ence of di
es
el to
compe
n
sate fo
r the shortfall
i
n
ge
nerati
on t
o
meet
the re
quir
ed l
oad c
a
pacity. T
he
main a
d
va
ntag
e
s
of
PMSM are high torque
densit
y, high
efficiency and s
m
all s
i
z
e
.
Photov
oltaic power
gener
ation system
is
the
PV gen
eratio
n
techno
logy is
treated as th
e most
pro
m
i
s
ing tech
no
lo
g
y
among r
ene
w
able e
nerg
i
e
s
.
Photovoltaic (PV) power generation syst
em is a pr
om
isi
ng source
of energy with
great
int
e
rest in clean
and
renew
ab
le e
n
e
r
gy sources.
Ke
y
w
or
ds
:
Grid Integratio
n, Pow
e
r Electroni
c, PV,
W
i
nd, Di
esel, Battery, PMSM, F
u
zz
y
,
P
I
and PSO
1. Introduc
tion
Ren
e
wable
-
Energy Sou
r
ces ne
w strategi
e
s
like P
V
and Wind
, these appli
c
atio
n
s
become mo
re integrated
with t
he gri
d
-based sy
ste
m
s [1]. A power-con
dition
ing syste
m
u
s
ed in
a grid
co
nne
cted for ph
oto-voltaic (PV) g
enerati
on pl
a
n
ts [2]. A new powe
r
-ele
ctronic te
chn
o
lo
gy
for the integration of energy s
ource
s to develop a mathemati
c
al
model of a dc/a
c full-bri
d
ge
swit
chin
g
co
nverter with
curre
n
t control fo
r PV g
r
i
d
-conn
ecte
d
system
an
d
energy-stora
ge
system for the grid
system is disconnected fo
r any
reason, and the di
stributed generation still
sup
p
lie
s t
o
any
sect
io
n of
local loa
d
s [
3
]
.
T
he av
aila
ble po
wer from the PV system is hig
h
ly
depe
ndent o
n
sola
r radi
ation. To overcome th
is defi
c
ien
c
y of the PV system,
the PV module
wa
s integrated with the wind
-turbine
system [4]. These ar
e voltage
s decrease with wi
nd
penetration a
nd
in
crea
se with sola
r
p
e
netration
[5]. The
ren
e
wa
bl
e en
ergy,
Wi
nd e
nergy an
d PV
energy whi
c
h
with power el
ectro
n
ics a
r
e
cha
ngin
g
c
h
a
r
acte
r pa
rt in the electri
c
ity gene
ration [6]
.
Incre
a
si
ng o
r
i
entation for the use of PV in
industry a
nd ele
c
trical applia
nce
s
b
e
ca
use
PV energy is predi
ctable t
o
play big rol
e
in futu
re smart grid
s a
s
distributio
n rene
wable
so
urce
[7]. PV system with PMS
M
drive i
s
in
vestigated.
T
he PV sy
ste
m
appli
c
ation
is p
r
o
s
pe
cte
d
, in
orde
r to
hig
h
light the i
r
radi
ation effe
ct o
n
the PV
pan
el feedi
ng th
e
PMSM [8]. T
he PV
sou
r
ce
to
an A
C
voltage source by i
n
verter have
the abilit
y
for controlling
a PMSM
[9].
A way cont
rol (PI)
in additio
n
to
the co
ntroll
e
r
integ
r
al
rela
tive formulate
d
and i
m
ple
m
ented, u
s
in
g sp
eed
co
ntrol
magnet
syn
c
hron
ou
s mot
o
r d
r
ive
syste
m
and
a
p
e
rmanent pilot pha
se. While
the
ne
w stra
tegy
prom
otes tra
d
itional PI co
ntrol pe
rform
ance to
a large extent, an
d prove
s
to
be a mod
e
l-f
r
ee
approa
ch
co
mpletely, it also
kee
p
s th
e
stru
cture an
d
feature
s
of a
simple PI
con
t
rol [10].The
use
con
s
ol
e mod
e
instea
d of Fuzzy-PI co
n
t
rol to improv
e the perfo
rmance of en
gine
s PMSM. To
control the speed of PMSM motor usi
n
g fuzzy logi
c (FL
)
app
roa
c
h leads to a
spe
ed control
to
Evaluation Warning : The document was created with Spire.PDF for Python.
ISSN: 25
02-4
752
IJEECS
Vol.
1, No. 3, March 20
16 : 543 – 555
544
improve th
e
dynamic beh
avior of the
motor d
r
ive
system an
d i
mmune
disorders to d
o
wn
load
and pa
ram
e
ter variatio
ns [
11]. In the drive system
s, and gai
ns fro
m
the traditio
nal ca
n’t usu
a
lly
be set
in
p
r
opo
rtion
-
inte
gral (PI) co
ntrolle
r spe
e
d
large eno
ugh be
cau
s
e
of
me
cha
n
i
c
al
resona
nce. As a re
sult, Perform
a
n
c
e d
egra
dation a
nd sp
eed
co
ntrol. The p
r
opo
sed F
L
C
has
been
co
mpa
r
ed with
traditi
onal PI control with
re
spe
c
t to the
spe
ed of respon
se a
nd
dyna
mic
load Torque.
Simulation and expe
rim
ental re
sult
s have prove
d
that FLC wa
s pro
p
o
s
e
d
is
sup
e
rio
r
to
th
e tra
d
itional
PI. This F
L
C
can
be
a
goo
d solution
for the hi
gh
-pe
r
forma
n
ce e
ngi
ne
lifts Systems. A modern
approa
ch t
o
co
ntro
l th
e sp
eed
of PMSM usin
g
parti
cle
swarm
optimizatio
n (PSO) to im
prove the al
gorithm p
a
ra
meters ob
server PI-. Simulate the system
unde
r differe
nt ope
rating
year
Con
d
itio
ns a
r
e
prepa
red and
th
e experim
ental setup. Use
P
S
O
algorith
m
an
d
optimizatio
n
make
s a
po
werful en
gine,
with faste
r
re
spo
n
se an
d h
i
gher
re
sol
u
tion
dynamic a
n
d
sensitive to
load variation [12-1
5
].
Grid is a sy
stem that would be
com
e
th
e
integratio
n of
ren
e
wable
e
nergy
so
urce
s a
nd while
kee
p
ing
th
e balan
ce between su
pply
a
nd
deman
d.
Applying hybrid
energy sy
stems usi
ng
r
ene
wa
ble e
nergy sources. Re
newa
b
le
energie
s
, con
s
istin
g
of ph
o
t
ovoltaics
an
d win
d
a
s
e
n
e
rgy
sou
r
ces,
batterie
s
to
store
the ex
cess
gene
rated
en
ergy
and
a
di
esel
ge
ne
rat
o
r
as a
ba
ck-up
system.
H
y
brid
sy
st
em
s b
a
s
e
d
on
P
V
and WE h
a
ve a long life
t
ime and no
rmally lo
w
maintena
nce
cost, and t
he appli
c
atio
n of
PV/WG/battery-ba
s
e
d
hyb
r
id sy
stems.
The aim of
u
s
ing a
WE/PV/diesel
syst
em to get low the
total co
st
an
d en
su
ring
th
e en
ergy ava
ilabilit
y. By using
the
HO
MER
softwa
r
e to
analy
s
is the
system
fea
s
i
b
ility and
co
n
duct th
e
syst
em e
c
o
nomi
c
al, it u
s
ed
to
obtain th
e o
p
t
imal de
sign
b
y
evaluating
all
the
po
ssibl
e
sol
u
ti
on
s. T
he
system
co
nsi
s
ts
of
WE and
PV a
s
rene
wable
p
o
w
er
sou
r
ces,
a di
esel
for
ba
ckup p
o
we
r, th
e batteri
es to sto
r
e
exce
ss en
ergy
a
nd imp
r
ove t
h
e
system reliabi
lity.
2. The Math
e
m
atical Mod
e
ls for Sy
stem’s Compon
ents
They h
a
ve,
Mathemati
c
al
Mod
e
l PV
Syst
em, Mat
hematical M
odel
Win
d
System,
Mathemati
c
al
Model Di
ese
l
System, Mathematic
al M
odel Di
esel
System, Mathematical Mo
del
Battery System, Battery price an
d wo
rth and Math
e
m
a
t
ical Model P
V
/WG/die
s
el/
battery syste
m
:
Figure 1. System Topolo
g
y
2.1. Mathem
atical Model
PV Sy
stem
PV System, T
he ene
rgy is
prod
uced by the sol
a
r
pa
ne
ls is directly sent to the con
s
ume
r
load. The re
n
e
wa
ble ene
rg
y conversion
system
s (PV). The PV generated p
o
wer by a particul
a
r
sola
r i
rra
diati
on level
an
d
power
output,
PV
output p
o
we
r (W) an
d
solar
irradi
ation
(w/m
2
). The
PV panel
s
are
se
nsitive
to tempe
r
a
t
ure
whi
c
h i
s
mo
st influ
enced by th
e variation
s
of
temperature
is the o
pen
-circuit voltag
e. Sola
r i
rra
diation level,
the variatio
n in am
bien
t
temperature i
s
take
n into consi
deration.
It can be obta
i
ned from the
sola
r ra
diatio
n by the following formula:
p
t
I
t
A
η
(1)
DC bus
AC
bus
PV
Battery
W
i
nd
AC L
o
ad
Diesel
Gri
d
DC-
A
C
DC-
D
C
AC-
D
C
Evaluation Warning : The document was created with Spire.PDF for Python.
IJEECS
ISSN:
2502-4
752
Adv
a
nc
ed Optimal for Power-Elec
t
ronic
Sy
s
t
ems
for t
he Grid In
tegration of ... (S
a
l
a
m
W
.
S
.
)
545
p
pv
(t): The output power of
each PV system at time t
A : A denotes the PV area (m
2
)
I(t): The sol
a
r radiation
(kW/m
2
)
η
pv
:
The overall efficiency of
PV panels a
nd DC/DC co
nverter
2.2. Mathem
atical Model
Wind Sy
stem
Wind
Syste
m
, the en
ergy is p
r
od
uced by th
e
wind turbine i
s
di
re
ctly se
nt to the
con
s
um
er loa
d
. The rene
wable ene
rgy conversi
on
system
s (win
d).
The wind turbine gen
erated
power
by wi
nd spee
d a
n
d
po
we
r outp
u
t, Wind tu
rb
ine outp
u
t po
wer (kW)
an
d Wi
nd velo
city
(m/s
).
Table 1. Power gen
eration
& wind spe
e
d
po
w
e
r ge
neratio
n
w
i
nd spee
d
starts
above 3.5 m/s
rated
9.5
m/s
stop
exceeding 25 m/
s
It can be obta
i
ned from the
wind
spe
ed b
y
the followin
g
formula:
P
t
0
v
t
V
c
u
t
or
v
t
V
c
u
t
P
v
t
V
c
u
t
v
V
c
u
t
Vc
u
t
t
v
P
v
t
V
c
u
t
(2)
V(t) : wind sp
eed (m/
s
)
P
r-
W
i
nd
: rated
power of the wind g
ene
rat
o
r (kW)
V
cut-in
: cut-in speed of the wind gen
erato
r
(m/s)
V
cut-out
: cut-out spee
d of the wind g
ene
rator (m/
s
)
v
r
: rated spe
ed of the win
d
gene
rato
r (m/s), re
sp
ecti
vely
and
p
Wi
n
d
(t) =N
W
i
nd
x P
W
i
nd(t)
N
Wi
n
d
:Num
be
r of wind ge
n
e
rato
rs
p
Wi
n
d
(t):Ove
r
a
ll produ
ce
d p
o
we
r
2.3. Mathem
atical Model
Diesel Sy
stem
Die
s
el syste
m
,
power ge
nerato
r
sho
u
l
d
be excl
u
d
e
d
to the b
a
ttery sto
r
age
ca
lculatio
n.
To satisfy loa
d
wh
en b
a
ttery stora
ge i
s
d
eplete
a
nd
when
wind
po
wer a
nd
sola
r p
o
we
r fail at th
is
times ope
rate
d Die
s
el ge
ne
rator
system.
It can
be
obt
ained
from
th
e fuel
co
nsu
m
ption
of
the
die
s
el
gen
erator
by the f
o
llowin
g
formula:
Cons
B
P
A
P
(3)
P
D
:output power of the die
s
el
P
N
D
: rated powe
r
B
D
= 0.0845 (L/kWh): coefficient
of the consumption
curve
A
D
= 0.246 (L
/kWh
): co
efficient
of the co
nsum
ption cu
rve
And
C
P
C
o
n
s
(4)
C
f
: hourly co
st of the fuel con
s
um
ption
P
fuel
: fuel
price
Evaluation Warning : The document was created with Spire.PDF for Python.
ISSN: 25
02-4
752
IJEECS
Vol.
1, No. 3, March 20
16 : 543 – 555
546
2.4. Mathem
atical Model
Battery
Sy
st
em
Battery, The
exce
ss
ene
rg
y from wi
nd t
u
rbin
e a
nd
so
lar p
anel
s i
s
store
d
in th
e
batterie
s
via the bi-direction
al inverters. To
cover the e
ner
gy deficit by the
store
d
en
erg
y
in batterie
s
.
In
this type
syst
em by
stori
n
g excess
en
ergy to
maxi
mize th
e u
s
a
ge of
ren
e
wa
ble e
nergy. It is
cap
able of re
duci
ng in fuel
con
s
umptio
n
.
It can
be o
b
tained
from th
e state
of
ch
arge
(S
O
C
) (battery ba
nk
is in
ch
argin
g
state,
battery ban
k is in disch
a
rgi
ng state
)
by the followi
ng formul
as:
Battery bank i
s
in ch
argi
ng
state:
E
t
E
t
1
1
σ
E
t
η
E
t
η
E
η
η
η
(5)
E
Batt
(t) : charg
e
quantitie
s o
f
battery bank at time (t), (kWh
)
E
Batt
(t_1) : ch
arge q
uantitie
s of battery
b
ank at time (t-1), (kWh
)
σ
: hourly self
-disch
arge rat
e
,
η
Inv
:denotes t
he inverte
r
efficien
cy
η
BC
: charg
e
e
fficiency of the battery ban
k
Battery bank i
s
in disch
a
rgi
ng state:
E
t
E
t1
1
σ
E
t
η
In
v
E
t
η
In
v
E
η
In
v/
η
η
In
v
(6)
η
BF
: disch
argi
ng efficien
cy of battery ban
k
2.5. Batter
y
Price and Worth
If the lifetime
of each b
a
ttery (5 years):
C
P
1
1
1i
1
1
i
1
1i
(7)
2.6. Mathem
atical Model
PV/WG/Dies
e
l/Batter
y
S
y
stem
C
i1
i
1
i
1
N
C
N
C
N
C
N
C
C
(8)
and
C
N
C
N
C
C
(9)
2.7. Data
bas
e
w
i
th Infor
m
ation Sy
st
em and Algo
rithm Work
In this
wo
rk, there a
r
e
many vari
abl
es
lik
e
PV
Sys
t
em Variables
, Wind Sys
t
em
Variabl
es,
Di
esel V
a
ria
b
l
e
s, Battery
Variabl
es
an
d Loa
d vari
able
s
. About
discu
s
s the
s
e
variable
s
in a
ll this wo
rk
system ea
ch o
n
e
vari
able it h
a
s code a
nd t
h
is code in
clu
de symb
ols t
o
definition the
s
e varia
b
le
s suppo
se the fo
llowing:
PVP
o
w
erS
y
s
t
e
m
Pp
v
X
i
(10
)
WindP
o
w
erS
y
s
t
e
m
Pwind
Pw
X
j
(11
)
Diesel
P
ow
er
S
y
st
em
P
diesel
P
d
Xk
(12
)
Batt
er
y
P
ow
er
S
y
st
em
P
ba
tt
er
y
P
bX
m
(13
)
Load
P
ow
erS
y
s
t
e
m
Pload
Pl
X
n
(14
)
Usi
ng this
symbols, to kno
w
beh
avior a
syst
em in on
e day with hel
p status e
qua
tions:
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Adv
a
nc
ed Optimal for Power-Elec
t
ronic
Sy
s
t
ems
for t
h
e Grid In
tegration of ... (S
a
l
a
m
W
.
S
.
)
547
Pv
Xi
,
i
0at
T
0
to
1
hours
12p
.
m
1
a
.
m
and
i
1atT
1
to2hours
1a
.
m
2
a
.
m
and
i
2atT
2
to3hours
2a
.
m
3
a
.
m
and
i
3atT
3
to4hours
3a
.
m
4
a
.
m
and
i
4atT
4
to5hours
4a
.
m
5
a
.
m
a
n
d
……………
…
i
23a
t
T
23
to24hours
11p
.
m
12p.
m
Pw
Xj,
j
0
at
T
0
t
o1hours
12p.
m
1
a
.
m
and
j
1atT
1
to2hours
1a
.
m
2
a
.
m
and
j
2atT
2
to3hours
2a
.
m
3
a
.
m
a
n
d
……….
.
j
23
a
t
T
23
to24hours
11p.
m
12p
.
m
and
P
d
Xk
,
k
0
atT
0
t
o1hours
12p
.
m
1
a
.
m
and
k
1atT
1
to2hours
1a
.
m
2
a
.
m
and
k
2atT
2
to3hours
2a
.
m
3
a
.
m
a
n
d
…………
.
.
k
23a
t
T
2
3
t
o24hours
11p
.
m
12p.
m
Pb
Xk
,
m
0
atT
0
t
o1hours
12p
.
m
1
a
.
m
and
m
1
a
t
T
1
to
2
h
o
u
rs
1a
.
m
2
a
.
m
and
m
2
a
t
T
2
to
3
h
o
u
rs
2a
.
m
3
a
.
m
a
n
d
…
…………
m
23a
t
T
2
3
t
o24hours
11p
.
m
12p.
m
Pl
Xk
,
n
0
at
T
0
t
o1hours
12p.
m
1
a
.
m
and
n
1atT
1
t
o
2hours
1a
.
m
2
a
.
m
and
n
2atT
2
t
o
3hours
2a
.
m
3
a
.
m
a
n
d………………
n
10
a
tT
21
to24hours
11p.
m
12p
.
m
3. Grid Integration
Grid Integ
r
ati
on, Re
ne
wa
ble-En
ergy S
our
ce
s ne
w
strategi
es li
ke PV and
Wind are
desi
gne
d to
operate
with
and inte
rcon
necte
d with
the ele
c
tri
c
ut
ility grid. Bel
o
w a
r
e th
e bl
ock
diagram
s of Grid Integ
r
ati
on syste
m
.
3.1. Photov
o
l
taic Sy
stem
Photovoltaic
module
con
s
i
s
ts of sol
a
r cells wh
i
c
h
co
nvert light direct
ly to electricity. PV
system
can b
e
cla
ssifie
d
into two types. T
hey are PV conn
ecte
d with Gri
d
and
PV conne
cte
d
without
Grid.
Figure 2. PV
con
n
e
c
ted wit
h
Grid
Figure 3. PV
con
n
e
c
ted
wit
hout
Grid
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548
3-2
Wind Tur
bine Gener
a
tion Sy
stem (WTGS
)
Wind T
u
rbin
e Gen
e
ratio
n
System (WTGS) i
s
use
d
to co
nvert
kineti
c
ene
rgy into
electri
c
al e
n
e
r
gy. As wind
ca
se varie
s
, the el
e
c
trical energy pro
d
u
c
ed fro
m
the gene
rato
r ne
eds
to be
co
nvert
ed fo
r
conve
n
ien
c
e. An
in
verter,
re
ctifier, tra
n
sfo
r
m
e
r
and
filter a
r
e
need
ed
wi
thin
the Wind
Turbine
Generation System
(WT
GS),
in order for ut
ility-gr
ade AC power to be
transmitted o
v
er long
dista
n
ce
s (Figu
r
e
4). A tran
sf
ormer i
s
u
s
uall
y
installed at
the und
erm
o
st of
the tower to
provide
volta
ge dive
rsi
on f
r
om th
e lo
w v
o
ltage by th
e
wind
turbi
ne,
to mediu
m
/hi
g
h
voltage for tra
n
sit.
Figure 4. PMSM Wind Ene
r
gy Conve
r
si
on System
Most mod
e
rn
Wind Tu
rbi
ne Gen
e
ratio
n
System (WTGS
)
have
intelligent fe
ature to
observe an
d control the system to diverse win
d
co
ndit
i
on
s.
Like
,
at
mosph
e
ri
c se
ns
or
s de
t
e
ct
wind
spe
ed a
nd directio
n. Other
sen
s
o
r
s ob
se
rve th
e
status a
nd
strength
of the turbine
part
s
to
bypass
run
-
to
-failure. Wi
nd
turbin
es ne
e
d
to
re
si
st extreme
weathe
r conditi
o
n
s, su
ch as
sto
r
ms
and lightni
ng.
In these typ
e
s of conditio
n
s, it is
impo
rtant to en
sure that the turbine mo
nitori
ng
system i
s
de
signed to provide high volta
ge.
4. Simulation Anal
y
s
is a
nd Results
Simulation Result, there
are two pa
rt
in this work, 1
st
by Hom
e
r an
d
2
nd
by Ma
tla
b
simulat
i
o
n
:
4.1. Simulati
on Result b
y
using Homer Soft
w
a
re
Model
s a re
newable
syst
em
,
Model
s a rene
wa
ble
system t
hat
satisfie
s el
ectri
c
ity
deman
d by combinin
g PV, WE and die
s
el and batteri
es with g
r
id o
r
without g
r
id.
By using ho
mer
softwa
r
e, it use to obtain t
he optimal de
si
gn by evalu
a
ting all the p
o
ssible
soluti
ons:
4.1.1. Simula
tion Re
sults
of Dies
el
w
i
t
h
H
y
brid S
y
s
t
em
First, die
s
el
with hybri
d
system
,
in this part, Model
a ren
e
wable
system that
satisfie
s
electri
c
ity de
mand by
co
mbining PV,
WE and
die
s
el. By using
home
r
softwa
r
e, it use to o
b
tain
the optimal d
e
sig
n
by evaluat
ing all the
possibl
e solut
i
ons:
Home
r software of PV, WE and diesel
as in
Figu
re
5, Result of PV and WE and die
s
el
as in
Figu
re 6
.
Figure 5. Ho
mer softwa
r
e
of PV, WE and diesel
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Adv
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Sy
s
t
ems
for t
he Grid In
tegration of ... (S
a
l
a
m
W
.
S
.
)
549
Figure 6. Re
sult of PV, WE and die
s
el
4.1.2. Simula
tion Re
sults
of Dies
el an
d Battery
w
i
th H
y
brid S
y
s
t
em
Secon
d
, die
s
el an
d b
a
ttery with hyb
r
id
system
,
i
n
thi
s
p
a
rt, Mo
del
a
rene
wa
ble
syste
m
that satisfie
s electri
c
ity de
mand by co
m
b
ining PV,
WE and batteri
es with di
esel
. By using homer
softwa
r
e, it use to obtain
the optimal d
e
sig
n
by evaluating all the possible
solution
s. Ho
mer
softwa
r
e of P
V
, WE and b
a
tteries
with
diesel a
s
in
F
i
gure
7 an
d Result of PV, WE and
batte
rie
s
with die
s
el
as in
Figure 8.
Figure 7. Ho
mer softwa
r
e
of PV, WE and batterie
s
wi
th diesel
Figure 8. Re
sult of PV, WE and batterie
s
with diesel
4.1.3. Simula
tion Re
sults
of Grid, Ba
tter
y
and H
y
br
id Sy
stem
Third,
G
r
id, battery
and hybrid syste
m
,
in this pa
rt, Model a
rene
wable
sy
stem that
satisfie
s
ele
c
tricity dem
an
d by
com
b
ini
ng PV,
WE
and
batterie
s
with
gri
d
. B
y
usin
g h
o
m
e
r
softwa
r
e, it use to obtain t
he optimal de
si
gn by evalu
a
ting all the p
o
ssible
soluti
ons.
Figure 9. Ho
mer softwa
r
e
of PV, WE and batterie
s
wi
th grid
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550
Figure 10. Re
sult of PV, WE and batteri
es with g
r
id
4.2. Simulati
on Result b
y
using Matlab soft
w
a
re
By using Ma
tlab, it use to obtain the
opt
imal desi
gn by evalua
ting all the possible
solut
i
o
n
s:
4.2.1. Simula
tion Re
sults
of Wind Ene
r
g
y
It has, Simul
a
tion of
Win
d
Power
re
spon
se a
nd
wind spee
d p
r
ofile used fo
r system
s
i
mulation.
By using the followin
g
valu
es to
kn
ow b
ehavior a
system in one da
y:
Time
= [0
1
2
3 4
5
6
7 8
9
10
11
12
13
14 1
5
1
6
1
7
18 1
9
2
0
2
1
22 2
3
], Win
d
spe
ed
= [9.4
9.3
9.5 10.4 10 1
0
.2 10 9.5 10.
3 11.4 11.6 1
1
.2 10 9.9
9.3
8.8 9.1 9.1 8.4 7.
5 7.4 7.2 7.2 7.2]
a. Wind spee
d profile u
s
ed
for system
s
i
mu
la
tion
b. Simulation of Wind Power re
sp
on
se
Figure 11.
Simulation Res
u
lt
s
of Wind Energy
By analysis simulation re
sults, There a
r
e so
me cases to do it as a followin
g
analysi
s
WTGS By Using PMSM (S
peed, T
o
rq
ue
, Current
) an
d (Tm
(
pu
)
,
Wi
nd Spee
d, Vdc, G
r
id Volt
age
and G
r
ad
Current). Fi
rst
st
ep, to ru
n the
PMSM with
different
spee
ds to g
e
t a
dif
f
erent
fre
que
ncy
to sel
e
ct
the f
r
equ
en
cy o
n
t
he
side
ge
ne
ration
with th
e
rate
d
spe
ed.
The
si
mulati
on
re
sult in
the
table (2
), it wa
s cl
early t
o
get 50
Hz
side of
gen
era
t
ion by usin
g
rotation
spe
ed 10
00 rad/
se
c
whi
c
h
us
in
g
the simul
a
tion system
of this work. Si
mulation Model of PMSM is illustrated in
figure
s
(1
2, 13) which usi
n
g this ste
p
. Seco
nd ste
p
, to use
diffe
re
nt
values
of wind spe
ed with
sele
cted the
simulation
model (wind
spee
d). Thi
r
d step, u
s
in
g these com
pone
nt
sy
st
e
m
s
rectifier
, DC bus
,
Inverter,
filter
,
load
&
grid
with WTG
& PMSM. Fin
a
l s
t
ep,
use
s
different
co
ntrol
sy
st
em
s,
like
cla
ssi
cal
PI
cont
rolle
r.
Expert System
Fuzzy Lo
gic Controlle
r a
nd
optimi
z
ati
o
n
PSO Controller
of
PMSM to
analyze
all result.
Figure 12. Simulation mo
d
e
l of wind spe
e
d
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nc
ed Optimal for Power-Elec
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ronic
Sy
s
t
ems
for t
he Grid In
tegration of ... (S
a
l
a
m
W
.
S
.
)
551
Table 2. PMSM with differe
nt spee
ds to
get different frequ
en
cy
Rated
Speed
(rad
/
sec) Time(sec)
Freque
nc
y
(
Hz)
50 0.42
2.38
100 0.2
5
200 0.1
10
1000
0.02
50
1500
0.01666
60
Figure 13. WTG & PMSM. Simulation model with
win
d
spe
e
d
At Speed=2
0
0
,10Hz ge
neration si
d
e
an
d 50Hz at Gri
d
side:
Figure 14. Simulation resp
onse of spe
e
d
Figure 15. Simulation resp
onse of curre
n
t Iabc
Figure 16. Simulation resp
onse of Grid
vab
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4.2.2. Simula
tion Re
sults
of PV Energy
It has, Simul
a
tion of Solar Powe
r re
sp
o
n
se, Sola
r pa
nel temp p
r
of
iles u
s
ed fo
r
system
simulatio
n
a
n
d
solar ra
diati
on p
r
ofile
s u
s
ed for sy
stem
simul
a
tion. B
y
using
the fo
llowing
value
s
to kno
w
beh
a
v
ior a system
in one day:
Time = [0 1 2
3 4 5 6 7 8 9
10 11 12 1
3
14 15 1
6
17 1
8
19 20 2
1
22
23], Ir = [0 0 0 0 0 0
0 10 120 300
420 690 695
390 200 280
200 150 20
1 0 0 0 0], Te
mp = [1 1.5 2.5 2.5 2.5 2.5 2.5
3 5.5 11 18 2
7
28 22 15 1
7
18 11 5 4 3 2
1 0]
a. Solar pan
e
l
temp profile
s used for
system
s
i
mu
la
tion
b. Solar radi
a
t
ion profile
s u
s
ed for
syste
m
simulat
i
o
n
c. Simulation
of Solar Power re
sp
on
se
Figure 17. Simulation Results of PV Energy
4.2.3. Simula
tion Re
sults
of H
y
brid S
y
stem
Simulation M
odel of
hybri
d
sy
stem a
s
sho
w
in
figu
re 18. T
able
3
simul
a
tion
Result
s of
hybrid sy
ste
m
and Simula
tion Re
sults o
f
hybrid syste
m
.
Figure 18. Simulation mo
d
e
l of hybrid system
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