UNIVERSITY OF SISTAN AND BALUCHESTAN A Novel Techno-Economical Optimization Approach Based on Linear Integer Programing (LIP) for Hybrid Renewable systems Saeed Reza Nazari Estahbanati Department of Mechanical Engineering, University of Sistan and Baluchestan. S. Masoud Barakati Department of Power Electronic Engineering, University of Sistan and Baluchestan. Mehri Mehrjoo Department of Telecommunication, University of Sistan and Baluchestan. Mohammad Ali Yazdanpanah Jahromi Department of Mechanical Engineering, University of Guilan.
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UNIVERSITY OF SISTAN AND BALUCHESTAN A Novel Techno-Economical Optimization Approach Based on Linear Integer Programing (LIP) for Hybrid Renewable systems.
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UNIVERSITY OFSISTAN AND BALUCHESTAN
A Novel Techno-Economical Optimization Approach Based on Linear
Integer Programing (LIP) for Hybrid Renewable systems
Saeed Reza Nazari Estahbanati Department of Mechanical Engineering, University of Sistan and Baluchestan.
S. Masoud Barakati Department of Power Electronic Engineering, University of Sistan and Baluchestan.
Mehri Mehrjoo Department of Telecommunication, University of Sistan and Baluchestan.
Mohammad Ali Yazdanpanah Jahromi Department of Mechanical Engineering, University of Guilan.
Wind Turbine Power
( / )ref refH H • Adjusting the measured wind speed
1/7 for open land
• The weibull distribution function ( ( ) )( 1)( ) ( ).( ) .kv
k ck vf v e
c c
0 5 10 15 20-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
Wind Speed(m/s)
pdf
4
. . ( , , )out days hours cE n n P f k c v
• Output energy of wind turbine• Power curve of small wind turbine “Lakota S, SC”
0 5 10 15 20 250
0.2
0.4
0.6
0.8
1
1.2
1.4
Wind speed (m/s)
Powe
r out
put (
kW)
5
maxmax max min
max min
. . .( ) . .( ).exp( .ln( ))oci ix cv N
iN iN
V VE EV S T T T S V S V V
E E V V
. . .( )ix sc ci N
iN
EI p I T T T
E
0 1000 2000 3000 4000 5000 6000 7000 8000 90000
200
400
600
800
1000
1200
Time(h)
Sola
ra R
adia
tion(
Wh/
m2 )
0 1000 2000 3000 4000 5000 6000 7000 8000 9000-10
-5
0
5
10
15
20
25
30
35
40
Time(h)
Tem
prat
ure(
C)
PV Array Power
6
0 200 400 600 800 1000 12000
1
2
3
4
5
6
voltage (v)
Cur
rent
(A)
0 200 400 600 800 1000 12000
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
voltage (v)
pow
er (W
)
. 1( ) .[1 exp( )]
1 .1 exp( )
x
x
V I VP V
bV bb
• b, usually changes from 0.01 to 0.18.
( ).( ).( )PV out xE P E solarwindow TotalDay
1( ) .[1 exp( )]
1 .1 exp( )
X
x
I VI V
bV bb
7
Operation of Battery• Capacity of the BT depends on temperature
' '' .(1 .( 298.15))bat bat c batC C T • δC suggested 0.6 % per degree
The best configurations among the results are shown in below table. The lowest Unit cost of electricity energy (UCEE) achieved in related on the candidate number 5 but the lowest LPSP is given by choice 3.
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The relation between LPSP and UCEE is shown in below figure. With increasing the LPSP the value of the UCEE is decreased and vice versa by decreasing the value of the LPSP the UCEE is increasing. The Branch and cut method is a suitable method to reach the best size. It is needed lower time in comparison of the evolutionary methods to reach the results and it guarantees that the obtain results is really the optimal solution.