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

( ) ( ) ( ( ) / )( )

( )PV WT ACLoad inverter DCLoad

batbat

P t P t P t PI t

V t

• The BT current rate

• ηinverter = 92%

'

( ). ..( 1) ( ).(1 )

24bat bat

bat

I t ttSOC t SOC t

C

SOCmax=1, SOCmin=1-DOD. and DOD is 60%.

• The Battery SOC

8

Optimization Problem

ObjectiveFunction minn(npv×UCEEPV+nWT×UCEEWT+nBAT×UCEEBAT)

Constrains

0<LPSP<0.03

SOCmin<SOC<SOCmax

npv ,nWT ,nBAT>0

(npv ,nWT ,nBAT)ϵƵ

Decision Variables Number of PV (nPV),WT(nWT),BAT(nBT)

9

Economic Analysis

minacap arep aACS C C C

ACSUCEE

ATED ATED stands the annual total energy demand in (kWh).

. ( , )acap cap projC C CRF i Y

(1 )( , )

(1 ) 1

n

n

i iCRF i n

i

1loani f

if

• Unit Cost of Electricity Energy

0 1000 2000 3000 4000 5000 6000 7000 8000 90000.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Time(h)

Lo

ad

(kW

) . ( , )arep rep repC C SFF i Y ( , )(1 ) 1reprep Y

iSFF i Y

i

( ) .(1).(1 )namain amaninC n C f

10

Reliability Analysis

0

( ( ) ( ))T

available neededt

Time P t P tLPSP

T

• Loss of Power Supply Probability

12

RESUALTS•The proposed methodology has been used to achieve the proper size of off-grid

power system, to supply the load demand of a remote area by using of branch and cut

based on linear integer programing (LIP). The typical meteorological of one year hourly

data collected for solar radiation, temperature and wind speed. The location of

Marvdasht, Fars, Iran (Latitude: 29°50'N, Longitude: 52°40'E) is chosen for case study.

Results displayed as an optimal Pareto front. Each solution of the best Pareto front was

achieved by a combination of hybrid systems in some manner to reach higher reliability.

13

optimal solutions of components

NoPV

numberWT number BT number

UCEE ($/kW)

LPSP%

1 2 2 1 257.6142 1.242 1 1 4 191.1375 2.403 2 1 2 211.8478 0.004 2 2 2 196.7711 2.855 3 2 1 187.5020 0.53

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.

16

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.

0 0.5 1 1.5 2 2.5 3180

190

200

210

220

230

240

250

260

LPSP%

UC

EE

($/k

W)

17

I really appreciate for your concern

The End