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1
Sizing optimization tool for Wind/Photovoltaic/Battery
plant considering potentials assessment and load profile
Dr. Nabiha BRAHMI, Prof. Maher CHAABENEUniversity of Sfax, Tunisia
Introduction
System configuration and modeling
Sizing algorithm
Simulation results
Conclusions
1
2
3
4
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
5
Plan
2
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
3
Our goal is to optimize the sizing of a standalone hybrid system.
•Fuel prices have raised.
•Fuel will break off in the following few decades.•Plants become decentralized.
Covering the energy demand of typical consumers in remote
area on the basis of maximizing the renewable energies
exploitation
Introduction
Introduction
System configuration and modeling
Sizing algorithm
Simulation results
Conclusions
1
2
3
4
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
5
4
Plan
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
System configuration
PMSG
Electrical load
Block diagram of a hybrid PV/Wind generators and storage system
Renewablegenerators
Battery bank
DC bus AC bus
Tank
Loads
5
mP
eP
PMSG
m
t
mP e
P
Where is the nominal power of the PMSG and presents the mechanical
power of the turbine. It is expressed by the following equation:
The output power of the generator is
determined as follows:
0.0140.87e m n
P P P
2 2
2
p
m
m
. .R .C .vP
m gear tG
18,4( )
2,14( , ) 0,73 13.2 ipC e
Where
nP
6
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
Wind generator model
mP
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
PV cells are combined in serie and parallel to form PV array.
ns : number of cells in series. np : number of module in parallel.
( )exp 1
pv pv s pv pv spv p ph p rs
s sh
q V I R V I RI n I n I
kTAn R
7
The equivalent circuit of PV cell is:
PV model
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
8
Introduction
System configuration and modeling
Sizing algorithm
Simulation results
Conclusions
1
2
3
4
5
Plan
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
Sizing
approach
Estimation of
renewable potentials
Load demand
profile WECS
PV Array
Battery
Models baseApproach description
9
Optimal sizing of plant
components
Sizing Appraoch
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
10
( KWh / month / m²)
30
1000h
solar _ monthly
( G )E
hG
The monthly average of solar energy is given by:
Where is the global solar radiation provided by the National
Meteorological Institute (INM).
Solar potential
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
11
( KWh / month / m²)The monthly wind energy is expressed by:24 30
1000wind
wind _ monthly
( P )E
2 31 3
(1 3 ) (1 )2
wind airP I c
k
Where is the turbulence intensity, and are the two parameters
of the Weibull distrubution which is given by:
I k c
1
( )
( )k
kv
ck v
f v ec c
The corresponding cumulative distribution function is given by:
( )
( )kv
cF v e
Wind potential
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
12
Parameters estimation of Weibull :
Least squares method
Maximum likelihood method
Modified maximum likelihood method
Rayleigh distribution
(NRMSE) Normalized Root Mean Square error
k
c
Wind potential
Classified speed:
Meteorological
database
Selection
Approach
Algorithm initialization
1. Solar potential estimation
2. Wind potential estimation
3. Load profile
)
max( )1Sini_ 2 ( )
max( )1Sini_ 2 (
i
wind i
Ploadi
PPV mean PPV
Ploadi
Pwind mean P
0Difference
_ ini_
_ ini_
S =S 0.5
S 0.2
new PPV PPV
new Pwind PwindS
_ ini_
_ ini_
S =S 0.5
S 0.2
new PPV PPV
new Pwind PwindS
Calculation of the battery
capacity and of the tank
volume
End
_ ini_
_ ini_
S =S 0.5
S 0.2
new PPV PPV
new Pwind PwindS
13
( )Loss mean Need
tank maxV V
No
NoYes
Yes
Yes
No
14
d
bat max
Daut.EC
V DOD
60maxDOD DOD % Guarantee to protect the battery against excessive discharge
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
Battery Sizing
E
1r
2r
CbV
bI
E
15
3 6 excesstank
water
. EV
gH
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
Tank volume sizing
Introduction
System configuration and modeling
Sizing algorithm
Simulation results
Conclusions
1
2
3
4
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
5
16
Plan
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
0 50 100 150 200 250 300 3500
1
2
3
4
5
6
7
8
9
10
Days
V(m/s)
Measured wind speed at height of
1 2 3 4 5 6 7 8 9 10 11 120
2
4
6
8
10
Month
Receiv
ed irr
adia
tion [
KW
h/m
²]
Daily monthly solar irradiation
17
12m
18
1 2 3 4 5 6 7 8 9 10 11 120
20
40
60
80
100
Month
Month
ly e
nerg
ies[K
Wh/m
²]
PPV
Wind
Renewable potentials in Sfax
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
19
Daily farm energetic consumption
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
0 5 10 15 2010
20
30
40
50
60
70
80
90
100
Hours
Pow
er(
Kw
h)
agriculture dairy farming rest of farmer
1 2 3 4 5 6 7 8 9 10 11 120
1000
2000
3000
4000
5000
6000
7000
8000
Month
Mon
thly
ene
rgie
s[K
Wh/
m²]
PPV Wind renewable Needs
Monthly generated and consumed energies
Following the achievement of iterations, the obtained rounded surfaces for PV
panels and wind blades are: 92
46
final_ppv
final_wind
S m²
S m²
20
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
1 2 3 4 5 6 7 8 9 10 11 12-2
-1.5
-1
-0.5
0
0.5
1
1.5x 10
6
Month
Mon
thly
ene
rgy[
KWh/
mon
th]
Difference between monthly renewable generations and load demand
21
12
1
( ( ) ( ))
0.005%12
Monthly
ienergy
Energy i Needs i
Balance
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
By computing the luck of energy during all the year, the plant needs a battery
bank of a capacity equal to . The obtained tank volume is . 1200Ah3700
tankV m
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
22
Introduction
System configuration and modeling
Sizing algorithm
Simulation results
Conclusions
1
2
3
4
5
Plan
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
23
Optimal plant components sizes are computed thanks to an iterative approach based on the meeting of renewable generations to load profile supplying an autonomous agriculture farm
The sizing is based on the renewable potential, the generators models and the load profile.
A case study is considered in order to validate the obtained results.
Conclusions
24
IntroductionSystem Configuration and modeling
Sizing Algorithm Simulation results
Conclusions
Conclusions
Wind data, solar data and load data of an agriculture farm have been collected and studied.
Economical and feasible components of the hybrid power system have been selected so
that minimized system cost can be achieved.
Modeling of individual component has been done by using Matlab /Simulink.
Individual models have been combined to form the complete system.
Thank you
25