Techno-Economic Energy Analysis of Wind
Techno-Economic Energy Analysis of Wind
Techno-Economic Energy Analysis of Wind
Renewable Energy
journal homepage: www.elsevier.com/locate/renene
Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Department of Electrical Engineering, Universitas Tanjungpura, Pontianak 78124, Indonesia
c
Renewable Energy Research Group, King Abdulaziz University, Jeddah 21589, Saudi Arabia
b
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 20 April 2015
Received in revised form
27 December 2015
Accepted 24 January 2016
Available online 2 February 2016
The potential of hybrid wind/solar energy system in the west coast area of Saudi Arabia is analyzed in
this paper. The investigation puts emphasis on the energy production and cost of energy from both wind
turbine and photovoltaic (PV) in the hybrid system. Unmet electric load and excess electricity are taken
into consideration. The annual average solar irradiation and wind speed considered in this study are
5.95 kWh/m2/day and 3.53 m/s, respectively. MATLAB and HOMER software are used to perform the
technical and economic analyses of the hybrid system. As indicated from the simulation results, the PV
array shares more electricity production than the wind turbine generator if both wind turbine and PV
array are utilized in the wind/solar hybrid system with the same sizes. The wind levelized cost of energy
is $0.149/kWh, which is more expensive than the solar energy of $0.0637/kWh. The energy cost of the
hybrid system is dominated by battery and wind turbine expenses.
2016 Elsevier Ltd. All rights reserved.
Keywords:
Techno-economic analysis
Hybrid wind/solar system
Excess electricity
Energy cost
1. Introduction
The world is still injecting a considerable amount of investment
in renewable energy resources. This trend has been driven by the
continuous changes in the climate resulting in global warming. In
recent years, many efforts have been made to increase the implementation of renewable sources of energy through researches and
application, not only in the developed countries but also in the
developing countries [1]. The increased exploitation is aimed at
reducing carbon emission from energy generation and improving
the reliability/security of energy supply [2].
Increase in fossil fuel consumption for electric power generation
has forced the kingdom of Saudi Arabia to pay more attention on
renewable energy generation. The kingdom now recognizes that
reducing dependency on fossil fuel for domestic consumption will
give positive impact on national economic growth and environmental issues. Generating some electricity from renewable resources instead of using fossil fuel will increase the revenue for the
kingdom from petroleum. Moreover, it is predicted that CO2
emission from fossil power generation system will increase for
375
u2 u1
ln Z2=Z
0
ln Z1=Z
(1)
where the wind speed at hub height u2 (m/s), the wind speed at
anemometer height u1 (m/s), the hub height z2 (m), the anemometer height z1(m) and the surface roughness z0 (m), and the power
law is dened as
u2 u1
Z2
Z1
a
(2)
376
PPV PPV;STC fPV ftemp
IT
IT;STC
(4)
!
r
Id
Ib
1 cos b
Ib 3 b
1
sin
I R Id 1
IT 1
2
2
Io b b
Io
I
1 cos b
I
rg
2
(5)
Fig. 2. Wind rose of Yanbu.
PW
r
P
r0 W;STP
(3)
where I is the global horizontal radiation (kW/m2), Io is the extraterrestrial horizontal radiation (kW/m2), Ib is the direct beam radiation on a horizontal surface (kW/m2), Id is the diffuse radiation
on a horizontal surface (kW/m2), rg is the ground reectance or
albedo (%), b is the tilt angle of the surface (degree), and Rb is the
ratio of beam radiation on the tilted surface to beam radiation on
the horizontal surface (dimensionless) as follows:
Rb
cos q
cos qz
(6)
377
16
12
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
(7)
(8)
284 n
d 23:45 sin 360
365
(9)
ftemp
T
Ta;NOCT
T
1 ap Ta IT c;NOCT
c;STC
IT;NOCT
hmp;STC
T
Ta;NOCT
1 ap IT c;NOCT
IT;NOCT
0:9
(10)
CNPC;tot
Cann;tot
CRF i; Rproj
(11)
where Cann,tot is the total annualized cost ($/yr), i is the annual real
interest rate (%), Rproj is the project lifetime (yr), and CRF() is a
function returning the capital recovery factor.
The capital recovery factor (CRF) is a ratio given by
CRFi; N
i1 iN
1 iN 1
(12)
i0 f
1f
(13)
where i is the annual real interest rate, i' is the annual nominal
interest rate, and f is the annual ination rate.
The levelized cost of energy (COE) is the average cost per kWh of
useful electrical energy produced by the system. The COE is
calculated by dividing the annualized cost of producing electricity
378
1.2
1.0
0.8
0.6
0.4
0.2
0.0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Sep
Oct
Nov
Dec
45
40
Temperature (C)
35
30
25
20
15
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
COE
Cann;tot
Eserved
Table 1
Azimuth angles.
(14)
Facing
Azimuth angle ( )
S
SW
W
NW
N
NE
E
SE
0 or 360
45
90
135
180
225 or 135
270 or 90
315 or 45
379
Table 3
PV Data.
Quantity
PV array
Wind turbine
PV array
Rated capacity
Mean output
Capacity factor
Total production
1 kW
0.23 kW
22.60%
1982 kWh/yr
1 kW
0.16 kW
16.10%
1412 kWh/yr
Lifetime
Cost of investment
Cost of replacement
Cost of O&M
30 yr
$ 2000/kW
$ 1200/kW
$ 30/kW/yr
Table 4
Wind turbine data.
Wind turbine
Lifetime
Cost of investment
Cost of replacement
Cost of O&M
20 yr
$ 3000/kW
$ 1500/kW
$ 40/kW/yr
380
1.4
Table 5
Inverter data.
1.2
Inverter
30 yr
$ 400/kW
$ 375/kW
$ 20/kW/yr
Power (kW)
Lifetime
Cost of investment
Cost of replacement
Cost of O&M
1.0
0.8
0.6
0.4
0.2
Table 6
Battery data.
0.0
Battery
Lifetime
Cost of investment
Cost of replacement
Cost of O&M
12 yr
$ 1200/unit
$ 1200/unit
$ 60/unit/yr
8
Wind Speed (m/s)
12
16
Table 7
Levelized cost.
Levelized cost
PV
$0.0637/kWh
Wind
$0.149/kWh
20
Frequency (%)
15
10
0
0
10
12
14
381
0.6
PV
Wind
Power (kW)
0.5
0.4
0.3
0.2
0.1
0.0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Load (kW)
150
max
daily high
mean
daily low
min
100
50
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Ann
120
PV
Wind
Power (kW)
90
60
30
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
382
Power (kW)
200
battery charge power
battery discharge power
100
10
15
20
10
15
20
10
15
Septem ber 22
20
60
battery SOC
50
40
400
renewable output
Power (kW)
demands
unmet load
excess electricity
200
that the battery does not produce electricity by itself, but it is used
for optimizing the energy in and out for the hybrid system according to its capacity level. Increasing the battery size contributes
to the higher NPC and hence, to the COE of the hybrid system.
However, the battery is still useful to minimize the unmet load [37].
4.4. Increasing PV and/or wind turbine sizes
The sizes of PV and wind turbine are related to the electric power production. The more the PV or wind turbine sizes are
increased, the more electric power will be generated and hence,
unmet load can be reduced to a minimum percentage. As shown in
Table 8, increasing PV or wind turbine sizes makes the wind/solar
hybrid system producing more electricity in order to minimize
unserved loads, but it raises the unused electricity due to excess
production.
The bigger size of PV or wind turbine also gives additional expenses to the hybrid system and therefore it increases total NPC of
the system. However, the COE of hybrid system depends on the cost
383
16
14
12
10
8
6
4
2
1000
2000
3000
4000
5000
6000
(a)
5.8
Excess Electricity(%)
5.6
5.4
5.2
5
18
4.8
4.6
4.4
4.2
200
400
600
800
1000
1200
32
30
28
26
24
22
20
20
100
15
(b)
50
10
Fig. 15. Increasing battery size related to: (a) unmet electric load, (b) excess electricity.
Excess Electricity(%)
PV Size (%)
Table 8
Hybrid system Congurations.
Conguration (PV, wind turbine)
Unmet load
Excess electricity
COE ($/kWh)
200-kW,
400-kW,
200-kW,
400-kW,
675,982
1,075,003
961,141
1,357,429
675,982
675,982
675,982
675,982
536,412
661,088
627,198
673,395
20.6%
2.2%
7.2%
0.4%
5.6%
24.7%
21.4%
40%
0.329
0.313
0.357
0.370
200-kW
200-kW
400-kW
400-kW
384
4.4
4.2
5. Conclusion
4
3.8
3.6
3.4
3.2
3
20
40
60
80
100
PV Size (%)
Fig. 17. PV size combination vs total NPC.
0.46
Acknowledgment
0.44
COE ($/kWh)
0.42
0.4
References
0.38
0.36
0.34
0.32
0.3
20
40
60
80
100
PV Size (%)
Fig. 18. PV size combination vs total COE.
25
20
15
10
5
0
25
20
160
15
140
10
Excess Electricity(%)
120
5
100
385
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