UTILIZING ANNUAL WIND SPEED DATA AS A REPRESENTATIVE OF LOCATIONS AND SIZING OUTSTANDING WIND TURBINE OF OPTIMUM POWER DUTY TO RUN A CERTAIN
LOAD AROUND THE GLOBE
M.A. Alghoul a,b,c*, A.A. Aljaafar d, S.W. Lim d, W.J. Hee d , K. Sopian a
a Solar Energy Research Institute, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysiab Energy and Building Research Center, Kuwait Institute for Scientific Research, Safat 13109, Kuwait
c Center of Research Excellence in Renewable Energy (CoRe-RE), Research Institute, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia
d The School of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia
*Corresponding author e-mail: [email protected]
ABSTRACT: Electricity generated by wind is fast becoming one of the most affordable and cheapest
forms of energy. Literature on sizing wind power systems are limited to specific wind speed data and load
profile for designated locations. Also, case studies employed different brands and power capacities of
wind turbines and batteries. Due to these huge discrepancies, it is very hard to generalize the outcomes for
other locations. Generalizing the outcome to the world instead of a specific location is a more practical
measure for industries, customers, and researchers. In this study, there is no pre-selection of locations;
instead, a range of annual wind speeds (3-12 m/s) were used as inputs to be representative of so many
locations around the globe. The aim of this study is to size an outstanding wind turbine power for a
certain load profile using only annual wind speed data instead of the regular approach of using monthly
wind speed data for specific locations. The load profile was selected for many small-scale applications
(8kW) with an operating load of 10 hrs. Seven types of wind turbines with different power sizes were
implemented: [SW Whisper 500 (3kW), BWC Excel-R (7.5kW), BWC Excel-S (10kW), PGE 20-25
(25kW), Fuhrlander FL30/13 (30kW), PGE 11-35 (35kW), and the Entegrity EW15 (50kW)] under their
respective minimum hub heights. The outstanding wind turbine power is determined based on the
optimum values of the techno-economic feasibility parameters using HOMER simulation tool. The results
showed that the outstanding wind turbine that could power an 8 kW load around the globe using annual
wind speed range of 3-12m/s was PGE 20-25 (25kW). Also, the results showed that the different hub
heights of the outstanding wind turbine lead to slight influence on the techno-economic parameters values
at low wind speeds (3-4) m/s and insignificant influence at higher wind speeds (5-12) m/s. This reflects
that the power duty of the outstanding wind turbine is at each annual wind speed value. Validation test is
performed for (3) locations using their monthly wind speed data. The validation results confirmed that the
optimum wind turbine power to run (8 kW) load at the three tested locations is still PGE 20-25 (25kW).
Finally it can be concluded that the proposed sizing approach utilizing annual wind speed data (3-12m/s)
a representative of locations is accurate to predict the outstanding wind turbine of optimum power duty to
run 8kW load around the globe.
Keywords: certain load profile, annual wind speed data (3-12m/s) as representative of locations, different wind turbines size, HOMER simulation tool, evaluation parameters of techno-economic feasibility, outstanding wind turbine of optimum power duty, validation test
Contents outlines1. INTRODUCTION2. MATERIALS AND METHOD
2.1 Research Design 2.2 Materials2.3 HOMER Simulation Tool
3. RESULTS AND DISCUSSION 3.1 determining the outstanding wind turbine power 3.1.1 Effect of wind speed and wind turbine sizes on number of turbines 3.1.2 Effect of wind speed and wind turbine sizes on number of batteries 3.1.3 Effect of wind speed and wind turbine sizes on battery lifetime 3.1.4 Effect of wind speed and wind turbine sizes on initial cost 3.1.5 Effect of wind speed and wind turbine sizes on O&M cost, total NPC and COE 3.1.6 The Outstanding wind turbine size powering under a certain load around the Globe
3.2 Effect of Different Hub Heights of the Outstanding Wind Turbine (PGE 20-25) on optimizing the Parameters of Techno-economic feasibility 3.2.1 Effect of hub height on number of turbines 3.2.2 Effect of hub height on number of batteries 3.2.3 Effect of hub height on battery lifetime 3.2.4 Effect of hub height on initial cost 3.2.5 Effect of hub height on O&M cost, total NPC and COE 3.3 Validation of the Outstanding Wind Turbine at Dammam City, Saudi Arabia 3.3.1 Effect of different wind turbine sizes on number of turbines 3.3.2 Effect of different wind turbine sizes on number of batteries 3.3.3 Effect of different wind turbine sizes on battery lifetime 3.3.4 Effect of different wind turbine sizes on cost of energy3.3.5 Determining Wind Turbine Size at other Different Tested Locations Using their Monthly Wind Speed Data4. CONCLUSION
1. INTRODUCTIONWind is a renewable source of energy that is freely available, clean, and economical inexpensive (no fuel
costs and no price risk). Due to the promising prospect of renewable energy, many researches have been
carried out by researchers and companies to evaluate the feasibility of harnessing renewable energy at
their respective locations. Some of them have adopted HOMER software (Hybrid Optimization Model for
Electric Renewables) as their simulation tool in assisting them in their respective researches. HOMER
was developed at National Renewable Energy Laboratory (NREL) and can be considered as global
standard for preliminary techno-economic analysis of sustainable micro-grid systems such as remote
power, island utilities and micro-grids [1].
Table 1(A, B) shown below summarizes the R&D aspects covered by previous researchers studies on
components sizing and techno-economic feasibility of wind power systems done by HOMER simulation
tool.
Table 1-A: Summary of previous studies on components sizing and techno-economic feasibility of wind power systems done by HOMER simulation tool
References Location Wind Speed Wind power system type
Load profile
(kWh/day)
Application
Ashourian et al. 2013[1]
Tioman Island,
Malaysia
Annual(3.18 m/s)
Standalone: Hybrid PV-
Wind-Diesel-Battery-Fuel
Cell
496 30 chalets
Sadeghi et al. (2012)[2]
Baladeh city, North of Iran
Monthly (3.0 – 4.0
m/s)
Grid-connected
NA Residential buildings
Aagreh & Al-Ghzawi
(2013) [3]
Ajloun city,Jordan
Annual4.57 m/s @10 m height
6.76 m/s@ 60 m height
Grid-connected:
Hybrid Wind-PV-Battery
97 Small hotel
Goodbody et al. (2012)[4]
Ireland NA Grid-connected:
Hybrid Wind-PV-Diesel-
Hydro-Biomass-Battery
12-25 Apartment, households and retail unit
Adaramola (2012)[5]
Ondo State, Nigeria
Annual(3.26 m/s)
Standalone: Hybrid Wind-
PV-Diesel-Battery
25 Households
Osorio et al. (2012)[6]
Madrid (Cuatro
Vientos), Burgos, Alto do Rodicio and Punta
Candelaria, Spain
Annual Madrid (CuatroVientos)
(3.92 m/s)Burgos –(5.08 m/s)
Alto do
Grid-connected:
Hybrid Wind-Diesel-Battery
Oct-March (63)Apr-
Sept(62)
Dairy cattle farms
Rodicio – (6.18 m/s)
PuntaCandelaria – (7.38 m/s)
Fahmy et al. (2012)[7]
Hurghada, Egypt
Annual (6.93 m/s)
Standalone: Hybrid Wind-PV-Battery-
Fuel Cell
60 Small Scale Brackish Reverse Osmosis
Desalination Unit and a Tourism Motel
Moniruzzaman & Hasan (2012)[8]
Bandarban, Bangladesh
Annual (4.12 m/s)
Grid-connected:
Hybrid Wind-PV-Diesel-
Battery
35 Household/small restaurant
Sadrul Islam et al. (2012)
[9]
St. Martin Island,
Bangladesh
Annual(4.71 m/s)
Standalone: Hybrid Wind-
PV-Diesel-Battery
78 Households and shops
Badawe et al. (2012) [10]
Mulligan, Labrador, Canada.
Annual(6.26 m/s)
Standalone: Hybrid Wind-
PV-Diesel-Battery
79 Microwave repeaters (telecommunication)
Abulqasem et al. (2011)[11]
Mrair-Gabis Village, Libya
Annual(3.7-4.4 m/s)
Standalone: Hybrid Wind-
PV-Diesel-Battery
86 Small Scale Seawater Reverse OsmosisDesalination Unit
Chowdhury & Oo (2012)
[12]
Australia Annual(2.13–6.11
m/s)
Grid-connected:PV-Wind-
Battery system
1000 Electricity generation
Ibrahim et al. (2010)[13]
Kuala Terengganu,
Malaysia
Monthly (3.16 m/s)
Standalone:PV-Wind-
Diesel-Battery-Fuel Cell system
20 Residential building
Thakur et al. (2012)[14]
Jabalpur Engineering
College, Jabalpur,
India
Monthly(4.0 m/s)
Standalone:PV-Wind-
Diesel-battery system
2000 College
Fantidis et al. (2012)[15]
Plaka, Greece Annual(6.44 m/s)
Standalone:Hybrid PV-
wind, Wind-diesel
15.15-15.4 60 household electricity
Nandi & Ghosh (2010)
[16]
Chittagong, Bangladesh
Monthly(3.0- 5.0m/s)
Standalone:PV-Wind-
Battery system
160 Households
Niazi et al. (2014)[17]
Nok kundi &Ormara, Pakistan
Monthly (4.1- 5.5) &
(2.2- 5.1)
Grid-connected:
Hybrid Wind-
13.1 small houses
m/s PV-DieselShaahid
(2007)[18]Dhahran
(East-Coast, KSA)
Monthly (3.3- 5.6m/s)
Grid-connected:
Hybrid Wind-Diesel-Battery
351 100 of typical residential buildings
Amini (2010) [19]
Ghardaia and Djanet, Algeria
NA PV systems, Wind
generators and Batteries
NA Rural Health Clinics
Amin et al. (2014)[20]
St. Martin Island,
Bangladesh
Monthly (3.6- 6.5m/s)
Standalone: Hybrid Wind-
PV-Diesel-Battery
1421 650 households.
Soe & Zheng (2014) [21]
Wetkaik village,
Myanmar
Annual(3.7 m/s)
Grid-connected:
Hybrid Wind-Diesel-Battery
1167 850 households
Diab et al. 2015[22]
(Alexandria, Qena and Aswan), Egypt
Monthly(4.8- 6.2m/s)(4.3- 5.6m/s)(4.3- 5.5m/s)
Standalone: hybrid
PV/wind/diesel /battery
19,906 tourist village
Table 1-B: Continued summary of previous studies on components sizing and techno-economic feasibility of wind power systems done by HOMER simulation toolReferences Turbines spec. & no.
of turbinesBattery spec. & no of batteries
Costs aspects
Ashourian et al. 2013
- BWC XL-1- 1kW at 20 m height- 40 turbines
- Surrette 6CS25P- 540 batteries
- Initial - $ 1, 971, 000- COE - $ 1.104/kWh
Sadeghi et al. (2012)
- Enercon E33- 340kW at 50 m height- 3 turbines
NA - Initial - $ 294,000- COE - $ 1.28/kWh
Aagreh & Al-Ghzawi (2013)
- Novergy- 12kW at 25, 40, 60
m height- Grid-connected: 1
turbine- Stand-alone: 2 - 3
turbines
- Surrette 4KS25P- Stand-alone: 24 –
55 batteries
- Grid-connected:Initial - $ 24, 000 – 104,000NPC - $ 44, 300 – 162, 600
- Stand-alone:Initial - $ 84, 400 – 117, 200NPC - $ 119, 700 – 291, 500
Goodbody et al. (2012)
NA NA - Wind and Grid system: COE - € 0.045 – 0.16/kWh- Wind/Diesel system:
COE - € 0.178 - 0.37/kWhAdaramola (2012) - BWC Excel-R/48
- 7.5kW at 43m height- 1 turbine
- Surrette 6CS25P- 0 – 36 batteries
Initial - $ 29, 185 – 44, 915COE - $ 0.578 – 0.682/kWh
Osorio et al. (2012)
- Westwind- 20kW at 18m height
- Hoppecke 4 OPzS 200
- COE - € 0.472 – 0.731/kWh
- 1 turbine - 60 batteriesFahmy et al.
(2012)- Generic 3 kW- PV-Wind-Battery
system: 2 turbines- Wind-Battery
system: 4 turbines- PV-Wind-Fuel Cell
system: 40 turbines
- Trojan L16P- PV-Wind-Battery
system: 10 batteries
- Wind-Battery system: 20 batteries
- PV-Wind-Battery:Initial - $ 40, 750COE - $ 0.321/kWh
- Wind-Battery:Initial - $ 36, 500COE - $ 0.356/kWh
- PV-Wind-Fuel Cell:Initial - $ 799, 800COE - $ 4.305/kWh
Moniruzzaman & Hasan (2012)
- African 3.6 model- 1 kW at 10 m- 1 turbine
- 6FM200D- 16 batteries
- PV-Wind-Diesel:Initial - $ 15, 000COE - $ 0.454/kWh
- Wind-Diesel system:Initial - $ 15, 000COE - $ 0.507/kWh
Sadrul Islam et al. (2012)
- Generic 3 kW- 2 turbines
- Hoppecke 8 OPzS- 25 batteries
- NPC - $ 136, 427COE - $ 0.34/kWh
Badawe et al. (2012)
- BWC Excel-R/48- 7.5kW at 30m height
- VRLA GNB XL3000
- 24 batteries
- Initial - $ 968, 420- COE - $ 3.39/kWh
Abulqasem et al. (2011)
- BWC Excel-R- 7.5kW at 20m height- 1 turbine
- Trojan L16P- 0-70 batteries
- Initial - $ 123, 950- COE - $ 0.369/kWh
Chowdhury & Oo (2012)
- Fuhrlander FL100- 100 kW- 1 turbine
- S4KS25P- 25 batteries
- Initial - $ 361, 250- COE - $ 0.183/kWh
Ibrahim et al. (2010)
- BWC Excel-R- 7.5 kW- 0 – 32 turbines
- Surrette 6CS25P- 0 – 125 batteries
- Grid-PV-Wind-FC:NPC: $ 53, 197COE: $ 0.57/kWh
Thakur et al. (2012)
- Northern Power NW100/19
- 100 kW- 5 turbines
- Surrette 6CS25P- 0 – 50 batteries
- PV-Wind-Diesel-battery:NPC - $ 1, 458, 954
COE – 0.227/kWh
Fantidis et al. (2012)
- Fuhrlander 30- 30 kW at 26 m
- Trojan T-105 - Wind/diesel/battery: COE - $ 0.242/ kWh- Wind/PV/battery:
COE - $ 0.252/kWh.Nandi & Ghosh
(2010)- WES 5 Tulipo- 3 kW- 14 – 52 turbines
- USB US-250- 285 – 300 batteries
- PV-Wind-Battery:Initial - $ 231, 255COE - $ 0.47/kWh
- Wind-Battery system:Initial - $ 337, 100COE - $ 0.63/kWh
Niazi et al. (2014) - Bergey Excel BWXL- 1kW at 25m height- 2 turbine
NA Nok kundi:- NPC of $15,872- COE $0.087/kWhOrmara:- NPC of $14,508- COE $0.078/kWh
Shaahid (2007) NA NA - COE -$0.070/kWh
Amini (2010) NA - 10 batteries - Initial $14,600- NPC of $17,323
Amin et al. (2014) - Fuhrlander AG(FL30)- 1.5kW at 19m height- 3 turbines
Beacon Smart Energy 25
- 500 batteries
- Initial $2,140,000- NPC of $3,991,487- COE $0.602/kWh
Soe & Zheng (2014)
- PGE 20-25- 25kW at 25m height- (8-12) turbines
- Trojan L16P- 500 batteries
- COE 0.257 $/kWh
Diab et al. (2015) NA NA - COE 0.172 $/kWh- COE 0.182 $/kWh- COE 0.179 $/kWh
In this section, an overview discussion will be performed based on table 1 (A, B). Throughout the
literature survey, the case studies that are done covered locations from different continents such as Asia,
Africa, North America, Australia and Europe. The annual average wind speeds ranged from 2.13 to 7.38
m/s. However, all of the annual wind speeds are below 10m/s. There are many simulation studies
covering stand-alone or grid-connected system. Some researchers tended to design a hybrid wind power
system such as PV-Wind power system or PV-Wind-Diesel power system due to the limited wind
resource at their sites and therefore, other power systems are needed in order to sustain the designed load.
From Table 1 also, the studied load profiles are ranging from 12kWh/day to 2MWh/day. The applications
of the case studies covered residential buildings, small business premises, desalination units and college
building. Moreover, different case studies employed different models of wind turbine with different
power capacity. The wind turbines’ capacity ranges from 1 to 100 kW depending on the applications.
Besides, different brands of batteries are also used for different case studies. For the costs aspect, there is
no general trend that can be seen from the case studies; different turbines and batteries (brand, type &
power) will definitely affect the techno-economic aspects of wind turbine system. Also, many researchers
who conducted studies on wind power system focused on case studies related to their specific wind speed
and load data as shown from the literature summary in table 1.
So far, there is no research that generalizes the outstanding wind turbine size for a certain load to be
applicable many locations around the globe. Also, scientific investigation regarding how the different
wind turbine sizes and wind turbine hub heights can affect the wind power system is still limited and not
discussed extensively using the parameters of the techno-economic feasibility. This research intends to
uncover the effect of different annual wind speed, different wind turbines sizes, as well as different hub
heights on the values of the techno-economic feasibility parameters of wind power system. Also in this
study, the analysis will reveal the possibility of using annual wind speed data as a sufficient data to
predict the outstanding wind turbine size that can power a certain load at locations within annual wind
speed range (3-12 m/s) which is more practical for researchers and customers to learn lessons. There are
no pre-selections of locations in this research; instead, a range of annual wind speed (3-12 m/s) is taken as
inputs into HOMER to represent so many locations around the planet and to generate output.
2. MATERIALS AND METHOD
2.1 RESEARCH DESIGN
Figure 1: Block diagram of the study evolution methodology
The studied load is chosen to be a common load for many small-scale applications as learned from
literature summarized in Table 1. 8 kW load is assumed to operate for 10 hours from 8 o’clock in the
morning till 6 o’clock in the evening. For each hour, the load profile is assumed a full load as shown in
Figure 2. On average, the small scale unit will consume 80 kWh of electricity per day.
Objectives
Simulation results: Techno-economic
feasibility parameters of wind turbine power
system
Input data/ components/ design scope
- To size the outstanding wind turbine power fit around the globe for a certain load using annual wind speed data range (3-12) m/s instead of actual monthly wind speed data of the respective locations. - To validate the outstanding wind turbine using actual monthly wind speed data of some locations. The implemented hub height is the minimum for each turbine.- To determine the effect of the other hub heights of the outstanding wind turbine on the values of techno-economic parameters.
1. No. of turbine2. No. of batteries3. Battery lifetime4. Initial capital cost ($)5. Operating cost ($/yr.)6. Total NPC ($)7. COE ($/kWh)
- Primary load (8kW)- Batteries type (Trojan L16P) specifications- Converter cost /kW- (7) Types of wind turbines and their specifications - hub heights of the implemented wind turbines - Capacity shortage (0%) is assumed- Annual wind speed range (3-12) m/s as input data to present any location around the globe - Actual monthly wind speed data for some locations i.e. Dammam city as case studies for validation purposes
Figure 2: 8kW load profile of a small scale wind power system operating 10 hour daily
In this work, the real monthly wind speed data that can describe respective location will not be used as
input data in the base line of wind speed. Instead of that, only the annual wind speed will be used as input
data, and will be directly keyed-in the sensitivity values window of HOMER simulation tool within the
range (3-12) m/s, as shown in Figure 3. The annual wind speed values falls within 3-12 m/s is taken as
inputs to represent any location around the planet. Wind speeds of 1 and 2 m/s are disregarded in this
study, as most of the wind turbines have a minimum cut-in speed of around 3 m/s. Also, the maximum
annual wind speed value used in this study is 12 m/s which reflect extreme exceptional case under the
index value of wind resource.
Figure 3: Annual wind speed data keyed-in the software to represent any location around the globe
Because the analysis depended on the annual wind speed data only, the obtained results are regarded as a
preliminary indicator for techno-economic feasibility, where the actual feasibility is logically higher than
the obtained results. Generally, under this stage of analysis, the results of techno-economic parameters are
adequate and appropriate for comparison purposes to predict the outstanding size of wind turbine that can
power (8kW) load around the globe.
For the validation step of the proposed sizing approach, real monthly wind speed data will be directly
keyed-in in the base line of wind speed. Figure 4 illustrates the monthly wind speed data of Dammam city
as a case study to predict the outstanding wind turbine size among the seven wind turbines. If the results
of this case predict the same wind turbine size to power the load, it can be concluded that proposed sizing
approach is fit to predict the outstanding wind turbine around the globe for a certain load profile.
Figure 4: monthly wind speed input data for Dammam city
However, to confirm the accuracy of the proposed sizing approach under different annual wind speed, the
validation will test another two locations besides Dammam city location. The monthly wind speed data
(m/s) for the three tested locations is shown in table 2.
Table 2: The real monthly wind speed data (m/s) for the three tested locations
Month Dammam / Saudi [23]
Ras Monief / Jordan [24]
kokhanok, Alaska / USA [25]
January 4.16 6.56 7.73
February 4.72 6.76 10.01
March 4.72 7.17 8.53
April 4.72 6.17 7.22
May 5 5.85 7.09
June 5.27 6.49 7.84
July 4.72 6.95 7.03
August 3.88 6.22 6.68
September 3.88 5.49 7.33
October 3.61 4.83 6.86
November 4.16 6.46 8.46
December 4.16 6.14 9.32
Annual 4.41 6.3 7.84
2.2 Materials
The wind turbines were selected from the list of wind turbines available in the HOMER software. The
most important criteria in selecting these turbines are its expected suitability vis-à-vis the load demand.
After series of evaluations, seven types of wind turbine with different sizes were selected to be simulated
in this study. These seven wind turbines are: SW Whisper 500, BWC Excel-R, BWC Excel-S, PGE 20-
25, Fuhrlander FL 30/13, PGE 11-35, and Entegrity EW15. For each wind turbine, there are
recommended hub heights by the manufacturer; hence, the simulation will include the possible hub height
of the selected turbines. The rated power of the wind turbines varies from 3 kW to 50 kW. The Capital
Cost of each of the wind turbines is taken from the company’s website or latest journals publications that
used the wind turbine. As for the Replacement Cost and Operation & Maintenance (O&M) Cost, the
values are estimated to be 85% and 2.5% of the Capital Cost, respectively. The specifications of each
wind turbine are tabulated in Table 3(A-B).
Table 3-A: Specifications of wind turbines
Wind Turbine AC/DC Rated Power (kW)
Rotor Diameter (m) Hub Height (m) No. of
BladesSW Whisper 500 DC 3 4.5 9.1, 12.8, 21.3 2
BWC Excel-R DC 7.5 7 18, 24, 30, 37, 43, 49 3BWC Excel-S AC 10 7 18, 24, 30, 37, 43, 49 3
PGE 20/25 AC 25 20 24, 25, 30, 36 3Fuhrlander FL 30/13 AC 30 13 19, 25, 29 3
Entegrity EW15 AC 50 15 25, 30 3PGE 11/30 AC 35 11 19, 24 3
Table 3-B: Continued specifications of wind turbines
Wind Turbine
Cut-In Wind Speed (m/s)
Rated Wind Speed (m/s)
Cut-Out Wind Speed
(m/s)Manufacturer Cost ($)
SW Whisper 500 3.4 10.5 25 Southwest Windpower, USA 8,985
BWC Excel-R 3 13.8 25 Bergey Windpower Co., USA 26,870
BWC Excel-S 2.5 12 25 Bergey Windpower Co., USA 31,770
PGE 20/25 3.5 9 25 Energie PGE, Canada 70,000
Fuhrlander FL30/13 3 12 21 Fuhrlander, Germany 78,000
PGE 11/30 4.8 14 25 Energie PGE, Canada 105,000
Entegrity EW15 4.6 11.3 22.4 Entegrity Wind Systems Inc., Canada 160,000
The Trojan L16P type battery was selected in this study due to its popularity and corresponding low costs.
The valve regulated lead acid battery is rated at 6 V and has a capacity of 360 Ah. Capital Cost for one
battery is set at $320. The replacement battery will cost another $320, while the Operation and
Maintenance (O&M) cost for a year is fixed at $5. The battery should operate without problems for the
next 4 years at least [11]. Table 4 shows the specifications of the L16P battery.
Table 4: Battery SpecificationsBattery model Trojan L16P
Types of battery Valve Regulated Lead Acid (VRLA)Voltage (V) 6Capacity rate 360 Ah
Dimensions (mm) 295 (L) x 178 (W) x 424 (H)Weight (kg) 52
Quantity considered 1 - 100
An electronic power converter is included in order to maintain the flow of energy between the AC and the
DC bus. The power converter can either be an inverter (if the wind turbine supplies DC current) or a
rectifier (if the wind turbine supplies AC current). The size of the convertor that is used in this study
varies from 0 to 20 kW. The Capital and Replacement Cost are $1095 with no cost for Operation and
Maintenance (O&M).
2.3 HOMER simulation tool
Software, which is the acronym of "Hybrid Optimization Model for Electric Renewables", is employed in
this field to simulate the life cycle cost of the system and accounting for the capital, replacement,
operation and maintenance, fuel, and interest costs. From the simulation, the cost associated with the wind
turbines will be optimized in order to enable us to determine the optimal turbine for the organization. This
software is able to model small renewable or non-renewable systems and techno-economically inspect the
desired power system. Its important functions are listed below [26]:
i. Coming up the lowest cost combination of parts that run into electrical and thermal loads
ii. Simulation of thousands of possible system configurations
iii. Optimization of the life cycle cost and a sensitivity analysis on most inputs
Techno-economics is the combination of technical and economic analysis of a power system. The
technical analysis studies the purpose and positioning options for a new wind turbines, grid connection
solutions, planning, and environmental matters. In this work, the technical analyses that needs to be
accounted for include the number of turbines, the number of batteries, and their corresponding lifetime.
On the other hand, the economic analysis involves cost-related aspects in designing the wind power
system, which admits the initial price of the system, Operation and Maintenance (O&M) costs, Total Net
Present Cost (NPC), and Cost of Energy (COE). Post-simulations, HOMER groups the feasible cases in
an ascending order of the net present (or life cycle) cost. This price is the present value of the initial,
component replacement, performance, maintenance, and fuel prices. [27].
3. RESULTS AND DISCUSSION
In the first part of the discussion, the minimum hub height required by the wind power system will be
used to study the effects of wind speed and wind turbine on each of the techno-economic feasibility
parameters.
3.1 determining the outstanding wind turbine power
The outstanding size of wind turbine will be determined based on the following evaluation parameters:
1. Technically is feasible under each annual wind speed with:
Number of turbines with optimal power duty (towards minimum)
Number of batteries with optimal power duty (towards minimum)
Optimal battery lifetime (towards maximum)
2. Economically is feasible under each annual wind speed with:
Initial cost (towards minimum)
Total NPC (towards minimum)
O&M cost (towards minimum)
Levelized cost of energy COE (towards minimum)
3.1.1 Effect of Wind Speed and Wind Turbine Sizes on Number of Turbines
Figure 5.2 shows the number of turbines vs. the annual wind speed using different wind turbines of
different sizes. From Figure 5.2, it is shown that the relationship of annual wind speed and number of
turbines that are needed is not an inverse-linear relationship. It can be seen that the number of wind
turbines decreases as the annual wind speed increases. This demonstrated that higher annual wind speeds
results in higher power outputs, thus the required numbers of turbines to sustain the load becomes less
and less. In other words, an increase in the wind speed will help reduce the number of turbines needed by
the wind power system.
3 4 5 6 7 8 9 10 11 120
2
4
6
8
10
12
14
16
18
SW Whisper 500 (3kW) BWC Excel-R (7.5kW) BWC Excel-S (10kW)
PGE 20-25 (25KW) Fuhrlander FL 30-13 (30kW) PGE 11-35 (35KW)
Entegrity EW15 (50kW)
Wind Speed (m/s)
No.
of T
urbi
nes
Fig 5: No. of turbines vs. annual wind speed for different wind turbines of different sizes
A turbine’s size, with a minimum quantity of turbines, is most crucial when designing a wind power
system. Therefore, in this round of evaluation, a turbine’s size with a minimum number of turbines
“wins”. Based on Figure 5:
At an annual wind speed of 3 m/s, only three turbines, namely PGE 20-25 (25kW), Fuhrlander
FL30/13 (30 kW), and PGE 11-35 (35kW), are technically capable of sustaining loads. However,
the wind power system needs 4,6,14 turbines to accomplish the aforementioned tasks. This
indicates that when the wind resource is limited (low annual wind speed), the technical feasibility
of the system requires the support of more turbines.
Starting from 4 m/s and up till 12 m/s, all types of wind turbine are technically feasible, with
different turbine quantities. Of course, lower power capacity turbines [SW Whisper 500 (3kW)]
will require more to satisfy the load requirements as opposed to higher capacity wind turbines.
In this round of analysis, it can be concluded that the recommended turbine to power an (8 kW) load at an
annual wind speed of 3 m/s is the PGE 20-25 (25kW) with 4 turbines. At an annual wind speed of 4 m/s,
the recommended wind turbine is again PGE 20-25 (25kW) with 1 turbine. At an annual wind speed of 5
m/s, the recommended turbines are PGE 20-25 (25kW), Fuhrlander FL30/13 (30 kW), and Entegrity
EW15 (50kW) with 1 turbine. At an annual wind speed of 6-9 m/s, the recommended turbines are PGE
20-25 (25kW), Fuhrlander FL30/13 (30 kW), PGE 11-35 (35kW), and Entegrity EW15 (50kW) with 1
turbine. At an annual wind speed of 10 m/s, the recommended turbines are BWC Excel-S (10 kW), PGE
20-25 (25kW), Fuhrlander FL30/13 (30 kW), PGE 11-35 (35kW), and Entegrity EW15 (50kW) with 1
turbine. Finally, at an annual wind speed of 11-12 m/s, all the studied wind turbines are recommended,
except SW Whisper 500 (3kW), with 1 turbine.
The SW Whisper 500 (3kW), BWC Excel-R (7.5kW), and BWC Excel-S (10kW) possess the minimum
number of turbines at high annual wind speeds only. BWC Excel-S (10 kW), PGE 20-25 (25kW),
Fuhrlander FL30/13 (30kW), PGE 11-35 (35kW), and the Entegrity EW15 (50kW) turbines possess the
extreme minimum number of turbines (1 wind turbine) and compared to PGE 20-25 (25kW), Fuhrlander
FL30/13 (30kW), and Entegrity EW15 (50kW), they showed a faster rate of reaching the minimum
number of turbine and at low annual wind speed, while the PGE 11-35 (35kW) turbine have the minimum
number of turbines at 6 m/s of annual wind speed. Therefore, the most outperformed turbine for (8 kW)
load in this round of analysis is the PGE 20-25 (25kW), followed by Fuhrlander FL30/13 (30 kW), and
the Entegrity EW15 (50kW) wind turbine.
3.1.2. Effect of Wind Speed and Wind Turbine Sizes on Number of Batteries
The battery is used as a backup when the output from the wind power system is inadequate to sustain the
load. The wind power system utilizing the minimum number of batteries is regarded as outperformed.
At lower annual wind speed, most of the systems require battery support. However, as the annual
wind speed increases, the wind power system gradually lessens its dependence on batteries. This
is due to the production of more usable power, thus the need for lesser batteries. From Figure (6),
4 - wind turbines show the number of batteries needed as being under 10: PGE 20-25 (25 kW),
Fuhrlander FL30/13 (30 kW), PGE 11-35 (35 kW), and Entegrity EW15 (50 kW). This occurs
when the wind speed is (5.0 m/s) and above for PGE 20-25 (25 kW), while the speed is (7.0 m/s)
and above for Fuhrlander FL30/13 (30 kW), and the speed is (8.0 m/s) and above for PGE 11-35
(35 kW), with the wind speed being (6.0 m/s) and above for Entegrity EW15 (50 kW). This again
shows that the larger the capacity of wind power system, the less its reliance upon batteries will
be. However, we need to compare the systems in terms of cost in order to determine the most
optimum system. The outperformed turbine in this round of analysis is the Entegrity EW15
(50kW), followed by the PGE 20-25 (25kW) wind turbine.
3 4 5 6 7 8 9 10 11 120
10
20
30
40
50
60
70
80
90
SW Whisper 500 (3KW) BWC Excel-R (7.5KW) BWC Excel-S (10KW)PGE 20-25 (25KW) Fuhrlander FL30-13 (30KW) PGE 11-35 (35KW)Entegrity EW15 (50KW)
Wind Speed (m/s)
No. o
f Bat
teries
Fig. 6: No. of batteries vs. annual wind speed for different sizes of wind turbine
3.1.3 Effect of Wind Speed and Wind Turbine Sizes on Battery Lifetime
In Figure 7, batteries with a longer lifespan remain the best choice. The outstanding wind power system
will be selected based on its ability to protect and lengthen the battery’s lifetime. Due to the complexity of
determining the battery’s lifetime at different annual wind speeds, Figure 7 did not exhibit a clear trend.
Each size of wind turbine showed different battery lifetimes. However, at wind speeds of 3- 4 m/s, the
wind power system is unable to produce enough usable power for the load; thus, the batteries are heavily
used. Due to this, its lifetime is shorter (~4 - 5 years) compared to higher annual wind speeds. For annual
wind speeds of 5 m/s and above, there are at least one wind power system with a fit lifetime of up to 10
years for their battery bank system.
3 4 5 6 7 8 9 10 11 120
2
4
6
8
10
12
SW Whisper 500 (3kW) BWC Excel-R (7.5kW) BWC Excel-S (10kW)PGE 20-25 (25KW) Fuhrlander FL30-13 (30kW) PGE 11-35 (35KW) Entegrity EW15 (50kW)
Wind Speed (m/s)
Batte
ry L
ifetim
e (y
rs)
Fig 7: Battery lifetime vs. annual wind speed for different sizes of wind turbine
Figures 8 and 9 show the relation between the battery quantity and lifetime for two sizes of turbines;
BWC Excel-R (7.5 kW) and PGE 20-25 (25kW). In Figure 8, the unstable battery lifetime at different
annual wind speeds is observed; while the obvious stable battery lifetime is shown in Fig 9 at annual wind
speeds of (5-12 m/s).
The higher number of batteries indicates that the wind power system is more dependent on battery power.
Due to the frequency of the battery usage, its lifetime is relatively low. In contrast, the lower quantity of
battery implies that the system is less dependent on batteries, with the power mainly coming from the
wind turbine. Therefore, the battery exhibits a longer lifetime. For the entire annual wind speed range,
wind turbine PGE 20-25 (25 kW) exhibited the highest battery lifetime with a fit battery lifetime at most
of wind speed range, as shown in Figures 7 and 9.
3 4 5 6 7 8 9 10 11 120
10
20
30
40
50
60
70
80
0
2
4
6
8
10
12
batteries lifetime
Annual Wind Speed
No.
of B
atte
ries
Bat
tery
Life
time
Fig. 8: No. of batteries & battery lifetime vs. annual wind speed for BWC Excel-R (7.5 kW) turbine
3 4 5 6 7 8 9 10 11 120
5
10
15
20
25
30
35
40
45
50
0
2
4
6
8
10
12
battery lifetime
Annual Wind Speed
No.
of B
atte
ries
Bat
tery
Life
time
Fig. 9: No. of batteries & battery lifetime vs. annual wind speed for PGE 20-25 (25kW) turbine
3.1.4 Effect of Wind Speed and Wind Turbine Sizes on Initial Cost
From here on out, the discussion will involve the cost aspects of the system, which encompasses initial
Cost, O&M Cost, total NPC, and COE.
The results indicate that initial cost decreases as the annual wind speed increases, due to the effect of
quantities of turbines and the battery bank size. PGE 11-35 (35 kW) shows the extreme highest initial cost
compare to other turbines observed at an annual wind speed 3 m/s. From the 4 m/s henceforth, Entegrity
EW15 (50 kW) resulted in the highest initial cost compared to other turbine systems.
Moreover, PGE 20-25 (25 kW) and SW Whisper 500 (3 kW) are the best in terms of initial cost, as they
frequently report the lowest initial cost in Figure 10 At the annual wind speed range (3-7 m/s), the lowest
initial cost was held by PGE 20-25 (25 kW), while at the annual wind speed range (8-12 m/s), the lowest
initial cost was held by SW Whisper 500 (3 kW).
3 4 5 6 7 8 9 10 11 12$0
$200,000
$400,000
$600,000
$800,000
$1,000,000
$1,200,000
$1,400,000
$1,600,000
SW Whisper 500 (3kW) BWC Excel-R (7.5kW) BWC Excel-S (10kW)PGE 20-25 (25KW) Fuhrlander FL30-13 (30kW) PGE 11-35 (35KW)Entegrity EW15 (50kW)
Wind Speed (m/s)
Initi
al C
ost (
$)
Fig. 10: Initial Cost vs. annual wind speed for different sizes of wind turbine
3.1.5 Effect of Wind Speed and Wind Turbine Sizes on O&M Cost, Total NPC and COE
In this subsection, the outstanding wind turbine should offer the lowest operation and maintenance cost
(O&M cost), the lowest total net present cost (total NPC), and the lowest cost of energy (COE). The
trends for these three parameters are similar to the initial cost. From the 4 m/s henceforth, Entegrity
EW15 (50kW) showed the highest O&M cost, total NPC, and COE. The lowest O&M cost, lowest total
NPC, and lowest COE were mainly achieved by the PGE 20-25 (25kW) from 3-8 m/s, then SW Whisper
500 (3kW) from 9-12 m/s.
3 4 5 6 7 8 9 10 11 120
10000
20000
30000
40000
50000
60000
SW Whisper 500 (3kW) BWC Excel-R (7.5kW) BWC Excel-S (10kW) PGE 20-25 (25KW) Fuhrlander FL30-13 (30kW) PGE 11-35 (35KW)Entegrity EW15 (50kW)
Wind Speed (m/s)
O&
M C
ost (
$/yr
)
Fig. 11: O&M cost vs. annual wind speed for different sizes of wind turbine
3 4 5 6 7 8 9 10 11 120
500,000
1,000,000
1,500,000
2,000,000
2,500,000
SW Whisper 500 (3kW) BWC Excel-R (7.5kW) BWC Excel-S (10kW)PGE 20-25 (25KW) Fuhrlander FL30-13 (30kW) PGE 11-35 (35KW)Entegrity EW15 (50kW)
Wind Speed (m/s)
Tota
l NPC
($)
Fig. 12: Total NPC vs. annual wind speed for different sizes of wind turbine
3 4 5 6 7 8 9 10 11 120.00
1.00
2.00
3.00
4.00
5.00
6.00
SW Whisper 500 (3kW) BWC Excel-R (7.5kW) BWC Excel-S (10kW) PGE 20-25 (25KW) Fuhrlander FL30-13 (30kW) PGE 11-35 (35KW)Entegrity EW15 (50kW)
Wind Speed (m/s)
COE($/kW
h)
Fig. 13: COE vs. annual wind speed for different sizes of wind turbine
3.1.6 The outstanding wind turbine size powering a certain load around the Globe
The outstanding turbine had been highlighted and discussed based on the techno-economic feasibility
parameters. Table 4 demonstrated the outstanding wind turbines that are potentially able to power the
load (8kW) at each annual wind speed (3-12 m/s) across all the evaluations. The table showed that there
are two distinct wind turbines. PGE 20-25 (25kW) was found to be absolutely superior at a wind speed
range (3-8 m/s) in terms of system cost, system size, and stability. SW Whisper 500 (3kW) was found to
be superior at an annual wind speed range (9-12 m/s) in terms of system cost. However, under the annual
wind speed (9-12 m/s), PGE 20-25 (25kW) is still superior in terms of system size and stability, and lag
step from SW Whisper 500 (3kW) in terms of system cost. It can be surmised that under the annual wind
speed of (3-12 m/s) that represent any location around the globe, the compromise confirmed that the
Outstanding wind turbine is PGE 20-25 (25kW) in terms system cost, system size, and stability
concurrently.
As a result of this, it is concluded that the outstanding wind turbine is the PGE 20-25 turbine; with rated
power of (25kW) for supplying the (8kW) load. From this evaluation, one important lesson learned is that
the power system required to sustain the 8 kW load is found to be almost three times the load.
Table 5: The outstanding turbines based on techno-economic feasibility parameters
System size and stability Economic feasibility
Annual wind speed
Min No. of
turbines
Min No. of
batteries
Max Battery lifetime
Min Initial Cost
Min O&M Cost
Min Total NPC
Min COE
superior
3 m/s 25kW 25kW 25kW 25kW 25kW 25kW 25kW 25kW
4 m/s 25kW 25kW 25kW, 3kW.
25kW 25kW 25kW 25kW 25kW
5 m/s 25kW, 30kW, 50kW.
25kW 25kW 25kW 25kW 25kW 25kW 25kW
6 m/s 25kW, 30kW, 50kW, 35kW.
25kW 25kW, 50kW, 30kW.
25kW 25kW 25kW 25kW 25kW
7 m/s 25kW, 30kW, 50kW, 35kW.
@ 50kW: 9
@ 25kW: 4
25kW, 50kW, 30kW, 35kW.
25kW 25kW 25kW 25kW 25kW
8 m/s @25kW,30kW, 50kW,
35kW}:1 @
3kW : 7
@ 50kW : 0
@ 25kW : 2
@ 3kW :
37
@25kW : 10@
3kW : 8.5
@ 25kW :72,830@ 3kW :72,095
@ 25kW :2,268
@ 3kW :2,706
@ 25kW :101,824 @ 3kW :106,693
@25kW : 0.27
@ 3kW : 0.28
25kW
9 m/s @(25kW,30kW, 50kW,
35kW): 1 @ 3kW
: 4
@50kW : 0 @
25kW : 2 @
3kW : 35
@25kW : 10
@ 3kW : 9.1
@ 3kW :62,470
@ 25kW :71,735
@25kW : 2,256
@ 3kW : 2,278
@ 3kW :91,
590@ 25kW :100,579
@ 3kW : 0.24
@25kW : 0.27
at cost level: 3kW
at size level:
25kW
10 m/s @(25kW,30kW, 50kW, 35kW,
10kW): 1 @
3kW :4
@(50kW, 30kW) : 0 @25kW :1 @3kW :2
0
@(25kW ,
3kW) :10
@ 3kW :58,765
@ 25kW :71,415
@ 3kW :1,827 @
25kW :2,232
@ 3kW :82
,119@ 25kW :9
9,954
@ 3kW : 0.22
@25kW : 0.27
at cost level: (3kW)
at size level: 25kW
11 m/s @{25kW,30kW, 50kW, 35kW, 7.5kW,
10kW}:1
@(50kW, 30kW,
35kW) : 0 @25kW
: 1
@(25kW, 3kW):
10
@ 3kW :52,340
@ 25kW :71,415
@ 3kW :1,7
24 @ 25kW :
2,232
@ 3kW :74
,385@ 25kW :9
9,954
@ 3kW : 0.20
@25kW : 0.27
at cost level: (3kW)
at size level: 25kW
@ 3kW : 3
@ 3kW:28
12 m/s @{25kW, 30kW, 50kW, 35kW, 7.5kW,
10kW}:1 @
3kW : 3
@(50kW, 30kW,
35kW): 0 @
25kW : 2 @
3kW : 24
@(25kW,3kW) :
10
@ 3kW :51,060
@ 25kW :72,830
@ 3kW :1,629 @
25kW :2,268
@ 3kW :71
,884@ 25kW :101,824
@ 3kW :0.1
9 @25kW
: 0.27
at cost level: (3kW)
at size level: 25kW
Range 3-8m/s
Recommended turbine at 3-8 m/s in terms of system cost, system size and stability: PGE 20-25 (25kW)
Range 9-12m/s
Recommended turbine at 9-12 m/s in terms of system cost:SW Whisper 500 (3kW)
Range 3-12m/s
Recommended turbine as a compromise in terms of system size, system cost and stability: PGE 20-25 (25kW)
Features of the outstanding wind turbine PGE 20-25 (25kW) in terms of system cost, system size, and
battery stability at each annual wind speed is shown in Figure 14. It can be seen that the number of
turbines at low annual wind speed is high compared to wind turbines used at other annual wind speeds.
Also, despite the high number of batteries, the battery life time remains low, which means that the
dependence on the battery bank to power the load is dominant at low annual wind speed 3-4 m/s. So,
adopting higher hub heights at low annual wind speed could optimize the power capacity and
consequently reduce the dependency on the batteries and improve battery life. This round of analysis will
be performed and evaluated in the next section.
3 4 5 6 7 8 9 10 11 120
5
10
15
20
25
30
35
40
45
00.10.20.30.40.50.60.70.80.911.11.21.3
No. Turbine No. Batteries Battery Lifetime COE
Wind Speed (m/s)
Num
ber
kWh/
$
Figure 14: No. of turbines, batteries number & life time, and levelized COE of the outstanding wind
turbine PGE 20-25 (25kW) vs. annual wind speed
3.2 Effect of Different Hub Heights of the Outstanding Wind Turbine (PGE 20-25) on optimizing the Parameters of Techno-economic feasibility
From previous discussion, it was concluded that the outstanding turbine size for the 8 kW load of constant
profile is the PGE 20-25 (25kW). In this round of analysis, the effect of hub heights offered by the
manufacturer on the power duty of the outstanding wind turbine at each annual wind speed will be tested.
From the manufacturer’s brochure, the PGE 20-25 wind turbine has 3 hub height options; 25 m, 30 m,
and 36 m. If techno-economic results at higher hub heights are not found to be viable at certain annual
wind speed, this means that wind turbine size and annual wind speed did impose more impacts compared
to higher hub heights and it can be concluded that the proposed sizing approach versus the studied annual
wind speed range.
4.2.1 Effect of Hub Height on Number of Turbines
3 4 5 6 7 8 9 10 11 12 wind 3 4 5 6 7 8 9 10 11 120
1
2
3
4
5
H = 25 H = 30 H = 36
Wind Speed (m/s)
No. o
f Tur
bine
s
Fig. 15: No. of turbines vs. annual wind speed for PGE 20-25 turbine
From Figure 15, at 3 m/s annual wind speed with a hub height of 25 m, PGE 20-25 turbine requires 4
turbines. At the following two hub heights (30 and 36 m), the number of turbines end up at 3. For annual
wind speed of 4 m/s and above, the number of turbines are constant (1 turbine) for the three hub heights.
Therefore, it is concluded that the increase of hub heights do not generally influence the number of PGE
20-25 wind turbines under annual wind speeds between (4-12 m/s).
3.2.2 Effect of Hub Height on Number of Batteries
3 4 5 6 7 8 9 10111205
10152025303540455055
H = 25 H = 30 H = 36
Wind Speed (m/s)
No.
of B
atte
ries
Fig. 16: No. of batteries vs. annual wind speed for PGE 20-25 turbine
As shown in Figure 16, at 3-4 m/s annual wind speeds, the number of batteries is still high at the three
hub heights, and the effect of higher hub height influenced the batteries’ reduction to between 5-8
batteries. At 5 m/s, the number of batteries under the three hub heights falls between 10 - 15 batteries. So,
the reduction in the number of batteries is 5. At wind speeds of 6-12 m/s, the variation in the number of
batteries is negligible at the three hub heights.
Generally, the number of batteries decreases as the wind speed and hub height increases. As pointed out
earlier, the power duty of the wind turbine increases as the wind speed increases. If the power from the
wind turbine is sufficient to sustain the load demand, then the number of batteries decreases.
For wind speeds of 5 m/s and above, the number of batteries needed by the system falls under 15; which
is reasonable since some designers may opt for a fixed amount of batteries to be installed in the system,
due to the fact that the intermittent availability of wind may result in a variable energy output. It can be
concluded that the effect of hub height is found not able to reduce the number of batteries significantly at
annual low wind speeds (not exceeding 8 batteries). This means that at low annual wind speeds, the
higher hub heights are still unable to run the wind turbine to fit the power duty level.
3.2.3 Effect of Hub Height on Battery Lifetime
3 4 5 6 7 8 9 10 11 120
2
4
6
8
10
12
H = 25 H = 30 H = 36
Wind Speed (m/s)
Batte
ry L
ifetim
e (y
rs)
Fig. 17 Battery lifetime vs. annual wind speed for PGE 20-25 turbine
At a low annual wind speed of 3 m/s, all 3 hub heights for the PGE 20-25 wind turbine showed low
battery lifetimes, which is ~4 years. At 4 m/s, the enhancement in battery life is a bit more obvious, as
shown in Table 6. However, after that, the annual wind speed 5-12 m/s resulted in an optimum battery
lifetime of 10 years, as can be seen from the figure above, which means that at low annual wind speed,
higher hub heights are still not crucial.
Table 6: The increase in battery lifetime for different hub heights at 4 m/s.
Hub heights of PGE 20-25 Increase in hub height
Battery lifetime /Increase in battery lifetime
25 m - 4.7 / -30 m 5 m 5.8 / 23.4%36 m 11 m 6.4 / 36.1%
Lessons learned:
i. The battery bank’s lifetime at 3-4 m/s is low, because the batteries work frequently compared to
higher classes of wind power.
ii. At annual wind speed 5-12 m/s, the battery lifetime is at an optimum state. The wind turbine
produces sufficient power at this range of wind speed to sustain the load, as well provide proper
recharging of the batteries.
iii. The effect of hub height is only obvious at low annual wind speed, from 3 - 4 m/s. However,
although the hub height increases, the PGE 20-25 turbine is still heavily dependent on battery power
to sustain the load at 3-4 m/s annual wind speed.
Finally, from a technical perspective, the effects of hub height on the wind power system are
insignificant, with the exception of at low wind speed (3-4 m/s). There are only small influences of hub
height on power duty of the turbine at low annual wind speed. This means that the sizing approach for the
wind turbine power system and its accuracy at the minimum hub height is reasonable under each annual
wind speed. Therefore, keeping the wind power system at its minimum hub heights is still, technically, a
reasonable option.
3.2.4 Effect of Hub Height on Initial Cost
3 4 5 6 7 8 9 10 11 120
50,000
100,000
150,000
200,000
250,000
300,000
350,000
H = 25 H = 30 H = 36
Wind Speed (m/s)
Initi
al C
ost (
$)
Fig. 18: Initial cost vs. annual wind speed for PGE 20-25 turbine
This sub-section discusses the initial cost of the system. It should be pointed out here that the initial cost
include the system components only, and not the required cost of the land and infrastructure for higher
hub heights. Therefore, the initial cost in this context encompasses the system cost only.
First, the discussion will be on the effect of different hub heights on the initial cost of the system for the
PGE 20-25 wind turbine. The lowest hub height for the PGE 20-25 wind turbine (25 m) provides the
highest value of initial cost. This is followed by the next hub height of 30 m, and the hub height of 36 m
results in the lowest initial cost for annual wind speed range (3-10 m/s). Table 4.5 shows the difference in
initial costs at different annual wind speed.
From Table 7, at a wind speed 3 m/s, increasing the hub height to 30 m or 36 will slash the initial cost to
around 22.9% maximum, while increasing the hub height to 30 m or 36 m will slash the initial cost to
around 0% to 3.1% within a wind speed range of 4-12 m/s. It was determined that starting from wind
speed of 10 - 12 m/s, the initial costs for all the 3 hub heights were similar.
Table 7: The decrease in initial cost by increasing the hub height
Annual wind speed (m/s) Initial cost ($) / reduced initial cost
25 30 363 307,860 / - 239,780 / 22.1% 237,220 / 22.9%4 96,900 / - 95,805 / 1.1% 94,205 / 2.7%5 84,655 / - 81,960 / 3.1% 81,960 / 3.1%6 78,810 / - 77,395 / 1.8% 77,395 / 1.8%7 74,565 / - 74,565 / - 74,245 / 0.4%8 72,830 / - 72,830 / - 72,830 / -9 71,735 / - 71,415 / 0.4% 71,415 / 0.4%
10 71,415 / - 71,415 / - 71,415 / -
From the observations above, at low annual wind speeds, the initial cost of the system decreases as the
hub height increases. This is due to the lesser quantity of equipment (turbines, batteries, etc.) needed by
the system, which caused the initial cost to decrease. However, the differences in initial cost at different
hub heights were found to be insignificant from 4-12 m/s.
3.2.5 Effect of Hub Height on O&M Cost, Total NPC and COE of the outstanding PGE 20-25 turbine
Figures (19, 20, and 21) describe O&M Cost, Total NPC, and COE, respectively, against annual wind
speed, and will be discussed together, as these three figures display similar trends.
As shown in Figures (19, 20, and 21) and Tables 8 - 9 - 10, effect of multiple wind turbine hub heights are
found significant but the cost of the wind power system remains high and not competitive at low annual
wind speed of 3 m/s. At an annual wind speed of 4 m/s, effect of multiple wind turbine hub heights are
found marginal on the cost reduction values where the percentage of cost reduction for the total NPC and
levelized COE values did not exceed 10%. At an annual wind speed of 5 m/s and above, the effect of hub
heights on cost parameters and percentage of cost reduction values vanished.
3 4 5 6 7 8 9 10 11 120
2,000
4,000
6,000
8,000
10,000
12,000
14,000
H = 25 H = 30 H = 36
Wind Speed (m/s)
O$M
Cos
t ($/
yr)
Fig. 19: O&M cost vs. annual wind speed for PGE 20-25 turbine
3 4 5 6 7 8 9 10 11 120
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
450,000
500,000
H = 25 H = 30 H = 36
Wind Speed (m/s)
Tota
l NPC
($)
Fig. 20: Total NPC vs. annual wind speed for PGE 20-25 turbine
3 4 5 6 7 7 9 10 11 120
0.10.20.30.40.50.60.70.80.9
11.11.21.3
H = 25 H = 30 H = 36
Wind Speed (m/s)
CO
E ($
/kW
h)
Fig. 21: COE vs. annual wind speed for PGE 20-25 turbine
Table 8: Percentage of reduction of O&M cost for different hub heights
Annual wind speed (m/s) O&M cost ($/year) / reduction O&M cost 25 30 36
3 11,978 / - 10,390 / 13.2% 9,492 / 20.7%4 4,914 / - 4,371 / 11.0% 3,920 / 20.2%5 2,661 / - 2,529 / 4.9% 2,529 / 4.9%6 2,434 / - 2.399 / 1.4% 2,399 / 1.4%7 2,328 / - 2,328 / - 2,304 / 1.0%8 2,268 / - 2,268 / - 2,268 / -9 2,256 / - 2,232 / 1.0% 2,232 / 1.0%
10 2,232 / - 2,232 / - 2,232 / -
Table 9: Percentage of reduction of total NPC for different hub heights
Annual wind speed (m/s) Total NPC ($) / reduction total NPC25 30 36
3 460,979 / - 372,672 / 19.1% 358,555 / 22.2%4 159,719 / - 151,675 / 5.0% 144,313 / 9.6%5 118,666 / - 114,295 / 3.6% 114,295 / 3.6%6 109,930 / - 108,060 / 1.7% 108,060 / 1.7%7 104,319 / - 104,319 / - 103,694 / 0.5%8 101,824 / - 101,824 / - 101,824 / -9 100,579 / - 99,954 / 0.6% 99,954 / 0.6%
10 99,954/ - 99,954 / - 99.954 / -
Table 10: Percentage of reduction of COE for different hub heights
Annual wind speed (m/s) COE ($/kWh) / Percentage of reduction in COE
25 30 363 1.248 / - 1.009 / 19.1% 0.971 / 22.1%4 0.432 / - 0.41 / 5.0% 0.391 / 9.5%5 0.321 / - 0.309 / 3.7% 0.309 / 3.7%6 0.297 / - 0.292 / 1.6% 0.292 / 1.6%7 0.282 / - 0.282 / - 0.281 / 0.3%8 0.276 / - 0.276 / - 0.276 / -9 0.272 / - 0.27 / 0.7% 0.27 / 0.7%
10 0.27 / - 0.27 / - 0.27 / -
From a financial perspective, the higher hub heights were minimally influential vis-à-vis the costs of the
wind power system at an annual wind speed range of 4-12 m/s.
Although the hub height minimally influences the techno-economic aspects of wind power systems, it
was found that wind power systems with higher hub heights are somehow preferable at low annual wind
speeds. However, if we consider the cost of the infrastructure for the wind turbine to stand higher hub
heights, it will increase the total cost of the wind power project (cost of wind power system and cost of
infrastructure for higher hub heights).
Overall, the effects of hub heights on the techno-economic aspects of wind power system can be regarded
to not be as important as annual wind speeds and wind turbine types. Similar to the first part of the
analysis, the effects of wind speed and types of wind turbine were more obvious than that in hub heights.
Finally, as the wind speed increases, lesser equipment (turbines, batteries, etc.) is needed by the system,
which reduces the initial, operation, and maintenance (O&M) costs, and consequently the total NPC cost.
3.3 Validation of the Outstanding Wind Turbine at Dammam City, Saudi Arabia
This round of analysis aims to determine the wind turbine size that can power a certain load using real
monthly wind speed data for testing and validation purposes. The tested location is Dammam city. The
determined wind turbine size will be compared with the outstanding wind turbine size determined by the
proposed sizing approach. If the wind turbine size is found same, this confirms that the proposed sizing
approach is accurate to predict the outstanding wind turbine size at any location around the globe.
The analysis in this section will be performed under the following assumptions:
1. Location of the study is Dammam city.
2. Studied load is 8 kW.
3. Real monthly wind speed data obtained from weather2 website.
4. Seven wind turbines of different sizes are used.
5. Minimum hub height for each wind turbine is implemented.
6. Implemented annual capacity shortage: (0%)
3.3.1 Effect of Different Wind Turbine Size on Number of Turbines
SW500
(3kW)
BWC-S(10
kW)
BWC-R(7.5kW
)
PGE 11
-35(35
kW)
EW15(50kW
)
FL30/
13(30k
W)
PGE 20-2
5(25kW
)
02468
10121416182022
22
1412
7
4 42
Wind Turbine Type
No. o
f Tur
bine
s
Figure 22: Number of turbines versus wind turbine sizes for Dammam city
Figure 22 illustrates the number of turbines vs. different wind turbine types at Dammam city. A turbine’s
size, with a minimum quantity of turbines, is most crucial when designing the wind power system.
Therefore, in this round of evaluation, PGE 20-25 (25kW) with 2 turbines was determined to be
outstanding.
3.3.2 Effect of Different Wind Turbine Size on Number of Batteries
The wind power system that utilized the minimum number of batteries is regarded as outperformed. From
Figure (23), 3 wind turbines required the minimum number of batteries below 100 to power the load. The
number of batteries was 86, 82, and 95 for PGE 20-25 (25kW), Fuhrlander FL30/13 (30kW) and PGE 11-
35 (35kW), respectively. Therefore, Fuhrlander FL30/13 (30kW) is regarded as an outstanding turbine in
terms of the minimum amount of batteries. However, the difference in the number of batteries between
Fuhrlander FL30/13 (30kW) and PGE 20-25 (25kW) was only 4 batteries. So, PGE 20-25 (25kW) could
be regarded as superior compared to other turbines.
BWC-S(10
kW)
SW500
(3kW)
EW15(50k
W)
BWC-R(7.5kW
)
PGE 11
-35(35
kW)
PGE 20
-25(25
kW)
FL30/
13(30k
W)
70
90
110
130
150
170
190193 192 192
186
9586 82
Wind Turbine Type
No. o
f Bat
teries
Figure 23: Number of batteries versus wind turbine sizes for Dammam city
3.3.3 Effect of Different Wind Turbine Size on Battery Lifetime
Batteries with a standard lifetime remain the best choice. All wind turbines showed standard lifetime of up to 10 years for their battery bank system, as shown in Figure 24.
SW50
0(3kW
)
BWC-R
(7.5k
W)
BWC-S(
10 kW
)
PGE 20
-25(25
kW)
FL30
/13(30
kW)
PGE 11
-35(35
kW)
EW15
(50kW
)0123456789
10
Wind Turbine Type
Bat
tery
Life
time
(yrs
)
Figure 5.24: Battery lifetime versus wind turbine sizes for Dammam city
3.3.4 Effect of Different Wind Turbine Sizes on Cost of Energy
From Figure (25), PGE 11-35 (35 kW) shows the extreme highest levelized cost of energy compared to
other turbines, while PGE 20-25 (25 kW) shows the lowest levelized cost of energy. So, PGE 20-25
(25kW) was determined to be absolutely superior in terms of levelized cost of energy.
PGE 11-35
(35kW
)
EW15
(50kW
)
BWC-S
(10 kW
)
BWC-R
(7.5k
W)
FL30/13
(30kW
)
SW50
0(3kW
)
PGE 20-25
(25kW
)0
0.30.60.91.21.51.82.12.42.7
33.3 3.052
2.859
2.106
1.6221.336
1.138
0.724
Wind Turbine Type
CO
E($
/kW
h)
Figure 25: COE versus wind turbine sizes for Dammam city
3.3.5 Determining Wind Turbine Size at other Different Tested Locations Using their Monthly Wind Speed Data
Based on Figures 22, 23, 24, and 25, it can be seen that the wind power system that has the minimum
amount of wind turbines, where the number of batteries approaches the minimum, with the standard
battery lifetime and lowest levelized cost of energy being PGE 20-25 (25 kW). As a result of this, it was
concluded that the outstanding wind turbine was the PGE 20-25 (25 kW) for powering 8 kW load at a
Dammam city.
Dammam city as a tested location with real monthly wind speed data, the recommended wind turbine
amongst the (7) wind turbines is again PGE 20-25 (25kW). The same analyses are performed for another
two locations using their real monthly data. The outstanding turbine size based on techno-economic
feasibility parameters for three tested locations is shown in table 11. The results of the analyses confirmed
that the outstanding wind turbine size is still again PGE 20-25 (25kW). This confirms that the shortcut
sizing approach adopted in section 3.1 is accurate to determine the outstanding wind turbine that is
confirmed using real monthly data at the tested locations. So, the proposed sizing approach is fit to predict
the outstanding wind turbine at any location around the globe.
Table11: The outstanding turbine size based on techno-economic feasibility parameters for three tested
locations
Case studies with real monthly
wind speed data
Wind turbine
sizes with min
No. of turbines
Wind turbine sizes
with min No. of
batteries
Wind turbine
sizes with max
Battery lifetime
Wind turbine
size with min COE
Optimum turbine size at the tested
locations using
monthly wind speed
data
Outstanding turbine size predicted by annual wind speed data
Dammam/Saudi
25kW@30kW: 82@25kW: 86
All sizes 25kW 25kW
25kWRas Monief/
Jordan25kW, 30kW 50kW
25kW All sizes 25kW 25kW
kokhanok, Alaska/ USA
25kW, 30kW 35kW, 50kW
25kW All sizes 25kW 25kW
4. CONCLUSION
This study proposed a shortcut sizing approach that predicts the outstanding wind turbine size to power a
certain load 8 kW at so many locations around the globe within annual wind speed range (3-12 m/s). For
this purpose, seven wind turbine types with different power were selected. The selection was based on the
expected appropriateness of the power capacity to power an 8 kW load, on top of the initial cost of each
wind turbine. The outstanding wind turbine size is determined based on the results of techno-economic
feasibility parameters. The results of the techno-economic feasibility parameters are obtained using
HOMER simulation tool. The seven turbines performances versus the annual wind speed range are
compared at each parameter. The results showed that the outstanding size of wind turbine is PGE 20-25
(25 kW). For further confirmation, validation test is performed at three locations using their monthly wind
speed data to predict the optimum wind turbine size. The validation results showed that optimum wind
turbine size is PGE 20-25 (25 kW) at the three tested locations. Moreover, the results showed that the
outstanding wind turbine size and annual wind speed did impose more impacts on the values of techno-
economic feasibility parameters compared to higher hub heights. Finally it can be concluded that the
proposed sizing approach utilizing annual wind speed data (3-12m/s) a representative of locations is
accurate to predict the outstanding wind turbine of optimum power duty to run 8kW load around the
globe.
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