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Aug 03, 2021

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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, Malaysia
b 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: dr.alghoul@gmail.com
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 outlines
1. INTRODUCTION
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 energy
3.3.5 Determining Wind Turbine Size at other Different Tested Locations Using their Monthly Wind Speed Data
4. CONCLUSION
1. INTRODUCTION
Wind 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
Tioman Island, Malaysia
Monthly (3.0 – 4.0 m/s)
Grid-connected: Hybrid Wind-PV-Battery
Ireland
NA
Adaramola (2012)[5]
Ondo State, Nigeria
Madrid (Cuatro
Candelaria, Spain
Punta
Hurghada, Egypt
60
Small Scale Brackish Reverse Osmosis Desalination Unit and a Tourism Motel
Moniruzzaman & Hasan (2012)[8]
St. Martin Island, Bangladesh
Mulligan, Labrador, Canada.
Mrair-Gabis Village, Libya
Desalination Unit
Kuala Terengganu, Malaysia
Monthly (3.16 m/s)
Monthly
Plaka, Greece
Nok kundi &
Ormara, Pakistan
Grid-connected: Hybrid Wind-PV-Diesel
Amini (2010) [19]
NA
St. Martin Island, Bangladesh
Monthly
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 tool
References
Costs aspects
- 40 turbines
- Surrette 6CS25P
- 540 batteries
- 3 turbines
- Grid-connected: 1 turbine
- Stand-alone:
Goodbody et al. (2012)
COE - $ 0.578 – 0.682/kWh
- Trojan L16P
- 1 turbine
- Generic 3 kW
- Trojan T-105
- COE $0.087/kWh
- 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
- 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
1. No. of turbine
1. No. of batteries
1. Total NPC ($)
1. COE ($/kWh)
- 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.
Input data/ components/ design scope
Simulation results:
Objectives
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.
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
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
3
3
Wind Turbine
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 Specifications
Voltage (V)
Weight (kg)
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)
1. Economically is feasible under each annual wind speed with:
· Initial cost (towards minimum)
· Total NPC (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.
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.
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.
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.
Fig. 8: No. of batteries & battery lifetime vs. annual wind speed for BWC Excel-R (7.5 kW) turbine
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).
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.
Fig. 11: O&M cost vs. annual wind speed for different sizes of wind turbine
Fig. 12: Total NPC vs. annual wind speed for different sizes of wind turbine
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
@ 50kW : 0
@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
@(25kW , 3kW) :10
@(50kW, 30kW, 35kW) : 0 @25kW : 1
@ 3kW:28
@(50kW, 30kW, 35kW): 0 @ 25kW : 2 @ 3kW : 24
@(25kW,3kW) : 10
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.
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
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
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
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
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
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)
25
30
36
3
307,860 / -
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.
Fig. 19: O&M cost vs. annual wind speed for PGE 20-25 turbine
Fig. 20: Total NPC vs. annual wind speed for PGE 20-25 turbine
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)
25
30
36
3
11,978 / -
10
2,232 / -
2,232 / -
2,232 / -
Table 9: Percentage of reduction of total NPC for different hub heights
Annual wind speed (m/s)
25
30
36
3
460,979 / -
10
99,954/ -
99,954 / -
99.954 / -
Table 10: Percentage of reduction of COE for different hub heights
Annual wind speed (m/s)
25
30
36
3
1.248 / -
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
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.
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.
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.
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
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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SW Whisper 500 (3kW) 3 4 5 6 7 8 9 10 11 12 0 17 9 7 7 5 4 4 3 3 BWC Excel-R (7.5kW) 3 4 5 6 7 8 9 10 11 12 0 11 5 3 2 2 2 2 1 1 BWC Excel-S (10kW) 3 4 5 6 7 8 9 10 11 12 0 13 6 4 2 2 2 1 1 1 PGE 20-25 (25KW) 3 4 5 6 7 8 9 10 11 12 4 1 1 1 1 1 1 1 1 1 Fuhrlander FL 30-13 (30kW) 3 4 5 6 7 8 9 10 11 12 6 2 1 1 1 1 1 1 1 1 PGE 11-35 (35KW) 3 4 5 6 7 8 9 10 11 12 14 4 2 1 1 1 1 1 1 1 Entegrity EW15 (50kW) 3 4 5 6 7 8 9 10 11 12 0 5 1 1 1 1 1 1 1 1
Wind Speed (m/s)
No. of Turbines
SW Whisper 500 (3KW) 3 4 5 6 7 8 9 10 11 12 0 77 60 51 35 37 35 20 28 24 BWC Excel-R (7.5KW) 3 4 5 6 7 8 9 10 11 12 0 75 58 55 54 40 21 12 42 38 BWC Excel-S (10KW) 3 4 5 6 7 8 9 10 11 12 0 54 55 46 82 39 23 47 34 24 PGE 20-25 (25KW) 3 4 5 6 7 8 9 10 11 12 43 15 7 8 4 2 2 1 1 2 Fuhrlander FL30-13 (30KW) 3 4 5 6 7 8 9 10 11 12 52 58 49 18 8 5 2 0 0 0 PGE 11-35 (35KW) 3 4 5 6 7 8 9 10 11 12 55 47 46 45 16 8 5 2 0 0 Entegrity EW15 (50KW) 3 4 5 6 7 8 9 10 11 12 0 52 43 9 3 0 0 0 0 0
Wind Speed (m/s)
No. of Batteries
SW Whisper 500 (3kW) 3 4 5 6 7 8 9 10 11 12 0 4.7 4 4.7 9.6 8.5 9.1 10 10 10 BWC Excel-R (7.5kW) 3 4 5 6 7 8 9 10 11 12 0 4.5999999999999996 4 4.3 4.3 7.4 10 10 6.5 8.1 BWC Excel-S (10kW) 3 4 5 6 7 8 9 10 11 12 0 4.0999999999999996 4.0999999999999996 4.4000000000000004 5.8 6.2 10 5.4 7.2 10 PGE 20-25 (25KW) 3 4 5 6 7 8 9 10 11 12 4.3 4.7 10 10 10 10 10 10 10 10 Fuhrlander FL30-13 (30kW) 3 4 5 6 7 8 9 10 11 12 4.0999999999999996 4.2 4.2 10 10 10 10 0 0 0 PGE 11-35 (35KW) 3 4 5 6 7 8 9 10 11 12 4.0999999999999996 4.4000000000000004 4.5 5.6 10 10 10 10 0 0 Entegrity EW15 (50kW) 3 4 5 6 7 8 9 10 11 12 0 4.0999999999999996 4.7 10 10 0 0 0 0 0
Wind Speed (m/s)
Battery Lifetime (yrs)
batteries 3 4 5 6 7 8 9 10 11 12 0 75 58 55 54 40 21 12 42 38 lifetime 3 4 5 6 7 8 9 10 11 12 0 4.5999999999999996 4 4.3 4.3 7.4 10 10 6.5 8.1
Annual Wind Speed
No. of Batteries
Battery Lifetime
battery 3 4 5 6 7 8 9 10 11 12 43 15 7 8 4 2 2 1 1 2 lifetime 3 4 5 6 7 8 9 10 11 12 4.3 4.7 10 10 10 10 10 10 10 10
Annual Wind Speed
No. of Batteries
Battery Lifetime
SW Whisper 500 (3kW) 3 4 5 6 7 8 9 10 11 12 0 192715 115395 94545 89425 72095 62470 58765 52340 51060 BWC Excel-R (7.5kW) 3 4 5 6 7 8 9 10 11 12 0 334900 168240 113540 86350 81870 76885 72910 55640 54360 BWC Excel-S (10kW) 3 4 5 6 7 8 9 10 11 12 0 443430 221360 154940 102920 88065 818 50 58855 54695 51495 PGE 20-25 (25KW) 3 4 5 6 7 8 9 10 11 12 307860 96900 84655 78810 74565 72830 71735 71415 71415 72830 Fuhrlander FL30-13 (30kW) 3 4 5 6 7 8 9 10 11 12 497780 187700 106820 94710 88225 83980 80830 78000 78000 78000 PGE 11-35 (35KW) 3 4 5 6 7 8 9 10 11 12 1500740 448180 237860 131445 119975 115225 110980 107730 105000 105000 Entegrity EW15 (50kW) 3 4 5 6 7 8 9 10 11 12 0 829780 186900 170545 164245 160000 160000 160000 160000 160000
Wind Speed (m/s)
Initial Cost ($)
SW Whisper 500 (3kW) 3 4 5 6 7 8 9 10 11 12 0 9759 7117 5281 3102 2706 2278 1827 1724 1629 BWC Excel-R (7.5kW) 3 4 5 6 7 8 9 10 11 12 0 14839 8886 6595 5574 3395 2506 2279 2790 2253 BWC Excel-S (10kW) 3 4 5 6 7 8 9 10 11 12 0 18043 10547 7486 6191 3988 2830 3641 2449 1784 PGE 20-25 (25KW) 3 4 5 6 7 8 9 10 11 12 11978 4914 2661 2434 2328 2268 2256 2232 2232 2268 Fuhrlander FL30-13 (30kW) 3 4 5 6 7 8 9 10 11 12 17060 8478 5710 2750 2476 2370 2274 2203 2203 2203 PGE 11-35 (35KW) 3 4 5 6 7 8 9 10 11 12 53103 17231 10057 5839 3994 3780 3673 3578 3507 3507 Entegrity EW15 (50kW) 3 4 5 6 7 8 9 10 11 12 0 30116 8025 5566 5376 5269 5269 5269 5269 5269
Wind Speed (m/s)
O&M Cost ($/yr)
SW Whisper 500 (3kW) 3 4 5 6 7 8 9 10 11 12 0 317468 206374 162057 129076 106693 91590 82119 74385 71884 BWC Excel-R (7.5kW) 3 4 5 6 7 8 9 10 11 12 0 524593 281829 197846 157603 125275 108916 102045 91303 83157 BWC Excel-S (10kW) 3 4 5 6 7 8 9 10 11 12 0 674007 25618 1 250638 182064 139045 118027 105399 86003 74298 PGE 20-25 (25KW) 3 4 5 6 7 8 9 10 11 12 460979 159719 118666 109930 104319 101824 100579 99954 99954 101824 Fuhrlander FL30-13 (30kW) 3 4 5 6 7 8 9 10 11 12 715861 296077 179816 129868 119882 114271 109906 106165 106165 106165 PGE 11-35 (35KW) 3 4 5 6 7 8 9 10 11 12 2179569 668450 366648 206092 171034 163544 157933 153568 149827 149827 Entegrity EW15 (50kW) 3 4 5 6 7 8 9 10 11 12 0 1214763 289482 241694 232963 227353 227353 227353 227353 227353
Wind Speed (m/s)
Total NPC ($)
SW Whisper 500 (3kW) 3 4 5 6 7 8 9 10 11 12 0 0.85 0.55000000000000004 0.43 0.34200000000000003 0.28399999999999997 0.24399999999999999 0.218 0.19800000000000001 0.191 BWC Excel-R (7.5kW) 3 4 5 6 7 8 9 10 11 12 0 1.417 0.7620000000000 0001 0.53 0.42 0.33 0.29399999999999998 0.27 0.24 0.22 BWC Excel-S (10kW) 3 4 5 6 7 8 9 10 11 12 0 1.8220000000000001 0.96299999999999997 0.67 0.49199999999999999 0.3 7 0.31 0.28000000000000003 0.23300000000000001 0.20100000000000001 PGE 20-25 (25KW) 3 4 5 6 7 8 9 10 11 12 1.24 0.43 0.32 0.28999999999999998 0.28000000000000003 0.27 0.27 0.27 0.27 0.27 Fuhrlander FL30-13 (30kW) 3 4 5 6 7 8 9 10 11 12 1.9379999999999991 0.8 0.48 0.35 0.32 0.3 0.28999999999999998 0.28000000000000003 0.28000000000000003 0.28000000000000003 PGE 11-35 (35KW) 3 4 5 6 7 8 9 10 11 12 5.89 1.8 0.99 0.55000000000000004 0.46 0.44 0.42 0.41 0.4 0.4 Entegrity EW15 (50kW) 3 4 5 6 7 8 9 10 11 12 0 3.28 0.78 0.65 0.63 0.61 0.61 0.61 0.61 0.61
Wind Speed (m/s)
COE($/kWh)
No. Turbine 3 4 5 6 7 8 9 10 11 12 4 1 1 1 1 1 1 1 1 1 No. Batteries 3 4 5 6 7 8 9 10 11 12 43 15 7 8 4 2 2 1 1 2 Battery Lifetime 3 4 5 6 7 8 9 10 11 12 4.3 4.7 10 10 10 10 10 10 10 10 COE 3 4 5 6 7 8 9 10 11 12 1.248 0.432 0.32100000000000001 0.29699999999999999 0.28199999999999997 0.27600000000000002 0.27200000000000002 0.27 0.27 0.27600000000000002
Wind Speed (m/s)
Number
kWh/$
H = 25 3 4 5 6 7 8 9 10 11 12 wind 3 4 5 6 7 8 9 10 11 12 4 1 1 1 1 1 1 1 1 1 H = 30 3 4 5 6 7 8 9 10 11 12 wind 3 4 5 6 7 8 9 10 11 12 3 1 1 1 1 1 1 1 1 1 H = 36 3 4 5 6 7 8 9 10 11 12 wind 3 4 5 6 7 8 9 10 11 12 3 1 1 1 1 1 1 1 1 1
Wind Speed (m/s)
No. of Turbines
H = 25 3 4 5 6 7 8 9 10 11 12 46 43 15 7 4 3 2 1 1 2 H = 30 3 4 5 6 7 8 9 10 11 12 52 43 10 6 4 2 2 1 1 2 H = 36 3 4 5 6 7 8 9 10 11 12 44 38 10 6 3 2 1 1 2 2
Wind Speed (m/s)
No. of Batteries
H = 25 3 4 5 6 7 8 9 10 11 12 4.3 4.7 10 10 10 10 10 10 10 10 H = 30 3 4 5 6 7 8 9 10 11 12 4.0999999999999996 5.8 10 10 10 10 10 10 10 10 H = 36 3 4 5 6 7 8 9 10 11 12 4.5 6.4 10 10 10 10 10 10 10 10
Wind Speed (m/s)
Battery Lifetime (yrs)
H = 25 3 4 5 6 7 8 9 10 11 12 307860 96900 84655 78810 74565 72830 71735 71415 71415 72830 H = 30 3 4 5 6 7 8 9 10 11 12 239780 95805 81960 77395 74565 72830 71415 71415 71415 72830 H = 36 3 4 5 6 7 8 9 10 11 12 237220 94205 81960 77395 74245 72830 71415 71415 71735 72830
Wind Speed (m/s)
Initial Cost ($)
H = 25 3 4 5 6 7 8 9 10 11 12 11978 4914 2661 2434 2328 2268 2256 2232 2232 2268 H = 30 3 4 5 6 7 8 9 10 11 12 10396 4371 2529 2399 2328 2268 2232 2232 2232 226 8 H = 36 3 4 5 6 7 8 9 10 11 12 9492 3920 2529 2399 2304 2268 2232 2232 0 2268
Wind Speed (m/s)
O$M Cost ($/yr)
H = 25 3 4 5 6 7 8 9 10 11 12 460979 159719 118666 109930 104319 101824 100579 99954 99954 101824 H = 30 3 4 5 6 7 8 9 10 11 12 372672 151675 114295 108060 104319 101824 99954 99954 99954 101824 H = 36 3 4 5 6 7 8 9 10 11 12 358555 144313 114295 108060 103694 101824 99954 99954 100579 101824
Wind Speed (m/s)
Total NPC ($)
H = 25 3 4 5 6 7 7 9 10 11 12 1.248 0.432 0.32100000000000001 0.29699999999999999 0.28199999999999997 0.27600000000000002 0.27200000000000002 0.27 0.27 0.27600000000000002 H = 30 3 4 5 6 7 7 9 10 11 12 1.0089999999999999 0.41 0.309 0.29199999999999998 0.28199999999999997 0.27600000000000002 0.27 0.27 0.27 0.27600000000000002 H = 36 3 4 5 6 7 7 9 10 11 12 0.97099999999999997 0.39100000000000001 0.309 0.29199999999999998 0.28100000000000003 0.27600000000000002 0.27 0.27 0.27200000000000002 0.27600000000000002
Wind Speed (m/s)
Wind Turbine Type
No. of Turbines
No. of batteries
Wind Turbine Type
No. of Batteries
Wind Turbine Type
Battery Lifetime (yrs)
Wind Turbine Type
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