A practical seasonal performance evaluation of small wind turbine in urban environment

Abstract

Due to the low environmental impact, smaller storage units, low wind speed, low power system distribution network impact, and low maintenance, small wind turbines have gained more attention. However, the usage of small turbines usually faces several shortcomings, and the actual yield is often lower than expected, generally because the output power is low when compared with the manufacturer, and the actual wind turbine behavior does not reproduces. In a view of performance evaluation of a small wind turbines using high-accuracy measurement devices to measure wind speed and energy production, this article illustrates an experimental seasonal performance evaluation of a 0.5-kW Hummer small wind turbine, placed in an urban environment. In addition, we study the influence of the height in the energy output and analyze its effect in the system performance, which is another aim in this work. Three cases have been carried out: 4 m in order to protect rotor blades during strong winds and storms in the first scenario and 6 m the manufacturing height in the second scenario while 10 m the third case. A 0.5-kW Hummer wind turbine has been installed in Noagia-Benghazi since 2010 for educational purposes, field studies, training, graduate projects, and research. The wind turbine seasonal performance under different periods was obtained and compared in terms of the wind speed, output power, energy production, and average wind speed. The average wind speed is 6.4, 4, 5.8, and 4 m/s, and the average energy production is 948.24, 172.8, 648, and 172.8 kWh in spring, summer, winter, and autumn, respectively. Spring has the highest wind speed followed by winter and autumn then summer for all height. Improvement is attained if the wind turbine tower height is 6 m, and 10 m where more energy is harvested. But the main problem at 10 m is that the system control needs more improvement because the wind speed exceeds 14 m/s which represents the maximum speed. The system can produce about 1.942 MW yearly and save CO₂ emissions.

Keywords

Renewable energy small wind turbines performance evaluation power curve energy production

Introduction

Due to economic encouragements, sustainability, environmental issue, global warming awareness, and low CO₂ emissions, renewable energy has gathered a great deal of attention in the past few years. Wind energy represents the most promising source of renewable energy in the world. Wind turbines are devices that harvest energy from the wind and convert the kinetic energy in the wind into mechanical energy and finally into electricity. The history of wind turbines indicates that the first practical wind mill was developed in 7th century in Iran and was used for producing electricity and pumping water as a standalone system. In 1951, the first utility grid–connected wind turbine was built. By the end of 2014, the total capacity of wind power was around 369.6 GW and is 600 GW by the end of 2018 and is expected to reach 666.1 GW by the end of 2019 (Tummala et al., 2016).

Small wind turbines are used to provide the required clean energy to small loads located in remote areas such as communication tower sites, monitoring station, private houses, and they also may be used for water pumping in areas that encounter frequent power outages (Aldricy et al., 2018; Sassi et al., 2019; Tahir et al., 2017a). Wind turbines are manufactured in a wide range of horizontal and vertical axis. Many papers focus on the construction of a small wind turbine system. The main components of wind turbines are the blades that capture wind and help the turbine rotate; a gear box that allows the wind turbine shaft to be coupled to the generator shaft; a generator that converts the mechanical power to electrical power; a controller which is the brain of the system, and a tower that supports the whole system and resists vibration due to variations in wind speed (Aldricy et al., 2018; Sassi et al., 2019). In wind energy resource assessment for urban application in Singapore, three sites are chosen as a case study, where long-term wind measurements were taken (Karthikeya et al., 2016). The maximum wind power density at the three sites are 45, 35, and 15 W/m², respectively, and the turbulence intensities as the wind speed approaches 15 m/s are 0.25 at Site 1 and 0.15 at Site 3. It is observed that the turbulence intensity decreases with increasing wind speeds.

The aim of this study is to assess the performance of a micro wind turbine in low average wind speed regions. Many authors emphasis on the performance evaluation of small wind turbines, for example, Sassi et al. (2019) tested a 0.5 kWp Hummer horizontal-axis wind turbine for different wind speeds. The average wind speed was 4 m/s, the wind power, output power, power coefficient, and tip-speed ratio (TSR) values were 28.672 W, 104.871, 0.376, and 3.391, respectively. The annual average energy produced is 644 kWh, and the total CO₂ emissions saving equals 0.558 ton/year at the speed of 4 m/s. The energy output and the plant capacity factor for a small wind turbine in the classification of 1–3 kW, 5–10 kW, 15–20 kW, and 50–80 kW-rated powers are investigated in Al-Hadhrami (2014). In addition to the effect of hub height, energy output is tested and examined by conducting measurements at 10, 20, 30, and 40 m and wind direction at 30 and 40 m above ground level for vertical- and horizontal-axis wind turbines. Ozgener (2006) presents the energy analysis of the 1.5 kW small wind turbine system with a hub height of 12 m above sea level with a 3 m rotor diameter in Turkey. The results show that when the average wind speed is 7.5 m/s, the output power produced is 616 W. Bilir et al. (2015) evaluated the performances of three different small-scale wind turbines in the Incek region of Ankara. These turbines were selected due to their low cut-in and rated wind speed values. According to the manufacturers, the hub heights of the selected wind turbines were also determined. According to the results, the generated energy from these turbines is 3.74, 3.5, and 1.878 kWh. In addition, it is found that the energy consumed in the household of Turkey is 2330 (kWh) yearly in 2012. Therefore, it was concluded that the first two wind turbines can supply the entire energy need of an average household in the region. The performance of small wind turbines was carried out in Sharjah city by Zafar et al. (2016). The study is centered on the small wind turbine design that has a blade span of 1.52 m. The output power of the turbine at wind speed 4 m/s was 85 W and the power coefficient is 0.48 at the same speed.

Wind turbines are classified based on their axis of rotation into horizontal-axis wind turbine and vertical-axis wind turbine and according to their capacity into small wind turbines which start from Watts to 5 kW; medium wind turbines: 5 kW to 5 MW; large wind turbines: 5–50 MW. Large wind turbines are of megawatt power, medium-size wind turbines are between 20 and 300 kW, and the output power rating of small wind turbines is less than 20 kW. These turbines are designed for low cut-in wind speeds (generally 3–4 m/s) (Sassi et al., 2019). As mentioned above, small wind turbines are suitable for remote areas, however storage units are necessary. In addition to the provision of maximum power point tracking which is essential to harvest as much energy as possible, numerous papers have focused on the aerodynamic design of wind turbines to optimize the output energy. Tahir et al. (2019) have compared experimental and simulation study on minimizing the cut-in speed and maximizing the mechanical power for a small wind turbine using the blade element momentum (BEM) analysis. It is also observed that at same wind speeds, the optimized blade has length of about 1.35 m, which is significantly less than the length of the old blade (1.5 m), the power generated is more than the power generated by the old blades. This means that improvement in turbine blades can improve the performance. Akour et al. (2018) selected and used three different airfoils (BW3, A18, and SG6043) as candidates for small wind turbine blade design. In addition, they compared the design experimentally and theoretically with the existing commercial wind turbines according to cost and output power. The results illustrate that the new design is more cost-effective and can produce more wind energy.

It was seen in the literature that some studies show that wind speed differs at different heights in different cities of Libya. For example Khalil and Asheibi (2015) illustrate the average wind speed at different coastline cities in Libya. In addition, the average wind speed at three different heights (10, 50, and 100 m) fluctuate between 9–10 m/s, 6.4–9 m/s, and 5–7 m/s, respectively. The average wind speed in the Benghazi region is between 6–6.4 m/s, these values are deemed suitable for onsite wind turbines (Sassi et al., 2019). The faster the wind speed, the more the energy is captured by the wind turbine. A performance evaluation of a 1.65-MW wind turbine in Darnah Libya was reported by Rajab et al. (2017), the system is modeled in Matlab/Simulink and validated using ATP Software. Two scenarios are conducted in order to study the system performance under fixed-speed and variable-speed mode. In addition, the study depicted the average wind speed for different cities in Libya. The average wind speed in Libya is roughly between 6 and 7.5 m/s at 40 m height.

In this article, the performance of a seasonal small wind turbine is evaluated and assessed experimentally on the site. The details regarding wind turbine structure with component specifications and functions are described in the next sections followed by case study, system analysis, and monitoring in different season. Finally, conclusion remarks are illustrated.

Analysis

The kinetic energy of wind is converted into mechanical energy by wind turbines. In order to efficiently capture wind, several key parameters need to be considered: air density (ρ) kg/m³, area of the blades, wind speed (υ) m/s, and rotor area (A) m². The force of the wind is stronger at higher air densities. Wind force generates torque, which causes the blades of the turbine to rotate. Therefore, the kinetic energy of the wind depends on air density; therefore, heavier (denser) winds carry more kinetic energy. The longer the blade, the bigger the rotor area of the wind turbine, and therefore, more wind can be captured under the same conditions. The other parameter is the wind speed. It is expected that wind kinetic energy increases as wind speed increases (Sassi et al., 2019).

The kinetic energy of the wind can be expressed as

E_{k} = 0.5 m υ^{2} = 0.5 ρ V υ^{2} = 0.5 ρ A d υ^{2}

(1)

where E_k is the wind kinetic energy, m is the wind mass, υ is the wind speed, ρ is the air density (1.225 kg/m³ at sea level), A = πR² is the rotor area, R is the blade length, and d is the thickness of the “air disc.” Therefore, the overall power of wind P = E_k/t.

The power content of the wind varies with the cube (the third power) of the average wind speed as illustrated in equation (2)

P_{i n} = 0.5 ρ A υ^{3}

(2)

Wind speed is one of the most important parameters to determine the available output power of wind turbines. Therefore, it is important to accurately monitor and measure it. The mechanical power produced by the wind turbine can be expressed as

P_{m e c h} = ω T

(3)

where T is the torque produced by the wind turbine blades in (Nm) and ω is the rotational speed in (rad/s).

Wind turbine system cannot extract all the wind power; therefore, there is a limit to how much can be extracted. The maximum power extracted by wind turbine is calculated by Betz limit that only 59% of the power extraction is possible (Wenehenubuna et al., 2015). Therefore, equation (1) can be rewritten to show the presence of efficiency

P_{m} = 0.5 ρ A C_{p} v_{w}^{3}

(4)

The power coefficient C_p represents the conversion efficiency of the turbine. If the pitch angle β = 0 as in this case, C_p is a function of the tip speed, λ, of the turbine. The efficiency of a wind turbine is usually characterized by its power coefficient as given below

C_{p} = \frac{V . I}{0.5 ρ A υ^{3}}

(5)

The electrical power produced can be determined by the following equation

P_{e l e} = V . I

(6)

In this article, the electrical equipment and mechanical equipment losses are neglected. The power coefficient represents the conversion efficiency of the turbine. If the pitch angle β = 0 as in this case, therefore, C_p is a function of the tip speed, λ, where λ is given by

λ = \frac{ω R}{υ}

(7)

where ω is the rotational speed (rad/s), and R is the radius of the blades.

Any measured wind speed value can be estimated for different heights using the following equation (Sassi et al., 2019; Wenehenubuna et al., 2015)

υ = υ_{0} [\frac{H}{H_{0}}]

(8)

where υ₀ is the original wind speed associated with the terrain height of H₀ and υ is the reduced wind speed at a terrain height of H.

Wind turbine component

The system consists of different parts: blades, tower, generator, yaw shaft, tail pole and tail wing, and inverter. The specification of wind turbine components are as follows:

Blades

The blades are the most important part of the wind turbine, as it directly contacts wind. The main function of the blades is to capture the wind kinetic energy and then convert the motion to the shaft rotation to electrical power through permanent magnet generator. The blade diameter is 2.7 m and is manufactured from PVC material. Another material is used in literature, for example, Zafar et al. (2016) used glass-reinforced plastic (GRP) blades which are ease of manufacturing, cost-efficient, light weight, and strengthen the blades.

Generator

According to manufacturer, the Hummer wind generator permanent magnetic generator (PMG) is used to convert rotor rotational power to electrical power. Many researchers reported that for small wind turbine, PMG is desirable because the generator is light weight, available, small dimensions, low in noise, swift in startup, quick in heat dissipation, and high in efficiency (Khalil et al., 2016; Zafar et al., 2016). In addition, the types of generator that can be connected to wind turbines and the advantages and disadvantages are presented by Tahir et al. (2017b).

Off-grid inverter

As a multi-function controller, the Hummer inverter is manufactured for a 0.5-kW wind turbine system. This inverter adopts sinusoidal pulse width modulation (SPWM) technology. It is able to convert DC with higher efficiency into AC with stable frequency, voltage, and filtering the noise as well. The controller regulates the process in which the AC produced by wind turbine is converted into DC and then charges the battery bank with DC. It also controls the switching on and off of dump load to protect the system from the overload risk because of too much power (Sassi et al., 2019).

Tower

The main purpose of the tower is to support the nacelle and resist vibration due to the wind speed variations. The wind turbine location and height are the main factors for system efficiency. The wind flow over the earth surface is effected by obstacles and topographic variations, which cause wind speed to decrease near the earth and for turbulence to increase, both of which decrease as the tower height increases. In this study, the tower height is 4 m to prevent damage to the whole system.

Rotor system

Classifying the wind turbines depending on this system, the system consist of three GRP blades with 2.7-m diameter. Its main purpose is to convert the wind kinetic energy into usable energy.

Tail

There is no doubt that the tail in small wind turbines keeps the rotor aligned into the wind, except the case that the wind speed exceeds its limits. In this case, the system turns the rotor sideways to the wind to limit the rotor speed in high winds, but the turbine continues producing power or may be stopped in case of very high speed.

Storage system

The small wind turbines output power rating is less than 20 kW. One of the available usages of these turbines is for remote applications, where the grid is far away and the electricity transmission line is difficult to reach. Therefore, these turbines are equipped with storage system.

System parameter

Table 1 illustrates the specific parameter of the wind turbine. To begin first with average output power which is 500 W, while the maximum output power is 1000 W which is reported at about 14 m/s wind speed.

Table 1.

Parameters of the wind turbine.

Parameter	Value
Rated power	500 W
Max power	1000 W
Charging voltage	24 V
Blade quantity	3 PCS
Blade material	GRP
Blade diameter	2.7 m
Startup wind speed	3 m/s
Rated wind speed	7 m/s
Rated rotating speed	600 r/min
Utilizing ratio (Cp)	0.48
Output frequency	0–300 Hz
Rated charging current	15 A
Max charging current	25 A
Generator efficiency	0.78
Suggested battery size	120 Ah/150 Ah

GRP: glass-reinforced plastic.

Case study: Noagia Solar Radiation Center

The horizontal axis wind turbine system was constructed at Noagia Solar Radiation Center in Benghazi city in the eastern part of Libya. The geographic coordinates for Benghazi: (32.11°N latitude and 20°.07 .00” E longitudes). The location is 3 m above sea level. A test center was constructed to study the different clean energy sources in the city. An aerial view of the center is shown in Figure 1. The field study results start from (2010–2018) and shows that the prevailing wind direction was North East. And the average wind speed about 5.3 m/s.

Figure 1.

Aerial view of the Noagia Solar Radiation Center in Benghazi city.

Experimental work

Experimental work is conducted to evaluate the onsite small horizontal-axis wind turbines. The turbine is installed and tested at 4-m height as illustrated in Figure 2. The turbine is designed to produce 500 W at average wind speed 7 m/s. The minimum wind speed needed to start the turbine rotor to rotate (cut-in speed) is approximately 3 m/s. Wind speed changes with time and space. To evaluate the wind turbine output and energy potential for the proposed site, the collected wind data should be analyzed. In this work, the daily and seasonal average wind speeds have been measured and monitored, and the results are depicted in the following sections.

Figure 2.

On field 0.5-kW Hummer wind turbine.

The system is equipped with a charge controller, battery, inverter, and measurement devices. The batteries begin charging at a slightly higher than cut-in speed. Depending on the batteries state of charge, when the battery is fully charged, the charge controller disconnects the turbine from the battery. The turbine produces a single phase alternating current (AC) that varies in voltage and frequency as the wind speed varies. The controller rectifies this AC into the direct current (DC) required for battery charging and controls the energy supplied to the batteries to avoid overcharging. The measurement devices shows the system status data like voltages (V), currents (I), frequency (F), charging current, state of charge, wind speed etc. the measurement devices are shown in Figure 3.

Figure 3.

Controller with dump load control and measurement device V, I, and frequency display.

Experimental results

Wind turbines have a potential impact on climatic conditions, so the performance evaluation is completed by measuring and calculating various parameters and comparing it with manufacturing data. Therefore, first of all starting with the manufacturing data as reference, Figure 4 reveals the relationship between wind turbine power and wind speed from the manufacturing data. The most remarkable trend is that with the increase in wind speed, the power also increases until wind speed reaches 14 m/s. At this speed, the power output is maximized. When the wind speed is higher than 14 m/s, the output power decreases. The turbine should be stopped when the speed reached 20 m/s. To test the wind turbine performance, different field tests have been carried out. Wind speed, power generation, power coefficient, and TSR are the main considered parameters. These values are measured, monitored, calculated, and stored using digital meters for different period of time. In addition, the average values of wind for each period are stored. At 14 m/s wind speed, the output power is 989 W, while the input power, power coefficient and TSR values are 9604 W, 0.1, and 12.52, respectively. In addition, it showed good performance and TSR at average speed, which are 0.41 and 12.11, respectively. The relationship between wind speed and output power and power coefficient are illustrated in Figures 4 and 5. The power coefficient C_p depends on the specific design of the wind turbine (especially the particular aerodynamic structure of the blades).

Figure 4.

Power–wind speed characteristic.

Figure 5.

Relationship between power coefficient and wind speed.

According to the RETScreen Expert, Clean Energy Management Software and the study made by Rajab et al. (2017) showed that the average yearly wind speed is 5.3 m/s at 4 m height.

The data used herein were chosen between numerous years period starting from 2010 to 2019 to illustrate the monthly and daily average wind speed. The daily measurements are very useful especially in the standalone system. The wind data are measured at 4 m heights above ground level. In addition, the data are analyzed and calculated at 6 m and 10 m. The results showed that the annual average wind speed is 5.32, 5.62, and 6.10 for 4, 6, and 10 m. The monthly average wind speed at 4, 6, and 10 m are shown in Figure 6.

Figure 6.

Comparison of average wind speed at different heights.

Seasonal and daily sample of wind speed at 4 m height

The daily and seasonal wind speed variations at 4 m height are considered in this study. As it could be noticed that from the tests, the highest wind speeds, for all months, at the same height are in February, March, and April (i.e., in spring season) followed by February, December, and January, then May and June. The lowest value is in June and July (summer season). The average wind speed in March is 6.6 m/s, whereas in December is 6.4 m/s, and 4.3 and 3.9 m/s in October and July, respectively.

Spring season (11th March sample) at 4 m height

According to Figure 7, the wind speed varies between 4 and 10 m/s. The output power varies between 80 and 760 W. The average speed was 6.4 m/s, and the average output power output is 439 W. The maximum power is at a wind speed of 10 m/s.

Figure 7.

Wind speed.

Figures 8 and 9 show the diurnal variation of wind speed with output power and power coefficient, respectively, at 4 m. As it can be noticed from these figures that there is a variation in the diurnal samples of wind speed between cut-in speed and 10 m/s as the maximum speed. Therefore, the maximum output power is about 750 W, and the maximum power coefficient C_p is 0.5 at 6 m/s wind speed. At various wind speeds, the TSR varied from 3.2 to 12.5.

Figure 8.

Wind speed characteristic.

Figure 9.

Power coefficient characteristic.

Summer season (15th July sample) at 4 m height

According to Figures 10 and 11, the wind speed varies between 2.7 and 5.3 m/s, and the output power varies between 9.3 and 245 W. The average speed was 4 m/s, and the average output power is 80 W. The maximum power is at 5.3 m/s in this test.

Figure 10.

Wind speed.

Figure 11.

Wind speed characteristic.

Figures 11 and 12 show the diurnal variation of wind speed with output power and power coefficient, respectively, at 4 m height in summer season. As it can be noticed from these figures that there is a variation in the diurnal samples of wind speed between cut-in speed and 5.3 m/s as the maximum speed. In this test, the maximum out power is about 245 W, and the maximum power coefficient C_p is 0.477 at 5.3 m/s wind speed. At various wind speeds, the TSR varied from 1.50 to 6.78.

Figure 12.

Power coefficient characteristic.

Winter season (10th December sample) at 4 m height

According to Figures 13 and 14, the wind speed varies between 4.5 and 7 m/s, and the output power varies between 125 and 495 W. The average speed was 5.8 m/s, and the average output power is around 300 W. The maximum power is 495 W at 7 m/s in this test.

Figure 13.

Wind speed.

Figure 14.

Wind speed characteristic.

Figure 15 shows the diurnal variation of wind speed with output power and power coefficient respectively at 4 m height in winter season. As it can be noticed from these figures that there is a variation in the diurnal samples of wind speed between cut-in speed and 7 m/s as the maximum speed. In this test, the maximum out power is about 245 W, and the maximum power coefficient C_p is 0.51 at 5.5 m/s wind speed. At various wind speeds, the TSR varied from 4.1 to 12.1.

Figure 15.

Power coefficient characteristic.

Autumn season (10th October sample) at 4 m height

According to Figures 16 and 17, the wind speed varies between 4 and 5 m/s, and the output power varies between 80 and 198 W. The average speed was 4 m/s, and the average output power output is 80 W. The maximum power is at 5 m/s in this test. Figures 17 and 18 show the diurnal variation of wind speed with output power and power coefficient, respectively, at 4 m height in autumn season sample. As it can be noticed from these figures that there is a variation in the diurnal samples of wind speed between cut-in speed and 5 m/s as the maximum speed. In this test, the maximum out power is about 198 W, and the maximum power coefficient C_p is 0.45 at 5 m/s wind speed. At various wind speeds, the TSR varied from 3.3 to 6.4.

Figure 16.

Wind speed.

Figure 17.

Wind speed characteristic.

Figure 18.

Power coefficient characteristic.

Extrapolation of wind speed with height

The wind speed velocity depends on the natural and the terrain properties of the site. The wind speed is increased with height until a certain height. In the study, herein three different heights are chosen: 4 m as the existing in the field, 6 m which is the manufacturing height, and 10 m as a new height. Figures 19 to 22 show the wind speed at different heights for the four tests above. As it could be noticed that the highest wind speeds, for all seasons, are at 10 m height (Figure 23). Spring has the highest wind speed followed by winter and autumn then summer. In addition, the average wind speed for the four seasons is shown in Figure 24. The average wind speed is one of the main factors that characterize the property of the site. The highest average wind speed is spring followed by winter and autumn then summer. The average wind speed is 6.4, 4, 5.8, and 4 m/s and the average energy production is 948.24, 172.8, 648, and 172.8 kWh in spring, summer, winter, and autumn, respectively.

Figure 19.

Relationship between wind speed and time in spring sample.

Figure 20.

Relationship between wind speed and time in winter sample.

Figure 21.

Relationship between wind speed and time in autumn sample.

Figure 22.

Relationship between wind speed and time in summer sample.

Figure 23.

Seasonal samples for the average wind speed.

Figure 24.

Average wind speed for the sampling seasons.

Conclusion

In this article, a seasonal performance evaluation of a 0.5-kW Hummer small wind turbine, placed in an urban environment is studied. In addition, we study the height effect in the wind speed and analyze its influence in the system performance, which is another aim in this work. Three cases have been carried out: 4 m in order to protect rotor blades during strong winds and storms in the first scenario and 6 m the manufacturing height in the second scenario while 10 m the third case. The wind turbine has been installed since 2010 for data recording, educational purposes, field studies, training, graduate projects, and research. The wind turbine seasonal performance was obtained and compared in terms of the wind speed, output power, energy production, average wind speed. At 4 m height, the average wind speed is 6.4, 4, 5.8, and 4 m/s and the average energy production is 948.24, 172.8, 648, and 172.8 kWh in spring, summer, winter, and autumn, respectively. Spring has the highest wind speed followed by winter and autumn then summer for all height. Improvement is attained if the wind turbine tower height is 6 m, and 10 m where more energy is harvested. But the main problem at 10 m is that the system control needs more improvement because the wind speed exceeds 14 m/s, which represents the maximum speed. The system can produce about 1.942 MW yearly and save CO₂ emissions.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Akour

Al-Heymari

Ahmed

et al . (2018) Experimental and theoretical investigation of micro wind turbine for low wind speed regions. Renewable Energy 116: 215–223.

Al-Hadhrami

(2014) Performance evaluation of small wind turbines for off grid applications in Saudi Arabia. Energy Conversion and Management 81: 19–29.

Aldricy

Ragab

Rajab

et al . (2018) Practical design and performance evaluation of micro-wind turbine in Libya. In: 2018 9th international renewable energy congress (IREC), Hammamet, Tunisia, 20–22 March, pp. 1–6. New York: IEEE.

Bilir

Imir

Devrim

et al . (2015) An investigation on wind energy potential and small scale wind turbine performance at Incek region Ankara, Turkey. Energy Conversion and Management 103: 910–923.

Karthikeya

Negi

Srikanth

(2016) Wind resource assessment for urban renewable energy application in Singapore. Renewable Energy 87: 403–414.

Khalil

Alfaitori

Asheibi

(2016) Modeling and control of PV/wind microgrid. In: The 8th international renewable energy congress, Hammamet, Tunisia, 22–24 March, pp. 1–6. New York: IEEE.

Khalil

Asheibi

(2015) The chances and challenges for renewable energy in Libya. In: 4th international conference on renewable energy research and applications, Palermo, 22–25 November.

Ozgener

(2006) A small wind turbine system (SWTS) application and its performance analysis. Energy Conversion and Management 47: 1326–1337.

Rajab

Almaktar

Al-Naily

et al . (2017) Modeling approach to evaluate wind turbine performance: case study for a single wind turbine of 1.65 MW in Dernah, Libya. In: The 8th international renewable energy congress, Amman, Jordan, 21–23 March, pp. 1–6. New York: IEEE.

10.

Sassi

Rajab

Tahir

et al . (2019) On-site 0.5–1KW Hummer wind turbine performance test. In: 2019, 10th international renewable energy congress (IREC), Sussa, Tunisia, 20–22 March, pp. 1–6. New York: IEEE.

11.

Tahir

Elgabaili

Rajab

et al . (2019) Optimization of small wind turbine blades using improved blade element momentum theory. Wind Engineering 43: 299–310.

12.

Tahir

Rajab

Ahmed

et al . (2017a) Genetic algorithm–based calculation of the excitation capacitance of a self-excited induction generator for stable voltage operation over load and speed variations. Wind Engineering 41: 421–430.

13.

Tahir

Rajab

Hammoda

et al . (2017b) Evaluating the value of the excitation capacitance of a wind turbine/induction generator system using genetic algorithms. In: The 8th international renewable energy congress, Amman, Jordan, 21–23 March, pp. 1–6. New York: IEEE.

14.

Tummala

Velamati

Sinha

et al . (2016) A review on small scale wind turbines. Renewable and Sustainable Energy Reviews 56: 1351–1371.

15.

Wenehenubuna

Saputra

Sutantoa

(2015) An experimental study on the performance of Savonius wind turbines related with the number of blades. Energy Procedia 68: 297–304.

16.

Zafar

Gadalla

Al-Naiser

(2016) Performance evaluation of a novel small wind turbine: UAE case study. In: Power conference POWER2016, Charlotte, NC, 26–30 June.