International Journal of Energetica (IJECA)
https://www.ijeca.info
ISSN: 2543-3717 Volume 8. Issue 1. 2023 Page 01-11
This open access article is licensed under the CC BY-NC license (https://creativecommons.org/licenses/by-nc/4.0/) Page 1
Predictive Study on the Application of the Soweto Wind Turbine
Results in the Coastal Region of South Africa
T. Sithole
1*
, V.R. Veeredhi
2
, T.Sithebe
2
1
Department of Electrical Engineering, University of South Africa, SOUTH AFRICA
2
Department of Mechanical Engineering, University of South Africa, SOUTH AFRICA
*Corresponding author E-mail: sitholetshepo7@gmail.com
Abstract – This study evaluates the performance of three wind turbine prototypes
(Prototypes 1, 2, and 3) in Soweto, South Africa, by analyzing their monthly energy
generation under different time of day/month conditions. Prototype 3 emerges as the
most efficient, generating 39.5 W at a wind speed of 1.17 m/s and projecting a
maximum of 40 kWh per month. Building upon these results, a predictive study
examines the feasibility of implementing the same technology in coastal regions,
specifically Gqeberha, where stronger winds prevail. Utilizing empirical data from
Soweto, the study forecasts an improved energy output of up to 54.3 W at a wind speed
of 5.16 m/s (18.6 km/h) and up to 100 kWh per month. The findings highlight the
potential benefits of utilizing wind turbine technology in coastal areas, contributing
valuable insights to renewable energy system development in similar geographical
contexts.
Keywords: Predictive study, Coastal regions, Soweto, Port elizabeth result.
Received: 10/02/2023 – Revised: 11/03/2023 – Accepted: 03/04/2023
I. Introduction
In the past, South Africa heavily relied on electricity
generated from fossil fuels like oil and coal, which has
limited the country's overall electricity supply. However,
South Africa possesses abundant solar resources, with an
average of 2,500 hours of sunshine per year and radiation
levels ranging from 4.5 to 6.6 kWh/m
2
. This places South
Africa among the top three countries in the world in
terms of solar potential. Additionally, the country has a
significant wind power potential, estimated at 67,000
GW, which proves to be competitive alongside its solar
potential [1].
Wind energy is a viable source of power in regions with
consistent and strong winds. South Africa's climate offers
favorable conditions for substantial wind energy
production, particularly in the coastal regions of the
Eastern and Western Capes. In 2014, the first major wind
farm in South Africa began operating, marking a
significant milestone in the country's wind energy sector.
According to the South African Wind Energy
Association (SAWEA) report, there are currently 33
wind farms in the country, with 22 fully operational and
11 under construction [2].
Amidst the increasing global demands for
decarbonization and sustainability, South Africa has
embraced the proliferation of wind energy. This support
stems from the recognition of the risks posed by climate
change to various resources in the country, including
water security, agriculture, and shorelines. The growing
renewable power sector not only addresses these
challenges but also reduces the country's reliance on coal,
aligning with international policies and lowering the
demands for coal-related ventures. The impact of wind
energy spill-overs is particularly evident in the Eastern
Cape province, which has secured 51% of South Africa's
wind farm allotments, benefiting the impoverished
region. Furthermore, major banks have become hesitant
to provide financial support for coal-related projects,
https://www.ijeca.info/
https://creativecommons.org/licenses/by-nc/4.0/
T. Sithole et al. / International Journal of Energetica (IJECA) Vol. 8, N°1, 2023, pp. 01-11
Page 2
indicating a shift in capital spending towards the
development of high-tech wind turbines on wind farms
[3-8]. Moreover, the use of fossil fuels in the
generation of electricity contributes significantly to
Greenhouse Gas (GHG) emissions, which further
contributes to climate change [9, 10].
According to [11], utilizing renewable energy as an
alternative energy source will help reduce
environmental problems, essentially GHG emissions
and air pollution.
In this article, presentation will be done on results of the
7 rotor-blade prototype (Design-3) wind turbine that was
optimally designed and eventually implemented and
tested in residential area in Soweto, Johannesburg, South
Africa. A predictive study will be done using the Design
3 results to predict the possible implementation of the
same technology in the high gust area of South Africa.
II. Selection of Appropriate Hardware and
Implementation
In this section, the selection and implementation of the
required hardware will be discussed. The following
hardware components were selected: AC-DC inverter,
anemometer, storage batteries, rotor coupling hub, three-
phase AC permanent magnet generator, battery regulator/
charge controller, AC cabling and monitoring devices. .
II.1. Windy Boy Vertiv Inverter
A Windy boy inverter as in Figure 1, has 93% to 95%
efficiency [12], and the cost of this electronic device is
approximately R800.00. It has the ability to protect itself
from spikes, surges and over voltages. It can be used for
both off-grid and grid tied applications.
Figure. 1. Windy Boy Vertiv Inverter [12]
II.2. UT363-B Anemometer
This instrument was acquired to measure wind and
temperature for the applications at the test household in
Soweto. The UT363-BT Mini Anemometer is a mini
wind speed and temperature tester. This lightweight
device is equipped with the latest magnetic sensing
technology, and directly displays the airflow speed on an
LCD screen. Bluetooth function can be added for data
transfer and analysis by means of the iENV cell phone
App; this can be downloaded from Google Play or Apple
Store. The UT363-BT Mini Anemometer was taken for
calibration at a South African National Accreditation
System (SANAS) accredited laboratory and this
calibration cost approximately R550.00. Figure 2 shows
a UT363-BT Anemometer.
Figure. 2. UT363 Wind Anemometer
II.3. Storage Batteries
Storage of power is an important factor in wind turbine
use. These battery store the generated energy of the
turbine, and then the stored energy is sent through an
electronic regulator to the inverter for output supply.
Figure 3, illustrates two 12V 100A/h VRLA batteries
coupled in series, which suited system implementation.
Each battery cost approximately R850,00. The batteries
can be connected in series or parallel depending on the
wind turbine charge controller specification.
Figure. 3. 2x 12V 100 Ah VRLA Batteries coupled to the Soweto SWT
T. Sithole et al. / International Journal of Energetica (IJECA) Vol. 8, N°1, 2023, pp. 01-11
Page 3
II.4. Rotor Coupling hub used for the Soweto project
A rotor hub was purchased from a Chinese supplier and
this was used to couple the wind turbine blade to the
generator shaft. The rotor hub is the component that
usually holds the blades and connects them to the main
shaft of the wind machine. It is a key component not only
because it holds the blades in their proper position for
maximum aerodynamic efficiency, it also rotates to drive
the generator. Hubs come in many different shapes and
configurations, mostly dependent on the type of
generator used and the design of the rotor blades as
shown in Figure 4.
Figure. 4. 7-Blade wind turbine blade hub used for Soweto Project
II.5. Three Phase AC Permanent Generator
In terms of the generators for wind-power
application, there are different concepts in use today.
The major distinction among them is made between
fixed speed and variable speed wind turbine
generators. In the early stage of wind power
development, fixed-speed wind turbines and induction
generators were often used. Figure 5, shows permanent
magnetic synchronous generators (PMSGs) used for the
Soweto project.
Figure. 5. Soweto’s Three-phase PMSG used.
II.6. Battery Regulator / Charge Controller
The battery regulator/ charge controller essentially forms
a protection against overcharging a bank of batteries. It
also acts as monitoring system when the batteries are
fully charged; the controller sends a full energy stored
code from the charge controller to the load [13]. Figure 6,
shows the charge controller connected to the battery bank
during testing in Soweto.
Figure. 6. Charge controller connected to the batteries during testing in
Soweto.
II.7. AC cabling routing for the Soweto SWT project
The importance of neat cabling in wind turbines should
be considered when constructing a system. Figureure 7,
shows a medium AC cable running from the wind turbine
tower to the charge regulator during testing in Soweto.
The anticipated current delivery of the cable is a
maximum of 50 Amps.
Figure. 7. Three-phase AC medium cabling routing during testing in
Soweto
II.8. 7- Designed Rotor blades for prototype 3
In my recent 2022 article [14] showed the blade design
and optimisation using BEM Theory. Different blade
design aspects were taken into consideration while
adapting and developing further blade designs in the
https://www.sciencedirect.com/topics/engineering/wind-machines
https://www.sciencedirect.com/topics/engineering/aerodynamic-efficiency
https://www.sciencedirect.com/topics/engineering/rotor-blade
T. Sithole et al. / International Journal of Energetica (IJECA) Vol. 8, N°1, 2023, pp. 01-11
Page 4
Soweto project.
The finished blade designs for Prototype 3 when
implemented are shown in Figure 8. The design
procedure and final specifications were further detailed
in [14].
Figure 8. Prototype 3 (design 3) 7- rotor blades for Soweto SWT project
II.9. Developed wind turbine tower for the Soweto
project
Wind turbine towers are usually made out of concrete,
steel (tubular), or lattice (steel). Their purpose is to create
balance within the structure of the wind turbine whenever
there is movement of wind. It is known that the greater
the height of the wind tower, the better the wind turbine
will perform. Figure 9, shows a chosen wind turbine
tower designed for this project.
Figure. 9. Developed steel tower for the Soweto SWT.
II.10. Power Wattmeter and DP-3051 Software package
The power wattmeter was compatible with the DPA-
3051 software package and thus used together. A power
wattmeter was used to record data and stored in the
device memory. The DPA-3051 software package was
used to extract data from the power wattmeter and
therefore give outcomes of the wind turbine in the form
of graphing. See Figure 10:
Figure. 10. Power wattmeter and DPA -3051 software used for the Soweto
project.
III. Result and discussion
III.1. Case study for the Eastern Cape province, South
Africa
[15] Stated their research problems to be as follows:
An assessment of generating electricity from wind for six
sites of the Eastern Cape Province: Gqeberha (PE),
Queenstown, Fort Beaufort, Makhanda/Grahamstown,
Graaff Reinet and Bisho.
The research was done at the Fort Hare University in
South Africa from June 2014 to December 2014.
III.2. Research methodology used for the Eastern Cape
province study
The following technique and procedures were used in
order to accomplish the project [15]:
The series of five-year wind speed average data (01/2009
to 12/2013) for 6-Eastern Cape Weather Station were
acquired at South African Weather Services (SAWS).
The analysing of data with MATLAB was done with the
use of a Weibull distribution.
III.3. Results and conclusion obtained for the Eastern
Cape Province from case study: Reviewed.
Figure 11, shows location of six sites in the Eastern Cape
Province that research was conducted on. Table 1, shows
weather station coordinates that were used for Eastern
Cape case study. Figure 12, shows the variation of wind
speed per day for Eastern Cape sites from (2009-2013).
Figure 13, shows the annual Weibull Probability
T. Sithole et al. / International Journal of Energetica (IJECA) Vol. 8, N°1, 2023, pp. 01-11
Page 5
Frequency Density for part of the Eastern Cape for
period under consideration.
As depicted in Figure 13, it is the observation of
variation of wind speed for six Eastern Cape sites from
2009 to 2013. The respective maxima fluctuate from site
to site. Most inland sites trends have lower wind speed
conditions, except Gqeberha (PE) and Bisho, which are
located very near the coast.
Moreover, the minimum probability of an event in
Gqeberha (PE) is 0.13 but the city also has the highest
wind speed, while Fort Beaufort has the least spread
among these sites/regions [15].
Figure. 11. Location of six Sites in the Eastern Cape Province [15]
Table1. Weather station coordinates used for Eastern Cape case study
[15]
Figure. 12. Variation of wind speed per day for Eastern Cape sites (2009-
2013) [15]
Figure. 13. The annual Weibull Probability Frequency Density for part of
the Eastern Cape for period under consideration [15]
Therefore, in this study, it was determined to use
characteristics of P.E (Gqeberha) region in the Eastern
Cape Province with Soweto’s in order to determine the
feasibility of implementing the Soweto Technology in
the coastal region of P.E.
III.4. Predictive study results for soweto and eastern
cape province regions
It is of major importance that the assessment of wind
potential is performed correctly. All characteristics must
be considered as they will impact every aspect of the
assessment, such as the evaluation of physical
performance, investment viability and system design.
Figure 14 illustrates the Unit-T anemometer tool that was
used in Soweto to measure the effectiveness of wind
periods for the area. According to [16], this tool is mostly
used by meteorologists to analyse weather. The device
has the ability to measure wind speed in (m/s) and (km/h)
and temperature in (°C) and (°F), with data logging
capture. It also has the ability to give outputs in the form
of waveforms for analysis.
The device has Bluetooth functionality to transfer data to
the user after measuring wind speed. The portable device
can be plugged into the wind turbine and allowing
convenient extraction of data.
Figure 14. Unit-T 363-B Anemometer [16]
T. Sithole et al. / International Journal of Energetica (IJECA) Vol. 8, N°1, 2023, pp. 01-11
Page 6
Table 2, 3 and 4 shows data that was collected for
Soweto wind measurement effectiveness with the use of
a Unit-T Bluetooth Anemometer every 24-hour intervals.
The highest wind power probability as in Figure 15 was
found to be 2.3 m/s (8.28 km/h) using Soweto data
recorded in Table 2, 3 & 4 and results were compared to
that of Statistics of South African weather services.
Table 2. Phase two of Soweto Wind Measurement Data
Figure 15. Probability of wind and normalized wind power for Soweto
area
Table 3. Phase three of Soweto Wind Measurement Data.
T. Sithole et al. / International Journal of Energetica (IJECA) Vol. 8, N°1, 2023, pp. 01-11
Page 7
Table 4. Phase four of Soweto Wind Measurement Data
The average wind speed per year for Gqeberha (PE), as
determined by Weather Spark [17], is 11.6 mph
(approximately 5.16m/s). Knowing that Soweto has an
average wind speed of 2.3 m/s, characteristic variables
were found as shown in Table 5.
As per my recent article published by ETASR peer
review open journal (Engineering, Technology and
Applied Science Research), Titled: Implementation and
Evaluation of a Low Speed and Self-regulating Small
Wind Turbine for Urban Areas in South Africa, results
showed that Prototype 3 with maximum pitch angle of
12° produced the maximum output power of 39.5 W
during testing and the maximum power output was
achieved at average wind speed of 1.17 m/s (4.2 km/h)
with energy production to generate a maximum 40 kWh
per month.
Figure 16, thus shows the predicted power output for
Prototype 3 (Design 3) when it is applied in the
Gqeberha (PE) region, assuming that it operates
continuously. The analysis yields a maximum output
power of 54.3 W at the average wind speed in Gqeberha.
Figure 16. Predicted (output power vs. blade maximum pitch angle as
derived for Prototype 3 in Gqeberha (PE) region).
Table 5. Predicted wind speed between Soweto and Gqeberha (PE).
Figure 17 shows kWh energy production per month over
a year, when the Soweto Technology results were
predicted for Gqeberha (PE)’s wind speed. It can be seen
that the predicted production of energy per month in
Figure 17 was positive when compared to energy
production for the prototype 3 when it was implemented
in Soweto.
T. Sithole et al. / International Journal of Energetica (IJECA) Vol. 8, N°1, 2023, pp. 01-11
Page 8
Figure 17. Projected (kWh production vs. months) for Prototype 3
when predicted to be applied in the Gqeberha (PE) region.
Scientific research showed that while the minimum
probability of an event in Gqeberha was 0.13, the city
also has the highest wind speed [15]. Then the predicted
annual Probability Density Frequency for Gqeberha (PE)
and Soweto in Figure 18 shows that Soweto has the
maximum event probability of 0.16 with least wind
speed.
Figure. 18. The predicted annual probability density frequency for
Soweto and Gqeberha (PE)
Predictive Investment Analysis for the Soweto Wind
Turbine
An investment analysis for the Soweto project is crucial
as this will determine the viability of the project in the
long term. In this section, the lists of materials that will
be used for this project will be given together with the
estimated prices. Next, the project viability in terms of
investment versus profitability and pay-back period of
the investment will be analysed.
A. Budget for the Soweto project
Table 6 shows the total wattage that was consumed for
this project, and Table 7 shows a list of all material that
were used for this project. The prices of the main
hardware and electronic devices were taken from the
internet sources. The total energy consumption is 2910
W/day.
Table 6. Energy consumption of appliances in Soweto
However, to calculate the minimum power of a
generator, it is necessary to add the loss of energy from
the electrical system; this can be estimated as 10 % of the
electrical system’s total consumption. [18] Stated that
electrical energy consumption can be calculated as
follows:
(1)
= 2619 W
B. The predicted study of pay-back period and
profitability for this project
The predicted energy yielded using the Soweto Wind
Turbine System in kWh will be compared to the energy
yield of electricity suppliers in South Africa such as
Eskom and City Power. The conclusion will be given on
the expediency of this project, based on economic
considerations. It is already known that the start-up
investment is R15,600.00 (Table 7).
Table 7. List of materials for the Soweto project.
T. Sithole et al. / International Journal of Energetica (IJECA) Vol. 8, N°1, 2023, pp. 01-11
Page 9
The internal rate of return is given as IRR; to calculate
the (IRR), total start-up investment (R15,600.00) should
be included. As shown in Table 7, the life span of a small
wind turbine will be given as (n) and (r) as rate of
interest. According [18], the formula to calculate (IRR)
then becomes:
………………… (2)
“r” is the rate of average interest of the total start-up
investment, as shown in Table 7. Therefore, the Soweto
technology life span is estimated to be 20 years and rate
of interest to be 7% of the start-up investment. Thus we
get an Equation (3) as follows: [18]
( )
(3)
The Capital cost (Cc) for production of energy in (kWh)
taking into account that (I) is regarded as the Initial
investment and will be included in the equation of (IRR).
(CF) is the Capacity Factor and (P) is the minimum
power generated. Moreover, we will assume that the
wind functions for 10.5 hours per day. Then (Cc) will be
calculated as follows in Equation (4): [18].
(4)
( ) ( ) (5)
(
)(
) (6)
[19] Stated that maintenance is performed to prevent
failures, that is preventive maintenance or it is for
correcting a failure event, which is corrective
maintenance. The importance of Operation and
Maintenance in wind turbine site is to ensure the Wind
Turbine Generator (WTG) availability. When the WTG
works, there would be possibility of issues such as errors
/ warning signals which may affects the availability of
the WTG.Operation and maintenance (O&M) costs make
up 25-30% of the total costs of a wind turbine. This is
almost as much as the cost of the wind turbines and about
as much as the costs of construction and installation.
According to [20], O&M costs are related to a limited
number of cost components, and include: (i) Regular
maintenance (batteries, etc.) (ii) Repairs; (iii) Spare parts
replacement and (iv) Administration. Thus, for the
Soweto small wind turbine, if we assume that O&M is
20% of the initial investment, then Equation (7) will be
as follows: [18]
(
)
(7)
Therefore, the cost of power production (R /kWh) is the
total cost of maintenance and operation plus the cost of
capital (Cc) as shown in Equation (8): [18]
(8)
As per Equation 8, it is seen that the estimated average
cost to generate 1 kWh was R0.4567 /kWh with the
Soweto turbine, considering all initial capital outlay
costs.
However, according to [21], the average cost of
generating 1 kWh in South Africa is about R1.85 /kWh +
15 % tax = R2.13 /kWh for an average household that
consumes between 100 and 1000 kWh per month, with a
tariff addition of R5.00 per kWh where 1000 kWh usage
is exceeded per month.
C. The predicted pay-back of the capital investment
calculations
The payback period is the time period (generally in
years) in which a return is required from an investment or
the amount of time it takes for the positive cash flow to
exceed the initial investment, without concern for the
time value of money [22, 23].
[18] Further stated that to calculate the AEO = Annual
energy output (kilowatt-hours/year) use the following
Equation (9):
AEO = Emean × 365 (where Emean is appliances energy
consumption shown in Table: 6): 2910 × 365 1062.15
kWh/yea (9)
Table 8 and 9 [24], was used to analyse the annual
energy production of selected turbines at the different
sites and estimate the payback period of the investment.
The total predicted energy generated per year by means
of the Soweto technology would be 1062,15 kWh/year.
Looking at Table 8, under: region - Northern and site
location - Johannesburg, it is apparent that the AEO
calculated would fall under the power category of
Johannesburg as shown in Table 8.
T. Sithole et al. / International Journal of Energetica (IJECA) Vol. 8, N°1, 2023, pp. 01-11
Page 10
Table 8. Annual energy production of selected turbines at different sites
[24].
This project initial plan was to use 500W Wind
Generator as a departure point, therefore, Table 9,
further shows that with the range of 300 W-1 kW modern
designed wind turbine application, the predicted payback
period would be 16 years if all regular maintenance
(batteries, etc.), repair, supply of spare parts and
administration are taken into consideration.
Table 9. Estimated payback period of selected turbines at different sites
[24]
IV. DISCUSSION
• The highest wind power probability derived
from wind anemometer collected data in Soweto was
approximately 2.3 m/s, demonstrating that the
Anemometer was calibrated correctly as compared to
average wind speed referenced in South African Weather
Service (SAWS).
• The results showed that a predictive case study
which was done for regions in Eastern Cape, specifically
for the Gqeberha (PE) area, utilizing the empirically
obtained data in Soweto, projected an energy output of
up to 54.3 W per wind speed of 5.16 m/s (18.6 km/h) at
Gqeberha and up to 100 kWh per month production
energy.
• A predictive investment analysis to determine
profitability and viability of prototypes revealed that
when all initial capital outlay costs and operational costs
over a 20-year period were considered, the average cost
of generating 1 kWh was R0.4567 /kWh. This derived
cost compares extremely favorably with the amount
charged by electricity companies in South Africa such as
Eskom and City Power, which is (in 2022) approximately
R1.85 /kWh + 15% tax = R2.13 /kWh) for an average
household that consumes between 100 to 1000 kWh per
month. Moreover, at above 1000 kWh usage, the tariff
increases to R5.00 per kWh, which then raises the
anticipated cost savings even further. It was also
predicted that the payback period for the Soweto project
to be 16 years.
• Social and environmental impact of the Soweto
technology as well as challenges and barriers to its
widespread adoption can be found in my 2022 article
[25].
V. CONCLUSION
The following are the major conclusions drawn from the
research:
1. The benefits of this research was to achieve
possible application of low-cost small-scale wind turbine
in South Africa for low wind speed areas, thereby
providing low-cost electricity to households and
inhabitants in urban as well as in rural areas for a very
large region in South Africa. This was achieved by
developing a test prototype for low wind speed condition
in Soweto, Johannesburg, South Africa, and Moreover
prediction case study using Soweto test results were
shared in number (2).
2. A predictive case study for the Eastern Cape,
focused on the Gqeberha (PE) area, was conducted using
the empirically obtained data for the Soweto and
Gqeberha (PE) areas, and it was concluded that it would
be feasible to implement the Soweto technology in Port
Elizabeth due to the results emanating presumably from
the conditions at lower altitude (higher density air), and
much higher wind speed resources at or near the coastal
region.
3. Finally, the predictive case study between
Soweto and P.E that was carried out contributed to new
knowledge created within the field of study as it hasn’t
been done before and it is original.
T. Sithole et al. / International Journal of Energetica (IJECA) Vol. 8, N°1, 2023, pp. 01-11
Page 11
Declaration
The authors declare that they have no known
financial or non-financial competing interests in any
material discussed in this paper.
The authors declare that this article has not been
published before and is not in the process of being
published in any other journal.
The authors confirmed that the paper was free of
plagiarism
Reference
[1] S. Jain and P.K. Jain. "The rise of renewable energy
implementation in South Africa." Energy Procedia, 143,
2017, pp. 721-726.
[2] N.N. Rad, A. Bekker, and M. Arashi. "Enhancing wind
direction prediction of South Africa wind energy hotspots
with Bayesian mixture modeling." Sci Rep 12, 2022,
11442 https://doi.org/10.1038/s41598-022-14383-8
[3] G. Josie. "The Science Behind Decarbonization: The
Race To Zero." Stanford Earth Matters Magazine, 2021.
[4] E.C. Merem. "Appraising Variations In Climate Change
Parameters Along The Lower West African Region."
Journal of Safety Engineering, 7:1:1-19, Climate Change
and Shorelines, May. 2018.
[5] E.C. Merem. "Techniques of Remote Sensing and GIS as
Tools for Visualizing Impact of Climate Change-Induced
Flood in the Southern African Region." American Journal
of Climate Change, vol 6, 2017, 306-327.
[6] B. Babalwa. "South Africa: Kangnas Wind Farm kicks
off operations." ESI Africa, 2020.
[7] M. Jamie. "South Africa Will Be A Wind Energy
Powerhouse." Olifansfontein, South Africa: My
Broadband News, 2020.
[8] PR Newswire. "Second Wind's Technology Gains
Ground in South Africa's Expanding Wind Energy
Market." 2011. https://www.prnewswire.com/news-
releases/second-winds-technology-gains-ground-in-south-
africas
[9] Memon, M. H., Baloch, A. H. Memon, S. H. Qazi, R.
Haider, and D. Ishak. "Assessment of Wind Power
Potential Based on Raleigh Distribution Model: An
Experimental Investigation for Coastal Zone."
Engineering, Technology & Applied Science Research,
vol. 9, no. 1, 2021, pp. 3721-3725.
https://doi.org/10.48084/etasr.2381
[10] Y. Kassem, H. Gokcekus, and H. S. A. Lagili. "A
Techno-Economic Viability Analysis of the Two-Axis
Tracking Grid-Connected Photovoltaic Power System for
25 Selected Coastal Mediterranean." Engineering,
Technology & Applied Science Research, vol. 11, no. 4,
Aug. 2021, pp. 7508-7514.
https://doi.org/10.48084/etasr.4251
[11] F. Elmahmoudi, O. E. K. Abra, A. Raihani, O. Serrar, and
L. Bahatti. "Elaboration of a Wind Energy Potential Map
in Morocco using GIS and Analytic Hierarchy Process."
Engineering, Technology & Applied Science Research,
vol. 10, no. 4, Aug. 2020, pp. 6068-6075.
https://doi.org/10.48084/etasr.3692
[12] SMA. "Wind Power Inverter." Available from:
http://ust.su/upload/iblock/bb1/Sollight-SMA-
WindyBoy5000-6000.pdf Accessed: 15th January 2020.
[13] Myint, A. S., Tun, H. M., and Naing, Z. M.
"Implementation of Wind Turbine Controller Design for
Smart Campus." International Journal of Scientific and
Research Publications, Jun. 2014, vol. 4, no. 5, pp. 1-10.
[14] T.S Sithole, V.R Veeredhi, and T. Sithebe. "Small Wind
Turbine Blade Optimization using blade elementary
method theory (BEMT)." IJISRT, Dec. 2022, vol. 7, no.
12, pp. 16-21. https://doi.org/10.5281/zenodo.7444983
[15] C. Shonhiwa, G. Makaka, and K. Munjeri. "Estimation of
Wind Power Potential of Six Sites in Eastern Cape
Province of South Africa." Physical Science International
Journal, June 2015, pp. 209-218.
[16] ElectroMann SA. "Wind Power (Technology and
Economics)." Aug. 2021. Available from:
https://www.electromannsa.com/products/uni-t-ut363bt-
bluetooth-mini-wind-speed-meter
[17] Weather Spark. Average Weather in Port Elizabeth. 2020.
https://tinyurl.com/y6kd795c
[18] Moreno, F.G. Design of a Small Wind Generator. 2008.
https://tinyurl.com/yy45y38z
[19] Rajeesh, K.C. and Sankar, S. IMPROVING BATTERY
LIFE IN THE WIND TURBINE GENERATOR USING
ULTRACAPACITOR. International Journal of Advanced
Technology in Engineering and Science, no 03, 2015, pp.
2348–7550.
[20] Castellà, a.t. operations and maintenance costs for
offshore wind. 2020. Available:
https://upcommons.upc.edu/bitstream/handle/2117/32973
1/master-thesis-xavier-turc-castell-.pdf
[21] Business -Tech. South Africa’s Petrol and Electricity
prices vs. the world. 2019 Jun. Available:
https://tinyurl.com/y6gkx49p
[22] Ayompe, L. Performance and policy evaluation of solar
energy technologies for domestic application in Ireland.
2011. https://tinyurl.com/3rbpt938
[23] Mostafaeipour, A. Economic evaluation of small wind
turbine utilization in Kerman, Iran. Energy Conversion
and Management, 73, 2013, pp. 214-225.
[24] Olatayo, K.I. A development path for small wind energy
systems in South Africa. 2017 May.:
http://repository.nwu.ac.za/bitstream/handle/10394/25628
/Olatayo_KI_2017.pdf?sequence=1&isAllowed=y
[25] T.S Sithole, V.R Veeredhi, and T.Sithebe. A Review on
Small Wind Turbine Aerodynamic Performance for
Contribution of Power Supply for Low Wind Speed
Areas. IJCEEE, May 2022, vol. 4, no. 5, pp. 1-6.
https://wairco.org/IJCEEE/May2022.html
https://doi.org/10.1038/s41598-022-14383-8
https://www.prnewswire.com/news-releases/second-winds-technology-gains-ground-in-south-africas
https://www.prnewswire.com/news-releases/second-winds-technology-gains-ground-in-south-africas
https://www.prnewswire.com/news-releases/second-winds-technology-gains-ground-in-south-africas
https://doi.org/10.48084/etasr.2381
https://doi.org/10.48084/etasr.4251
https://doi.org/10.48084/etasr.3692
http://ust.su/upload/iblock/bb1/Sollight-SMA-WindyBoy5000-6000.pdf
http://ust.su/upload/iblock/bb1/Sollight-SMA-WindyBoy5000-6000.pdf
https://doi.org/10.5281/zenodo.7444983
https://www.electromannsa.com/products/uni-t-ut363bt-bluetooth-mini-wind-speed-meter
https://www.electromannsa.com/products/uni-t-ut363bt-bluetooth-mini-wind-speed-meter
https://tinyurl.com/y6kd795c
https://tinyurl.com/yy45y38z
https://upcommons.upc.edu/bitstream/handle/2117/329731/master-thesis-xavier-turc-castell-.pdf
https://upcommons.upc.edu/bitstream/handle/2117/329731/master-thesis-xavier-turc-castell-.pdf
https://tinyurl.com/y6gkx49p
https://tinyurl.com/3rbpt938
http://repository.nwu.ac.za/bitstream/handle/10394/25628/Olatayo_KI_2017.pdf?sequence=1&isAllowed=y
http://repository.nwu.ac.za/bitstream/handle/10394/25628/Olatayo_KI_2017.pdf?sequence=1&isAllowed=y
https://wairco.org/IJCEEE/May2022.html