DOI: https://doi.org/10.14710/ijred.2023.44018

Domestic Wind Energy Planning for Deprived Communities in the Tropics: A Case Study of Nigeria

1Department of Physics, Bowen University Iwo, Nigeria

2Department of Mechanical Engineering Science, University of Johannesburg, South Africa

3Department of Biochemistry, Covenant University Canaanland, Nigeria

4 Department of Mechanical Engineering, Afe Babalola University, Ado-Ekiti, Nigeria

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Received: 22 Jan 2022; Revised: 28 Nov 2022; Accepted: 16 Jan 2023; Available online: 8 Feb 2023; Published: 15 Mar 2023.
Editor(s): H Hadiyanto
Open Access Copyright (c) 2023 The Author(s). Published by Centre of Biomass and Renewable Energy (CBIORE)
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract

Despite the notable inventions in solar energy, it is still too high for standalone users from developing countries. For example, it cost $2200 to provide power for a two-bedroom apartment while the average citizen lives below the country’s poverty line of $381.75 per year. The use of fossil fuel generators remains cheaper, except there is an affordable energy option for the average populace. The objective of this study is to investigate the wind energy potential for domestic or standalone use in Nigeria. It is proposed that the domestic wind turbine will be relatively cheap for adoption. Hence, there is the need to wholistic examine the prospects of wind energy generation in Nigeria. Though previous studies had been carried out, none has been wholistic as presented in this research work. Forty years wind speed and wind direction dataset, i.e., 1980-2020, was obtained from the Modern-Era Retrospective analysis for Research and Applications (MERRA). The analysis of the wind energy potential across the research locations was considered using five sampling techniques, i.e., considering the general statistics of the forty years dataset; considering ten years in an evenly distributed pattern and accruable wind energy across the nation. It was observed that the early wet season (MAM) is the most unstable among the seasons. Also, sudden multi-directionality of the wind vectorization within forty years was observed. This event is ascribed to evidence of climate change to wind energy generation. Wind energy generation prospect was seen to be generally sustainable and reliable with SON, MAM, DJF and JJA having energy distribution of 325-950 kWh, 539-1700 kWh, 161-650 kWh and 761-3650 kWh respectively. Despite the variation of energy generation over the years within all seasons over Nigeria, it was found that it is predictable and can be optimized using various technological solutions.

 

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Keywords: Wind energy; renewable energy; wind speed; wind direction; wind

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Section: Original Research Article
Language : EN
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  1. Adeoye, O. S. (2014). Estimation of Potential Load Demand of Local Government Areas of Ekiti State, Nigeria. American Journal of Engineering Research, 3,101-106
  2. Ajayi, O.O. (2013). Sustainable energy development and environmental protection: The case of five West African Countries. Renew. Sustain. Energy Rev., 26, 532–539. https://doi.org/10.1016/j.rser.2013.06.009
  3. Ajayi, O.O., Fagbenle, R.O., Katende, J., Ndambuki, J.M., Omole, D.O., & Badejo, A.A. (2014). Wind Energy Study and Energy Cost of Wind Electricity Generation in Nigeria: Past and Recent Results and a Case Study for South West Nigeria. Energies, 7,8508-8534. https://doi.org/10.3390/en7128508
  4. Akinsanola, A. A., Kehinde, O. O., Akintayo, T. A. & Seyni, S. (2021). Projected changes in wind speed and wind energy potential over West Africa in CMIP6 models, Environ. Res. Lett. 16, 044033. https://doi.org/10.1088/1748-9326/abed7a
  5. Bilgili, M., Yasar, A., & Simsek, E. (2011). Offshore wind power development in Europe and its comparison with onshore counterpart. Renewable Sustainable Energy Rev., 15 (2): 905-915. https://doi.org/10.1016/j.rser.2010.11.006
  6. Carrete, M., Sanchez-Zapata, J.A., Benitez, J.R., Lobon, M., Montoya, F., & José, A. D. (2012). Mortality at wind-farms is positively related to large-scale distribution and aggregation in griffon vultures. Biological Conservation, 145, 102–108. https://doi.org/10.1016/j.biocon.2011.10.017
  7. Chapman, S., & George, A.S. (2013). How the factoid of wind turbines causing ‘vibroacoustic disease’ came to be ‘irrefutably demonstrated’. Environment, 37,244-249. https://doi.org/10.1111/1753-6405.12066
  8. Ciang, C.C., Lee, J.R., & Bang, H.J. (2008). Structural health monitoring for a wind turbine system: a review of damage detection methods. Meas. Sci. technol., 19,122001. https://doi.org/10.1088/0957-0233/19/12/122001
  9. Crichton, F., Chapman, S., Cundy, T., & Keith, J. P. (2014). The link between health complaints and wind turbines: support for the nocebo expectations hypothesis. Front. Public Health, 2,220. https://doi.org/10.3389/fpubh.2014.00220
  10. Dicorato, M., Forte, G., Pisani, M., & Trovato, M., (2011). Guidelines for assessment of investment cost for offshore wind generation. Renew. Energy, 36(8), 2043-2051. https://doi.org/10.1016/j.renene.2011.01.003
  11. Dia-Diop, A., Zebaze, S., Wade, M., Djiondo, R., Diop, B., Efon, E. & Lenouo, A. (2020). Interannual Variability of Rainfall over the West Africa Sahel. Journal of Geoscience and Environment Protection, 8, 85-101. https://doi.org/10.4236/gep.2020.83007
  12. Effioma, S. O., Nwankwojike, B. N., & Abam, F. I. (2016). Economic cost evaluation on the viability of offshore wind turbine farms in Nigeria. Energy Reports, I,48-53. https://doi.org/10.1016/j.egyr.2016.03.001
  13. Fagbenle, R. O., Fasade, A. O., Amuludun, A. K., & Lala, P. O. (1980). Wind energy potential of Nigeria. In Proceedings of 12th Biennial Conference of West Africa Science Association, University of Ife, Osogbo, Nigeria, 20–26 July 1980
  14. Fagbenle, R. O., Katende, J., Ajayi, O. O., & Okeniyi, J. O. (2011). Assessment of wind energy potential of two sites in North East, Nigeria. Renew. Energy, 36,1277–1283. https://doi.org/10.1016/j.renene.2010.10.003
  15. Farris, A. (2019). Wind power. Energy British Columbia 2017. http://www.energybc.ca/wind.html (Accessed 7 July 2019)
  16. Glen, S. (2022). How to Calculate the Least Significant Difference (LSD), From StatisticsHowTo.com: Elementary Statistics for the rest of us! https://www.statisticshowto.com/how-to-calculate-the-least-significant-difference-lsd/ (Accessed 3 August 2019)
  17. Global Wind Energy Council (GWEC). (2016). Global Wind Statistics 2015; Technical Report; Global Wind Energy Council (GWEC): Brussels, Belgium, https://www.gwec.net/wp-content/uploads/vip/GWEC-Global-Wind-2015-Report_April-2016_22_04.pdf (Accessed 7 July 2019)
  18. Haryanto, Y. D., Riama, N. F., Purnama, D. R., & Sigalingging, A. D. 2021). The Effect of the Difference in Intensity and Track of Tropical Cyclone on Significant Wave Height and Wave Direction in the Southeast Indian Ocean. The Scientific World Journal, 2021, 5492048. https://doi.org/10.1155/2021/5492048
  19. IRENA (2018). Renewable Power Generation Costs in 2018. https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2019/May/IRENA_Renewable-Power-Generations-Costs-in-2018.pdf (Accessed 11th November, 2021)
  20. International Renewable Energy Agency (2012). Wind power. Renewable energy technologies: Cost Analysis Series. Vol.1: Power Sector Issue 5/5. https://www.irena.org/publications. Accessed 19th July, 2019
  21. ISTABREEZE (2021). https://istabreeze.us/i-700w-12v-24v-48v-wind-turbine/ (Accessed 11th November, 2021)
  22. Leung, D.Y.C., & Yang, Y. (2012). Wind energy development and its environmental impact: a review. Renew Sustain Energy Rev., 16,1031–1039. https://doi.org/10.1016/j.rser.2011.09.024
  23. Li, J., Shi, Pi., & Gao, H. (2010). China Wind Power Outlook, Chinese Renewable Energy Industries Association (CREIA), Global Wind Energy Council and Greenpeace. https://gwec.net/china-wind-energy-outlook-2010/ (Accessed 10th March 2022)
  24. Lucena, J., & Lucena, K. (2019). Wind energy in Brazil: an overview and perspectives under the triple bottom line. Clean Energy, 3(2), 69-84. https://doi.org/10.1093/ce/zkz001
  25. Matha, D., Sandner, F., Molins, C., Campos, A., & Cheng, P.W. (2015). Efficient preliminary floating offshore wind turbine design and testing methodologies and application to a concrete spar design. Phil. Trans. R. Soc. A., 373, 20140350. https://doi.org/10.1098/rsta.2014.0350
  26. Madariaga, A., de Alegr, I.M., Martin, J.L., Egu, P., & Ceballos, S., (2012). Current facts about offshore wind farms. Renewable Sustainable Energy Rev., 16(5), 3105-3116. https://doi.org/10.1016/j.rser.2012.02.022
  27. Ojo, S. O., Emmanuel, I., Omitusa, O. & Adeyemi, B. (2020). Determination of Optimal Solar Power and Corresponding Tilted Angle in Different Geoclimatic Zones in Nigeria, Journal of Energy Research and Reviews, 6(2): 33-48. https://doi.org/10.9734/jenrr/2020/v6i230165
  28. Ojosu, J.O., & Salawu, R.I., (1990a). A Survey of wind energy potential in Nigeria. Sol. Wind Technol., 7, 155–167. https://doi.org/10.1016/0741-983X(90)90083-E
  29. Ojosu, J.O., & Salawu, R.I. (1990b). An evaluation of wind energy potential as a power generation source in Nigeria. Sol. Wind Technol., 7, 663–673. https://doi.org/10.1016/0741-983X(90)90041-Y
  30. Okoro, O.I., Chikuni, E., & Govender, P. (2007). Prospect of wind energy in Nigeria. In Proceedings of the International Conference on Domestic Use of Energy, Cape Town, South Africa, 10-13 April 2007. https://www.researchgate.net/publication/228827644_Prospects_of_wind_energy_in_Nigeria (Accessed 2nd May, 2020)
  31. Omole, D.O, & Ndambuki, J.M. (2014). Sustainable living in Africa: Case of water, sanitation, air pollution & energy. Sustainability, 6,5187–5202. https://doi.org/10.3390/su6085187
  32. Oyedeji, A. A., Okesola, A. A., Lamidi, M. O., Madaki, M. K., Abdulhamid, A. F., & Asaolu, G. O. (2018). Wind Energy Technology in Nigeria: Prospects, Challenges and Solution. Covenant Journal of Engineering Technology CJET, 2(2), 52-58
  33. Pierre, C., Hiernaux, P., Rajot, J.L, Kergoat, L., Webb, N. P., Abdourhamane Touré, A., Marticorena, B., & Bouet, C. (2022). Wind erosion response to past and future agro-pastoral trajectories in the Sahel (Niger). Landsc Ecol., 37, 529–550 . https://doi.org/10.1007/s10980-021-01359-8
  34. Rakhshani, E., Rueda-Torres, J. L., Palensky, P. & van Meijden, M. D., (2019). Determination of Maximum Wind Power Penetration Considering Wind Turbine Fast Frequency Response, 2019 IEEE Milan PowerTech, 2019, 1-6, https://doi.org/10.1109/PTC.2019.8810492
  35. Ragatoa, D.S., Ogunjobi, K.O., Klutse, N.A.B., Okhimamhe, A. A. , & Eichie, J. O. (2019). A change comparison of heat wave aspects in climatic zones of Nigeria. Environ Earth Sci., 78, 111. https://doi.org/10.1007/s12665-019-8112-8
  36. Rienecker, M. M. Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J., Liu, E., Bosilovich, M.G., Schubert, S.D., Takacs, L., Kim, G-K., Bloom, S., Chen, J., Collins, D., Conaty, A., da Silva, A. Gu, W., Joiner, J., Koster, R.D., Lucchesi, R., Molod, A., Owens, T., Pawson, S., Pegion, P., Redder, C.R., Reichle, R., Robertson, F. R., Ruddick, A. G., Sienkiewicz, M., and Woollen, J. (2011). MERRA: NASA's Modern-Era Retrospective Analysis for Research and Applications. J. Climate, 24, 3624-3648. https://doi.org/10.1175/JCLI-D-11-00015.1
  37. Ruxton, G.D., & Beauchamp, G. (2008). Time for some a priori thinking about post hoc testing. Behavioral Ecology, 19(3), 690-693. https://doi.org/10.1093/beheco/arn020
  38. Shi, W., Dong, Z., Chen, G., Bai, Z., & Ma, F. (2022). Spatial and Temporal Variation of the Near-Surface Wind Environment in the Sahara Desert, North Africa. Front. Earth Sci. 9:789800. https://doi/org/10.3389/feart.2021.789800
  39. Torralba, V., Doblas-Reyes F.J., & Gonzalez-Reviriego, N. (2017). Uncertainty in recent near-surface wind speed trends: a global reanalysis intercomparison. Environmental Research Letters, 12(11),114019. https://doi.org/10.1088/1748-9326/aa8a58
  40. World Bank (2020). Nigeria releases new report on poverty and inequality in country, https://www.worldbank.org/en/programs/lsms/brief/nigeria-releases-new-report-on-poverty-and-inequality-in-country (Accessed 11th November, 2021)
  41. Zach, L. (2020). How to Use Dunnett’s Test for Multiple Comparisons, https://www.statology.org/dunnetts-test/ (Accessed 11th March 2022)
  42. Zephyr Corpration (2011) Compact and ultra-light wind turbine for efficient wind power series, https://www.zephyreco.co.jp/en/products/technologies.jsp (Accessed 14th November, 2022)

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