Feasibility of Wind Energy Utilization for Sustainable Power Generation in Ilorin, Kwara State, Nigeria's North-Central Region
Main Article Content
Abstract
The escalating energy demands across Nigeria, especially in remote rural areas, have outpaced the capacity of the national electricity grid, necessitating the development of independent and sustainable energy sources. Among the renewable options, wind energy stands out as a promising solution. This study focuses on assessing the potential of wind energy in Ilorin, located in Kwara State, within Nigeria's north-central region. Utilizing data collected from 2007 to 2021 by the Nigerian Meteorological Agency, the research examines monthly average wind speeds at two specific coordinates in Ilorin, considering variations in air density. The study utilizes a 15-year set of monthly average wind velocities obtained from the Nigerian Meteorological Agency (NiMet) Headquarters in Abuja, measured at a height of 10 meters above ground level. By employing the 2-coefficient Weibull statistical model and extrapolation principles across different altitudes ranging from 150 to 900 meters above ground level, the study reveals distinct seasonal patterns of wind speeds ranging from 1.1 to 5.1 m/s in Ilorin. Furthermore, wind power density values ranging from 6.7 to 39.20 W/m2 are identified, with optimal wind attributes observed at altitudes exceeding 900 meters. These findings provide valuable insights for assessing the feasibility of wind energy utilization and designing efficient systems in Nigeria's north-central regions, aiding in the sustainable energy transition.
Downloads
Article Details
References
Rasp, S., Dueben, P. D., Scher, S., Weyn, J. A., Mouatadid, S., & Thuerey, N. (2020). WeatherBench: a benchmark data set for data‐driven weather forecasting. Journal of Advances in Modeling Earth Systems, 12(11), e2020MS002203. DOI: https://doi.org/10.1029/2020MS002203
Tan, J. D., Chang, C. C. W., Bhuiyan, M. A. S., Nisa’Minhad, K., & Ali, K. (2022). Advancements of wind energy conversion systems for low-wind urban environments: A review. Energy Reports, 8(1), 3406-3414. DOI: https://doi.org/10.1016/j.egyr.2022.02.153
Lawal, O. A., Jimoh, A. A., Abdulkadir, Z. A., Bello, A. B., Balogun, M. O., & Atanda, A. R. (2023, March). Mitigating the Challenge of Energy Crisis via Energy Audit and Efficiency Measures: A Case of a Household in Nigeria. In 2023 7th International Conference on Green Energy and Applications (ICGEA), 218-223. DOI: https://doi.org/10.1109/ICGEA57077.2023.10125637
Kumar, R. (2013). Decision tree for the weather forecasting. International Journal of Computer Applications, 76(2), 31-34. DOI: https://doi.org/10.5120/13220-0620
Holmstrom, M., Liu, D., & Vo, C. (2016). Machine learning applied to weather forecasting. Meteorol. Appl, 10(1), 1-5.
Grover, A., Kapoor, A., & Horvitz, E. (2015). A deep hybrid model for weather forecasting. In Proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining, 379-386 DOI: https://doi.org/10.1145/2783258.2783275
Hasan, N., Uddin, M. T., & Chowdhury, N. K. (2016, October). Automated weather event analysis with machine learning. In 2016 International Conference on Innovations in Science, Engineering and Technology (ICISET), 1-5. DOI: https://doi.org/10.1109/ICISET.2016.7856509
Scher, S., & Messori, G. (2018). Predicting weather forecast uncertainty with machine learning. Quarterly Journal of the Royal Meteorological Society, 144(717), 2830-2841. DOI: https://doi.org/10.1002/qj.3410
Kwok, K. C. S., & Hu, G. (2023). Wind energy system for buildings in an urban environment. Journal of Wind Engineering and Industrial Aerodynamics, 234, 105349 DOI: https://doi.org/10.1016/j.jweia.2023.105349
Eltamaly, A. M. (2013). Design and implementation of wind energy system in Saudi Arabia. Renewable Energy, 60(1), 42-52. DOI: https://doi.org/10.1016/j.renene.2013.04.006
Ajayi, O. O., Ohijeagbon, O. D., Nwadialo, C. E., & Olasope, O. (2014). New model to estimate daily global solar radiation over Nigeria. Sustainable Energy Technologies and Assessments, 5, 28-36. DOI: https://doi.org/10.1016/j.seta.2013.11.001
Nze-Esiaga, N., & Okogbue, E. C. (2014). Assessment of wind energy potential as a power generation source in five locations of Southwestern Nigeria. Journal of Power and Energy Engineering, 2(5), 1-12. DOI: https://doi.org/10.4236/jpee.2014.25001
Labuschagne, C. J., & Kamper, M. J. (2021). Wind generator impedance matching in small-scale passive wind energy systems. IEEE Access, 9, 22558-22568. DOI: https://doi.org/10.1109/ACCESS.2021.3056226
Fagbenle, R. O., Katende, J., Ajayi, O. O., & Okeniyi, J. O. (2011). Assessment of wind energy potential of two sites in North-East, Nigeria. Renewable energy, 36(4), 1277-1283. DOI: https://doi.org/10.1016/j.renene.2010.10.003
Ahmed, A., & Kunya, B. I. (2019). Investigation of Wind Energy Resource on the Basis of Weibull and Rayleigh Models in North-Eastern and Western, Nigeria. American Journal of Aerospace Engineering, 6(1), 27-32. DOI: https://doi.org/10.11648/j.ajae.20190601.15
Adaramola, M. S., & Oyewola, O. M. (2011). Evaluating the performance of wind turbines in selected locations in Oyo state, Nigeria. Renewable Energy, 36(12), 3297-3304. DOI: https://doi.org/10.1016/j.renene.2011.04.029
Garba, A. D., & Al-Amin, M. (2014). Assessment of Wind Energy Alternative in Nigeria from the Lessons of the Katsina Wind Farm. Assessment, 6(4), 91-94.
Adeyeye, K. A., Ijumba, N., & Colton, J. S. (2021). A techno-economic model for wind energy costs analysis for low wind speed areas. Processes, 9(8), 1463-1475. DOI: https://doi.org/10.3390/pr9081463
Ajayi, O. O., Fagbenle, R. O., & Katende, J. (2011). Wind profile characteristics and econometric analysis of wind power generation of a site in Sokoto State, Nigeria. Energy Sci. Technol, 1(2), 54-66.
Rehman, S., Natarajan, N., Mohandes, M. A., Meyer, J. P., Alam, M. M., & Alhems, L. M. (2022). Wind and wind power characteristics of the eastern and southern coastal and northern inland regions, South Africa. Environmental Science and Pollution Research, 29(57), 85842-85854. DOI: https://doi.org/10.1007/s11356-021-14276-9
Ajayi, O. O., Fagbenle, R. O., & Katende, J. (2011). Wind profile characteristics and econometric analysis of wind power generation of a site in Sokoto State, Nigeria. Energy Sci. Technol, 1(2), 54-66.
Ajayi, O. O., & Fagbenle, R. O. (2011). Assessment of wind power potential and wind electricity generation using WECS of two sites in South-West, Nigeria, 1(2) 78-92.
Fagbenle, O., Joshua, O., Afolabi, A., Ojelabi, R., Fagbenle, O., Fagbenle, A., & Akomolafe, M. (2018, March). Cost management practice of construction firms and its influencing factors: Lessons from southwestern Nigeria. In Construction Research Congress, 692-700. DOI: https://doi.org/10.1061/9780784481271.067
Argungu, G. M., Bala, E. J., Momoh, M., Musa, M., Dabai, K. A., Zangina, U., & Maiyama, B. A. (2013). Statistical analysis of wind energy Resource potentials for power generation In Jos, Nigeria, Based on Weibull distribution function. The International Journal of Engineering and Science, 2(5), 22-31.
Hemeida, A. M., El-Ahmar, M. H., El-Sayed, A. M., Hasanien, H. M., Alkhalaf, S., Esmail, M. F. C., & Senjyu, T. (2020). Optimum design of hybrid wind/PV energy system for remote area. Ain Shams Engineering Journal, 11(1), 11-23. DOI: https://doi.org/10.1016/j.asej.2019.08.005
Akporhonor, G. K., Otuagoma, S. O., & Akporhonor, T. A. (2023). Nigerian wind energy status. Wind Engineering, 0309524X231206559. DOI: https://doi.org/10.1177/0309524X231206559
Boghdady, T., Sweed, I. A., & Ibrahim, D. K. (2023). Performance Enhancement of Doubly-Fed Induction Generator-Based-Wind Energy System. International Journal of Renewable Energy Research (IJRER), 13(1), 311-325.
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(12), 8508-8534 DOI: https://doi.org/10.3390/en7128508