Analyzing the Monthly and Annual Wind Speed Characteristics of the Kilwa Offshore Zone Using Rayleigh Probability Distribution

DEISM DANFORD MLAY; Wilfred Johnson Kileo; Enock Michael Kandimba; Paul Theophily Nsulangi

doi:10.18535/sshj.v9i07.1932

Abstract

This study analyses the wind speed characteristics in the Kilwa offshore zone, situated along Tanzania's southern coast. The Rayleigh probability distribution model, which only has one parameter the scale parameter was used for analysing the wind speed characteristics since it is simpler to estimate and work with. In order to match the hub heights used in modern offshore wind turbines, wind speeds were initial measured at a height of 10 meters and then projected to higher heights of 50 and 70 meters using standard wind profile equations. Analysis of monthly and annual wind speed distributions revealed that average wind speeds ranged from 9 to 10 m/s. They show a high potential for energy generation because they are within the ideal operating range for modern offshore wind turbines. The region's feasibility for the utilization of sustainable offshore wind energy is further demonstrated by the consistent and advantageous wind conditions that are seen throughout the year. The study highlights Kilwa's potential for offshore wind farm development, which serves the broader goal of generating sustainable offshore wind energy solutions and enhancing energy sources. The study not only identifies Kilwa as a potential location for offshore wind generation but also establishes a foundation for more comprehensive feasibility and investment analyses in the future.

Keywords

Offshore energy resourceOffshore wind energyKilwa offshore zoneRayleigh probability distributionWind speed characteristics

References

Adedipe, O., Abolarin, M. S., & Mamman, R. O. (2018). A Review of Onshore and Offshore Wind Energy Potential in Nigeria. IOP Conference Series: Materials Science and Engineering, 413(1). https://doi.org/10.1088/1757-899X/413/1/012039DOI ↗Google Scholar ↗
Ahmad, S., Abdullah, M., Kanwal, A., Tahir, Z. ul R., Saeed, U. Bin, Manzoor, F., Atif, M., & Abbas, S. (2022). Offshore wind resource assessment using reanalysis data. Wind Engineering, 46(4), 1173–1186. https://doi.org/10.1177/0309524X211069384DOI ↗Google Scholar ↗
Al-Noor, N. H., & Assi, N. K. (2020). Rayleigh-Rayleigh Distribution: Properties and Applications. Journal of Physics: Conference Series, 1591(1), 0–15. https://doi.org/10.1088/1742-6596/1591/1/012038DOI ↗Google Scholar ↗
Allouhi, A., Zamzoum, O., Islam, M. R., Saidur, R., Kousksou, T., Jamil, A., & Derouich, A. (2017). Evaluation of wind energy potential in Morocco’s coastal regions. Renewable and Sustainable Energy Reviews, 72(November 2016), 311–324. https://doi.org/10.1016/j.rser.2017.01.047DOI ↗Google Scholar ↗
Argin, M., Yerci, V., Erdogan, N., Kucuksari, S., & Cali, U. (2019). Exploring the offshore wind energy potential of Turkey based on multi-criteria site selection. Energy Strategy Reviews, 23(October 2018), 33–46. https://doi.org/10.1016/j.esr.2018.12.005DOI ↗Google Scholar ↗
Benazzouz, A., Mabchour, H., El Had, K., Zourarah, B., & Mordane, S. (2021). Offshore wind energy resource in the Kingdom of Morocco: Assessment of the seasonal potential variability based on satellite data. Journal of Marine Science and Engineering, 9(1), 1–20. https://doi.org/10.3390/jmse9010031DOI ↗Google Scholar ↗
Bishoge, O. K., Zhang, L., & Mushi, W. G. (2018). clean technologies The Potential Renewable Energy for Sustainable Development in Tanzania : A Review. 70–88. https://doi.org/10.3390/cleantechnol1010006DOI ↗Google Scholar ↗
Chen, X., Foley, A., Zhang, Z., Wang, K., & O’Driscoll, K. (2020). An assessment of wind energy potential in the Beibu Gulf considering the energy demands of the Beibu Gulf Economic Rim. Renewable and Sustainable Energy Reviews, 119(November), 109605. https://doi.org/10.1016/j.rser.2019.109605DOI ↗Google Scholar ↗
Chitteth Ramachandran, R., Desmond, C., Judge, F., Serraris, J. J., & Murphy, J. (2022). Floating wind turbines: marine operations challenges and opportunities. Wind Energy Science, 7(2), 903–924. https://doi.org/10.5194/wes-7-903-2022DOI ↗Google Scholar ↗
Costoya, X., deCastro, M., Carvalho, D., Feng, Z., & Gómez-Gesteira, M. (2021). Climate change impacts on the future offshore wind energy resource in China. Renewable Energy, 175, 731–747. https://doi.org/10.1016/j.renene.2021.05.001DOI ↗Google Scholar ↗
Irena, K., Ernst, W., & Alexandros, C. G. (2021). The cost-effectiveness of CO2 mitigation measures for the decarbonisation of shipping. The case study of a globally operating ship-management company. Journal of Cleaner Production, 316, 128094. https://doi.org/10.1016/j.jclepro.2021.128094DOI ↗Google Scholar ↗
Kibona, T. E. (2020). Application of WRF mesoscale model for prediction of wind energy resources in Tanzania. Scientific African, 7, e00302. https://doi.org/10.1016/j.sciaf.2020.e00302DOI ↗Google Scholar ↗
Laurent, T., Wilfred, L., Kileo, J., & Michael, E. (2024). Different Heights Monthly and Yearly Mean Wind Speeds Investigation Using a Weibull Model : A Case of Short Ferry Route. 08(0), 4998–5020.Google Scholar ↗
Li, Y., Huang, X., Tee, K. F., Li, Q., & Wu, X. P. (2020). Comparative study of onshore and offshore wind characteristics and wind energy potentials: A case study for southeast coastal region of China. Sustainable Energy Technologies and Assessments, 39(March). https://doi.org/10.1016/j.seta.2020.100711DOI ↗Google Scholar ↗
Marcel, E. T., Mutale, J., & Mushi, A. T. (2021). Optimal Design of Hybrid Renewable Energy for Tanzania Rural Communities. 47(5), 1716–1727.Google Scholar ↗
Mazumder, G. C., Md Ibrahim, A. S., Shams, S. N., & Huque, S. (2019). Assessment of Wind Power Potential at the Chittagong Coastline in Bangladesh. Dhaka University Journal of Science, 67(1), 27–32. https://doi.org/10.3329/dujs.v67i1.54569DOI ↗Google Scholar ↗
Michael, E., Tjahjana, D. D. D. P., & Prabowo, A. R. (2021). Estimating the potential of wind energy resources using Weibull parameters: A case study of the coastline region of Dar es Salaam, Tanzania. Open Engineering, 11(1), 1093–1104. https://doi.org/10.1515/eng-2021-0108DOI ↗Google Scholar ↗
Olaofe, Z. O. (2017). Assessment of the offshore wind speed distributions at selected stations in the South-West Coast, Nigeria. International Journal of Renewable Energy Research, 7(2), 565–577. https://doi.org/10.20508/ijrer.v7i2.5439.g7031DOI ↗Google Scholar ↗
Ongaki, N. L., Maghanga, C. M., & Kerongo, J. (2021). Evaluation of the Technical Wind Energy Potential of Kisii Region Based on the Weibull and Rayleigh Distribution Models. Journal of Energy, 2021, 1–17. https://doi.org/10.1155/2021/6627509DOI ↗Google Scholar ↗
Pallikonda, K., & Rsr, G. (2020). Use of Rayleigh Distribution Method for Assessment of Wind Energy Output in Cleveland-Ohio. 1(1), 11–18. https://doi.org/10.22044/RERA.2019.1601DOI ↗Google Scholar ↗
Paraschiv, L. S., Paraschiv, S., & Ion, I. V. (2019). Investigation of wind power density distribution using Rayleigh probability density function. Energy Procedia, 157(2018), 1546–1552. https://doi.org/10.1016/j.egypro.2018.11.320DOI ↗Google Scholar ↗
Rae, G., & Erfort, G. (2020). Offshore wind energy - South Africa’s untapped resource. Journal of Energy in Southern Africa, 31(4), 26–42. https://doi.org/10.17159/2413-3051/2020/v31i4a7940DOI ↗Google Scholar ↗
Saeed, M. A., Ahmed, Z., & Zhang, W. (2020). Wind energy potential and economic analysis with a comparison of different methods for determining the optimal distribution parameters. Renewable Energy, 161, 1092–1109. https://doi.org/10.1016/j.renene.2020.07.064DOI ↗Google Scholar ↗
Salvação, N., & Guedes Soares, C. (2018). Wind resource assessment offshore the Atlantic Iberian coast with the WRF model. Energy, 145, 276–287. https://doi.org/10.1016/j.energy.2017.12.101DOI ↗Google Scholar ↗
Shu, Z. R., Li, Q. S., & Chan, P. W. (2015). Investigation of offshore wind energy potential in Hong Kong based on Weibull distribution function. Applied Energy, 156, 362–373. https://doi.org/10.1016/j.apenergy.2015.07.027DOI ↗Google Scholar ↗

[refR-1] Adedipe, O., Abolarin, M. S., & Mamman, R. O. (2018). A Review of Onshore and Offshore Wind Energy Potential in Nigeria. IOP Conference Series: Materials Science and Engineering, 413(1). https://doi.org/10.1088/1757-899X/413/1/012039DOI ↗Google Scholar ↗

[refR-2] Ahmad, S., Abdullah, M., Kanwal, A., Tahir, Z. ul R., Saeed, U. Bin, Manzoor, F., Atif, M., & Abbas, S. (2022). Offshore wind resource assessment using reanalysis data. Wind Engineering, 46(4), 1173–1186. https://doi.org/10.1177/0309524X211069384DOI ↗Google Scholar ↗

[refR-3] Al-Noor, N. H., & Assi, N. K. (2020). Rayleigh-Rayleigh Distribution: Properties and Applications. Journal of Physics: Conference Series, 1591(1), 0–15. https://doi.org/10.1088/1742-6596/1591/1/012038DOI ↗Google Scholar ↗

[refR-4] Allouhi, A., Zamzoum, O., Islam, M. R., Saidur, R., Kousksou, T., Jamil, A., & Derouich, A. (2017). Evaluation of wind energy potential in Morocco’s coastal regions. Renewable and Sustainable Energy Reviews, 72(November 2016), 311–324. https://doi.org/10.1016/j.rser.2017.01.047DOI ↗Google Scholar ↗

[refR-5] Argin, M., Yerci, V., Erdogan, N., Kucuksari, S., & Cali, U. (2019). Exploring the offshore wind energy potential of Turkey based on multi-criteria site selection. Energy Strategy Reviews, 23(October 2018), 33–46. https://doi.org/10.1016/j.esr.2018.12.005DOI ↗Google Scholar ↗

[refR-6] Benazzouz, A., Mabchour, H., El Had, K., Zourarah, B., & Mordane, S. (2021). Offshore wind energy resource in the Kingdom of Morocco: Assessment of the seasonal potential variability based on satellite data. Journal of Marine Science and Engineering, 9(1), 1–20. https://doi.org/10.3390/jmse9010031DOI ↗Google Scholar ↗

[refR-7] Bishoge, O. K., Zhang, L., & Mushi, W. G. (2018). clean technologies The Potential Renewable Energy for Sustainable Development in Tanzania : A Review. 70–88. https://doi.org/10.3390/cleantechnol1010006DOI ↗Google Scholar ↗

[refR-8] Chen, X., Foley, A., Zhang, Z., Wang, K., & O’Driscoll, K. (2020). An assessment of wind energy potential in the Beibu Gulf considering the energy demands of the Beibu Gulf Economic Rim. Renewable and Sustainable Energy Reviews, 119(November), 109605. https://doi.org/10.1016/j.rser.2019.109605DOI ↗Google Scholar ↗

[refR-9] Chitteth Ramachandran, R., Desmond, C., Judge, F., Serraris, J. J., & Murphy, J. (2022). Floating wind turbines: marine operations challenges and opportunities. Wind Energy Science, 7(2), 903–924. https://doi.org/10.5194/wes-7-903-2022DOI ↗Google Scholar ↗

[refR-10] Costoya, X., deCastro, M., Carvalho, D., Feng, Z., & Gómez-Gesteira, M. (2021). Climate change impacts on the future offshore wind energy resource in China. Renewable Energy, 175, 731–747. https://doi.org/10.1016/j.renene.2021.05.001DOI ↗Google Scholar ↗

[refR-11] Irena, K., Ernst, W., & Alexandros, C. G. (2021). The cost-effectiveness of CO2 mitigation measures for the decarbonisation of shipping. The case study of a globally operating ship-management company. Journal of Cleaner Production, 316, 128094. https://doi.org/10.1016/j.jclepro.2021.128094DOI ↗Google Scholar ↗

[refR-12] Kibona, T. E. (2020). Application of WRF mesoscale model for prediction of wind energy resources in Tanzania. Scientific African, 7, e00302. https://doi.org/10.1016/j.sciaf.2020.e00302DOI ↗Google Scholar ↗

[refR-13] Laurent, T., Wilfred, L., Kileo, J., & Michael, E. (2024). Different Heights Monthly and Yearly Mean Wind Speeds Investigation Using a Weibull Model : A Case of Short Ferry Route. 08(0), 4998–5020.Google Scholar ↗

[refR-14] Li, Y., Huang, X., Tee, K. F., Li, Q., & Wu, X. P. (2020). Comparative study of onshore and offshore wind characteristics and wind energy potentials: A case study for southeast coastal region of China. Sustainable Energy Technologies and Assessments, 39(March). https://doi.org/10.1016/j.seta.2020.100711DOI ↗Google Scholar ↗

[refR-15] Marcel, E. T., Mutale, J., & Mushi, A. T. (2021). Optimal Design of Hybrid Renewable Energy for Tanzania Rural Communities. 47(5), 1716–1727.Google Scholar ↗

[refR-16] Mazumder, G. C., Md Ibrahim, A. S., Shams, S. N., & Huque, S. (2019). Assessment of Wind Power Potential at the Chittagong Coastline in Bangladesh. Dhaka University Journal of Science, 67(1), 27–32. https://doi.org/10.3329/dujs.v67i1.54569DOI ↗Google Scholar ↗

[refR-17] Michael, E., Tjahjana, D. D. D. P., & Prabowo, A. R. (2021). Estimating the potential of wind energy resources using Weibull parameters: A case study of the coastline region of Dar es Salaam, Tanzania. Open Engineering, 11(1), 1093–1104. https://doi.org/10.1515/eng-2021-0108DOI ↗Google Scholar ↗

[refR-18] Olaofe, Z. O. (2017). Assessment of the offshore wind speed distributions at selected stations in the South-West Coast, Nigeria. International Journal of Renewable Energy Research, 7(2), 565–577. https://doi.org/10.20508/ijrer.v7i2.5439.g7031DOI ↗Google Scholar ↗

[refR-19] Ongaki, N. L., Maghanga, C. M., & Kerongo, J. (2021). Evaluation of the Technical Wind Energy Potential of Kisii Region Based on the Weibull and Rayleigh Distribution Models. Journal of Energy, 2021, 1–17. https://doi.org/10.1155/2021/6627509DOI ↗Google Scholar ↗

[refR-20] Pallikonda, K., & Rsr, G. (2020). Use of Rayleigh Distribution Method for Assessment of Wind Energy Output in Cleveland-Ohio. 1(1), 11–18. https://doi.org/10.22044/RERA.2019.1601DOI ↗Google Scholar ↗

[refR-21] Paraschiv, L. S., Paraschiv, S., & Ion, I. V. (2019). Investigation of wind power density distribution using Rayleigh probability density function. Energy Procedia, 157(2018), 1546–1552. https://doi.org/10.1016/j.egypro.2018.11.320DOI ↗Google Scholar ↗

[refR-22] Rae, G., & Erfort, G. (2020). Offshore wind energy - South Africa’s untapped resource. Journal of Energy in Southern Africa, 31(4), 26–42. https://doi.org/10.17159/2413-3051/2020/v31i4a7940DOI ↗Google Scholar ↗

[refR-23] Saeed, M. A., Ahmed, Z., & Zhang, W. (2020). Wind energy potential and economic analysis with a comparison of different methods for determining the optimal distribution parameters. Renewable Energy, 161, 1092–1109. https://doi.org/10.1016/j.renene.2020.07.064DOI ↗Google Scholar ↗

[refR-24] Salvação, N., & Guedes Soares, C. (2018). Wind resource assessment offshore the Atlantic Iberian coast with the WRF model. Energy, 145, 276–287. https://doi.org/10.1016/j.energy.2017.12.101DOI ↗Google Scholar ↗

[refR-25] Shu, Z. R., Li, Q. S., & Chan, P. W. (2015). Investigation of offshore wind energy potential in Hong Kong based on Weibull distribution function. Applied Energy, 156, 362–373. https://doi.org/10.1016/j.apenergy.2015.07.027DOI ↗Google Scholar ↗