Wind Energy Potential Assessment and Wind Turbine Performance Investigation in the Cotonou Coast (Benin Republic)

Abstract:

This paper presents a study of the monthly variability of wind energy potential at several heights and an investigation of the best fitting commercial wind turbine in the Cotonou coast (Benin Republic). The monthly Weibull parameters are calculated at 10 m and extrapolated at 30 and 50 m heights. The monthly Weibull wind power density and the wind speed carrying maximum energy are calculated at 10, 30 and 50 m. We showed that wind resource in the Cotonou coast is favorable for wind energy production at 30 and 50 m heights. The capacity factor of selected commercial wind turbines is calculated to investigate the best fitting wind turbine in the Cotonou coast. It turns out that Polaris 19-50 is the best fitting wind turbine in the selected turbines with a mean capacity factor of 0.49.

• Periodical: International Journal of Engineering Research in Africa (Volume 45)
• Pages: 89-98
• DOI: https://doi.org/10.4028/www.scientific.net/JERA.45.89
• Online since: November 2019
• Authors: Maurel Aza-Gnandji*, François Xavier Fifatin, Frédéric Dubas, Christophe Espanet, Vianou Antoine
• Keywords: Benin Republic, Capacity Factor, Weibull, Wind Energy

References

[1] M. S. Adaramola, M. Agelin­chaab, and S. S. Paul, Assessment of wind power generation along the coast of Ghana,, Energy Conversion and Management, vol. 77, no. 2014, pp.61-69, 2015. [Online]. Available: http://dx.doi.org/10.1016/j.enconman.2013.09.005.

DOI: 10.1016/j.enconman.2013.09.005

[2] S. O. Oyedepo, M. S. Adaramola, and S. S. Paul, Analysis of wind speed data and wind energy potential in three selected locations in south­east Nigeria,, pp.1-11, (2012).

DOI: 10.1201/b18529-3

[3] B. M. Mukulo, J. M. Ngaruiya, and J. N. Kamau, Determination of wind energy potential in the Mwingi­Kitui plateau of Kenya,, Renewable Energy, vol. 63, pp.18-22, 2014. [Online]. Available: http://dx.doi.org/10.1016/j.renene.2013.08.042.

DOI: 10.1016/j.renene.2013.08.042

[4] M. Mpholo, T. Mathaba, and M. Letuma, Wind profile assessment at Masitise and Sani in Lesotho for potential off­grid electricity generation,, Energy Conversion and Management, vol. 53, no. 1, pp.118-127, 2012. [Online]. Available: http://dx.doi.org/10.1016/j.enconman. 2011.07.015.

DOI: 10.1016/j.enconman.2011.07.015

[5] A. Mostafaeipour, A. Sedaghat, M. Ghalishooyan, Y. Dinpashoh, M. Mirhosseini, M. Se, and M. Pour­rezaei, Evaluation of wind energy potential as a power generation source for electric­ ity production in Binalood , Iran,, vol. 52, pp.222-229, (2013).

DOI: 10.1016/j.renene.2012.10.030

[6] A. Oluleye and S. B. Ogungbenro, Estimating the wind energy potential over the coastal stations of Nigeria using power law and diabatic methods,, vol. 5, no. November, pp.985-992, (2011).

[7] G. A. Tolessa, Assessment of wind power Potential at Zeway , Central Rift Valley,, vol. 2, no. 4, pp.11-18, (2013).

DOI: 10.9790/2402-0241118

[8] A. K. Azad, M. G. Rasul, and T. Yusaf, Statistical Diagnosis of the Best Weibull Methods for Wind Power Assessment for Agricultural Applications,, pp.3056-3085, (2014).

DOI: 10.3390/en7053056

[9] S. Mohammed, A. Benmansour, N. Ghellai, M. Benmedjahed, M. Abdellatif, and T. Hellal, Temporal assessment of wind energy resource at four locations in Algerian Sahara,, Energy Conversion and Management, vol. 76, pp.654-664, 2013. [Online]. Available: http://dx.doi.org/10.1016/j.enconman.2013.07.086.

DOI: 10.1016/j.enconman.2013.07.086

[10] Ali Naci Celik, A statistical analysis of wind power density based on the Weibull and Rayleigh models at the southern region of Turkey,, vol. 29, pp.593-604, (2003).

DOI: 10.1016/j.renene.2003.07.002

[11] S. A. Ahmed, M. A. Omer, and A. A. Abdulahad, Analysis Of Wind Power Density In Azmar Mountain (Sulaimani Region­ North Iraq),, vol. 2, no. 5, pp.1403-1407, (2012).

[12] T. P. Chang, Wind Speed and Power Density Analyses Based on Mixture Weibull and Maximum Entropy Distributions,, pp.39-46, (2010).

[13] B. S. Premono, D. Tjahjana, S. Hadi, B. Kristiawan, M. Anwar, A. T. Wijayanta, S. Hadi, D. Danardono, D. Ariawan, J. Triyono, and others, Wind energy potential assessment to es­ timate performance of selected wind turbine in northern coastal region of Semarang­Indonesia,, vol. 1788, p.030026, (2017).

DOI: 10.1063/1.4968279

[14] A. Ilinca, E. McCarthy, J.­L. Chaumel, and J.­L. Rétiveau, Wind potential assessment of Quebec Province," Renewable Energy, vol. 28, no. 12, pp.1881-1897.

DOI: 10.1016/s0960-1481(03)00072-7

[16] A. B. Akpo, J. C. T. Damada, H. E. V. Donnou, B. Kounouhewa, and C. N. Awanou, Evalua­ tion de la production énergétique d'un aérogénérateur sur un site isolé dans la région côtière du Bénin,, Revue des Energies Renouvelables, vol. 18, no. 3, pp.457-468, (2015).

[17] Wyoming Weather Web., [Online]. Available: http://weather.uwyo.edu\/upperair/.

[18] Geography of Benin," Aug. 2016, page Version ID: 736815877. [Online]. Available: https://en.wikipedia.org/w/index.php,title=\Geography_of_Benin&oldid=736815877.

[19] B. Safari and J. Gasore, A statistical investigation of wind characteristics and wind energy potential based on the Weibull and Rayleigh models in Rwanda,, Renewable Energy, vol. 35, no. 12, pp.2874-2880, Dec. 2010. [Online]. Available: http://linkinghub.elsevier.com/retrieve/ pii/S0960148110001990.

DOI: 10.1016/j.renene.2010.04.032

[20] I. Fyrippis, P. J. Axaopoulos, and G. Panayiotou, Wind energy potential assessment in Naxos Island, Greece,, Applied Energy, vol. 87, no. 2, pp.577-586, 2010. [Online]. Available: http://dx.doi.org/10.1016/j.apenergy.2009.05.031.

DOI: 10.1016/j.apenergy.2009.05.031

[21] E. S. Takle and J. M. Brown, Note on the Use of Weibull Statistics to Characterize Wind­Speed Data,, Journal of Applied Meteorology, vol. 17, no. 4, pp.556-559, Apr. (1978).

DOI: 10.1175/1520-0450(1978)017<0556:notuow>2.0.co;2

[22] J. V. Seguro and T. W. Lambert, Modern estimation of the parameters of the Weibull wind speed distribution for wind energy analysis,, vol. 85, (2000).

DOI: 10.1016/s0167-6105(99)00122-1

[23] S. Vela, A review of wind speed probability distributions used in wind energy analysis Case studies in the Canary Islands,, vol. 13, pp.933-955, (2009).

DOI: 10.1016/j.rser.2008.05.005

[24] M. Nedaei, E. Assareh, and M. Biglari, An extensive evaluation of wind resource using new methods and strategies for development and utilizing wind power in Mah­shahr station in Iran,, Energy Conversion and Management, vol. 81, no. June 2012, pp.475-503, 2014. [Online]. Available: http://dx.doi.org/10.1016/j.enconman.2014.02.025.

DOI: 10.1016/j.enconman.2014.02.025

[25] M. Adaramola and O. Oyewola, Evaluating the performance of wind turbines in selected locations in Oyo state, Nigeria,, Renewable Energy, vol. 36, no. 12, pp.3297-3304, Dec. (2011).

DOI: 10.1016/j.renene.2011.04.029

[26] O. Ohunakin, M. Adaramola, and O. Oyewola, Wind energy evaluation for electricity generation using WECS in seven selected locations in Nigeria,, Applied Energy, vol. 88, no. 9, pp.3197-3206, Sep. 2011. [Online]. Available: http://linkinghub.elsevier.com/retrieve/ pii/S0306261911001796.

DOI: 10.1016/j.apenergy.2011.03.022

[27] S. Mathew, Analysis of wind regimes for energy estimation,, vol. 25, pp.381-399, (2002).

[28] E. K. Akpinar and S. Akpinar, An assessment on seasonal analysis of wind energy characteris­ tics and wind turbine characteristics,, vol. 46, pp.1848-1867, (2005).

DOI: 10.1016/j.enconman.2004.08.012

[29] S. Mathew, Wind energy: fundamentals, resource analysis, and economics. Berlin ; New York: Springer, 2006, oCLC: ocm79439670.

[30] Upwind International AG ­ Ayitepa Wind Farm., [Online]. Available: http: //upwindinternational.com/wind­energy/ayitepa­wind­farm/ayitepa­wind­farm.php.