ASSESSMENT OF WIND ENERGY POTENTIAL FOR ACCRA, GHANA USING TWO PARAMETER WEIBULL DISTRIBUTION FUNCTION
Abstract
This study investigates the predictive ability of two-parameter Weibull distribution function for Accra, Ghana using fifteen years (2002 – 2016) meteorological parameter of monthly mean wind speed data. The monthly and annual averaged wind speed was estimated to be . The annual mean values of the maximum energy – carrying wind speed and most probable wind speed were found to be and respectively. The two parameters of the Weibull statistics found in this study for Accra were within the range for the shape parameters and for the scale parameters. The results of the wind power density indicated that the location has a good prospect for wind power generation with the highest value of found in September, 2006. The linear relationship between the monthly mean wind power density and mean wind speed shows that a perfect correlation with coefficient of correlation of 99.3 % exists between them. The results obtained from this study revealed that the Weibull function was found appropriate for analyzing measured wind speed data and in predicting the wind power density for the region under investigation. Therefore, Accra has an excellent prospect for wind power generation
References
Acakpovi, A., Issah, M. B., Fifatin, F. X and Michael, M. B (2017). Wind velocity extrapolation in Ghana by Weibull probability density function. Wind Engineering 1–13 DOI: 10.1177/0309524X17723205
Ahmed, S. A (2011). Investigation of Wind Characteristics and Wind Energy Potential at RasGhareb Egypt. Renewable and Sustainable Energy Reviews., 15, 2750 – 2755. https://doi.org/10.1016/j.rser.2011.04.003
Ajavon, A. S. A., Salami, A. A., Kodjo, M. K and Bédja, K.-S (2015). Comparative characterization study of the variability of wind energy potential by wind direction sectors for three coastal sites in Lomé, Accra and Cotonou. Journal of Power Technologies., 95(2), 134–142.
Akpootu, D. O and Iliyasu, M. I (2017). Estimation of Tropospheric Radio Refractivity and Its Variation with Meteorological Parameters over Ikeja, Nigeria. Journal of Geography, Environment and Earth Science International., 10(1): 1-12. DOI: 10.9734/JGEESI/2017/32534
Akpootu, D. O., Idris, M., Nouhou, I., Iliyasu, M. I, Aina, A. O., Abdulsalami, M. J., Ohaji, D. E and Abubakar, M. B (2021). Estimation and Investigation of the Variability of Tropospheric Radio Refractivity and Radio Field Strength over Accra, Ghana. Journal of Atmospheric & Earth Science., 5: 026. DOI: 10.24966/AES-8780/100026
Akpootu, D. O., Okpala, C. N., Iliyasu, M. I., Ohaji, D. E., Idris, M., Abubakar, M. B., Aina, A. O and Abdulsalami, M (2022). Investigation of wind power potential in two selected locations in the Coastal Region of Nigeria. SCIENCE FORUM (JOURNAL OF PURE AND APPLIED SCIENCES) 22(1), 95 – 103. http://dx.doi.org/10.5455/sf.profdon03
Arslan, O (2010). Technoeconomic analysis of electricity generation from wind energy in Kutahya Turkey. Energy., 35, 20-131 https://doi.org/10.1016/j.energy.2009.09.002
Ayenagbo, K., Kimatu, J. N and Rongcheng, W (2011). A model for a sustainable energy supply strategy for the social-leconomic development of Togo. Journal of Economics and International Finance., 3(6), 387–398.
Brew-Hammond, A and Kemausuor, F (2009). Energy for all in Africa? to be or not to be?! Current Opinion in Environmental Sustainability., 1(1), 83–88.
Carta, J. A., Ramırez, P and Velázquez, S (2009). A review of wind speed probability distributions used in wind energy analysis: case studies in the Canary Islands. Renewable Sustainable Energy Reviews., 13, 933-55. https://doi.org/10.1016/j.rser.2008.05.005
Celik, A. N. (2003). Energy output estimation for small-scale wind power generators using Weibull representative wind data. Journal of Wind Engineering and Industrial Aerodynamics., 91(5), 693–707.
Deichmann, U., Meisner, C., Murray, S and Wheeler, D (2011). The economics of renewable energy expansion in rural Sub- Saharan Africa. Energy Policy., 39(1), 215–227.
Dikko, I and Yahaya, D. B (2012). Evaluation of Wind Power Density in Gombe, Yola and Maiduguri, North Eastern Nigeria. Journal of Research in Peace, Gender and Development., 2(5), 115-122.
Guenoukpati, A., Salami, A.A., Kodjo, M.K., and Napo, K (2020). Estimating Weibull Parameters for Wind Energy Applications Using Seven Numerical Methods: Case studies of Three Coastal Sites in West Africa. International Journal of Renewable Energy Development., 9(2), 217-226 https://doi.org/10.14710/ijred.9.2.217-226
Jowder, F. A. L. (2009). Wind power analysis and site matching of wind turbine generators in Kingdom of Bahrain. Applied Energy., 86(4), 538–545.
Justus, C. G., Hargraves, W. R., Mikhail, A and Graber, D (1978). Methods for estimating wind speed frequency distributions. Journal of Applied Meteorology., 17(3), 350 – 353.
Keyhani, A., Ghasemi-Varnamkhasti, M., Khanali, M and Abbaszadeh, R (2010). An assessment of wind energy potential as a power generation source in the capital of Iran, Tehran. Energy., 35(1), 188–201.
Lipson, C and Sheth, N. J (1973). Statistical Design and Analysis of Engineering Experiments. McGraw Hill, New York.
Mentis, D., Hermann, S., Howells, M., Welsch, M and Siyal, S. H (2015). Assessing the technical wind energy potential in Africa a GIS-based approach. Renewable Energy., 83, 110–125.
Mostafaeipour, A., Sedaghat, A., Dehghan-Niri, A. A and Kalantar, V (2011). Wind energy feasibility study for city of Shahrbabak in Iran. Renewable and Sustainable Energy Reviews., 15(6), 2545–2556.
Noviadi, E. T and Adnan, A (2018). Identification the Potential Wind Speed for Energy in Pekanbaru Using Some Simple Mixture Distribution Modelling. Applied Mathematical Sciences., Vol. 12, no. 29, 1393 – 1401. https://doi.org/10.12988/ams.2018.810139
Nze-Esiaga, N and Okogbue, E. O (2014). Assessment of Wind Energy Potential as a Power Generation Source in Five Locations of South Western Nigeria. Journal of Power and Energy Engineering., 2, 1-13. http://dx.doi.org/10.4236/jpee.2014.25001
Olomiyesan, B. M (2018). Performance evaluation of Weibull function for wind data analysis in two selected locations in North-Western, Nigeria. International Journal of Physical Research., 6(1). 18 – 24.
Oyedepo, S. O., Adaramola, M. S and Paul, S. S (2012). Analysis of Wind Speed Data an Wind Energy Potential in Three Selected Locations in South-East Nigeria. International Journal of Energy and Environmental Engineering., 3(7), https://doi.org/10.1186/2251-6832-3-7
Ridao, A.R., Garcia, E.H., Escobar, B.M and Toro, M.Z (2007). Solar energy in Andalusia (Spain): Present state and prospects for the future. Renewable & Sustainable Energy reviews., 11(1), 148–161.
Safari, B. (2011). Modeling wind speed and wind power distributions in Rwanda. Renewable and Sustainable Energy Reviews., 15(2), 925–935.
Seth, M and Modjinou, M (2012). Opportunities in the Ghana Renewable Energy Act 2011, Act 832.
Wikipedia (2021) Accessed online on 8th August, 2021.
Copyright (c) 2022 FUDMA JOURNAL OF SCIENCES
This work is licensed under a Creative Commons Attribution 4.0 International License.
FUDMA Journal of Sciences
