Wind energy of Cameroon by determining Weibull parameters: potential of a environmentally friendly energy

Cameroon, a country of the Sub-Saharan Africa, faces a challenging problem of access to electricity. Its overall electricity production in 2012 was 305 kWh per inhabitant for gross electricity consumption of 6.2 TWh. Recently, the Cameroonian government launched many wind farm installation projects among which a 42-MW wind farm in Mount Bamboutos hills in 2015 that would expand to 80 MW. Therefore, there is a necessity for a clear assessment of the wind potential of the country. In this study, thirteen numerical methods were used to estimate the Weibull parameters to assess the wind potential. The wind speed data were collected in a period of 38 years (from January 1982 to December 2019) from the NASA website. The effectiveness of each method was performed through the computation of relative power density error, the coefficient of determination (R2), the root mean square error and Chi-square test (χ2). The results suggested that the best method to estimate the wind power density is the energy density method, followed by the novel energy pattern factor method. It was found that the maximum likelihood method was the best in three sites. The graphical method was the effective method to estimate the cumulative data frequency distribution, followed by the empirical method of Lysen. The wind power densities were found to be of class 1 and favorable for small-scale applications like livestock watering, farm irrigation and water pumping.