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Purpose The purpose of this paper is to evaluate the wind energy potential of Mount Bamboutos in Cameroon by comparing nine numerical methods in determining Weibull parameters for the installation of a sustainable wind farm. Design/methodology/approach By using statistical analysis, the analysis of shape and scale parameters, the estimation of the available wind power density and wind direction frequency distributions, the objective of this paper is to compare nine numerical methods in estimating Weibull parameters for the installation of a sustainable wind farm in Mount Bamboutos, Cameroon. Findings The results suggested that the minimum and maximum values of the standard deviation occurred in the months of May and November 2016, respectively. The graphical method appeared to be the most effective method with the maximum value of variance and minimum values of chi-square and RMSE. The scale factor parameter values indicated that Mount Bamboutos hills were a potential site for electricity generation. The analysis of wind power density showed that it reached the maximum and minimum values in February and September, respectively. The wind direction frequency distributions showed that the prevailing wind directions were North-East. Originality/value The wind energy potential of Mount Bamboutos in Cameroon was performed by using nine numerical methods. Therefore, it could be effective to have a prediction model for the wind speed profile. The analysis of wind power density showed that it reached the maximum and minimum values in February and September, respectively. The wind direction frequency distributions showed that the prevailing wind directions were North-East.

In this paper, a stability analysis of a hybrid nanofluid flow between two parallel and stationnary plates filled with a porous medium was investigated. The hybrid nanofluid is composed of water as regular fluid, copper ( Cu ) and alumina ( Al 2 O 3 ) as nanoparticles. A mathematical modeling of the problem was developed by taking account other effects such as aspiration (suction/injection) and magnetic field. An eigenvalue differential equation namely the modified Orr-Sommerfeld equation governing the stability of the flow was derived and solved numerically by spectral collocation method with expansions in Chebyshev polynomials. The effect of the density of particles, suction/injection Reynolds number, Hartmann number, Darcy number and volume fraction on the flow stability was examined and presented. It was found the following: the Darcy number affects the stability of the flow, the suction/injection reduces the drag and the transition is delayed/prevented, the magnetic field makes the dissipation very important because the kinetic energy of the electrically conductive fluid is absorbed by the Lorentz force, and the volume fraction and the density of nanoparticles increased the inertia of the fluid which decreased the speed gradient and damped the disturbances.

Purpose This paper aims to investigate the profile of the wind speed of a Cameroonian city for the very first time, as there is a growing trend for new wind energy installations in the West region of Cameroon. Two well-known artificial neural networks, namely, multi-layer perceptron (MLP) and nonlinear autoregressive network with exogenous inputs (NARX), were used to model the wind speed profile of the city of Bapouh in the West-region of Cameroon. Design/methodology/approach In this work, the profile of the wind speed of a Cameroonian city was investigated for the very first time since there is a growing trend for new wind energy installations in the West region of Cameroon. Two well-known artificial neural networks namely multi-layer perceptron (MLP) and nonlinear autoregressive network with exogenous inputs (NARX) were used to model the wind speed profile of the city of Bapouh in the West-region of Cameroon. The meteorological data were collected every 10 min, at a height of 50 m from the NASA website over a period of two months from December 1, 2016 to January 31, 2017. The performance of the model was evaluated using some well-known statistical tools, such as root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). The input variables of the model were the mean wind speed, wind direction, maximum pressure, maximum temperature, time and relative humidity. The maximum wind speed was used as the output of the network. For optimal prediction, the influence of meteorological variables was investigated. The hyperbolic tangent sigmoid (Tansig) and linear (Purelin) were used as activation functions, and it was shown that the combination of wind direction, maximum pressure, maximum relative humidity and time as input variables is the best combination. Findings Maximum pressure, maximum relative humidity and time as input variables is the best combination. The correlation between MLP and NARX was computed. It was found that the MLP has the highest correlation when compared to NARX. Originality/value Two well-known artificial neural networks namely multi-layer perceptron (MLP) and nonlinear autoregressive network with exogenous inputs (NARX) were used to model the wind speed profile.

The aim of this paper is to analyze and compare efficiently of 10 (ten) numerical methods namely, the empirical method of Justus (EMJ), the empirical method of Lysen (EML), the method of moments (MoM), the graphical method (GM), the Mabchour’s method (MMab), the energy pattern factor method (EPFM), the maximum likelihood method (MLM), the modified maximum likelihood method (MMLM), the equivalent energy method (EEM), and the alternative maximum likelihood method (AMLM) in order to estimate Weibull parameters for wind energy potential. They were performed by using wind speed data collected in the meteorological station of Bafoussam city, in the west region of Cameroon, in the period from 2007 to 2013. The results of this study obtained from statistical analysis show that the MLM presents relatively more excellent ability throughout the simulation tests, followed by EEM, EPFM and EMJ respectively. They also demonstrated that EEM presented minimum error in estimating the monthly wind power density and that the wind potential of Bafoussam city can be interesting for some applications such as rural electrification and water pumping in agriculture.

In this paper, the performance of micro wind turbine (MWT) is evaluated by taking into account low average wind speed cities in the West Cameroon region such as Bandjoun and Bangangte. The k-ϵ turb...