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For the purpose of providing cheap, affordable and reliable electrical energy to communities in need and power-up new industries and enterprises, a small onshore wind farm with an estimated capacity of 500 kW is designed and studied. With the help of a wind rose, wind resource map, and results from Weibull statistics, a potential site is selected and the wind farm is positioned along Cameroon’s coastline for maximum energy capture. Using the PARK model for wind turbine layout optimization, two different layout patterns (Checkers pattern and column pattern) are studied for the purpose of minimizing the wake effect and thereby, maximizing the output power from the farm. The Checkers model was found suitable as compared to the column model to be used on Grand Batanga, a small locality South of the city of Kribi, Cameroon. Keywords: Wind farm, Layout, Optimization

For the future installation of a wind farm in Cameroon, the wind energy potentials of three of Cameroon’s coastal cities (Kribi, Douala and Limbe) are assessed using NASA average monthly wind data for 31 years (1983–2013) and compared through Weibull statistics. The Weibull parameters are estimated by the method of maximum likelihood, the mean power densities, the maximum energy carrying wind speeds and the most probable wind speeds are also calculated and compared over these three cities. Finally, the cumulative wind speed distributions over the wet and dry seasons are also analyzed. The results show that the shape and scale parameters for Kribi, Douala and Limbe are 2.9 and 2.8, 3.9 and 1.8 and 3.08 and 2.58, respectively. The mean power densities through Weibull analysis for Kribi, Douala and Limbe are 33.7 W/m2, 8.0 W/m2 and 25.42 W/m2, respectively. Kribi’s most probable wind speed and maximum energy carrying wind speed was found to be 2.42 m/s and 3.35 m/s, 2.27 m/s and 3.03 m/s for Limbe and 1.67 m/s and 2.0 m/s for Douala, respectively. Analysis of the wind speed and hence power distribution over the wet and dry seasons shows that in the wet season, August is the windiest month for Douala and Limbe while September is the windiest month for Kribi while in the dry season, March is the windiest month for Douala and Limbe while February is the windiest month for Kribi. In terms of mean power density, most probable wind speed and wind speed carrying maximum energy, Kribi shows to be the best site for the installation of a wind farm. Generally, the wind speeds at all three locations seem quite low, average wind speeds of all the three studied locations fall below 4.0m/s which is far below the cut-in wind speed of many modern wind turbines. However we recommend the use of low cut-in speed wind turbines like the Savonius for stand alone low energy needs

The method of generalized extreme value family of distributions (Weibull, Gumbel, and Frechet) is employed for the first time to assess the wind energy potential of Debuncha, South-West Cameroon, and to study the variation of energy over the seasons on this site. The 29-year (1983–2013) average daily wind speed data over Debuncha due to missing values in the years 1992 and 1994 is gotten from NASA satellite data through the RETScreen software tool provided by CANMET Canada. The data is partitioned into min-monthly, mean-monthly, and max-monthly data and fitted using maximum likelihood method to the two-parameter Weibull, Gumbel, and Frechet distributions for the purpose of determining the best fit to be used for assessing the wind energy potential on this site. The respective shape and scale parameters are estimated. By making use of the P values of the Kolmogorov-Smirnov statistic (K-S) and the standard error (s.e) analysis, the results show that the Frechet distribution best fits the min-monthly, mean-monthly, and max-monthly data compared to the Weibull and Gumbel distributions. Wind speed distributions and wind power densities of both the wet and dry seasons are compared. The results show that the wind power density of the wet season was higher than in the dry season. The wind speeds at this site seem quite low; maximum wind speeds are listed as between 3.1 and 4.2 m/s, which is below the cut-in wind speed of many modern turbines (6–10 m/s). However, we recommend the installation of low cut-in wind turbines like the Savonius or Aircon (10 KW) for stand-alone low energy need.

A complex nonlinear model for a single-mesh helical gear train is developed by including a time-varying mesh stiffness, axial vibrations, torsional vibrations, shaft and bearing damping, generator back EMF (Electromotive Force) and gear backlashes. With the help of a time series and Fast Fourier Transform (FFT) frequency spectrum, the effects of these nonlinear terms on the wind turbine and generator rotational speeds are studied under different excitation conditions by numerically integrating the associated equations using the RK4 algorithm. Results show that for lightly damped oscillations, an extra harmonic is induced in the generator dynamics due to contributions from internal excitations. However, this extra vibration can be suppressed at higher damping. Big helical angles will generally induce heavy nonlinear vibrations in the turbine and generator; a smaller mesh frequency will induce extra noise in the generator; and the external excitation due to wind gust has a greater influence on the nonlinearity of the wind turbine dynamics as compared to the internal excitations due to static transmission errors, time-varying mesh stiffness and the generator back EMF.

To implement the European Union (EU)-Africa Green Energy Initiative in Cameroon to boost the renewable energy sector, we model the performance of a 500 W monocrystalline solar panel in major cities of Cameroon located in different climatic zones to select the best location for the installation of a solar farm. We also evaluate the contribution of seasonal and weather variability to the amount and stability of power generated by the panel using the artificial neural network (ANN). The ANN model was used to train and test the ERA5 hourly data for Bamenda. The model was then used to estimate Photovoltaic (PV) output in Douala, Yaounde, Ngaoundere, Garoua, and Maroua with a mean absolute error of 4.109 × 10−5, 4.699 × 10−5, 3.563 × 10−5, 3.106 × 10−5, and 3.083 × 10−5 kW, respectively. The results show that the ANN can capture the influence of weather variability on the generated output power. Cloud cover and rainfall are found to negatively affect the amount and stability of generated power in the lower latitude cities of Douala and Yaounde compared to the northern cities, with these effects being stronger in the rainy season than in the dry season. Garoua followed by Maroua are proving to be the best locations for installing a solar park in terms of the amount and stability of electricity generated throughout the year. The Cameroonian government, its EU partners, and other stakeholders involved in the development of solar energy in the country will be able to use the results of this study for better decision-making. [ABSTRACT FROM AUTHOR]

A theoretical scheme for an experimental implementation involving bisolitonic matter waves from an attractive Bose-Einstein condensate, is considered within the framework of a non-perturbative approach to the associate Gross-Pitaevskii equation. The model consists of a single condensate subjected to an expulsive harmonic potential creating a double-condensate structure, and a gravitational potential that induces atomic exchanges between the two overlapping post condensates. Using a non-isospectral scattering transform method, exact expressions for the bright-matter-wave bisolitons are found in terms of double-lump envelopes with the co-propagating pulses displaying more or less pronounced differences in their widths and tails depending on the mass of atoms composing the condensate. [ABSTRACT FROM AUTHOR]