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International audienceIn this work 28 years of wind data measured at 10m above ground level (AGL) from Maroua meteorological station is utilized to assess the potential of wind energy at exposed ridges tops of mountains surrounding the city of Maroua. The aim of this study is to estimate the cost of wind-generated electricity using six types of wind turbines (50 to 2000 kW). The Weibull distribution function is employed to estimate Weibull shape and scale parameters using the energy pattern factor method. The considered wind shear model to extrapolate Weibull parameters and wind profiles is the empirical power law correlation. The results show that hilltops in the range of 150-350m AGL in increments of 50 fall under Class 3 or greater of the international system of wind classification and are deemed suitable to outstanding for wind turbine applications. A performance of the selected wind turbines is examined as well as the costs of wind-generated electricity at the considered hilltops. The results establish that the lowest costs per kWh are obtained using YDF-1500-87 (1500 kW) turbine while the highest costs are delivered by P-25-100 (90 kW). The lowest costs (US$) per kWh of electricity generated are found to vary between a minimum of 0.0294 at hilltops 350m AGL and a maximum of 0.0366 at hilltops 150m AGL with corresponding energy outputs that are 6 125 and 4 932 MWh respectively. Additionally the matching capacity factors values are 38.05% at hilltops 150m AGL and 47.26% at hilltops 350m AGL. Furthermore YDF-1500-87 followed by Enercon E82-2000 (2000 kW) wind turbines provide the lowest cost of wind generated electricity and are recommended for use for large communities. Medium wind turbine P-15-50 (50 kW) despite showing the best coefficients factors (39.29% and 48.85% at hilltops 150 and 350m AGL in that order) generates electricity at an average higher cost/kWh of US$0.0547 and 0.0440 at hilltops 150 and 350m AGL respectively. P-15-50 is deemed a more advantageous option for off-grid electrification of small and remote communities

This paper explores the performance analysis of five Weibull distribution methods to select the more accurate estimation for the Weibull parameters using time-series of measured daily wind speed data collected in three localities in the Adamaoua region of Cameroon. The Weibull distribution with two parameters, the shape k, and the scale C, was specifically considered to be a good quality probabilistic model for wind speed distributions. The five Weibull distribution methods proved to be effective in evaluating the parameters of the Weibull distribution. This fact was supported by the values of the root mean square error, the Chi-square (χ²) and the correlation coefficient R² which showed magnitudes very close to each other. In addition, the comparison between wind speed distributions predicted by the Weibull methods and wind speed distributions measured locally, suggested that the most accurate two-parameter Weibull distribution method is the Energy Pattern Factor Method (EPF). As a result, to reduce uncertainties related to the wind energy output calculation, the EPF is recommended for estimating wind speed distributions.

In order to help designers, consider disassembly in their design activities, a method for evaluation of product disassembly is proposed. Criteria characterizing the disassembility of a product are identified. Each criterion is assigned a coefficient, thus proposing an index of easy fixations (f If) as a design indicator to evaluate the level of disassembly of a solution generated by the designer. This index is calculated as a weighted average of the indicators for evaluating the disassembility of the product. The proposed method uses information such as the list of subsets or parts, the component tree, the part geometry, the functional links between components and parts, the properties of the components. It has been tested on one product: the soy roaster.