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Hybrid Renewable Energy Systems (HRESs) have been touted as an appropriate way for supplying electricity to remote and off-grid areas in developing countries, especially in sub-Saharan Africa (SSA), where rural electrification challenges are the most pronounced. This study proposes a two-step methodology for optimizing and analyzing a stand-alone photovoltaic/wind/battery/diesel hybrid system to meet the electricity needs of Fanisua, an off-grid and remote village of northern Nigeria. In the first step, the MATLAB environment was used to run simulations and optimize the system via the genetic algorithm. Then, techno-economic and emissions analysis was carried out in the second step to compare the proposed system to the existing traditional modes of rural electrification in sub-Saharan Africa, namely, the grid-extension and diesel generator. The break-even distance parameter was adopted in the comparison with grid-extension. Besides, the hypothetical project of replacing the diesel generator by the optimal system was analyzed using the Simple Payback Period (SPP) and Net Present Value (NPV) parameters. The resulting optimal design architecture included an 89.271-kW photovoltaic array, a 100.31-W diesel generator, and 148 batteries with a total annualized cost (TAC) and cost of energy (COE) of USD 43,807 and USD 0.25/kWh, respectively. The break-even distance found was 16.2 km, while the NPV and SPP of the hypothetical project were USD 572,382 and 2.8 years, respectively. The savings in carbon dioxide (CO2) emissions of the proposed system compared to the grid extension and the diesel generator were found to be 85,401.08 kg/year and 122,062.85 kg/year, respectively. This study highlighted the role that solar PV-based HRESs could play in the sustainable electricity supply in rural areas of sub-Saharan Africa.

This paper presents a study of the transient hot plate method with simultaneous measurements of front (heated) and rear face temperatures. In contrast to the classical device, a single sample of the material to be thermally characterized is set in contact with a planar heating element and inserted between two pieces of insulating material. The purpose was to simultaneously estimate thermal effusivity and conductivity of metals in a limited time t 2 (<90 s) using a low-cost device. Heat transfer has been modelled with a quadrupole formalism to simulate the front and rear face temperatures T 0 (t) and T 2 (t). Simulation is used to fix the minimal thickness of the sample so that the front face temperature remains independent of thermal conductivity during a time t 1 > 30 s. The thermal effusivity is estimated between 0 and t 1 by minimization of the quadratic errors between the experimental curve and the simulated curve T 0 (t). The thermal conductivity is estimated between 0 and t 2 by minimization of the quadratic errors between the experimental curve and the simulated curve T 2 (t). To validate the model and the estimation process, experimental tests were realized on four samples of metals with conductivities varying from 6 to 140 W m −1 • C −1 and having typical area 44.5 × 44.5 mm 2 and thickness varying from 16.7 to 80 mm.

The aim of this paper is to show the interest of the covariance analysis applied to measurement error in the particular case of the identification of a drying characteristic curve from experimental drying data. The modelisation of drying by use of the Drying Characteristic Curve (DCC) method is first presented with usual specifications (power function, critical moisture content. . .). The experimental procedure used to obtain drying curves and the data processing are detailled and analysed. Measurements errors are identified at the first step of the DRYING TECHNOLOGY Vol. 20, No. 10, pp. 1919-1939, 2002 procedure and their effects on the estimation error of the exponent of the power function are estimated. Three different methods for estimating are presented under their matrix form: the least square method and two methods based on the hhGauss-Markovii or hhMaximum likelihoodii theorem, firstly under a simplified form suited if the estimation errors are uncorrelated and secondly under a complete form suited even if the estimation errors are correlated. These three methods are applied to experimental results obtained with ginger roots drying. The value of the exponent of the power function and then the distances between the three corresponding theoretical drying curves (representing product water content vs. time) and the experimental points are studied. It is shown that in this particular application, the complete Gauss-Markov method leads to the better fitting and that the simplified Gauss-Markov method, since it is a priori non appliable in this case where errors are correlated, gives quite better results than the oridnary least squares method. The covariance matrices of the estimation errors of reduced water content, reduced drying rate and exponent are also presented in order to show the correlations existing between the measurement errors of each variable during a drying cycle.

Purpose The purpose of this paper is contribution to estimate the potential of wind energy in Douala in Cameroon, by modeling and predicting the regime of wind. The paper deals with the analysis and comparison of seven numerical methods for the assessment of effectiveness in determining the parameters for the Weibull distribution, using wind speed data collected at Douala International Airport in Cameroon, in the period from September 2011 to May 2013, obtained by meteorological equipment belonging to the Laboratory of Energy Research of the Institute of Geological and Mining Research. Design/methodology/approach By using ANOVA, root mean square error and chi-square tests to compare the proposed methods, this study aims to determine which methods are effective in determining the parameters of the Weibull distribution for the available data, in an attempt to establish acceptable criteria for better usage of wind power in Douala, which is the economic capital and ought to have prominence in the use of renewable sources for electricity generation in Cameroon. Findings The study helps to determine that moment, empirical and energy pattern factor methods used to determine the shape parameter k and the scale parameter c of the Weibull distribution present a better curve fit with the histogram of the wind speed. This fact is clearly validated by means of the statistical tests. But, all the seven methods gave excellent performance. Then, k reaching levels ranging from 3.5 to 5.5 and c range from 1.7 to 2.4. Originality/value Then as far as we are concerned, for a significant contribution, it could be more effective to have a model for prediction of wind characteristics using wind data collected per hour, one at least three years. A comparison of results obtained from lots of other methods (seven in this case) is necessary before an efficient discussion. Standard deviations and errors between measured and predicted data must also be presented.