The aim of this work is to study the influence of the physicochemical characteristics of neem seeds, according to their mass and oil content, on the production of biodiesel. After the physical characterization of the seeds and extraction of the oil (triglycerides), biodiesel was produced from crude neem seed oil by transesterification with ethanol in the presence of sodium hydroxide. This study shows that the physicochemical characteristics of these seeds vary according to the origin of the samples. The seeds from Zidim, with a mass average of 200 seeds evaluated at 141.36 g and an almond content of 40.70%, have better characteristics compared to those collected in the city of Maroua, with average values evaluated at 128.00 g and 36.05%, respectively. Almonds have an average lipid content of 53.98 and 56.75% for the Maroua and Zidim samples, respectively. This study also reveals that neem oil, by its physicochemical characteristics, has a satisfactory quality for a valorization in the production of biodiesel. However, its relatively high free fatty acid content is a major drawback, which leads to a low yield of biodiesel, evaluated on average at 89.02%, and requires a desacidification operation to improve this yield. The analysis of biodiesel indicates physicochemical characteristics close and comparable to those of petrodiesel, particularly in terms of calorific value, density, kinematic viscosity, acid value, evaluated at 41.00 MJ/kg, 0.803, 4.42 cSt, and 0.130 mg/g, respectively.

A techno-economic study of a hybrid PV/Battery/Grid-connected system for energy supply is carried out in this paper to respond to the problem of electrical load shedding. An optimal design of the system is realized thanks to a double-objective optimization based on a proposed operational strategy of the system and on Firefly Algorithm (FA). The system is designed for household energy supply in three different towns of the northern part of Cameroon. For different LPSP (Loss of Power Supply Probability), the double objective simulation determines the optimal configurations of the system with their related cost. The optimal and reliable PV/Battery subsystem configuration corresponding to LPSP of 0% obtained for one household is composed for the towns of Maroua and Garoua by 8 PV modules and a battery capacity of 11.304 kWh with 1-day autonomy. For the town of Ngaoundéré, it is composed by 10 PV modules and battery capacity of 11.304 kWh with 1-day autonomy. The related investment costs corresponding to these optimal configurations are USD 6225.6 for Maroua and Garoua and USD 7136.6 for Ngaoundéré. The great proportion of the monthly energy demand consumed by the load is provided by the PV/Battery system. The monthly PV/Battery energy represents 60.385% to 72.546% of the load consumed in Maroua, 58.371% to 71.855% of the load consumed in Garoua, and 61.233% to 74.160% of the load consumed in Ngaoundéré. The annual main grid energy consumed for one household is 1299.524 kWh in Maroua, 1352.818 kWh in Garoua, and 1260.876 kWh in Ngaoundéré. Moreover, the annual PV/Battery energy consumed for one household is 1580.730 kWh in Maroua, 1527.815 kWh in Garoua, and 1619.530 kWh in Ngaoundéré. Thus, the PV/Battery system, by reducing the grid energy consumption, acts as the principal source of energy of the whole system. The time the PV/Battery/Grid-connected system needs to be economically more advantageous than the electric grid without blackouts is 17 years for Maroua and 18 years for both Garoua and Ngaoundéré. It is demonstrated in this paper that the hybrid PV/Battery/Grid-connected system is an effective solution for electrical load shedding in sub-Saharan zones. This system is very useful for grid energy consumption reduction. For a long-term investment, the PV/Battery/Grid-connected system is more economically advantageous than the main grid alone.

Different configurations of on/off-grid-connected hybrid renewable energy systems (HRESs) are analyzed and compared in the present research study for optimal decision making in Sub-Saharan Africa, facing the problems of electricity deficit. A multi-criteria analysis is performed for this purpose using MATLAB software for simulation. The obtained results show that the levelized cost of energy (LCOE) corresponding to 0% power supply deficit probability (PSDP) is 0.0819 USD/kWh, 0.0925 USD/kWh, 0.3979 USD/kWh, 0.3251 USD/kWh, 0.1754 USD/kWh, 0.1641 USD/kWh, 0.5385 USD/kWh, and 1.4515 USD/kWh, respectively, for the Grid-PV/Wind/Battery, Grid-PV/Battery, Grid-Wind/Battery, Grid-Wind, PV/Wind/Battery, PV/Battery, Wind/Battery, and stand-alone Wind systems. The CO₂ emissions are 14,888.4 kgCO₂/year, 16,916.6 kgCO₂/year, 13,139.7 kgCO₂/year, 6430.4 kgCO₂/year, 11,439 kgCO₂/year, 14,892.5 kgCO₂/year, 10,252.6 kgCO₂/year, and 1621.5 kgCO₂/year, respectively, for the aforementioned systems. It is found that the Grid-connected PV/Wind/Battery is the most cost-effective system leading to a grid energy cost reduction of 30.89%. Hybridization of different renewable energy sources (RESs) could significantly improve the electricity cost and reduce the CO₂ emissions. However, this improvement and this reduction depend on the used RES and the system configuration. On-grid-connected HRESs are more cost-effective than off-grid-connected HRES. The least polluting energy system is the stand-alone Wind system, which allows a reduction in the grid CO₂ emissions by 93.66%. The sensitivity analysis has proven that the long-term investment, the decrease in the battery cost, and the decrease in the discount rate could lead to the reduction in the LCOE.

Sustainable future development relies on solar radiation, which is the main source of renewable energy. Thus, in this article, the monthly average global solar irradiation of four sites in the Sudanian zone region of Chad is estimated using different empirical models. The data used in this study were collected at the General Directorate of Meteorology of Chad. The reliability and accuracy of six models estimating global solar radiation were validated and compared by statistical indicators identifying the most accurate model. The results obtained show that the Allen model has the best performance for the Moundou site (5.760 kWh/m²/d, R2=0.843), the Angstrom Prescott model for the Sarh sites (5.658 kWh/m²/d, R2=0.805) and Pala (5.793 kWh/m²/d, R²=0.889), the Sabbagh model for the Bongor site (5.657 kWh/m²/d, R²=0.888). These models are validated against NASA data. The results show that the Sudanian zone of Chad has good solar potential and is therefore suitable for possible exploitation.

A techno-economic study of a stand-alone PV water pumping system for water supply is done in this paper. An optimal design of the system is realized thanks to a double-objective optimization based on a proposed operational strategy of the system and on firefly algorithm (FA). The two objective functions simulated simultaneously using FA are: the function defining the cost of water (COW) and the function which defines the loss of water supply probability (LWSP). The system is designed to supply water to around 328 households in Cameroon, each composed by an average of six (06) persons. For different LWSP, the double-objective simulation determines the optimal configurations of the system with their related cost. The optimal and reliable (LWSP of 0%) system configuration obtained is composed by a number of 7 PV modules, a reservoir volume of 98.4 m³ with 2 days autonomy, a total dynamic head of 40 m, and a pump power of around 1 kW. The related COW corresponding to this configuration is 0.1185 $/m³, and the total investment cost is 27,506 $. The sensitivity analysis of the system revealed that the PV size, the volume of reservoir storage, and the efficiency of the pump influence the system both technically and economically, whereas the total dynamic head only influences the system economically. The validation of the optimized system has been done by comparison with manufacturer datasheets. It is demonstrated in this paper that the techno-economic analysis of energy systems based on multi-objective optimization using firefly algorithm is a powerful tool for decision-making.