This article focuses on the predictive study of electricity demand in West African countries based on the multivariate linear regression model and the ARIMA model. The objective of the study is first to establish for each country a linear regression model and ARIMA model, then to compare the two (2) models based on the MAD, RMSE and MAPE coefficients, and finally to deduce of this comparison the best valid model to establish the electricity demand prediction of the country. We have come to the conclusion that the ARIMA model is more adequate for predicting the electricity demand of most of West African countries with the exception of Gambia, Ghana, Guinea, Liberia and Nigeria where the multivariate linear regression model performs better.

The rate of access to electricity in Togo is estimated at 45% in 2018 despite the enormous solar potential with approximately 3203.1 hours that the country has. In order to remedy such a situation, the country plans, as part of its energy policy, to build a 30 MWp solar power plant with energy storage in Dapaong in northern Togo. In this article we propose a pre-feasibility study for the construction of the plant by addressing the technical, financial, environmental and social aspects. The construction of such a plant would require the installation of 112,320 solar panels of 275 Wp over an area of approximately 80 Hectares. We consider within the framework of this study, an energy storage duration of 2 h or 68 MWh thanks to the use of Lithium-ion batteries. The installation of this plant should require, according to our study, an investment of 82.4 million USD (50 billion XOF) with a cost of electricity produced by the plant of 0.16 USD/kWh (98.37 XOF/ kWh). This plant should make it possible to avoid an emission of around 30,749.76 tons of CO2 equivalent per year by producing clean electricity of around 42.7 GWh per year.

Reliable and sustainable electricity supply remains a major challenge for public infrastructure in Sub-Saharan Africa, where frequent grid interruptions and abundant solar resources create favorable conditions for hybrid renewable energy systems. This study presents a comprehensive techno-economic assessment of a hybrid photovoltaic–battery energy storage system–green hydrogen (PV–BESS–H₂) system designed for a public administrative building in Ouagadougou, Burkina Faso. The system was evaluated using an annual building load profile together with locally measured solar irradiance and ambient temperature data. Dynamic simulations were performed in MATLAB/Simulink to assess the technical performance, energy flows, economic viability, and operational behavior of the proposed system. The selected configuration consists of a 77 kWp solar PV array, an 80 kWh lithium-ion battery, a 2 Nm³ h⁻¹ electrolyzer, an 8.4 kg hydrogen storage tank, and a 10.6 kW fuel cell. Annual simulations show that the system generates 140.69 MWh of solar PV electricity and achieves a self-sufficiency ratio of 98.7% while limiting the unmet load to 1.3% of the annual electricity demand. Comparative analysis demonstrates that integrating battery and hydrogen storage substantially reduces the required storage capacities compared with standalone PV–BESS and PV–H₂ configurations. The economic assessment yields a Levelized Cost of Electricity (LCOE) of USD 0.095 kWh⁻¹ and a Levelized Cost of Hydrogen (LCOH) of USD 21.544 kg⁻¹. Sensitivity analysis identifies the discount rate, solar PV investment cost, electrolyzer cost, and project lifetime as the principal drivers of the system’s economic performance. The results demonstrate that the complementary operation of battery and hydrogen storage can enhance the technical and economic performance of renewable energy systems of public buildings in regions with abundant solar resources while providing a practical framework for the design and evaluation of hybrid PV–BESS–H₂ systems.

In sub-Saharan Africa the cost of transport is very expensive for the populations. As the car fleet is mainly made up of thermal cars, the high cost of transport is largely linked to the oil’s import. Faced with such a situation, it is important to find other means of transport in order to reduce the transport’s cost for the populations. One of the means of transport which seems to be an alternative solution is the solar electric car. But the difficulty for the solar electric car is its range. To improve car's range, it is necessary to analyze the performance of the car in driving conditions in order to understand the parameters that influence the range. Understanding and mastering these parameters will make it possible to make the best decisions to improve the car's range. In this article, we are interested in analyzing the energy performances of a solar electric car in Togo in order to understand the parameters that influence the car’s range. The simulation results show a considerable reduction in the car's range for high driving speeds, for excessive consumption of the auxiliary electrical circuits of the car, for driving the vehicle on a large slope, and when the car is transporting a large weight. The solar panel on the roof of the car is of great importance because it makes a significant contribution to the car’s range in sunny periods.

The building and public works sector is a major source of greenhouse gas emissions in developing countries due to the high material intensity of infrastructure and the dependence on imported materials. In Burkina Faso, as in most African countries, environmental assessments remain limited by the lack of locally representative emission factors, creating uncertainty in carbon accounting. This study estimates emission factors for key construction materials in Burkina Faso using a simplified cradle-to-gate Life Cycle Assessment (LCA) adapted to national technical, energy, and logistical conditions. The materials analyzed include cement, steel, flat glass, aluminium, aggregates, sand, timber, ceramic tiles, paint, bitumen, and asphalt mixes. The results reveal significant variations in the carbon intensity of construction materials in the Burkina Faso context. Aluminium exhibits the highest emission factor (12.804 tCO₂/t), followed by paint (2.50 tCO₂/t), steel (1.970 tCO₂/t), Portland cement (1.060 tCO₂/t), ceramic tiles (0.99 tCO₂/t), flat glass (0.84 tCO₂/t), bitumen (0.628 tCO₂/t), asphalt mixes (0.130 tCO₂/t), timber (0.16 tCO₂/t), aggregates (0.008 tCO₂/t), and sand (0.0013 tCO₂/t). Portland cement exhibits a slightly higher emission factor than the values commonly reported in the literature (0.85–0.95 tCO₂/t), while steel, aluminium, flat glass, ceramic tiles, bitumen, asphalt mixes, timber, and paint remain within internationally reported ranges. In contrast, sand exhibits a slightly lower emission factor than typical literature values, reflecting its limited processing requirements. Aggregates and sand show the lowest emission factors due to minimal industrial processing and greater local availability. These differences are mainly driven by import dependence, long- distance maritime and road transportation, the characteristics of the national electricity mix, and local production conditions. The study supports the development of context-specific carbon assessments and environmental databases for Burkina Faso and other West African countries.