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It is commonly recommended to incorporate diesel generators into distributed hybrid renewable energy systems (HRESs) to lower the system's total cost and make the generated electricity affordable. Due to the environmental and economic issues associated with fossil fuel use, biomass power technologies (BPT) appear to be an attractive alternative to diesel generators. The HOMER software was used to model, simulate, and optimise two photovoltaic/wind/battery systems integrated with different BPT (anaerobic digestion or gasification) to satisfy the electrical needs of Babadam, a remote community in northern Cameroon. The results indicated that the anaerobic digester integrated system's overall optimal architecture included a 98.1 kW photovoltaic array, a 30 kW biogas generator, and 200 batteries, with a cost of energy (COE) of $0.347/kWh. On the other hand, the gasifier integrated option is made up of an 81.8 kW photovoltaic array, a 15 kW syngas generator, and 200 batteries and has a COE of $0.319/kW. Additionally, compared to the PV/Wind/Battery system, integrating the biogas (resp. syngas) generator showed a potential COE decrease of 29% (resp. 40%). The sensitivity analysis highlighted the validity of this COE reduction potential everywhere in sub‐Saharan Africa, leading to the conclusion that integrating BPT into HRESs can effectively contribute to Sustainable Development Goal 7. [ABSTRACT FROM AUTHOR]

Due to environmental and economic drawbacks of fossil fuels, global renewable energy (RE) capacity has increased significantly over the last decade. Solar photovoltaic (PV) is one of the fastest-growing RE technologies. Selecting an appropriate site is one of the most critical steps in utility-scale solar PV planning. This paper aims at proposing a rational multi-criteria decision-making (MCDM) approach based on the Brown–Gibson model for optimal site selection for utility-scale solar PV projects. The proposed model considers the project's net present value (NPV) along with seven suitability factors and six critical (constraint) factors. The RETScreen software was applied in calculating the NPV, the simple payback period and the carbon emission savings of the project at each alternative site. The weights of the suitability factors were determined using the analytical hierarchy process. Applied to the case study of finding the best location for a 5 MW solar PV project in northern Cameroon, the optimization results showed that Mokolo was the optimal location. The sensitivity analysis results revealed that the rankings of alternative sites based on the project's NPV and the proposed model are not consistent. Compared to the traditional MCDM approaches, the proposed model provides decision-makers with a more practical thinking method in the optimal location process of utility-scale solar projects. [ABSTRACT FROM AUTHOR]