Battery-coupled PV systems for residential applications in Benin: An optimal sizing and cost-effectiveness analysis

Despite the high amount of renewable energy resources available in Benin, the share of electricity generated from renewable energy (RE) sources is still low with high dominance of conventional energy resources and regular power shortage. This study examined autonomous photovoltaic systems with batteries as an alternative to Benin's public electricity grid. Five different load profiles with the same daily energy consumption were investigated, and their effect on the PV/battery system cost was estimated. The PV/battery system's sizing was optimized using decision criteria such as cost of energy (COE) and loss of power supply probability (LPSP). The multi-objective problem was solved using the non-dominated genetic sorting algorithm II (NSGA-II) metaheuristic. The effect of geographical location on the cost of PV/battery systems was also investigated. The findings revealed that load profiles that prioritized deferred energy consumption had higher energy costs than those that prioritized direct consumption from solar panels. The PV/battery systems proved to be less expensive for consumers than the tariffs currently charged by Benin's national grid, regardless of geographical location. The widespread use of these systems could significantly reduce greenhouse gas emissions. Consequently, substituting the electricity grid with photovoltaic/battery systems for the five load profiles investigated in this research could effectively avoid the release of around 1.94 tons of carbon dioxide into the atmosphere.