Techno–Economic Viability of Commercial-Scale Photovoltaic Solar-Powered Mini–Grid Systems in Sub-Saharan Africa

Abstract

Sub-Saharan Africa is currently the darkest part of the world socioeconomically despite having the most solar energy potential globally with half a billion people lacking access to electricity and Nigeria contributing the biggest share resulting in huge unemployment rates, famine, infant mortality, insecurity, low human development index, and political instability among other hydra headed problems. This research aims to probe the commercial viability of solar-powered mini-grid systems for sustainable electricity generation in Sub-Saharan Africa, using Southwest Nigeria as a case study, given its median geographical and geopolitical environment in the region. This is against the background that over 97% of solar mini-grid projects in Sub-Saharan Africa have failed within 5years or are being propped up by external funding instead of being commercially self-sustaining. The 2000 to 2021 solar energy data for 23 locations across Southwest, Nigeria, were obtained from the Langley Research Center, the National Renewable Energy Laboratory, and the Nigerian Meteorological Agency, in addition to scant and isolated data as comparators. the mean mainland and offshore (Bight of Benin) All Sky Solar Insolation was 4.7KWH/m2/day and 4.9KWH/m2/day.  A hypothetical 100kW solar mini-grid system was designed and optimally computed with HOMER simulation, MATLAB Simulink, and TELCOE evaluation, which yielded competitive values of $0.0137/kWh, $0.018928/kWh, and $0.019633/kWh, respectively. The system was finally tested by computing the Techno-Economic Renewable Energy Viability Index (TEREVI), which gave a very high value of 0.850911, well above the 0.60 threshold for the region. This conclusively shows that solar photovoltaic energy mini-grid in standalone or hybrid configuration or catenated clusters is commercially viable with the use of a proper comprehensive modeling technique, such as TEREVI, for planning and decision making, as well as keeping the grid capacity within optimal limits