Large-scale transferability of a PSO-optimized hybrid energy system: A comparative study of two African regions

Abstract

This study looks at the resilience and cross-region fidelity of a HRES (Hybrid Renewable Energy Systems) across multiple climates in Africa. The study modelled the systems with a PSO (Particle Swarm Optimization) algorithm in MATLAB (Matrix Laboratory). “Large-scale transferability” refers to the system’s capacity maintained against tight acceptance criteria. Normalized load curves were used to derive the climate impacts and case studies were in Laâyoune–Sakia El Hamra, Morocco and Ouagadougou, Burkina Faso. They display high adaptability of the systems; a complementarity of winds and solar see a LCOE (Levelized Cost of Energy) of 0.0954 USD/kWh and an annual system cost of $100,039 in Laâyoune–Sakia El Hamra, in Ouagadougou dominates mostly solar, with additional storage requirements, remained very competitive, with LCOE at 0.1014 USD/kWh (+6.3% variance). Both sites achieved similar levels of reliability (Loss of Load Probability, LLP ≈ 0.01) and reduced CO2 emissions significantly (275.29 tCO2/yr and 283.13 tCO2/yr, respectively). LCOE variation was less than 6.5% and LLP variation is less than 0.002, regardless of climate change. These results demonstrate that the flexibility of the methodology employed ensures the maintenance of techno-economic advantages, even in the face of a 45% decrease in wind power potential. Thus, the present paper contributes to the further evolution of HRES design—from an ad hoc narrow-site-specific optimization regime to a scalable, context-sensitive design framework. It also proposes a proven path toward sustainable and affordable renewable energy growth in developing countries.