Abstract:
Rural electrification remains a challenge in many African countries mainly due to resource
constraints. Grid extension in rural areas is more often infeasible due to the uneconomical nature
of the investment and topography issues. Off-grid solutions, therefore, present an opportunity for
policymakers to extend access to electricity to rural areas using optimal designs of Hybrid Electric
Systems (HESs) that are not only cost-effective but also environmentally friendly. Using the
improved Hybrid Optimization by Genetic Algorithms(iHOGA), this study designed an optimal
HES for two villages in Mchinji district, Malawi. To capture the impact of uncertainty of load,
solar irradiation, and fuel inflation, stochastic optimization was performed using Monte Carlo
simulation. The optimal configuration was a system consisting of the PV/Battery/Generator. Both
mono-objective and multi-objective optimization were carried out to minimize the Net Present Cost
(NPC)/Levelized Cost of Energy (LCOE), and the NPC+ Carbon emissions, respectively. The
mono-objective optimization resulted in a Net Present Cost of 3,214,754.5 € and an LCOE of
0.1156€/kWh. The multi-objective optimization resulted in a relatively higher NPC of 3,287,729.5
€ and LCOE of 0.1182€/kWh with emissions 4 % less than in Mono-objective optimization. Multi
objective optimization strikes the much-needed balance between cost optimality and
environmental consciousness. The incorporation of Montecarlo simulation in the study brings
forth practicality as it addresses the flaws of deterministic models. The study results are
informative to policymakers and developers that rural electrification using a well-designed HES
is possible preceded by a study of this nature.
