Abstract

The main objective of this paper is to propose a methodology to design and optimize a stand-alone hybrid PV/wind/diesel/battery minimizing the Levelized Cost of Energy (LCE) and the CO₂ emission using a Multi-Objectives Genetic Algorithm approach. The methodology developed was applied using the solar radiation, temperature and the wind speed collected on the site of Potou located in the northwestern coast of Senegal. The LCE and the CO₂ emission were computed for each solution and the results were presented as a Pareto front between LCE and the CO₂ emission. These results show that as the LCE increases the CO₂ emission decreases. For example, the solution A (left solution on the Pareto front) presents 2.05 €/kWh and 11.89 kgCO₂/year, however the solution E (right solution on the Pareto front) shows 0.77 €/kWh and 10,839.55 kgCO₂ /year. It was also noted that the only PV/battery or Wind/ battery was not an optimal configuration for this application on the site of Potou with the use of the load profile and the specifications of the used devices. For all solutions, the PV generator was more adapted to supply the energy demand than the wind turbines.

Key words: Hybrid system, optimization, genetic algorithm, cost of energy, CO₂ emission.