Multi-objective optimization of hybrid PV/wind/diesel/battery systems for decentralized application by minimizing the levelized cost of energy and the CO2 emissions

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.