Multi-objective optimisation of hybrid renewable energy systems for Colombian non-interconnected zones

Colombia's Atlantic coast wind and solar resources could enhance energy mix and self-generation. Renewable clean energy has been studied in response to fossil fuel pollution. Wind and solar photovoltaic systems have low initial, operational, and levelized energy costs. Variable wind and sun radiation may limit availability. In this regard, hybrid renewable energy systems (HRES) and energy storage have become crucial. These systems can effectively meet load demand by utilising complementary renewable resources. This study deals with sizing a wind and photovoltaic HRES with storage, using a Particle Swarm Optimisation algorithm for yearly variable resources in a non-interconnected zone in La Guajira, Colombia. The study evaluates the LCOE, probability of load loss, and the system's CO2 emission. It develops a sensitivity analysis to determine the importance of each objective factor. From a life cycle analysis, an HRES configuration with low LCOE and environmental emission rates is associated with the size of the wind resource; the HRES configuration with minimum LCOE values is close to obtaining higher equivalent CO2e emissions. The study highlights the configuration obtained for the Colombian context, giving more importance to the environmental factor and reaching an LCOE of 0.754 USD/kWh and emission of 18.97 tCO2e/year; this configuration also increases the wind energy generation, reaching 41 % more share, compared to the configuration obtained when the economic factor is a priority.