A Multiobjective Optimization Model for the Design of Hybrid Renewable Energy Systems

Fossil fuels are the main energy sources nowadays. Nevertheless, they issue huge amount of carbon dioxide and other byproducts to atmosphere boosting air pollution and greenhouse effect. Beside those issues fossil fuels are vehicles of geopolitical and market instability and bad wealth distribution among countries. The consequent environment impact and increasing energy costs impose the need for other cleaner and equitable sources. Hybrid renewable energy systems (HRES) poses as viable alternative sources for conventional fossil fuels. In this paper, we present a multiobjective optimization model in MILP for the selection and sizing of components of HRES, which considers sustainability criteria in objective function. The model is dynamic in the sense of what technologies should be selected (activated) and what should be withdraw (deactivated) within the planning horizon to satisfy optimization criteria and demand dynamics. The model was conceived for evaluating energy generation and charge technologies and it is general enough to cover all kinds of energy technologies. The suitability of the model is tested for different hypothetical scenarios. Results demonstrated the model is suitable to assist decision makers in planning strategically the energy resource needs in different contexts.