Optimization of Sustainable Fuel Station Retrofitting: A Set-Covering Approach considering Environmental and Economic Objectives

In this work, we propose a mixed-integer linear programming (MILP) model that optimizes economic and environmental objectives by retrofitting fuel stations for the case study of Spain. The model contains set-covering constraints that ensure that there is at least one retrofitted fuel station within a radius of 20 kilometers of each retrofitted fuel station. The results indicate that by retrofitting fuel stations to allow for electric vehicles, both economic and environmental objectives improve, while showing which power plants would be tasked with the increase in electricity production to satisfy the increased electric demand.