A New MILP Formulation for Renewables and Energy Storage Integration in Fast Charging Stations

The deployment of fast charging stations (FCSs) can tackle one of the main barriers to the widespread adoption of plug-in electric vehicles (PEVs), i.e., the otherwise long charging time of PEVs. Moreover, feeding the demand of FCSs from renewable energy sources (RESs) can maximize the positive environmental impact of PEVs and decrease the energy costs associated with charging. However, due to their stochastic behavior, RESs are usually insufficient to meet the energy demand of FCSs in a cost-effective way and need to be coupled with energy storage systems (ESSs). This article proposes a new probabilistic mixed integer linear programing (MILP) formulation for determining the optimal capacity and type of renewable generation and energy storage to minimize the energy costs associated with an FCS, while meeting its performance requirements. The proposed formulation accounts for renewable generation uncertainties as well as a wide range of technical and operational characteristics of different energy storage technologies (e.g., depth of discharge (DoD), number of allowable charging/discharging cycles, and calendric lifetime) and allows for choosing the optimal combination of ESSs and RESs. A set of numerical studies has been conducted in GAMS environment to validate the feasibility and effectiveness of the proposed formulation.