A Stochastic Optimal Planning Model for Fully Green Stand-Alone PEV Charging Stations
Majid Moradzadeh, Morad Abdelaziz
Abstract
Electric vehicle users need access to recharging services within the all-electrical driving range of their vehicles. However, public charging stations to be located on remote highways are in many cases far from the power grid, where a connection to the power grid may be impossible, costly, or impractical. This article formulates a stochastic mixed integer linear programming (MILP) planning model for energy storage and renewable energy systems to cover the energy demand of stand-alone charging stations for plug-in electric vehicles (PEVs) entirely using green energy generated by renewable energy sources (RESs). The proposed model accounts for the stochastic behavior of PEVs and RESs as well as the technical, economic, and operational characteristics of a variety of energy storage technologies. A customer satisfaction criterion is introduced to allow for a tradeoff between performance and investment costs. The proposed model can also be used for designing fully green PEV charging stations in urban and rural settings to capitalize on PEV environmental benefits by avoiding the use of fossil-fuel-generated electric power in their charging or to reduce the main grid load. A set of numerical studies have been performed in General Algebraic Modeling System (GAMS) environment to demonstrate the feasibility and effectiveness of the proposed model.