A Novel Dynamic Capacity Expansion Framework Includes Renewable Energy Sources for an Electric Vehicle Charging Station

Abstract

This paper proposes a novel capacity expansion framework for electric vehicle charging stations (EVCSs) through short-term functional decisions and long-term planning under stochastic power demand. Energy resources such as solar, wind, energy storage systems, and microgas turbines supply energy to the microgrid. An EVCS works as a vehicle-to-grid (V-G), and it can send energy to the microgrid. The capacities of solar panels, storage systems, and wind turbines can be expanded by implementing capacity expansion planning in a microgrid. The short-term and long-term expansion problem has been solved by optimizing the hourly operation of the resources and with a five-year planning horizon, respectively. A hybrid algorithm combining the sample average approximation technique and the apriori progressive hedging algorithm (SAAT-APHA) has been proposed in this study. The impact of the availability of different resources, including wind, solar, and V-G power on the system performance has been analyzed. Finally, a comparison has been performed with three other algorithms, and the results show the superiority of the proposed method.