End User Incentive-based Approach for Fast Charging Station

Abstract

The development of electric vehicles (EVs) is influenced by various factors such as cost, autonomy, charging speed, and infrastructure. The objective of this research paper is to model an EV fast-charging station that provides incentives to end users in terms of money. The charging station incorporates a renewable energy source (solar) and an energy storage system, taking into account the demand for EVs, state of charge (SOC), and vehicle arrival and departure times. This approach aims to increase the revenue of the station and reduce the high energy demand from the grid. To incentivize end users, the vehicle-to-grid (V2G) and battery swapping modes have been implemented. The Monte Carlo approach is used to model the demand for EVs and the production of renewable energy, considering hourly intervals. Subsequently, the installation and utilization of the EV fast-charging station (EVCS) are optimized using the Adaptive Harris Hawk Optimization (AHHO) algorithm. The system is analyzed with and without V2G and battery swapping modes. The comparison between the two modes reveals that the system with V2G and battery swapping provides both revenue and incentives to end users.