Abstract
This research paper offers a comprehensive exploration of how to enhance the charging infrastructure for Electric Vehicles (EVs) in urban settings. The analysis assesses three hypothetical charging infrastructures in a city, each with generators connected to the national grid and strategically placed AC and DC chargers. The proposed method employs GPS data, EV battery levels, and energy availability across the charging infrastructures. Using an optimization algorithm implemented via the Pandapower Python library, the most appropriate charging infrastructure is identified for individual drivers. The algorithm considers factors such as GPS data and energy availability to suggest the optimal charging station for each EV’s battery level. This pioneering solution aims to streamline the charging process, enhance user experience, and encourage efficient use of urban charging infrastructure for electric vehicles.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call