Big data analysis for an electric vehicle charging infrastructure using open data and software

This paper describes a big data analysis strategy for electric vehicle charging infrastructure, mainly built upon open data sets and open software components. The data acquisition module periodically retrieves the real-time status information of each charger from the public data portal, while the downloaded XML files are parsed to extract fields of interest. At this stage, we present the distribution of charging facilities in Jeju City based on our own map viewer implementation, the city-wide dynamics of the number of chargers in operation based on MySQL queries, and the visualization of regional occupancy rates based on the R GISTools library. After combining a variety of statistical and machine learning techniques to understand the demand pattern of electric vehicle charging, we will integrate renewable energy to charging-intensive power grids as much as possible.