EVisionary: A Prediction Platform for Electric Vehicle Charging Capacity based on the Impact Analysis of Climate Factors

This paper presents EVisionary, a system platform that analyzes the impact of climate factors on electric vehicle charging demand and predicts the charging capacity of electric vehicles. The platform utilizes big data statistical analysis methods and implements seven machine learning and deep learning time series prediction models to forecast short-to-medium-term electric vehicles’ charging demand. A case study of the electric vehicle charging data set in Dundee, Scotland is used to explore the relationship between climate factors and charging demand. Performance comparisons of the prediction models are conducted, and the platform enables users to set data analysis and forecast parameters for valuable analysis and forecast results.