A Stochastic Method for Prediction of the Power Demand at High Rate EV Chargers

Abstract

High rate (<;100 kW) electric vehicle chargers (HREVCs) are crucial for achieving the benefits of reduced CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> and particulate emissions promised by EVs by enabling journey distances greater than the range of the vehicle. A method for predicting the expected demand pattern at these HREVCs is presented in this paper. This is critical to plan a network of chargers. This novel method uses the freely available traffic flow data and travel patterns extracted from the OpenStreetMap combined with a novel EV battery capacity prediction method, to find future HREVC usage patterns in the U.K. and their dependence on location and EV characteristics. This planning method can be replicated to find HREVC power demand for any location on the strategic road network in the U.K. and can be used in the analysis of the role of high rate EV charging in the wider energy system.