Investigation of the user behaviour of EV drivers and consequent grid impacts

This paper presents the methodology adopted within the EU-project "XL-Connect" for investigating the future Electric Vehicle (EV) user behaviour and consequent impacts for the energy system. The user behaviour has been investigated through literature research, a survey and expert interviews. The findings from the user behaviour analysis have been used to formulate the "XL-Connect" framework evaluating grid impacts of EVs. A probabilistic calculation component stands for the cornerstone of the framework, which calculates probabilistic power network state and grid security indicators based on two categories of inputs resulting from data-driven models. At first, a "Grid generator" defines grid operational or planning scenarios, which embrace grid structure properties, including network topology, electrical properties of network elements or settings of controllable assets. Secondly, a "Scenario generator" composes power injection profiles and operational uncertainty (i.e. confidence bounds) related to consumption, production, energy storage or EV (dis)charging patterns. Third, an "EV pattern generator" provides (dis)charging power profiles and spatiotemporal probability of their occurrence in a power system. The scenario parametrisation of data-driven models is based on real-world datasets and data science approaches (e.g. cluster analysis).