A tool to derive battery electric vehicle energy demands from given trip data. venco.py provides normalized, aggregated electric vehicle fleet demand profiles for two cases: Uncontrolled charging and a technical (mobility-constrained) potential for controlled charging including vehicle-to-grid.
Future electric vehicle fleets pose both challenges and opportunities for power systems. While increased power demand from transport electrification necessitates expansion of power supply, vehicle batteries can to a certain degree shift their charging load to times of high availability of power. The model-adequate description of power demand from future plug-in electric vehicle fleets is a pre-requisite for modelling sector-coupled energy systems and drawing respective policy-relevant conclusions. Vehicle Energy Consumption in Python (venco.py) is a tool that provides boundary conditions for load shifting and vehicle-to-grid potentials based on transport demand data and techno-economic assumptions. It has been applied to various national travel surveys to derive hourly load-shifting constraining profiles for the energy system optimization model REMix.
REMix is a powerful software for energy systems optimization. It can be used for the planning and techno-economical assessment of future multi-energy systems of any spatial, temporal and technological scope. REMix offers a wide range of methods and features that can be flexibly selected by the user.