Modelling Tool

venco.py – 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.

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 so far been applied to the German travel survey (Mobilität in Deutschland) on a national scale to derive hourly load-shifting constraining profiles for the energy system optimisation model REMix.

Modelling procedure of the venco.py model.
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venco.py follows an object-oriented approach containing four main classes in the data pipeline from mobility data to estimated load shifting potentials of electric vehicle fleets. These classes provide a read-in of mobility data sets, the composition of trip and park diaries, the modeling of charging infrastructure at specific parking categories (e.g. home or shopping) as well as the modeling of uncontrolled charging and load shifting.

Current development work focusses on charging behavior across multiple days, the integration of other data sets (e.g. commercial transport) and the validation of the tool with empirical charging data.

Departments, research groups and challenges related to the VencoPy model:

Department

Energy Systems Analysis

The Energy Systems Analysis department generates system-analytical knowledge, which we provide across sectors up to the global level and based in part on methods and modelling tools developed in-house.

Research Group

Energy System Modelling

The Energy System Modelling research group is developing methods and solutions for the planning and operation of future energy infrastructures. The primary focus lies in examining how various technologies can contribute to creating energy systems that are sustainable, reliable, and cost-effective.

Challenge

Strategies for sustainable energy systems

Energy transition is a dynamic process that must be continuously adapted to new influences such as technical innovations or socially negotiated framework conditions.

Contact

Energy System Modelling

Research Group
Institute of Networked Energy Systems