Engineering and Technology

An open tool for creating battery-electric vehicle time series from empirical data, emobpy

C. Gaete-morales, H. Kramer, et al.

Discover emobpy, an innovative open-source tool transforming battery-electric vehicle profiles using empirical mobility data. Developed by Carlos Gaete-Morales, Hendrik Kramer, Wolf-Peter Schill, and Alexander Zerrahn, this tool generates essential time series data for BEV mobility and grid demand, revealing critical insights into grid availability and charging strategies in Germany.

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Abstract

This paper introduces emobpy, an open-source Python-based tool that generates battery-electric vehicle (BEV) profiles based on empirical mobility statistics and customizable assumptions. The tool creates time series data for BEV mobility, driving electricity consumption, grid availability, and grid electricity demand, which are crucial inputs for various energy models. The authors illustrate its application by generating 200 vehicle profiles for Germany, revealing a median grid availability of 5-7 GW for a million-vehicle fleet due to significant parking time. Different charging strategies demonstrate the smoothing effect on grid electricity demand.

Publisher

Scientific Data

Published On

Jun 11, 2021

Authors

Carlos Gaete-Morales, Hendrik Kramer, Wolf-Peter Schill, Alexander Zerrahn

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