From Communauté de la Fabrique des Mobilités


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Logiciel EV.PNG

We introduce emobpy. It is an open-source, python-based tool that creates profiles of battery-electric vehicles (BEV), based on empirical mobility statistics and customizable assumptions. We additionally provide a first application of the tool and create vehicle profiles based on representative German mobility data. An emobpy profile consists of four time series: (i) vehicle mobility containing the vehicle’s location and distance travelled, (ii) driving electricity consumption, specifying how much electricity is taken from the battery for driving; (iii) BEV grid availability, providing information whether and with which power rating a BEV is connected to the electricity grid at a certain point in time; and (iv) BEV grid electricity demand, specifying the actual charging electricity drawn from the grid, based on different charging strategies.

emobpy is a Python tool that can create battery electric vehicle time series. Four different time series can be created: vehicle mobility time series, driving electricity consumption time series, grid availability time series and grid electricity demand time series. The vehicles mobility time series are created based on mobility statistics. For driving electricity consumption time series, the properties of vehicles can be selected from a database with several actual battery electric vehicles models. is developed by the research group Transformation of the Energy Economy at DIW Berlin (German Institute of Economic Research).

Article : https://www.nature.com/articles/s41597-021-00932-9

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Tags: charge, Réseau, network

Categories: Logiciel

Theme: Voiture électrique et charge, Carburants alternatifs, Logiciel Libre


Challenge: Améliorer la résilience des systèmes de transports et des solutions de mobilité

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Other related common: Everest

Wealth sought: Expérimentation, Cas d'usages

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Community of interest: Communauté du Logiciel Libre, Communauté autour du Véhicule Electrique - sa charge et les réseaux


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