motorized_individual_travel¶
Motorized Individual Travel (MIT)
Main module for preparation of model data (static and timeseries) for motorized individual travel.
Contents of this module * Creation of DB tables * Download and preprocessing of vehicle registration data from KBA and BMVI * Calculate number of electric vehicles and allocate on different spatial
levels. Seeegon.data.metadata
- Extract and write pre-generated trips to DB
Configuration
The config of this dataset can be found in datasets.yml in section emobility_mit.
Scenarios and variations
- Scenario overview
- Change scenario variation for 2050: adjust in
emobility_mit->scenario->variation->eGon100RE
Trip data
The electric vehicles’ trip data for each scenario have been generated using simBEV. The methodical background is given in its documentation.
6 different vehicle types are used: * Battery Electric Vehicle (BEV): mini, medium, luxury * Plug-in Hybrid Electric Vehicle (PHEV): mini, medium, luxury
Tecnnology | Size | Max. charging capacity slow [kW] | |||
---|---|---|---|---|---|
Max. charging capacity fast [kW] | Battery capacity [kWh] | ||||
Energy consumption [kWh/km] | |||||
BEV | mini | 11 | 120 | 60 | 0.1397 |
BEV | medium | 22 | 350 | 90 | 0.1746 |
BEV | luxury | 50 | 350 | 110 | 0.2096 |
PHEV | mini | 3.7 | 40 | 14 | 0.1425 |
PHEV | medium | 11 | 40 | 20 | 0.1782 |
PHEV | luxury | 11 | 120 | 30 | 0.2138 |
The complete tech data and assumptions of the run can be found in the metadata: <WORKING_DIRECTORY>/data_bundle_egon_data/emobility/mit_trip_data/<SCENARIO>/ metadata_simbev_run.json.efficiency_fixed
- explain scenario parameters
- run params (all in meta file?)
EV allocation
The EVs per registration district (Zulassungsbezirk) is taken from KBA’s vehicle registration data. The numbers per EV type (BEV and PHEV)
- RegioStaR7
- scenario parameters: shares
Further notes
- Sanity checks
Model paametrization
Example queries
-
class
MotorizedIndividualTravel
(dependencies)[source]¶ Bases:
egon.data.datasets.Dataset
-
download_and_preprocess
()[source]¶ Downloads and preprocesses data from KBA and BMVI
Returns: - pandas.DataFrame – Vehicle registration data for registration district
- pandas.DataFrame – RegioStaR7 data