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""" |
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Heavy Duty Transport / Heavy Goods Vehicle (HGV) |
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Main module for preparation of model data (static and timeseries) for |
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heavy duty transport. |
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**Contents of this module** |
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* Creation of DB tables |
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* Download and preprocessing of vehicle registration data from BAST |
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* Calculation of hydrogen demand based on a Voronoi distribution of counted |
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truck traffic among NUTS 3 regions. |
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* Write results to DB |
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* Map demand to H2 buses and write to DB |
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**Configuration** |
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The config of this dataset can be found in *datasets.yml* in section |
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*mobility_hgv*. |
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**Scenarios and variations** |
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Assumptions can be changed within the *datasets.yml*. |
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In the context of the eGon project, it is assumed that e-trucks will be |
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completely hydrogen-powered and in both scenarios the hydrogen consumption is |
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assumed to be 6.68 kgH2 per 100 km with an additional |
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[supply chain leakage rate of 0.5 %]( |
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https://www.energy.gov/eere/fuelcells/doe-technical-targets-hydrogen-delivery). |
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### Scenario NEP C 2035 |
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The ramp-up figures are taken from |
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[Scenario C 2035 Grid Development Plan 2021-2035]( |
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https://www.netzentwicklungsplan.de/sites/default/files/paragraphs-files/ |
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NEP_2035_V2021_2_Entwurf_Teil1.pdf). According to this, 100,000 e-trucks are |
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expected in Germany in 2035, each covering an average of 100,000 km per year. |
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In total this means 10 Billion km. |
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### Scenario eGon100RE |
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In the case of the eGon100RE scenario it is assumed that the HGV traffic is |
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completely hydrogen-powered. The total freight traffic with 40 Billion km is |
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taken from the |
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[BMWk Langfristszenarien GHG-emission free scenarios (SNF > 12 t zGG)]( |
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https://www.langfristszenarien.de/enertile-explorer-wAssets/docs/ |
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LFS3_Langbericht_Verkehr_final.pdf#page=17). |
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## Methodology |
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Using a Voronoi interpolation, the censuses of the BASt data is distributed |
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according to the area fractions of the Voronoi fields within each mv grid or |
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any other geometries like NUTS-3. |
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""" |
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from pathlib import Path |
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import csv |
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from loguru import logger |
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import requests |
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from egon.data import config, db |
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from egon.data.datasets import Dataset |
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from egon.data.datasets.emobility.heavy_duty_transport.create_h2_buses import ( |
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insert_hgv_h2_demand, |
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) |
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from egon.data.datasets.emobility.heavy_duty_transport.db_classes import ( |
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EgonHeavyDutyTransportVoronoi, |
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) |
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from egon.data.datasets.emobility.heavy_duty_transport.h2_demand_distribution import ( # noqa: E501 |
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run_egon_truck, |
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) |
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WORKING_DIR = Path(".", "heavy_duty_transport").resolve() |
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DATASET_CFG = config.datasets()["mobility_hgv"] |
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TESTMODE_OFF = ( |
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config.settings()["egon-data"]["--dataset-boundary"] == "Everything" |
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) |
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def create_tables(): |
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engine = db.engine() |
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EgonHeavyDutyTransportVoronoi.__table__.drop(bind=engine, checkfirst=True) |
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EgonHeavyDutyTransportVoronoi.__table__.create( |
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bind=engine, checkfirst=True |
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) |
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logger.debug("Created tables.") |
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def download_hgv_data(): |
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sources = DATASET_CFG["original_data"]["sources"] |
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# Create the folder, if it does not exist |
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WORKING_DIR.mkdir(parents=True, exist_ok=True) |
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url = sources["BAST"]["url"] |
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file = WORKING_DIR / sources["BAST"]["file"] |
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response = requests.get(url) |
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with open(file, "w") as f: |
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writer = csv.writer(f) |
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for line in response.iter_lines(): |
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writer.writerow(line.decode("ISO-8859-1").split(";")) |
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logger.debug("Downloaded BAST data.") |
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class HeavyDutyTransport(Dataset): |
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def __init__(self, dependencies): |
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super().__init__( |
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name="HeavyDutyTransport", |
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version="0.0.2", |
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dependencies=dependencies, |
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tasks=( |
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{ |
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create_tables, |
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download_hgv_data, |
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}, |
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run_egon_truck, |
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insert_hgv_h2_demand, |
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), |
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) |
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openego /
eGon-data
