<< Go Back

Metadata

Name
Data bundle for egon-data: A transparent and reproducible data processing pipeline for energy system modeling
Repository
ZENODO
Identifier
doi:10.5281/zenodo.5846441
Description
egon-data provides a transparent and reproducible open data based data processing pipeline for generating data models suitable for energy system modeling. The data is customized for the requirements of the research project eGon. The research project aims to develop tools for an open and cross-sectoral planning of transmission and distribution grids. For further information please visit the eGon project website or its Github repository.

egon-data retrieves and processes data from several different external input sources. As not all data dependencies can be downloaded automatically from external sources we provide a data bundle to be downloaded by egon-data.

The following data sets are part of the available data bundle:


climate_zones_germany


Climate zones in Germany
source: Own representation based on DWD TRY climate zones
License: Attribution 4.0 International (CC BY 4.0)


emobility

Data on eMobility mit_trip_data:
motorized individual travel - individual trips of electric vehicles (EV) generated with simBEV v0.1.2 (https://github.com/rl-institut/simbev). simBEV generates driving profiles for BEVs and PHEVs based upon MID data (BMVI) per RegioStaR7 region type (BBSR).
Reiner Lemoine Institut, January 2022
License: Attribution 4.0 International (CC BY 4.0)


geothermal_potential

Spatial distribution of deep geothermal potentials in Germany
source: Assessment and Public Reporting of Geothermal Resources in Germany: Review and Outlook
License: Attribution 4.0 International (CC BY 4.0)


household_electricity_demand_profiles

Annual profiles in hourly resolution of electricity demand of private households for different household types (singles, couples, other) with varying number of elderly and children.
The profiles were created using a bottom-up load profile generator by Fraunhofer IEE developed in the Bachelor&#39;s thesis &quot;Auswirkungen verschiedener Haushaltslastprofile auf PV-Batterie-Systeme&quot; by Jonas Haack, Fachhochschule Flensburg, December 2012.
The columns are named as follows: &quot;&lt;HH_TYPE_PREFIX&gt;a&lt;PROFILE_ID&gt;&quot;, e.g. P2a0000 is the first profile of a couple&#39;s household with 2 children. See publication below for the list of prefixes. Values are given in Wh.
A related conference paper can be obtained here: http://publica.fraunhofer.de/documents/N-374761.html
License: Attribution 4.0 International (CC BY 4.0)


household_heat_demand_profiles

Sample heat time series including hot water and space heating for single- and multi-familiy houses. The profiles were created using the loadprofile generator by Fraunhofer IEE developed in the Master&#39;s thesis &quot;Synthesis of a heat and electrical load profile for single and multi-family houses used for subsequent performance tests of a multi-component energy system&quot;, Simon Ruben Drauz, RWTH Aachen University, March 2016
License: Attribution 4.0 International (CC BY 4.0)


hydrogen_storage_potential_saltstructures

The data are taken from figure 7.1 in Donadei, S., et al., (2020), p. 7-5..
Source: Flach lagernde Salze, (c) BGR Hannover, 2021.
Datenquelle: InSpEE-Salzstrukturen, (c) BGR, Hannover, 2015. &amp;
Donadei, S., Horv&aacute;th, B., Horv&aacute;th, P.-L., Keppliner, J., Schneider, G.-S., &amp;
Zander-Schiebenh&ouml;fer, D. (2020). Teilprojekt Bewertungskriterien und
Potenzialabsch&auml;tzung. BGR. Informationssystem Salz: Planungsgrundlagen,
Auswahlkriterien und Potenzialabsch&auml;tzung f&uuml;r die Errichtung von Salzkavernen
zur Speicherung von Erneuerbaren Energien (Wasserstoff und Druckluft) &ndash;
Doppelsalinare und flach lagernde Salzschichten: InSpEE-DS. Sachbericht.
Hannover: BGR.
License: The original data are licensed under the GeoNutzV, see https://sg.geodatenzentrum.de/web_public/gdz/lizenz/geonutzv.pdf


industrial_sites

Information about industrial sites with DSM-potential in Germany from a Master&#39;s thesis by Danielle Schmidt. The data set includes own information on the coordinates of every industrial site.
source: Schmidt, Danielle. (2019). Supplementary material to the masters thesis: NUTS-3 Regionalization of Industrial Load Shifting Potential in Germany using a Time-Resolved Model [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3613767
License: Attribution 4.0 International (CC BY 4.0)


nep2035_version2021

Data extracted from the German grid development plan - power
source: Netzentwicklungsplan Strom 2035 (2021), erster Entwurf | &Uuml;bertragungsnetzbetreiber (M) CC-BY-4.0
License: Attribution 4.0 International (CC BY 4.0)


pipeline_classification_gas

Parameters for the classification of gas pipelines
source: Single parameters extracted from Electricity, Heat and Gas Sector Data for Modelling the German System
License: Attribution 4.0 International (CC BY 4.0)


pypsa_eur_sec

Preliminary results from scenario generator pypsa-eur-sec
source: own calculation using pypsa-eur-sec fork (https://github.com/openego/pypsa-eur-sec)
License: Attribution 4.0 International (CC BY 4.0)


regions_dynamic_line_rating

German regions suitable to model dynamic line rating
source: Own representation based on Grunds&auml;tze f&uuml;r die Ausbauplanung des Deutschen &Uuml;bertragungsnetze (2020)
License: Attribution 4.0 International (CC BY 4.0)


re_potential_areas

Eligible areas for wind turbines and ground-mounted PV systems.
Reiner Lemoine Institut, January 2022
License: Attribution 4.0 International (CC BY 4.0)


WZ_definition

Definitions of industrial and commercial branches
source: Klassifikation der Wirtschaftszweige (WZ 2008)
Extract from Terms of Use: &copy; Statistisches Bundesamt, Wiesbaden 2008 Vervielf&auml;ltigung und Verbreitung, auch auszugsweise, mit Quellenangabe gestattet.


zensus_households

Dataset describing the amount of people living by a certain types of family-types, age-classes,sex and size of household in Germany in state-resolution.
source: Data retrieved from Zensus Datenbank by performing these steps:

Search for: &quot;1000A-2029&quot;
or choose topic: &quot;Bev&ouml;lkerung kompakt&quot;
Choose table code: &quot;1000A-2029&quot; with title &quot;Personen: Alter (11 Altersklassen)/Geschlecht/Gr&ouml;&szlig;e desprivaten Haushalts - Typ des privaten Haushalts (nach Familien/Lebensform)&quot;
Change setting &quot;GEOLK1&quot; to &quot;Bundesl&auml;nder (16)&quot; higher resolution &quot;Landkreise und kreisfreie St&auml;dte (412)&quot; only accessible after registration.


Extract from Terms of Use: &copy; Statistische &Auml;mter des Bundes und der L&auml;nder 2021, Vervielf&auml;ltigung und Verbreitung, auch auszugsweise, mit Quellennachweis gestattet.




&nbsp;
Data or Study Types
multiple
Source Organization
Unknown
Access Conditions
available
Year
2022
Access Hyperlink
https://doi.org/10.5281/zenodo.5846441

Distributions