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) 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's thesis "Auswirkungen verschiedener Haushaltslastprofile auf PV-Batterie-Systeme" by Jonas Haack, Fachhochschule Flensburg, December 2012. The columns are named as follows: "<HH_TYPE_PREFIX>a<PROFILE_ID>", e.g. P2a0000 is the first profile of a couple'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's thesis "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", 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. & Donadei, S., Horv��th, B., Horv��th, P.-L., Keppliner, J., Schneider, G.-S., & Zander-Schiebenh��fer, D. (2020). Teilprojekt Bewertungskriterien und Potenzialabsch��tzung. BGR. Informationssystem Salz: Planungsgrundlagen, Auswahlkriterien und Potenzialabsch��tzung f��r die Errichtung von Salzkavernen zur Speicherung von Erneuerbaren Energien (Wasserstoff und Druckluft) ��� 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'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 | ��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��tze f��r die Ausbauplanung des Deutschen ��bertragungsnetze (2020) 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: �� Statistisches Bundesamt, Wiesbaden 2008 Vervielf��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: "1000A-2029" or choose topic: "Bev��lkerung kompakt" Choose table code: "1000A-2029" with title "Personen: Alter (11 Altersklassen)/Geschlecht/Gr����e desprivaten Haushalts - Typ des privaten Haushalts (nach Familien/Lebensform)" Change setting "GEOLK1" to "Bundesl��nder (16)" higher resolution "Landkreise und kreisfreie St��dte (412)" only accessible after registration. Extract from Terms of Use: �� Statistische ��mter des Bundes und der L��nder 2021, Vervielf��ltigung und Verbreitung, auch auszugsweise, mit Quellennachweis gestattet.