https://wiki.openmod-initiative.org/api.php?action=feedcontributions&user=Wilko+Heitkoetter&feedformat=atomwiki.openmod-initiative.org - User contributions [en]2024-03-29T10:00:25ZUser contributionsMediaWiki 1.19.7https://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2023-08-07T18:33:29Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German high voltage grid (110, 220, 380 kV), e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
<br />
Model is under development. After release it will be directly downloadable.<br />
<br />
MODULE 1: Heat demand and power-to-heat capacities<br />
(Article: https://doi.org/10.1016/j.apenergy.2019.114161 ; Open Access Preprint: https://arxiv.org/abs/1912.03763 ; Open Dataset DOI: https://doi.org/10.5281/zenodo.2650200)<br />
<br />
MODULE 2: Regionalised load shifting potentials for 19 technologies from the residential, commercial and industrial sector, as well as sector coupling (dsmlib tool) <br />
(Article: https://doi.org/10.1016/j.adapen.2020.100001, dsmlib tool and dataset: https://zenodo.org/record/3988921)<br />
<br />
MODULE 3: Investment and dispatch optimisation of demand response; economic assessment from macro-economic and operator's perspective<br />
(Article: https://doi.org/10.3390/en15228577; Code repository: https://doi.org/10.5281/zenodo.6424639)<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Demand_responseDemand response2021-04-14T16:41:15Z<p>Wilko Heitkoetter: /* Germany */</p>
<hr />
<div><br />
= Europe<br/> =<br />
<br />
<br />
<br />
== Germany ==<br />
<br />
*[[Region4FLEX|region4FLEX]]: demand response potentials for the German 401 administrative districts (German: Landkreise); Sectors: Industry, Commercial, Residential, Power-To-Heat, E-Mobility, Power-to-Gas; [https://zenodo.org/record/3988921 Data on Zenodo]; [https://doi.org/10.1016/j.adapen.2020.100001 Publication associated with the data])</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2021-03-23T19:20:32Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German high voltage grid (110, 220, 380 kV), e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
<br />
Model is under development. After release it will be directly downloadable.<br />
<br />
MODULE 1: Regionalised load shifting potentials<br />
<br />
1.1 Heat demand and power-to-heat capacities: <br />
<br />
(Article: https://doi.org/10.1016/j.apenergy.2019.114161 ; Open Access Preprint: https://arxiv.org/abs/1912.03763 ; Open Dataset DOI: https://doi.org/10.5281/zenodo.2650200)<br />
<br />
1.2: Demand regionalisation of other load sectors & determination of load shifting potentials (dsmlib tool) <br />
<br />
(Article: https://doi.org/10.1016/j.adapen.2020.100001, dsmlib tool and dataset: https://zenodo.org/record/3988921)<br />
<br />
MODULE 2: Regionalised flexibility demand of the grid - in progress<br />
<br />
MODULE 3: Economic assessment of load shifting - in progress<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Demand_responseDemand response2020-09-29T17:31:07Z<p>Wilko Heitkoetter: /* Germany */</p>
<hr />
<div><br />
= Europe<br/> =<br />
<br />
<br />
== Germany ==<br />
<br />
*[[Region4FLEX|region4FLEX]]: demand response potentials for the German 401 administrative districts (German: Landkreise); Sectors: Industry, Commercial, Residential, Power-To-Heat, E-Mobility, Power-to-Gas; [https://zenodo.org/record/3988921 Data on Zenodo]; [https://arxiv.org/abs/2009.05122 Publication associated with the data])</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Demand_responseDemand response2020-09-29T17:22:21Z<p>Wilko Heitkoetter: Created page with " = Europe<br/> = == Germany == *region4FLEX: demand response potentials for the German administrative districts; Sectors: Industry, Commercial, Residential, ..."</p>
<hr />
<div><br />
= Europe<br/> =<br />
<br />
== Germany ==<br />
<br />
*[[Region4FLEX|region4FLEX]]: demand response potentials for the German administrative districts; Sectors: Industry, Commercial, Residential, Power-To-Heat, E-Mobility, Power-to-Gas; [https://zenodo.org/record/3988921 Data on Zenodo]; [https://arxiv.org/abs/2009.05122 Publication associated with the data])</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/DataData2020-09-29T17:11:52Z<p>Wilko Heitkoetter: /* Open data sources for energy modelling */</p>
<hr />
<div><br />
This is work in progress and supposed to become a link list to sources of open energy related data. We focus on collecting links to data relevant for the modelling of energy and electricity systems and markets. You are welcome to fill in the missing spots and non-existing pages. Also, you are welcome to extend the list of relevant data (e.g. for a European energy system model) that we should collect links to in the future:<br />
<br />
[[Data requirements for a European energy system model|Data requirements for a European energy system model]]<br />
<br />
<br />
= Open data sources for energy modelling =<br />
<br />
Open datasets related to energy are listed here by type.<br />
<br />
*Demand<br />
**[[Electricity demand|Electricity demand]]<br />
**[[Thermal demand|Thermal demand]]<br />
**[[Transport demand|Transport demand]]<br />
**[[Industrial demand|Industrial demand]]<br />
**[[Demand response|Demand response]]<br />
<br />
*Resources and Potentials<br />
**[[Weather data|Weather data and availability of renewable energy]]<br />
**[[Wind geographical potentials|Wind geographical potentials]]<br />
**[[Biomass potentials|Biomass potentials]]<br />
**[[Hydroelectricity data|Hydroelectricity potentials]]<br />
<br />
*Networks<br />
**[[Transmission network datasets|Electricity transmission network datasets]]<br />
**[[Distribution network datasets|Electricity distribution network datasets]]<br />
**[[Gas network datasets|Gas network datasets]]<br />
<br />
*Technologies<br />
**[[Power plant portfolios|Power plants]]<br />
**[[Technology assumptions|Generation technology assumptions and projections]]<br />
**[[Storage technology assumptions and projections|Storage technology assumptions and projections]]<br />
**[[End-use technology assumptions and projections|End-use technology assumptions and projections]]<br />
<br />
*[[Demographic and socio-economic data|Demographic and socio-economic data]]<br />
<br />
*[[Environmental data and regulations|Environmental data and regulations]]<br />
<br />
*[[Historical data and profiles|Historical data and profiles]]<br />
<br />
*[[Energy Scenarios|Energy scenarios]]<br />
<br />
*[[Country-specific targets and policies|Country-specific targets and policies]]<br />
<br />
<br/><br />
<br />
<br />
= Other lists of energy-related open datasets =<br />
<br />
*The Wikipedia article [https://en.wikipedia.org/wiki/Open_energy_system_databases open energy system databases] lists some of the portals serving open energy system datasets.<br />
*[http://datahub.io/dataset?q=energy datahub.io category "Energy"] has more datasets.<br />
*[http://energypedia.info/ Energypedia] is a wiki platform for collaborative knowledge exchange on renewable energy and energy access issues in the context of development cooperation. *[http://enipedia.tudelft.nl/ Enipedia (TU Delft)] is an active exploration into the applications of wikis and the semantic web for energy and industry issues. An extensive compilation of links to other data sources can be found at [http://enipedia.tudelft.nl/wiki/Energy_and_Industry_Data_Sets Energy and Industry Data Sets] and [http://enipedia.tudelft.nl/wiki/Electricity_Transmission_Network Electricity_Transmission Network].<br />
<br />
*[https://www.europeandataportal.eu/ European Data Portal]<br />
*[http://www.iea-etsap.org/web/E-techDS.asp IEA ETSAP energy technology data source (E-Tech-DS)] is a series of four-page technology briefs similar to the [https://www.iea.org/publications/freepublications/ IEA Energy Technology Essentials (filter for "essentials")]. The page contains short technical descriptions of 29 energy related technologies from power production, synthesised fuels, and fossil fuel production.<br />
*[http://www.iaee.org/en/EnergyDataLinks/ International Association of Energy Economists (IAEE) Energy Data Links (EDL)] provides a searchable database of energy-related resources<br />
*[http://en.openei.org/ OpenEI] features a wiki of crowd-sourced energy information and a database of single source data on buildings, energy, efficiency, consumption, demand, potential.<br />
*[[openenergy-platform.org/|Open Energy Platform]] (OEP) and [https://openenergy-platform.org/dataedit/schemas Open Energy Database] (OEDB) was started with the requirements gathered in the first openmod meetings and was developed completely open with support of the openmod community. Input and result data from research of energy system studies are available via an API. The OEDB provides some automated visualisations of the available data.<br />
*[http://open-power-system-data.org/data-sources Open Power System Data] has an extensive collection of links to data sources (Electricity consumption, Capacity and generation by fuel, Power plant data, Hydro power data, Prices and related data, Weather data, Wind and solar power time series, Country-specific data portals).<br />
*[http://www.ourenergypolicy.org/resource-library/ OurEnergyPolicy.org Resource Library]&nbsp;is a free online energy resource library updated weekly.<br />
*[http://www.pfbach.dk/ PFBach.dk], a collection of wind and solar in-feed profiles<br />
*[https://www.reeep.org/reegle-clean-energy-information-portal reegle] is a data provider of country energy profiles, energy statistics and a directory of relevant stakeholders. It also offers the clean energy search and an extensive glossary. There is also an insightful clean energy blog with interesting and up-to-date background information.&nbsp;<br />
<br />
<br />
= Data sharing techniques =<br />
<br />
The Open Knowledge foundation promotes the use of its '''[http://data.okfn.org/ data package]''' standard. It consists of using CSV for payload (data) and a file package.json to attach machine-readable metadata. The page links to many examples of existing, curated and maintained datasets that adhere to this standard. Additionally, they drive the creation of a software ecosystem that can create and digest this format. Due to its simplicity, using data packages does not depend on this ecosystem.<br />
<br />
'''GitHub repositories''' are another pragmatic way of sharing "small" (up to about 10 MB) datasets. A fun example is the [http://bundestag.github.io/gesetze/ Bundesgit], a collection of all German federal laws under version control. New laws or modfications are tracked as commits, allowing to "see" how a dataset -- laws, in that case -- evolve over time. The repository [https://github.com/openmundi/world.db openmundi/world.db] shows a more data-focused way of using Git, or GitHub, for collaborative collection of data. However, it clearly shows the limitations of using a version control system for code on data.<br />
<br />
An upcoming and (technically) promising project is '''[http://dat-data.com/ dat]''', which "is a version-controlled, decentralized data tool for collaboration between data people and data systems." Or, simply: Git for data. It is currently in public beta test, but has come a long way already.<br />
<br />
= Help finding energy data =<br />
<br />
You can find a list of the latest questions on energy data sources on StackExchange: [http://opendata.stackexchange.com/questions/tagged/energy http://opendata.stackexchange.com/questions/tagged/energy]<br />
<br />
<br />
= Data extraction scripts =<br />
<br />
Feel free to add scripts here, by creating a new wiki page, or place them on [https://gist.github.com/ Github Gists].<br />
<br />
*[https://gitlab.tubit.tu-berlin.de/electricity-modeling/crossborder-skript ENTSOE Cross-border Trading Flows Extraction Script by TU Berlin]<br />
*[http://www.open-power-system-data.org Open Power System Data] developed a data platform with open source scripts (based on Python and Jupyter Notebooks) for data on generation capacities, power plants, load timeseries and weather data. Project running until 07/2017. The public version of the data platform was released 10/2016.<br />
*[https://www.electricitymap.org/ electricitymap.org] has parser scrips for various online data sources in its [https://github.com/tmrowco/electricitymap-contrib#real-time-electricity-data-sources GitHub/parsers page] under GPLv3 license.<br />
*[https://github.com/OpenEnergyPlatform/open-MaStR open_MaStR] develop to download BNetzA Marktstammdatenregister powerplant data for Germany (AGPL-3.0)<br />
<br />
<br/><br />
<br />
<br/><br />
<br />
<br/><br />
<br />
<br />
= Interactive data visualizations =<br />
<br />
*[https://www.energy-charts.de/index.htm Energy Charts] by Fraunhofer ISE<br />
*[https://www.entsoe.eu/data/map/ Interactive Power Transmission Grid Map] by ENTSO-E<br />
*[https://transparency.entsog.eu/ Interactive Gas Transmission Grid Map] by ENTSO-G<br />
*[https://www.electricitymap.org/?page=map&solar=false&remote=true&wind=false Electricity Map] shows the current carbon intensity of electricity consumed/produced.<br />
*[https://www.agora-energiewende.de/en/service/recent-electricity-data/chart/matrix/19.09.2017/19.09.2018/ Recent Electricity Data] by Agora Energiewende (English and German)<br />
*[https://globalwindatlas.info/ Global Wind Atlas] by Technical University of Denmark<br />
*[https://globalsolaratlas.info/ Global Solar Atlas] by the World Bank Group<br />
*[https://www.epexspot.com/en/market-data/dayaheadauction/chart/auction-chart/ EPEX Spot Day Ahead Auction]<br />
*[https://wam.rl-institut.de/ WAM - Web Applications & Maps] by Reiner Lemoine Institut<br />
<br />
<br/><br />
<br />
<br />
= Data organization ideas =<br />
<br />
A scheme similar to [http://us-city.census.okfn.org/ http://us-city.census.okfn.org/] might be useful for mapping out what types of data are available where.</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2020-09-29T09:27:05Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German high voltage grid (110, 220, 380 kV), e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
<br />
Model is under development. After release it will be directly downloadable.<br />
<br />
MODULE 1: Regionalised load shifting potentials<br />
<br />
1.1 Heat demand and power-to-heat capacities: <br />
<br />
(Article: https://doi.org/10.1016/j.apenergy.2019.114161 ; Open Access Preprint: https://arxiv.org/abs/1912.03763 ; Open Dataset DOI: https://doi.org/10.5281/zenodo.2650200)<br />
<br />
1.2: Demand regionalisation of other load sectors & determination of load shifting potentials (dsmlib tool) <br />
<br />
(Preprint: https://arxiv.org/abs/2009.05122, dsmlib tool and dataset: https://zenodo.org/record/3988921)<br />
<br />
MODULE 2: Regionalised flexibility demand of the grid - in progress<br />
<br />
MODULE 3: Economic assessment of load shifting - in progress<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2020-09-29T08:04:31Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German high voltage grid (110, 220, 380 kV), e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
<br />
Model is under development. After release it will be directly downloadable.<br />
<br />
MODULE 1: Regionalised load shifting potentials<br />
1.1 Heat demand and power-to-heat capacities: <br />
<br />
(Article: https://doi.org/10.1016/j.apenergy.2019.114161 ; Open Access Preprint: https://arxiv.org/abs/1912.03763 ; Open Dataset DOI: https://doi.org/10.5281/zenodo.2650200)<br />
<br />
1.2: Demand regionalisation of other load sectors & determination of load shifting potentials (dsmlib tool) <br />
<br />
(Preprint: https://arxiv.org/abs/2009.05122, dsmlib tool and dataset: https://zenodo.org/record/3988921)<br />
<br />
MODULE 2: Regionalised flexibility demand of the grid - in progress<br />
<br />
MODULE 3: Economic assessment of load shifting - in progress<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2020-04-19T11:07:25Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German high voltage grid (110, 220, 380 kV), e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
<br />
Model is under development. After release it will be directly downloadable.<br />
<br />
WORKING PACKAGE 1: Regionalised load shifting potentials<br />
1.1 Heat demand and power-to-heat capacities: published (Article DOI: https://doi.org/10.1016/j.apenergy.2019.114161 ; <br />
<br />
Open Access Preprint: https://arxiv.org/abs/1912.03763 ; <br />
<br />
Open Dataset DOI: https://doi.org/10.5281/zenodo.2650200)<br />
<br />
1.2: Demand regionalisation of other load sectors - in progress<br />
<br />
1.3: Regionalised load shifting potentials - in progress<br />
<br />
WORKING PACKAGE 2: Regionalised flexibility demand of the grid - in progress<br />
<br />
WORKING PACKAGE 3: Economic assessment of load shifting - in progress<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2020-01-20T16:30:06Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German high voltage grid (110, 220, 380 kV), e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
<br />
Model is under development. After release it will be directly downloadable.<br />
<br />
WORKING PACKAGE 1: Regionalised load shifting potentials<br />
1.1 Heat demand and power-to-heat capacities: published (Article DOI: https://doi.org/10.1016/j.apenergy.2019.114161 ; <br />
<br />
Published Article 50 days free access link: https://authors.elsevier.com/a/1aNWZ15eiewC7J; <br />
<br />
Open Access Preprint: https://arxiv.org/abs/1912.03763 ; <br />
<br />
Open Dataset DOI: https://doi.org/10.5281/zenodo.2650200)<br />
<br />
1.2: Demand regionalisation of other load sectors - in progress<br />
<br />
1.3: Regionalised load shifting potentials - in progress<br />
<br />
WORKING PACKAGE 2: Regionalised flexibility demand of the grid - in progress<br />
<br />
WORKING PACKAGE 3: Economic assessment of load shifting - in progress<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Thermal_demandThermal demand2020-01-20T16:27:04Z<p>Wilko Heitkoetter: /* Regionalised heat demand and power-to-heat capacities for Germany (by DLR) */</p>
<hr />
<div><br />
= Introduction =<br />
<br />
Heating demand is broadly divided into low-temperature demand for space and water heating, and high-temperature demand for process heat in industry.<br />
<br />
Time series of low-temperature heating demand can be approximated by the degree-day assumption, which assumes that heating demand increases linearly with temperature below some threshold (e.g. 15 degrees Celsius). Temperature is averaged over a day, then multiplied with an intraday profile that reflects consumer behaviour (e.g. consumers may turn down their heating at night).<br />
<br />
<br/><br />
<br />
= Europe =<br />
<br />
== Eurostat yearly energy consumption ==<br />
<br />
[http://ec.europa.eu/eurostat/web/energy/data/energy-balances http://ec.europa.eu/eurostat/web/energy/data/energy-balances]<br />
<br />
For years 1990, 1995, 2000, 2005, 2008-2014<br />
<br />
Covers energy usage in EU, Balkans, Norway, Ukraine, Turkey, but NOT Switzerland.<br />
<br />
Distributed by sector (Industry, Transport, Residential, Services).<br />
<br />
Q: Is there any non-electric residential and service energy consumption other than low-T heating and cooking with natural gas?<br />
<br />
<br/><br />
<br />
== Odyssee-Mure database yearly energy data for Europe ==<br />
<br />
[http://www.odyssee-mure.eu/ http://www.odyssee-mure.eu/]<br />
<br />
This distinguishes between water and space heating by sector (Residential/Tertiary/Industry), but is incomplete (missing countries and years).<br />
<br />
<br/><br />
<br />
<br />
== BMWi yearly energy statistics for Germany ==<br />
<br />
[http://bmwi.de/DE/Themen/Energie/Energiedaten-und-analysen/Energiedaten/gesamtausgabe,did=476134.html BMWi energy statistics]<br />
<br />
This distinguishes between water and space heating.<br />
<br />
<br/><br />
<br />
<br />
== Germany: Regionalised heat demand and power-to-heat capacities (by DLR) ==<br />
<br />
[[Region4FLEX|region4FLEX model]], data of first working package on zenodo: [https://doi.org/10.5281/zenodo.2650200 Regionalised heat demand and power-to-heat capacities]<br />
<br />
METADATA<br />
<br />
Sector: Residential Buildings – Space Heating and Domestic Hot Water; Geographical scope: Germany; Geographical resolution: Administrative districts (NUTS-3); Temporal scope: 2011, three scenarios for 2030; Temporal resolution: 15min, Technologies: Single-storey heating, central heating (3 size classes), district heating (Power-to-heat: heat pumps, resisitive heating)<br />
<br />
<br/><br />
<br />
<br />
== Heat demand in Aarhus, Denmark ==<br />
<br />
Apparently available here:<br />
<br />
http://varmeplanaarhus.dk/SitePages/Home.aspx<br />
<br />
= USA =<br />
<br />
*The dataset [http://en.openei.org/datasets/dataset/commercial-and-residential-hourly-load-profiles-for-all-tmy3-locations-in-the-united-states Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States] on [http://en.openei.org/ OpenEI] contains hourly load profiles (for both electricity and heat) for synthetic reference buildings, modelled at over 1000 different locations (i.e. the TMY3 weather stations).</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Thermal_demandThermal demand2020-01-20T16:25:37Z<p>Wilko Heitkoetter: /* BMWi yearly energy statistics for Germany */</p>
<hr />
<div><br />
= Introduction =<br />
<br />
Heating demand is broadly divided into low-temperature demand for space and water heating, and high-temperature demand for process heat in industry.<br />
<br />
Time series of low-temperature heating demand can be approximated by the degree-day assumption, which assumes that heating demand increases linearly with temperature below some threshold (e.g. 15 degrees Celsius). Temperature is averaged over a day, then multiplied with an intraday profile that reflects consumer behaviour (e.g. consumers may turn down their heating at night).<br />
<br />
<br/><br />
<br />
= Europe =<br />
<br />
== Eurostat yearly energy consumption ==<br />
<br />
[http://ec.europa.eu/eurostat/web/energy/data/energy-balances http://ec.europa.eu/eurostat/web/energy/data/energy-balances]<br />
<br />
For years 1990, 1995, 2000, 2005, 2008-2014<br />
<br />
Covers energy usage in EU, Balkans, Norway, Ukraine, Turkey, but NOT Switzerland.<br />
<br />
Distributed by sector (Industry, Transport, Residential, Services).<br />
<br />
Q: Is there any non-electric residential and service energy consumption other than low-T heating and cooking with natural gas?<br />
<br />
<br/><br />
<br />
== Odyssee-Mure database yearly energy data for Europe ==<br />
<br />
[http://www.odyssee-mure.eu/ http://www.odyssee-mure.eu/]<br />
<br />
This distinguishes between water and space heating by sector (Residential/Tertiary/Industry), but is incomplete (missing countries and years).<br />
<br />
<br/><br />
<br />
<br />
== BMWi yearly energy statistics for Germany ==<br />
<br />
[http://bmwi.de/DE/Themen/Energie/Energiedaten-und-analysen/Energiedaten/gesamtausgabe,did=476134.html BMWi energy statistics]<br />
<br />
This distinguishes between water and space heating.<br />
<br />
<br/><br />
<br />
== Regionalised heat demand and power-to-heat capacities for Germany (by DLR) ==<br />
<br />
[[Region4FLEX|region4FLEX model]], data of first working package on zenodo: [https://doi.org/10.5281/zenodo.2650200 Regionalised heat demand and power-to-heat capacities]<br />
<br />
METADATA<br />
<br />
Sector: Residential Buildings – Space Heating and Domestic Hot Water; Geographical scope: Germany; Geographical resolution: Administrative districts (NUTS-3); Temporal scope: 2011, three scenarios for 2030; Temporal resolution: 15min, Technologies: Single-storey heating, central heating (3 size classes), district heating (Power-to-heat: heat pumps, resisitive heating)<br />
<br />
<br/><br />
<br />
<br />
== Heat demand in Aarhus, Denmark ==<br />
<br />
Apparently available here:<br />
<br />
http://varmeplanaarhus.dk/SitePages/Home.aspx<br />
<br />
= USA =<br />
<br />
*The dataset [http://en.openei.org/datasets/dataset/commercial-and-residential-hourly-load-profiles-for-all-tmy3-locations-in-the-united-states Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States] on [http://en.openei.org/ OpenEI] contains hourly load profiles (for both electricity and heat) for synthetic reference buildings, modelled at over 1000 different locations (i.e. the TMY3 weather stations).</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2020-01-20T16:07:58Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German high voltage grid (110, 220, 380 kV), e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
<br />
Model is under development. After release it will be directly downloadable.<br />
<br />
WORKING PACKAGE 1: Regionalised load shifting potentials<br />
1.1 Heat demand and power-to-heat capacities: published (Article DOI: https://doi.org/10.1016/j.apenergy.2019.114161 ; Published Article 50 days free access link: https://authors.elsevier.com/a/1aNWZ15eiewC7J; Open Access Preprint: https://arxiv.org/abs/1912.03763 ; Open Dataset DOI: https://doi.org/10.5281/zenodo.2650200)<br />
<br />
1.2: Demand regionalisation of other load sectors - in progress<br />
<br />
1.3: Regionalised load shifting potentials - in progress<br />
<br />
WORKING PACKAGE 2: Regionalised flexibility demand of the grid - in progress<br />
<br />
WORKING PACKAGE 3: Economic assessment of load shifting - in progress<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2020-01-20T16:06:33Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German high voltage grid (110, 220, 380 kV), e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
<br />
Model is under development. After release it will be directly downloadable.<br />
<br />
WORKING PACKAGE 1: Regionalised load shifting potentials<br />
1.1 Heat demand and power-to-heat capacities: published ((Article DOI: https://doi.org/10.1016/j.apenergy.2019.114161 ; Published Article 50 days free access link: https://authors.elsevier.com/a/1aNWZ15eiewC7J; Open Access Preprint: https://arxiv.org/abs/1912.03763 ; Open Dataset DOI: https://doi.org/10.5281/zenodo.2650200)<br />
1.2: Demand regionalisation of other load sectors - in progress<br />
1.3: Regionalised load shifting potentials - in progress<br />
<br />
WORKING PACKAGE 2: Regionalised flexibility demand of the grid - in progress<br />
<br />
WORKING PACKAGE 3: Economic assessment of load shifting - in progress<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Transmission_network_datasetsTransmission network datasets2019-11-19T15:38:35Z<p>Wilko Heitkoetter: </p>
<hr />
<div><br />
= Network datasets by region<br/> =<br />
<br />
== Europe ==<br />
<br />
{| style="width:100%" class="wikitable sortable" cellspacing="1" cellpadding="1" border="1"<br />
|-<br />
! Name<br />
! Version<br />
! <br />
Year<br/><br />
<br />
Published<br />
<br />
! Represented year<br />
! Region<br />
! Num. Substations or Buses<br />
! Num. Lines<br />
! Contains<br />
! Direct download?<br />
! Licence<br />
! Format<br />
|-<br />
| [http://scigrid.de/ SciGRID]<br />
| 0.2<br />
| 2015<br />
| 2015<br />
| Germany, but in principle whole world<br />
| 495<br />
| 825<br />
| Topology, Impedances<br />
| Yes<br />
| Apache Licence, Version 2.0 (code, documentation). ODBL (data)<br />
| CSV (csvdata)<br />
|-<br />
| [http://www.powerworld.com/knowledge-base/updated-and-validated-power-flow-model-of-the-main-continental-european-transmission-network Bialek European Model]<br />
| 2<br />
| 2013<br />
| 2009<br />
| Continental Europe<br />
| 1494 buses<br />
| 2322<br />
| Topology, Impedances, Loads, Generators<br />
| Yes<br />
| Public Domain Dedication<br />
| PowerWorld, Excel<br />
|-<br />
| [http://www2.nationalgrid.com/UK/Industry-information/Future-of-Energy/Electricity-Ten-Year-Statement/ National Grid ETYS 2014 Model]<br />
| <br/><br />
| 2014<br />
| 2014<br />
| Great Britain<br />
| 365<br />
| 316<br />
| Topology, Impedances, Loads, Generators<br/><br />
| Yes<br />
| Unclear<br />
| <br/><br />
|-<br />
| [https://www.apg.at/en/Stromnetz/APG-Netz Austrian Power Network Grid]<br/><br />
| <br/><br />
| 2015<br />
| 2015<br />
| Austria<br />
| <br/><br />
| ~100<br />
| Topology, Impedances<br />
| Yes<br />
| Unclear<br />
| PDF<br />
|-<br />
| [https://www.entsoe.eu/stum/ ENTSO-E STUM]<br />
| 1<br />
| 2015 and before<br />
| 2020?<br />
| Continental Europe?<br />
| 1000s<br />
| 1000s<br />
| Topology, Impedances<br />
| Requires registration<br />
| <span style="font-size: 13.6px; background-color: rgb(255, 255, 255)">Restrictive</span><br />
| CIM<br />
|-<br />
| [https://www.entsoe.eu/stum/ ENTSO-E STUM]<br />
| 2<br />
| 2015<br />
| 2030<br />
| GB, Ireland, Baltics, Finland, Continental Europe<br />
| 1000s<br />
| 1000s<br />
| <span style="font-size: 13.6px; background-color: rgb(255, 255, 255)">Topology, Impedances</span><br/><br />
| <span style="font-size: 13.6px; background-color: rgb(255, 255, 255)">Requires registration</span><br/><br />
| <span style="font-size: 13.6px; background-color: rgb(255, 255, 255)">Restrictive</span><br />
| Excel<br />
|-<br />
| [https://www.entsoe.eu/stum/ ENTSO-E STUM]<br />
| 3<br />
| 2016<br />
| 2030<br />
| GB, Ireland, Baltics, Finland, Continental Europe<br />
| 1000s<br />
| 1000s<br />
| <span style="font-size: 13.6px; background-color: rgb(255, 255, 255)">Topology, Impedances</span><br/><br />
| <span style="font-size: 13.6px; background-color: rgb(255, 255, 255)">Requires registration</span><br/><br />
| Restrictive<br />
| Excel<br />
|}<br />
<br />
<br/><br />
<br />
=== SciGRID ===<br />
<br />
[http://scigrid.de/ SciGRID] is a project which started in 2014 and will be running for three years. The aim of SciGRID is to develop an open and free model of the European transmission network based on data from the [http://www.openstreetmap.org/ OpenStreetMap]. It is carried out by [http://www.next-energy.de/ NEXT ENERGY - EWE Research Centre for Energy Technology], an independent non-profit institute at the University of Oldenburg, Germany, and funded by the [https://www.bmbf.de/ German Ministry of Education and Research],&nbsp; and the initiative [http://forschung-stromnetze.info/ Zukunftsfähige Stromnetze].<br />
<br />
An unofficial, post-processed version of SciGRID version 0.2 for Germany with attached load, generation and transformers is available as a [https://github.com/FRESNA/PyPSA/tree/master/examples/scigrid-de PyPSA example], see also [http://pypsa.org/index.html#screenshots-and-example-jupyter-ipython-notebooks screenshots].<br/><br />
<br />
=== GridKit European Dataset ===<br />
<br />
[https://github.com/bdw/GridKit GridKit] uses spatial and topological analysis to transform map objects from [http://www.openstreetmap.org/ OpenStreetMap] into a network model of the electric power system. It has been developed in the context of the [http://scigrid.de/ SciGRID] project at the [http://www.next-energy.de/ NEXT ENERGY - EWE Research Centre for Energy Technology], to investigate the possibility of 'heuristic' analysis to augment the route-based analysis used in [http://scigrid.de/ SciGRID]. This has been implemented as a series of scripts for the PostgreSQL database using the PostGIS spatial extensions.<br />
<br />
[https://zenodo.org/record/47317 Data extracts] are provided for Europe and North America in a similar CSV format to [http://scigrid.de/ SciGRID].<br />
<br />
=== osmTGmod Model<br/> ===<br />
<br />
[https://github.com/maltesc/osmTGmod osmTGmod] is a load-flow model of the German transmission-gird, based on the free geo-database [http://www.openstreetmap.org/ OpenStreetMap] (OSM). The model, respectively the heuristic abstraction process employs a PostgreSQL-database extended by PostGIS. The key part of the abstraction process is implemented in SQL and ProstgreSQL's procedural language pl/pgSQL. The abstraction and all additional modules are controlled by a Python-environment.<br />
<br />
=== Bialek European Model<br/> ===<br />
<br />
The 2nd version of the [http://www.powerworld.com/knowledge-base/updated-and-validated-power-flow-model-of-the-main-continental-european-transmission-network Bialek European Model] is downloadable as an Excel file and in the format of the proprietary modelling software [http://www.powerworld.com/ PowerWorld]. The model covers voltages from 110 kV (a single line in the Balkans) up to 380 kV. It is released under a Public Domain Dedication.<br/><br />
<br />
The 1st version was released in 2002-2004 and is no longer available (see [http://web.archive.org/web/20100525115039/http://www.see.ed.ac.uk/~jbialek/Europe_load_flow/ Archive mirror]). The 1st version did not contain the Balkans region.<br />
<br />
The methodology and validation for the 1st version of the model can be found in the paper [http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=1425573 Approximate model of European interconnected system as a benchmark system to study effects of cross-border trades] by Zhou and Bialek, 2005.<br />
<br />
The model contains the impedances and number of circuits of each line, but not the length (which can in principle be determined from the impedance and number of circuits, given standard line parameters). Only cross-border lines are assigned thermal capacities.<br />
<br />
There is currently no coordinate dataset for the buses. The PowerWorld file contains spatial data, but in an unknown projection. The [https://github.com/nworbmot/georef-bialek/ georef-bialek github project] is an attempt to fix this; there is also a [https://zenodo.org/record/35177 geo-referenced version] from Tue Vissing Jensen.<br />
<br />
=== DIW ELMOD-DE open model of Germany ===<br />
<br />
[http://www.diw.de/de/diw_01.c.528493.de/forschung_beratung/nachhaltigkeit/umwelt/verkehr/energie/modelle/elmod.html#ELMOD-DE ELMOD-DE] is an open model of the German electricity system developed at DIW and TU Berlin, which includes both a model of the high voltage transmission network, power plants, hourly load and weather data for the year 2012 and GAMS code to run linear optimisation simulations. It contains 438 geo-referenced network nodes and 697 transmission lines at 380 kV and 220 kV. Transformers are not modelled but per unit line series impedances are adjusted to the voltage level.<br />
<br />
The model includes 47 pages of documentation.<br />
<br />
The transmission data was, according to the documentation, derived from the VDE and TSO maps and from [http://www.openstreetmap.org/ OpenStreetMap]. The data is provided as-is without the code that generated it.<br />
<br />
=== National Grid Model ===<br />
<br />
[http://www2.nationalgrid.com/UK/Industry-information/Future-of-Energy/Electricity-Ten-Year-Statement/ National Grid Electricity Ten Year Statement 2014 Model]<br />
<br />
Shapefiles and maps of tower, lines, cables and substations [https://www.nationalgridet.com/network-and-assets/network-route-maps here].<br/><br />
<br />
=== Austrian Power Network Grid Model<br/> ===<br />
<br />
[https://www.apg.at/en/Stromnetz/APG-Netz Austrian Power Network Grid]<br/><br />
<br />
<br/><br />
<br />
=== Danish Power Network Grid Model<br/> ===<br />
<br />
[https://en.energinet.dk/Electricity/Energy-data/System-data Danish Transmission network data]<br />
<br />
The data are not directly available, but rather a [https://en.energinet.dk/About-us/Registrations/Formular056 registration form] is required before obtaining access.<br />
<br />
It has features not present in the ENTSO-E STUM (see below):<br />
<br />
*It's a full non-linear model with all the reactive power demand, P and Q capabilities of gens and shunt reactive power compensation.<br />
*It lists the power capabilities of the generators and their fuel type (wind/solar/gas etc), not just the dispatch.<br />
*They seem to have separated RE feed-in from the load, which wasn't the case for STUM where wind and solar are lumped with the load as residual load.<br />
<br />
What's missing are geocoordinates for the substations (which can be read off roughly from the JPG map) and time-dependence of the loads and/or variable generators. For Denmark, which has many CHP units, it would also be useful to know the heat demand and how the CHP units are operated.<br />
<br />
<br/><br />
<br />
=== RTE Network Dataset for France<br/> ===<br />
<br />
[https://clients.rte-france.com/lang/an/visiteurs/vie/indispos_caracteristiques_statiques.jsp RTE network dataset]<br />
<br />
=== Elia Network Dataset for Belgium ===<br />
<br />
[http://www.elia.be/en/grid-data/Grid-Technical-Data Elia network dataset]<br />
<br />
=== TenneT NL Network Dataset for the Netherlands<br/> ===<br />
<br />
[http://www.tennet.org/english/operational_management/transmission_services/Calculated_crossborder_cap/explanatory_documents.aspx TenneT NL]<br />
<br />
=== TenneT DE Network Dataset for Central Germany<br/> ===<br />
<br />
[http://www.tennettso.de/site/Transparenz/veroeffentlichungen/statisches-netzmodell/statisches-netzmodell Tennet DE]<br/><br />
<br />
=== Amprion Network Dataset for Western Germany<br/> ===<br />
<br />
[https://www.amprion.net/Energy-Market/Congestion-Management/Static-Grid-Model/ Amprion], [https://www.amprion.net/Netzausbau/Interaktive-Karte/ interactive map] of the grid extension projects<br/><br />
<br />
=== TransnetBW Network Dataset for Southwest Germany<br/> ===<br />
<br />
[https://www.transnetbw.de/de/strommarkt/engpassmanagement/standards-zukunft TransnetBW]<br/><br />
<br />
=== 50 Hertz Network Dataset for Eastern Germany<br/> ===<br />
<br />
[https://www.50hertz.com/de/Transparenz/Kennzahlen/StatischesNetzmodell 50 Hertz statistisches Netz]<br/><br />
<br />
<br/><br />
<br />
=== Ceps Network Dataset for <span lang="EN-GB">Czec</span>h Republic<br/> ===<br />
<br />
[https://www.ceps.cz/ENG/Cinnosti/Technicka-infrastruktura/Pages/Udaje-o-PS.aspx CEPS]<br/><br />
<br />
=== ENTSO-E Interactive Grid Map ===<br />
<br />
ENTSO-E announced its [https://www.entsoe.eu/map/Pages/default.aspx Interactive ENTSO-E Transmission Network Map] in March 2016.<br />
<br />
The map uses [http://www.openstreetmap.org/ OpenStreetMap] as a background and [https://www.mapbox.com/about/maps/ Mapbox] for displaying the map data.<br />
<br />
The map is based on the ENTSO-E static grid map, which is based on the TSOs' own maps. It is known to be an approximate artistic representation rather than an accurate geographical map. Some power plants may be incorrectly labelled (e.g. fuel type may not be accurate).<br />
<br />
The map includes information on the number of circuits and the voltage levels of transmission lines.<br />
<br />
Information, including all geographical coordinates, can be extracted from the web API, but requires further topological processing to be turned into an electrical network model. Lines need to be connected, etc. The [https://github.com/bdw/GridKit GridKit] project provides code for this purpose and has released an [https://zenodo.org/record/55853 unofficial dataset], which forms an electrical network model complete with buses, links, generators and transformers, full geographic coordinates, as well as all electrical metadata contained in the ENTSO-E map.<br />
<br />
=== ENTSO-E Static Grid Map ===<br />
<br />
ENTSO-E releases [https://www.entsoe.eu/publications/order-maps-and-publications/electronic-grid-maps/Pages/default.aspx maps of the European transmission grid], both electronically and in paper form.<br />
<br />
The maps for the whole ENTSO-E system are in the projection [http://prj2epsg.org/epsg/3034 EPSG 3034], which is a [https://en.wikipedia.org/wiki/Lambert_conformal_conic_projection Lambert Conformal Conic projection]. The lower left corner is approximately at (lon,lat) = (-9.5,28) and the upper left corner is at (75.5,58.5). This was checked in the [https://github.com/nworbmot/georef-bialek/ georef-bialek github project].<br />
<br />
=== ENTSO-E STUM ===<br />
<br />
ENTSO-E makes available a model of the European transmission system. Registration is required to download it on the [https://www.entsoe.eu/stum/ ENTSO-E STUM] page. It is not totally clear what one may and may not do with it (e.g. whether it is possible to publish results derived from it or an aggregation of the nodes, etc.).<br />
<br />
The first version of the model was released in the CIM XML-based format for the old UCTE area. The model was a winter snapshot for 2020, including TYNDP projects. The node names were obscured so that the model was unusable. Line capacities were missing.<br />
<br />
The second version, published in June 2015 as Excel spreadsheets, is more useful. It contains the whole ENTSO-E area with the exception of Norway, Sweden, Cyrus and Iceland. The node names are the same as those used by the TSOs. Quoting from the documentation: "It represents the power system of the ENTSO-E members for 2030 in Vision I of the TYNDP 2014", i.e. it includes planned TYNDP projects. It includes all nodes, lines, transformers and aggregated loads and generators at each node for one snapshot. Line data includes series reactance and resistance, but not line length or capacity or number of circuits or wires per circuit bundle. Geolocation data for the nodes is missing. Node names are recognisable from the substation names on the ENTSO-E map. The model is intended for a linear load flow only. It is not clear which wind/solar/load snapshot the model represents (it is an "exemplary scenario"). Generators are not distinguished by generation source.<br />
<br />
The third version, published in February 2016 as Excel spreadsheets has in addition thermal ratings for most transformers and most transmission lines, along with reactive power feed-in, consumption and compensation, so that a full non-linear power flow can be run on the grid.<br />
<br />
=== ENTSO-E Initial Dynamic Model of Continental Europe ===<br />
<br />
[https://www.entsoe.eu/publications/system-operations-reports/continental-europe/Initial-Dynamic-Model/Pages/default.aspx ENTSO-E Initial Dynamic Model of Continental Europe]<br />
<br />
Requires registration. Can model "the main frequency response of the system as well as the main inter-area oscillation modes".<br />
<br />
=== Flow-based market coupling data by Joint Allocation Office ===<br />
<br />
The joint allocation office hosts various official data (including [http://utilitytool.jao.eu/CascUtilityWebService.asmx?op=GetPTDFEarlyPublicationForAPeriod PTDFs]) around the Flow-based market coupling algorithm in use in Europe.<br />
<br />
[http://utilitytool.jao.eu/ http://utilitytool.jao.eu/]<br />
<br />
[http://utilitytool.jao.eu/CascUtilityWebService.asmx http://utilitytool.jao.eu/CascUtilityWebService.asmx]<br />
<br />
<br/><br />
<br />
<br/><br />
<br />
== Australia<br/> ==<br />
<br />
[https://data.gov.au/dataset/ds-ga-1185c97c-c042-be90-e053-12a3070a969b/details?q=national Lines] and [https://data.gov.au/dataset/ds-ga-13be62a4-4fe3-f812-e053-12a3070a22be/details?q=national substations]<br />
<br />
<br/><br />
<br />
== United States ==<br />
<br />
There is raster graphic of the US transmission grid at [https://www.e-education.psu.edu/geog469/book/export/html/111 https://www.e-education.psu.edu/geog469/book/export/html/111].<br />
<br />
=== Western Electricity Coordinating Council ===<br />
<br />
Apparently there is a a WECC Transmission Expansion Planning Policy Committee (TEPPC) 2024 Common Case GridView dataset, but the exact link seems elusive.<br />
<br />
The WECC [https://www.wecc.biz/TransmissionExpansionPlanning/Pages/Datasets.aspx Transmission Expansion Planning] has links to Excel files.<br />
<br />
=== Western US Power Grid ===<br />
<br />
The [http://nexus.igraph.org/api/dataset_info?id=15&format=html Western US Power Grid dataset] has 4941 nodes and 6594 lines, but apparently these are not well enough labelled to distinguish where and what the nodes/lines are.<br/><br />
<br />
=== GridKit North American Dataset ===<br />
<br />
[https://github.com/bdw/GridKit GridKit] uses spatial and topological analysis to transform map objects from [http://www.openstreetmap.org/ OpenStreetMap] into a network model of the electric power system. It has been developed in the context of the [http://scigrid.de/ SciGRID] project at the [http://www.next-energy.de/ NEXT ENERGY - EWE Research Centre for Energy Technology], to investigate the possibility of 'heuristic' analysis to augment the route-based analysis used in [http://scigrid.de/ SciGRID]. This has been implemented as a series of scripts for the PostgreSQL database using the PostGIS spatial extensions.<br />
<br />
[https://zenodo.org/record/47317 Data extracts] are provided for Europe and North America in a similar CSV format to [http://scigrid.de/ SciGRID].<br />
<br />
== Global ==<br />
<br />
=== OpenStreetMap ===<br />
<br />
The global OpenStreetMap (OSM) power grid data is visible at [http://www.itoworld.com/map/4 ITO World Electricity Distribution] and [http://enipedia.tudelft.nl/ Enipedia] has [http://enipedia.tudelft.nl/OpenStreetMap/ nightly extracts of the power grid from OSM].<br />
<br />
=== GridKit Datasets ===<br />
<br />
[https://github.com/bdw/GridKit GridKit] uses spatial and topological analysis to transform map objects from [http://www.openstreetmap.org/ OpenStreetMap] into a network model of the electric power system. It has been developed in the context of the [http://scigrid.de/ SciGRID] project at the [http://www.next-energy.de/ NEXT ENERGY - EWE Research Centre for Energy Technology], to investigate the possibility of 'heuristic' analysis to augment the route-based analysis used in [http://scigrid.de/ SciGRID]. This has been implemented as a series of scripts for the PostgreSQL database using the PostGIS spatial extensions.<br />
<br />
[https://zenodo.org/record/47317 Data extracts] are provided for Europe and North America in a similar CSV format to [http://scigrid.de/ SciGRID].<br />
<br />
=== IRENA OpenStreetMap Extract ===<br />
<br />
See [http://globalatlas.irena.org/NewsDetailPublic.aspx?id=2278 IRENA News Announcement]<br/><br />
<br />
== Non-Region Specific ==<br />
<br />
=== University of Washington Power Systems Test Case Archive ===<br />
<br />
[http://www.ee.washington.edu/research/pstca/ Power Systems Test Case Archive]<br />
<br />
=== IEEE PES Power Grid Library ===<br />
<br />
[https://power-grid-lib.github.io/ Overview]<br />
<br />
[https://github.com/power-grid-lib/pglib-opf Optimal Power Flow Cases]<br />
<br />
=== RWTH Aachen Transmission Expansion Problem Benchmark Case ===<br />
<br />
RWTH Aachen has published [http://www.ifht.rwth-aachen.de/en/tep A Benchmark Case for Network Expansion], which is "derived from the IEEE 118 bus network and modified in accordance with European standards such as a nominal frequency of 50Hz, the use of conventional voltage levels, and conductor dimensions."<br />
<br />
Registration is required to download the model.<br />
<br />
The paper describing the model is [http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=7232601 A benchmark case for network expansion methods], 2015.<br />
<br />
= Other lists of network datasets =<br />
<br />
*[http://enipedia.tudelft.nl/wiki/Electricity_Transmission_Network Enipedia list]<br />
<br />
*[http://enipedia.tudelft.nl/OpenStreetMap/ Nightly extracts of the power grid from OpenStreetMap]<br />
**See the maps at [http://www.itoworld.com/map/106 ITO World Electricity Generation] and [http://www.itoworld.com/map/4 ITO World Electricity Distribution] for a visual overview of what this covers.<br />
**This data is fed into the [http://enipedia.tudelft.nl/Elasticsearch.html search page here] where you locate data on individual power plants.<br />
<br />
*[http://www.maths.ed.ac.uk/optenergy/data/Summary.pdf Edinburgh University list]<br />
<br />
*[https://github.com/ComplexNetTSP/ComplexNetWiki/wiki/2.2.3-PowerGrid- Github repository] of several transmission network models<br/><br />
<br />
*[https://github.com/caesar0301/awesome-public-datasets#complex-networks Github list of complex network datasets]<br />
<br />
<br/><br />
<br />
= Free software for power system analysis =<br />
<br />
[https://github.com/rwl/PYPOWER PyPower] in Python<br/><br />
<br />
[https://github.com/FRESNA/PyPSA PyPSA]: Python for Power System Analysis<br />
<br />
[https://bitbucket.org/harald_g_svendsen/powergama/wiki/Home PowerGAMA] in Python<br />
<br />
[http://www.pserc.cornell.edu/matpower/ MATPOWER] in Matlab or Octave<br />
<br />
[http://sourceforge.net/projects/electricdss/ OpenDSS] in Delphi<br />
<br />
[http://faraday1.ucd.ie/psat.html PSAT] in Matlab or Octave<br />
<br />
[https://github.com/lanl-ansi/PowerModels.jl PowerModels.jl] in Julia<br />
<br />
[https://github.com/wheitkoetter/AutoGridComp AutoGridComp] in Python for the comparison of power grid models<br />
<br />
'''Other lists of power system analysis software'''<br />
<br />
[https://wiki.openelectrical.org/index.php?title=Power_Systems_Analysis_Software https://wiki.openelectrical.org/index.php?title=Power_Systems_Analysis_Software]<br />
<br />
[https://nkloc.wordpress.com/2011/11/11/power-system-simulation-software-list/ https://nkloc.wordpress.com/2011/11/11/power-system-simulation-software-list/]<br />
<br />
[http://www2.econ.iastate.edu/tesfatsi/ElectricOSS.htm http://www2.econ.iastate.edu/tesfatsi/ElectricOSS.htm]<br />
<br />
<br/><br />
<br />
= Typical electrical parameters for transmission infrastructure =<br />
<br />
== Calculating cable impedances ==<br />
<br />
See [http://www.openelectrical.org/wiki/index.php?title=Cable_Impedance_Calculations http://www.openelectrical.org/wiki/index.php?title=Cable_Impedance_Calculations] and electrical engineering textbooks.<br />
<br />
== Generalities on overhead alternating current transmission lines ==<br />
<br />
=== Three-phase power ===<br />
<br />
In almost all of the world electrical power is transmitted using alternating current with three phases separated by 120 degrees, see [https://en.wikipedia.org/wiki/Three-phase_electric_power Wikipedia: Three-phase electric power].<br />
<br />
For this reason the cables on power lines are bundled in groups of three.<br />
<br />
(Exceptions include: direct current power lines and some [https://en.wikipedia.org/wiki/Railway_electrification_system transmission systems for supplying trains], which are e.g. in Germany two-phase and at 16.7 Hz.)<br />
<br />
Current I and current limits are almost always quoted per phase.<br />
<br />
Voltage in the transmission system is almost always quoted as the phase-to-phase potential difference, often called line-to-line voltage V_{LL}, since this is the easiest value to measure. It is related to the line-to-ground or line-to-neutral potential difference V_{LN} by V_{LL} = \sqrt{3} V_{LN}.<br />
<br />
The apparent power transported in each phase is give by I*V_{LN}, so that for a complete transmission circuit the power is three times this value:<br />
<br />
S = 3*I*V_{LN} = \sqrt(3)*I*V_{LL}<br />
<br />
Often it is assumed that the voltage and current magnitudes are the same in each phase, i.e. that the system is balanced and symmetric. This should be the case in the normal operation of the transmission system. The impedances and limits below are quoted assuming that the system is balanced, so that only positive sequence impedances are given. See [https://en.wikipedia.org/wiki/Symmetrical_components Wikipedia: Symmetrical components].<br />
<br />
In an unbalanced system, the three phases can be described using the positive-, negative- and zero-sequence components, where the impedances are different for each sequence.<br />
<br />
=== Bundled conductors ===<br />
<br />
See [https://en.wikipedia.org/wiki/Overhead_power_line#Bundle_conductors Wikipedia: Overhead power line: Bundle conductors].<br />
<br />
Often the conducting wires for each phase are separated into bundles of several parallel wires, connected at intervals by spacers. This has several advantages: the higher surface area increases the current-carrying capacity, which is limited by the [https://en.wikipedia.org/wiki/Skin_effect skin effect], it reduces inductance and it helps to cool the wires.<br />
<br />
=== Circuits ===<br />
<br />
Each group of three phases is called a circuit. Power-carrying capability can be increased by having several circuits on a single pylon, so that wire bundles always appear in multiples of 3 in power lines.<br />
<br />
== European 50 Hz transmission lines ==<br />
<br />
The main European alternating current (AC) electricity system is operated at 50 Hz. (Other networks, such as those for electrified trains, operate at other frequencies and some transmission lines use direct current.)<br />
<br />
On the continent AC transmission voltages are typically 220 kV or 380 kV (sometimes quoted as 400 kV, since network operators often run their grid above nominal voltage to reduce network losses).<br />
<br />
220 kV overhead lines are typically configured with a bundle of 2 wires per phase with wires of cross-section Al/St 240/40.<br />
<br />
380 kV overhead lines are typically configured with a bundle of 4 wires per phase with wires of cross-section Al/St 240/40.<br />
<br />
We now list the impedances of the transmission lines, which can be used for example in the [http://www.electrical4u.com/medium-transmission-line/ lumped pi model].<br />
<br />
{| style="width:100%" class="wikitable sortable" cellspacing="1" cellpadding="1" border="1"<br />
|+ Electrical properties for single circuits<br />
|-<br />
! scope="col" | Voltage level (kV)<br />
! scope="col" | Type<br />
! scope="col" | Conductors<br />
! scope="col" | Series resistance (Ohm/km)<br />
! scope="col" | Series inductive reactance (Ohm/km)<br />
! scope="col" | Shunt capacitance (nF/km)<br />
! scope="col" | Current thermal limit (A)<br />
! scope="col" | Apparent power thermal limit (MVA)<br />
|-<br />
| 220<br />
| Overhead line<br />
| 2-wire-bundle Al/St 240/40<br />
| 0.06<br />
| 0.301<br />
| 12.5<br />
| 1290<br />
| 492<br />
|-<br />
| 380<br />
| Overhead line<br />
| 4-wire-bundle Al/St 240/40<br />
| 0.03<br />
| 0.246<br />
| 13.8<br />
| 2580<br />
| 1698<br />
|}<br />
<br />
In the table the thermal limit for the current is calculated as 645 A per wire at an outside temperature of 20 degrees Celsius.<br />
<br />
The thermal limit for the apparent power S is derived from the per-phase current limit I and the line-to-line voltage V by S = \sqrt{3}VI.<br />
<br />
Sources for the electrical parameters:<br />
<br />
Oeding and Oswald [http://www.springer.com/us/book/9783642192456 Elektrische Kraftwerke und Netze], 2011, Chapter 9<br />
<br />
See also comparable parameters in:<br />
<br />
*[http://www.dena.de/fileadmin/user_upload/Projekte/Energiesysteme/Dokumente/denaVNS_Abschlussbericht.pdf DENA Distribution Network Study], 2012, Table 5.6<br />
*[https://www.diw.de/documents/publikationen/73/diw_01.c.440963.de/diw_datadoc_2014-072.pdf DIW Data Documentation 72], 2014, Table 15, taken from Kießling, F., Nefzger, P., Kaintzyk, U., "Freileitungen: Planung, Berechnung, Ausführung", 2001, Springer<br />
*[https://www.zml.kit.edu/downloads/Elektrische_Energieuebertragung_Leseprobe_Kapitel_2.pdf KIT Electrical Parameters Reading Sample], 2013<br />
<br />
== European 50 Hz high voltage transformers ==<br />
<br />
Typical 380/220 kV transformers have a nominal power of around 400-500 MVA and a per unit series reactance of around 0.08-0.1.<br />
<br />
#TODO: references<br />
<br />
== Combining electrical parameters for multiple circuits ==<br />
<br />
In the table above, the impedances are quoted for a single circuit. The resistance and inductive reactance decrease proportional to the number of parallel circuits (with small modifications to the inductance due to the different geometry of the parallel circuits). Similarly the capacitance increases proportional to the number of parallel circuits (again, roughly because of changing geometry).<br />
<br />
<br/><br />
<br />
== Standard Test Test Networks ==<br />
<br />
[http://sites.ieee.org/pes-testfeeders/resources/ http://sites.ieee.org/pes-testfeeders/resources/]<br />
<br />
[https://github.com/e2nIEE/pandapower/tree/develop/pandapower/networks https://github.com/e2nIEE/pandapower/tree/develop/pandapower/networks]</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2019-05-09T08:28:06Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German high voltage grid (110, 220, 380 kV), e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
<br />
Model is under development. After release it will be directly downloadable.<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2019-05-08T14:28:52Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German transmission grid, e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
<br />
Model is under development. After release it will be directly downloadable.<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2019-05-08T14:23:18Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German transmission grid, e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
<br />
Model is under development. After release it will be directly downloadable.<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation to fulfill the flexibility demand of the transmission grid<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2019-05-08T14:21:29Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter(a_t)dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German transmission grid, e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
<br />
Model is under development. After release it will be directly downloadable.<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation to fulfill the flexibility demand of the transmission grid<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2019-05-08T14:17:48Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German transmission grid, e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
<br />
Model is under development. After release it will be directly downloadable.<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation to fulfill the flexibility demand of the transmission grid<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2019-05-08T14:17:26Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German transmission grid, e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
Model is under development. After release it will be directly downloadable.<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation to fulfill the flexibility demand of the transmission grid<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2019-05-08T14:07:43Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German transmission grid, e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|model_class=load shifting optimisation to fulfill the flexibility demand of the transmission grid<br />
|sectors=electricity plus sector coupling (EVs, P2Heat, P2Gas)<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2019-05-08T13:33:37Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German transmission grid, e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python<br />
|processing_software=PostgreSQL<br />
|GUI=No<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2019-05-08T13:32:51Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German transmission grid, e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|data_availability=all<br />
|open_future=No<br />
|modelling_software=Python, PostgreSQL<br />
|GUI=No<br />
|Demand sectors=Households, Industry, Transport, Commercial sector<br />
|Transfer (Electricity)=Transmission<br />
|Storage (Electricity)=Battery<br />
|Storage (Gas)=No<br />
|Storage (Heat)=Yes<br />
|georegions=Germany<br />
|georesolution=Administrative districts<br />
|timeresolution=15 Minute<br />
|network_coverage=transmission<br />
|math_modeltype=Optimization<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2019-05-08T13:22:06Z<p>Wilko Heitkoetter: </p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|contact_persons=Wilko Heitkoetter<br />
|contact_email=wilko.heitkoetter@dlr.de<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German transmission grid, e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
|Framework=Python, pgSQL<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|open_future=No<br />
|GUI=No<br />
|Storage (Gas)=No<br />
|Storage (Heat)=No<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetterhttps://wiki.openmod-initiative.org/wiki/Region4FLEXRegion4FLEX2019-05-08T13:16:26Z<p>Wilko Heitkoetter: Created page with "{{Model |Full_Model_Name=region4FLEX |author_institution=DLR Institute of Networked Energy Systems |authors=Wilko Heitkoetter, Wided Medjroubi |text_description=The open sourc..."</p>
<hr />
<div>{{Model<br />
|Full_Model_Name=region4FLEX<br />
|author_institution=DLR Institute of Networked Energy Systems<br />
|authors=Wilko Heitkoetter, Wided Medjroubi<br />
|text_description=The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German transmission grid, e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.<br />
|Framework=Python, pgSQL<br />
|open_source_licensed=Yes<br />
|license=Apache License 2.0 (Apache-2.0)<br />
|model_source_public=No<br />
|open_future=No<br />
|GUI=No<br />
|Storage (Gas)=No<br />
|Storage (Heat)=No<br />
|is_suited_for_many_scenarios=No<br />
|montecarlo=No<br />
|Model input file format=No<br />
|Model file format=No<br />
|Model output file format=No<br />
}}</div>Wilko Heitkoetter