|
|
| Line 6: |
Line 6: |
| | |contact_email=wilko.heitkoetter@dlr.de | | |contact_email=wilko.heitkoetter@dlr.de |
| | |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. | | |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. |
| − | |Framework=Python, pgSQL
| |
| | |open_source_licensed=Yes | | |open_source_licensed=Yes |
| | |license=Apache License 2.0 (Apache-2.0) | | |license=Apache License 2.0 (Apache-2.0) |
| | |model_source_public=No | | |model_source_public=No |
| | + | |data_availability=all |
| | |open_future=No | | |open_future=No |
| | + | |modelling_software=Python, PostgreSQL |
| | |GUI=No | | |GUI=No |
| | + | |Demand sectors=Households, Industry, Transport, Commercial sector |
| | + | |Transfer (Electricity)=Transmission |
| | + | |Storage (Electricity)=Battery |
| | |Storage (Gas)=No | | |Storage (Gas)=No |
| − | |Storage (Heat)=No | + | |Storage (Heat)=Yes |
| | + | |georegions=Germany |
| | + | |georesolution=Administrative districts |
| | + | |timeresolution=15 Minute |
| | + | |network_coverage=transmission |
| | + | |math_modeltype=Optimization |
| | |is_suited_for_many_scenarios=No | | |is_suited_for_many_scenarios=No |
| | |montecarlo=No | | |montecarlo=No |
