|
|
| Line 2: |
Line 2: |
| | |Full_Model_Name=Ancillary Services Acquisition Model | | |Full_Model_Name=Ancillary Services Acquisition Model |
| | |Acronym=ASAM | | |Acronym=ASAM |
| − | |author_institution=Europa-Universität Flensburg | + | |author_institution=Europa-Universität Flensburg |
| | |authors=Samuel Glismann | | |authors=Samuel Glismann |
| | |contact_persons=Samuel Glismann | | |contact_persons=Samuel Glismann |
| Line 19: |
Line 19: |
| | |External optimizer=Solvers supported by Pyomo | | |External optimizer=Solvers supported by Pyomo |
| | |GUI=No | | |GUI=No |
| − | |model_class=Agent-based Simulation, Market Model, Electricity System Model, German and European Electricity Market, | + | |model_class=Agent-based Simulation, Market Model, Electricity System Model, German and European Electricity Market, |
| − | |sectors=Electricity, Electricity Market, Electric power, | + | |sectors=Electricity, Electricity Market, Electric power, |
| | |Transfer (Electricity)=Distribution, Transmission | | |Transfer (Electricity)=Distribution, Transmission |
| | |Storage (Gas)=No | | |Storage (Gas)=No |
| Line 31: |
Line 31: |
| | |Observation period=Less than one month | | |Observation period=Less than one month |
| | |math_modeltype=Simulation, Agent-based | | |math_modeltype=Simulation, Agent-based |
| − | |is_suited_for_many_scenarios=No | + | |is_suited_for_many_scenarios=Yes |
| | |montecarlo=No | | |montecarlo=No |
| | |citation_references=Glismann (2021), “ Ancillary Services Acquisition Model: considering market interactions in policy design”, preprint Applied Energy Journal. https://arxiv.org/abs/2104.13047 | | |citation_references=Glismann (2021), “ Ancillary Services Acquisition Model: considering market interactions in policy design”, preprint Applied Energy Journal. https://arxiv.org/abs/2104.13047 |
| − | |example_research_questions=Redispatch design in the Netherlands | + | |example_research_questions=Redispatch design in the Netherlands |
| | |Specific properties=Clearing algorithms | | |Specific properties=Clearing algorithms |
| | |Integrated models=PyPSA | | |Integrated models=PyPSA |
Latest revision as of 14:18, 15 May 2021
|
Ancillary Services Acquisition Model
by Europa-Universität Flensburg
Authors:
Samuel Glismann
Contact:
Samuel Glismann
|
Agent-based model to simulate processes of ancillary services acquisition and electricity markets. ASAM uses the agent-based model framework Mesa and the toolbox for power system analyses PyPSA.
Based on Python (Pyomo). Using Python, PyPSA, Mesa for data processing.
Website / Documentation
Download
|
 Open Source
GNU General Public License version 3.0 (GPL-3.0)
Directly downloadable
Some input data shipped
|
| Model Scope |
Model type and solution approach |
| Model class
|
Agent-based Simulation, Market Model, Electricity System Model, German and European Electricity Market
|
| Sectors
|
Electricity, Electricity Market, Electric power
|
| Technologies
|
|
| Decisions
|
dispatch
|
| Regions
|
Europe
|
| Geographic Resolution
|
Individual power stations
|
| Time resolution
|
15 Minute
|
| Network coverage
|
|
|
| Model type
|
Simulation, Agent-based
|
|
|
|
| Variables
|
|
| Computation time
|
minutes
|
| Objective
|
|
| Uncertainty modeling
|
|
| Suited for many scenarios / monte-carlo
|
Yes
|
|
References
Scientific references
Glismann (2021), “ Ancillary Services Acquisition Model: considering market interactions in policy design”, preprint Applied Energy Journal. https://arxiv.org/abs/2104.13047
Example research questions
Redispatch design in the Netherlands
◀ back to model list
