Model Factsheet

Overview / Ancillary Services Acquisition Model (ASAM)

Model Ancillary Services Acquisition Model (ASAM)

General Information
Name Ancillary Services Acquisition Model
Acronym ASAM
Methodical Focus Agent-based Simulation , Market Model , Electricity System Model
Institution(s) Europa-Universität Flensburg
Author(s) (institution, working field, active time period) Samuel Glismann (EUF)
Current contact person Samuel Glismann
Contact (e-mail) samuel.glismann@tennet.eu
Website https://ancillaryservicesacquisitionmodel.github.io/ASAM/
Logo
Primary Purpose 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.
Primary Outputs Based on Python (Pyomo). Using Python, PyPSA, Mesa for data processing.
Support / Community / Forum
Framework
Link to User Documentation https://github.com/AncillaryServicesAcquisitionModel/ASAM/wiki
Link to Developer/Code Documentation https://github.com/AncillaryServicesAcquisitionModel/ASAM/wiki
Documentation quality expandable
Source of funding -
Number of developers less than 10
Number of users less than 10
Openness
Open Source
License GNU Lesser General Public License v3.0
Source code available
GitHub
Access to source code https://github.com/AncillaryServicesAcquisitionModel/ASAM
Data provided none
Collaborative programming
GitHub Organisation
GitHub Contributions Graph
Software
Modelling software Python
Internal data processing software
External optimizer
Additional software
GUI
Coverage
Modeled energy sectors (final energy) -
Modeled demand sectors -
Modeled technologies: components for power generation or conversion
Renewables -
Conventional -
Modeled technologies: components for transfer, infrastructure or grid
Electricity -
Gas -
Heat -
Properties electrical grid -
Modeled technologies: components for storage -
User behaviour and demand side management
Changes in efficiency
Market models -
Geographical coverage
Geographic (spatial) resolution -
Time resolution -
Comment on geographic (spatial) resolution
Observation period -
Additional dimensions (sector) -
Mathematical Properties
Model class (optimisation) -
Model class (simulation) -
Other
Short description of mathematical model class
Mathematical objective -
Approach to uncertainty -
Suited for many scenarios / monte-carlo
typical computation time -
Typical computation hardware -
Technical data anchored in the model -
Model Integration
Interfaces
Model file format .exe
Input data file format .csv
Output data file format .csv
Integration with other models
Integration of other models
References
Citation reference -
Citation DOI -
Reference Studies/Models -
Example research questions -
Model usage -
Model validation -
Example research questions -
further properties
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