Model Factsheet

Overview / Agent-based Modeling of Electricity System (AMES)

Model Agent-based Modeling of Electricity System (AMES)

General Information
Name Agent-based Modeling of Electricity System
Acronym AMES
Methodical Focus Agent-Based modeling
Institution(s) Iowa State University, Battelle Memorial Institute, Pacific Northwest National Laboratory
Author(s) (institution, working field, active time period) Leigh Tesfatsion; Iowa State University; tesfatsi@iastate.edu
Current contact person -
Contact (e-mail) tesfatsi@iastate.edu
Website https://github.com/ames-market
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Primary Purpose Agent-based computational platform modeling RTO/ISO-managed wholesale power market operations over a high-voltage transmission grid for successive days, with congestion handled by locational marginal pricing. Simulates day-ahead SCUC/SCED (security-constrained unit commitment and security-constrained economic dispatch) optimizations running in tandem with real-time SCED optimizations over successive days of operation, with continually updated state conditions. Market-participant agents can be endowed with reinforcement learning capabilities by means of an incorporated Java Reinforcement Learning Module (JReLM). Designed for federation with other domain simulators, thus permitting the co-simulation study of larger systems such as integrated transmission and distribution systems.
Primary Outputs
Support / Community / Forum
Framework
Link to User Documentation https://github.com/ames-market/AMES-V5.0#documentation
Link to Developer/Code Documentation -
Documentation quality good
Source of funding -
Number of developers less than 10
Number of users less than 10
Openness
Open Source
License AMES License - like bsd license
Source code available
GitHub
Access to source code https://github.com/ames-market/
Data provided example data
Collaborative programming
GitHub Organisation
GitHub Contributions Graph
Software
Modelling software
Internal data processing software
External optimizer
Additional software
GUI
Coverage
Modeled energy sectors (final energy) electricity
Modeled demand sectors -
Modeled technologies: components for power generation or conversion
Renewables -
Conventional -
Modeled technologies: components for transfer, infrastructure or grid
Electricity distribution, transmission
Gas -
Heat -
Properties electrical grid SCUC/SCED
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 .xls
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
Model specific properties -

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