Welcome to AMIRIS - the open Agent-based Market model for the Investigation of Renewable and Integrated energy Systems AMIRIS. This simulation model has evolved for more than ten years to a next-generation open-source tool.
Aim
AMIRIS aims at enabling scientists to dissect the complex questions arising with respect to future energy markets, their market design, and energy-related policy instruments. The model computes electricity prices endogenously based on the simulation of strategic bidding behavior of prototyped market actors. This bidding behavior does not only reflect marginal prices, but can also consider effects of support instruments like market premia, uncertainties and limited information, or market power.
Structure
The figure below provides an overview of the agents modeled in AMIRIS and illustrates the associated information, energy, and financial flows.
In AMIRIS actors are represented as agents that can be roughly divided into six classes: Power plant operators, traders, marketplaces, policy providers, demand, and storage facilities. Power plant operators provide generation capacities to traders, but do not trade on the markets themselves in the model. Instead, supply traders conduct the marketing and employ bidding strategies. Marketplaces serve as trading platforms and organize market clearing. Policy providers define a regulatory framework which impacts the decisions of other agents. Demand agents request energy directly at the electricity market. Finally, flexibility providers, e.g., storage operators, use forecasts to determine bidding patterns matching their objective. Check out this very short introduction video.
Enabling researchers
AMIRIS enables investigating the influence of political framework conditions on the behavior and profitability of energy market actors, considering different marketing paths. It also allows quantifying the influence of actors, their uncertainties and socioeconomic decisions on energy markets. We offer a range of example parameterizations (e.g., Germany 2015-2019) to facilitate a smooth and convenient start of model application.
Please also refer to our Research section to find the latest related publications and projects and see the Events section for material of our past trainings and upcoming events with AMIRIS developers and researchers.
Powerful, flexible, and performant
Due to its agent-based and modular nature, AMIRIS can be easily extended or modified. AMIRIS is based on the open Framework for distributed Agent-based Modelling of Energy systems FAME. Due to its high-performance computing capabilities and efficient development paradigms, AMIRIS can simulate even large-scale agent systems in a short time. Currently, a model year at hourly resolution can be simulated in less than a minute on standard desktop computers.
With AMIRIS-Py, we also provide a powerful Python wrapper to set up and run AMIRIS.
Please refer to the official amirispy documentation for further details.
Getting started
| Content | URL |
|---|---|
| AMIRIS gitlab project | https://gitlab.com/dlr-ve/esy/amiris/amiris |
| AMIRIS Python wrapper | https://gitlab.com/dlr-ve/esy/amiris/amiris-py |
| AMIRIS Example Parameterizations | https://gitlab.com/dlr-ve/esy/amiris/examples |
| Q&A at openmod forum | https://forum.openmod.org/tag/amiris |
| AMIRIS Wiki | https://gitlab.com/dlr-ve/esy/amiris/amiris/-/wikis/home |
| AMIRIS Javadoc | https://dlr-ve.gitlab.io/esy/amiris/amiris/ |
| FAME gitlab project | https://gitlab.com/fame-framework |
You will find recent material (e.g. from our workshops) and publications at Zenodo.
Citation
If you use AMIRIS for scientific work, please cite:
Schimeczek et al., (2023). AMIRIS: Agent-based Market model for the Investigation of Renewable and Integrated energy Systems. Journal of Open Source Software, 8(84), 5041, https://doi.org/10.21105/joss.05041
Contact
Feel free to get in contact or contribute to AMIRIS.
