Hello, I would like to ask what statistical methods / econometric (mathematical) models are taken into account in the model? Unfortunately, I have not found specific information on this anywhere.
The energy data have characteristics that prevent the use of most typical methods (autocorrelation, seasonality, etc.), so I would like to ask for specific information.
Hi Sylwia,
as an agent-based simulation, AMIRIS does not apply any statistical/econometrical methods directly.
Instead, these methods can be applied to infer input data for AMIRIS. However, this must be done in some pre-processing routine not provided by AMIRIS.
AMIRIS is documented in a very recent publication and a comprehensive Javadoc.
If you haven’t had the chance to experiment with agent-based simulation yet, I warmly recommend diving into the following papers as your starting point:
- Agent-Based Models in Electricity Markets: A Literature Review | IEEE Conference Publication | IEEE Xplore
- Redirecting
- Assessing the Plurality of Actors and Policy Interactions: Agent-Based Modelling of Renewable Energy Market Integration
- Models Within Models – Agent-Based Modelling and Simulation in Energy Systems Analysis
Some literature covering AMIRIS
I am not aware of much in the way of hybrid/agent‑based energy systems models within this community, so here are some examples from the DLR work in this regard:
2023
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Schimeczek, Christoph, Kristina Nienhaus, Ulrich Frey, Evelyn Sperber, Seyedfarzad Sarfarazi, Felix Nitsch, Johannes Kochems, and A Achra El Ghazi (17 April 2023). “AMIRIS: Agent-based Market model for the Investigation of Renewable and Integrated energy Systems”. Journal of Open Source Software. 8 (84): 5041. ISSN 2475-9066. doi:10.21105/joss.05041.
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Nitsch, Felix, Christoph Schimeczek, Ulrich Frey, and Benjamin Fuchs (17 April 2023). “FAME-Io: configuration tools for complex agent-based simulations”. Journal of Open Source Software. ISSN 2475-9066. doi:10.21105/joss.04958.
2022
- Nitsch, Felix and Christoph Schimeczek (18 February 2022). Backtesting the open source electricity market model AMIRIS by simulating the Austrian day-ahead market — Presentation. Presentation at 17th Symposium Energieinnovation EnInnov 2022, Graz, Austria.
2019
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Klein, Martin, Ulrich J Frey, and Matthias Reeg (2019). “Models within models: agent-based modelling and simulation in energy systems analysis”. Journal of Artificial Societies and Social Simulation. 22 (4): 6. ISSN 1460-7425. doi:10.18564/jasss.4129.
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Shinde, Priyanka, and Mikael Amelin (2019). Agent-based models in electricity markets: a literature review. 2019 IEEE Innovative Smart Grid Technologies — Asia (ISGT Asia), Chengdu, China. doi:10.1109/ISGT-Asia.2019.8880889.
2017
- Deissenroth, Marc, Martin Klein, Kristina Nienhaus, and Matthias Reeg (10 December 2017). “Assessing the plurality of actors and policy interactions: agent-based modelling of renewable energy market integration”. Complexity. 2017: 7494313. ISSN 1076-2787. doi:10.1155/2017/7494313.
Undated
- DLR (undated). Agent-based simulation model AMIRIS. Institute of Networked Energy Systems, German Aerospace Center (DLR). Germany. Project summary.
Videos
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Nitsch, Felix. 2023. Lightning talk: AMIRIS: open agent-based electricity market model. YouTube. 00:03:09.
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Schimeczek, Christoph. 2023. Lightning talk: FAME: open Framework for distributed Agent-based Modelling of Energy systems. YouTube. 00:02:36.
Search this forum
- topics tagged amiris
- topics tagged fame-abm-model-generator
Code
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FAME (ongoing). Framework for distributed Agent-based Modelling of Energy systems (FAME). Codebase.
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FAME-Io (ongoing). Python package for input file creation for FAME models and digestion of FAME outputs. Codebase.
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German Aerospace Center (ongoing). AMIRIS — The open agent-based electricity market model. German Aerospace Center (DLR). Cologne, Germany.
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