FAME-Io: Configuration tools for complex agent-based
simulations

Nitsch, Felix; Schimeczek, Christoph; Frey, Ulrich; Fuchs, Benjamin

doi:10.21105/joss.04958

Cited by 6 publications

(2 citation statements)

References 14 publications

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“…Due to this comprehensive modelling of actors in energy systems, scientists can utilise AMIRIS to investigate their specific research questions. Using FAME-Io (Nitsch et al, 2023), openly available and tested model configurations 2 can be easily adapted to this end.…”

Section: Statement Of Needmentioning

confidence: 99%

AMIRIS: Agent-based Market model for the Investigation of Renewable and Integrated energy Systems

Schimeczek¹,

Nienhaus²,

Frey³

et al. 2023

JOSS

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AMIRIS is an agent-based model (ABM) to simulate electricity markets. The focus of this bottom-up model is on the business-oriented decisions of actors in the energy system. These actors are represented as prototypical agents in the model, each with own complex decisionmaking strategies. Inter alia, the bidding decisions are based on the assessment of electricity market prices and generation forecasts (Nitsch, Deissenroth-Uhrig, et al., 2021), and diverse actors deciding on different time scales may be modelled. In particular, the agents' 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 (Frey et al., 2020). This allows assessing which policy or market design is best suited to an economic and effective energy system (Torralba-Díaz et al., 2020). The simulations generate results on the dispatch of power plants and flexibility options, technology-specific market values, development of system costs or CO2 emissions. One important output of the model are simulated market prices (Deissenroth et al., 2017).

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Section: Statement Of Needmentioning

confidence: 99%

AMIRIS: Agent-based Market model for the Investigation of Renewable and Integrated energy Systems

Schimeczek¹,

Nienhaus²,

Frey³

et al. 2023

JOSS

Self Cite

View full text Add to dashboard Cite

show abstract

“…Each component addresses one aspect within FAME's model development and usage workflow, see Figure 1. Of these, FAME-Core and FAME-Io (Nitsch et al, 2023) are the most important ones. While the first is a Java library supporting development and execute ABM simulations, the latter is a Python package 2 to configure complex simulations and manage files associated with FAME.…”

mentioning

confidence: 99%