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| | |Additional dimensions (Other)=grid congestion | | |Additional dimensions (Other)=grid congestion |
| | |math_modeltype=Simulation, Agent-based | | |math_modeltype=Simulation, Agent-based |
| − | |math_modeltype_shortdesc=depending on parameterization bidding behavior and market behavior can be defined, | + | |math_modeltype_shortdesc=depending on parameterization bidding behavior and market behavior can be defined. |
| | | | |
| − | bidding behavior, | + | bidding behavior: |
| − | bid marginal cost, complex bids
| + | |
| | | | |
| − | market behavior, | + | * bid marginal cost |
| − | pay as bid, pay as clear, redispatch, nodal pricing | + | * complex bids |
| | + | |
| | + | market behavior: |
| | + | |
| | + | * pay as bid |
| | + | * pay as clear |
| | + | * redispatch |
| | + | * nodal pricing |
| | |math_objective=Minimize cost, optimize dispatch per agent | | |math_objective=Minimize cost, optimize dispatch per agent |
| | |deterministic=Deterministic | | |deterministic=Deterministic |
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| | https://doi.org/10.1016/j.egyai.2023.100295 | | https://doi.org/10.1016/j.egyai.2023.100295 |
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| − |
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| | |example_research_questions=What influence does the availability of different order types on a market have? | | |example_research_questions=What influence does the availability of different order types on a market have? |
| | + | |
| | How can deep reinforcement learning for multiple markets be implemented in software? | | How can deep reinforcement learning for multiple markets be implemented in software? |
| | + | |
| | What is the best way for demand-side management to be implemented in bidding agents? | | What is the best way for demand-side management to be implemented in bidding agents? |
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| | How can different energy market designs be modelled in energy market simulations? | | How can different energy market designs be modelled in energy market simulations? |
| | |Model validation=benchmark to entsoe, comparison of real dispatch | | |Model validation=benchmark to entsoe, comparison of real dispatch |
Revision as of 12:04, 17 April 2024
|
Agent-based Simulation for Studying and Understanding Market Evolution
by INATECH Freiburg
Authors:
Florian Maurer, Nick Harder, Kim K. Miskiw, Johanna Adams, Manish Khanra, Parag Pratil
Contact:
Nick Harder
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ASSUME is an open-source toolbox for agent-based simulations of European electricity markets, with a primary focus on the German market setup. Developed as an open-source model, its primary objectives are to ensure usability and customizability for a wide range of users and use cases in the energy system modeling community.
Based on Python, Pyomo. Using PostgreSQL for data processing.
Website / Documentation
Download
|
 Open Source
Affero General Public License v3 (AGPL-3.0)
Directly downloadable
Input data shipped
|
| Model Scope |
Model type and solution approach |
| Model class
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German and European Electricity Market, Network-constrained Unit Commitment and Economic Dispatch, Agent-based electricity market model
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| Sectors
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All / Electricity
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| Technologies
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Renewables, Conventional Generation, CHP
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| Decisions
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dispatch
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| Regions
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depending on input data
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| Geographic Resolution
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NUTS0 - NUTS3, for DE
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| Time resolution
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15 Minute
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| Network coverage
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transmission, distribution
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|
| Model type
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Simulation, Agent-based
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|
|
depending on parameterization bidding behavior and market behavior can be defined.
bidding behavior:
- bid marginal cost
- complex bids
market behavior:
- pay as bid
- pay as clear
- redispatch
- nodal pricing
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| Variables
|
|
| Computation time
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minutes
|
| Objective
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Minimize cost, optimize dispatch per agent
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| Uncertainty modeling
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Deterministic
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| Suited for many scenarios / monte-carlo
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No
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|
References
Scientific references
Zenodo
https://dx.doi.org/https://doi.org/10.5281/zenodo.8088760
Reports produced using the model
https://doi.org/10.1007/978-3-031-48652-4_10
https://doi.org/10.1016/j.egyai.2023.100295
Example research questions
What influence does the availability of different order types on a market have?
How can deep reinforcement learning for multiple markets be implemented in software?
What is the best way for demand-side management to be implemented in bidding agents?
How can different energy market designs be modelled in energy market simulations?
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