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| {{Model | | {{Model |
− | |Full_Model_Name=Agent-based Simulation for Studying and Understanding Market Evolution | + | |Full_Model_Name=Agent-based Simulation for Studying and Understanding Market Evolution |
| |Acronym=ASSUME | | |Acronym=ASSUME |
| |author_institution=INATECH Freiburg | | |author_institution=INATECH Freiburg |
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| |contact_email=contact@assume-project.de | | |contact_email=contact@assume-project.de |
| |website=https://assume-project.de/ | | |website=https://assume-project.de/ |
− | |source_download=pip install assume-framework | + | |source_download=https://codeload.github.com/assume-framework/assume/zip/refs/heads/main |
| |logo=assume-project.png | | |logo=assume-project.png |
| |text_description=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. | | |text_description=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. |
− | |Primary outputs= electricity prices, power plant dispatch, cost and income | + | |Primary outputs=electricity prices, power plant dispatch, cost and income |
| |Support=OpenMod Forum, GitHub Issues | | |Support=OpenMod Forum, GitHub Issues |
| |Framework=mango-agents | | |Framework=mango-agents |
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| |license=Affero General Public License v3 (AGPL-3.0) | | |license=Affero General Public License v3 (AGPL-3.0) |
| |model_source_public=Yes | | |model_source_public=Yes |
− | |Link to source=https://github.com/assume-framework/assume/ | + | |Link to source=https://github.com/assume-framework/assume/releases |
| |data_availability=all | | |data_availability=all |
| |open_future=No | | |open_future=No |
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| |External optimizer=GLPK, CBC, Gurobi, C-Plex | | |External optimizer=GLPK, CBC, Gurobi, C-Plex |
| |GUI=No | | |GUI=No |
− | |model_class=German and European Electricity Market, Network-constrained Unit Commitment and Economic Dispatch, Agent-based electricity market model, | + | |model_class=German and European Electricity Market, Network-constrained Unit Commitment and Economic Dispatch, Agent-based electricity market model, |
− | |sectors=All / Electricity, | + | |sectors=All / Electricity, |
| |technologies=Renewables, Conventional Generation, CHP | | |technologies=Renewables, Conventional Generation, CHP |
| |Demand sectors=Households, Industry, Commercial sector | | |Demand sectors=Households, Industry, Commercial sector |
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| |citation_references=Zenodo | | |citation_references=Zenodo |
| |citation_doi=https://doi.org/10.5281/zenodo.8088760 | | |citation_doi=https://doi.org/10.5281/zenodo.8088760 |
− | |example_research_questions=How can different energy market designs be modelled in | + | |example_research_questions=How can different energy market designs be modelled in |
− | |Model validation=benchmark to entsoe | + | |Model validation=benchmark to entsoe, comparison of real dispatch |
| |Specific properties=reinforcement learning, RL, interoperability, market abstraction | | |Specific properties=reinforcement learning, RL, interoperability, market abstraction |
| |Integrated models=PyPSA, AMIRIS | | |Integrated models=PyPSA, AMIRIS |