This repository contains example implementations and usage patterns for the ASSUME (Agent-Based Electricity Markets Simulation Toolbox).
The ASSUME framework provides automated security measurement and evaluation capabilities for software systems. These examples demonstrate how to integrate and utilize ASSUME in various scenarios.
- Clone this repository
git clone https://github.com/assume-framework/assume-examples.git
- Install assume framework
In your selected python environment (virtualenv or conda) run:
pip install assume-framework
- Run the examples
If you want to have a database running and the grafana available run: docker compose up -d
(make sure you have docker installed).
Then run the tiny example:
assume -i inputs -s example_01a -c tiny -db "postgresql+psycopg2://assume:assume@localhost:5432/assume"
or more general:
assume -i inputs -s $scenario_name -c $case_study -db $database_url
The available examples are as follows:
- base: simple small example
- dam: small_dam
- dam_with_complex_clearing: small_with_opt_clearing
- base: small_with_vre
- eom_only: small_with_vre_and_storage
- dam_with_complex_opt_clearing: small_with_BB_and_LB
- dam_with_complex_opt_clearing: small_with_vre_and_storage_and_complex_clearing
- eom_and_crm: small_with_crm
- base: small_with_redispatch
- nodal_case: small_with_nodal_clearing
- zonal_case: small_with_zonal_clearing
- eom_case: market_study_eom
- ltm_case: market_study_eom_and_ltm
- base: small_learning_1
- base_lstm: small_learning_1_lstm
- base: small_learning_2
- base_lstm: small_learning_2_lstm
- base: small_learning_3
- dam: learning_with_complex_bids
- base_case_2019: large_2019_eom
- eom_crm_case_2019: large_2019_eom_crm
- dam_case_2019: large_2019_day_ahead
- base_case_2019_with_DSM: large_2019_with_DSM
- base_case_2019: large_2019_rl
- base_case_2021: large_2021_rl
Contributions are welcome! If you want to add your example, make sure it works and create a PR for it.
This project contains examples which are licensed as CC-BY-4.0 if not stated otherwise in the respextive license file.