assume-framework 0.1.0

ASSUME - Agent-Based Electricity Markets Simulation Toolbox

ASSUME

ASSUME is an open-source tool-box for an agent-based simulation of the European electricity and later on energy markets with a main focus on the German market setup. As a newly developed open-source model its priority is to ensure usability and customisability for a variety of users and use cases in the energy system modelling community.

The unique feature of the ASSUME toolbox is the integration of deep reinforcement learning methods into the behavioural strategies of market agents. The model comes with different predefined agent representations for the demand and generation side that can be used as plug-and-play modules, which facilitate reinforcement of learning strategies. This setup enables a research of new market designs and dynamics in the energy markets.

The project is developed by developers from INATECH at University of Freiburg, IISM at KIT, Fraunhofer ISI, FH Aachen. The project ASSUME is funded by the Federal Ministry for Economic Affairs and Climate Action (BMWK).

Documentation

Documentation

Installation

Installation

Using pip

The project is available on PyPi and can be simply installed:

pip install assume-framework

if you want to install it with testin capabilities run:

pip install assume-framework[test]

Using conda

First clone the repository:

git clone https://github.com/assume-framework/assume.git

Next, navigate to the cloned directory:

cd $where you cloned the repo$

Now, create a conda environment:

conda env create -f environment.yml

Afterwards, activate the environment:

conda activate assume-framework

Quick Start

There are 3 ways to run a simulation.
1.) local (without database and grafana)
2.) with docker (with database and grafana)
3.) use CLI to run simulations

1. To run an exemplar simulation without database and grafana, run the following command:

python examples/examples.py

2. If you have docker installed, you can run the following two commands

Note: you have to select 'timescale' in examples.py

    docker compose up -d
    python examples/examples.py

This will start a container for timescaledb and grafana with preconfigured grafana dashboard. Afterwards you can access the Dashboard on http://localhost:3000

3. You can also use the cli to run simulations:

assume -s example_01b -db "postgresql://assume:assume@localhost:5432/assume"

If you need help using the CLI run assume -h

Please note that if you have python running on windows that you need to alter the same_process binary in world to True (to be changed).

Development

install pre-commit

pip install pre-commit
pre-commit install

to run pre-commit directly, you can use

pre-commit run --all-files

Create Documentation

First, create an environment which includes the docs dependencies:

conda env create -f environment_docs.yml

To create the documentation or update the automatically created docs in docs/source/assume* run sphinx-apidoc -o docs/source -Fa assume

To create and serve the documentation locally, run

make -C docs html && python -m http.server --directory docs/build/html

Use Learning Capabilities

If you want to use the reinforcement learning strategies of Assume please make sure to install torch on top of the requirements listed in the requirements.txt. If you Ressources do not have a GPU available use the CPU only version of torch, which can be installed like this:

pip install "torch>=2.0.1+cpu" -f https://download.pytorch.org/whl/torch_stable.html

Licence

Copyright 2022-2023 ASSUME developers

ASSUME is licensed under the GNU Affero General Public License v3.0