Hierarchical Agent-based Markets for Local Energy Trading
An open-source tool for the agent-based development and testing of energy market applications (at a local level).
Due to the increasing complexity of energy systems, the need for more detailed and realistic models has arisen. Agent-based models are a promising approach to model the behavior of individual actors in energy systems. For this purpose, we developed HAMLET, a modular and extendable open-source toolbox for the development and testing of market designs with a focus on local interactions at the distribution level. HAMLET is designed to be used by researchers to investigate the interactions between market participants and the impact of different market designs on the technical and economic performance of energy systems.
HAMLET was developed with extendability and modularity in mind. Therefore, each functionality can be easily swapped for another to test, for example, other market clearing algorithms, trading strategies, or control strategies. The aim of the tool is to provide a common platform for researchers to develop and test their own market designs and to compare their results with other market designs.
A documentation is currently being developed and will be available soon.
HAMLET was developed and is maintained by the Chair of Renewable and Sustainable Energy Systems of the Technical University of Munich. Version 0.1 (February 2024) was developed as part of the research project STROM, funded by the Bavarian Ministry of Economic Affairs, Regional Development and Energy.
HAMLET offers...
- a fully open-source, agent-based energy market modelling toolbox
- a modular and extendable design for easy adaptation to your own research questions
- integrated time-series data for several plant types (household loads, pv, wind, heat pumps, electric vehicles etc...)
- template functionality for load and generation forecasting, trading strategies, market clearing algorithms and control strategies and much more...
so you only need to adapt the components you want to investigate and/or improve on
HAMLET is completely based on Python to keep the installation process simple. This installation guide will explain how to get HAMLET to run using PyCharm, Gurobi and Anaconda as example. However, other IDEs and package managers are perfectly suitable as well.
- IDE: e.g. PyCharm
- Package Manager: e.g. Anaconda
- Solver: e.g. Gurobi* or CPLEX. GLPK can be used although this is non-ideal.
*Installation explained later in this README
You can download or clone the repository to a local directory of your choice. You can use version control tools such as GitHub Desktop, Sourcetree, GitKraken or pure Git. The link for pure Git is:
git clone https://github.com/tum-ewk/hamlet.git
If using PyCharm, clone the repository, for example, to ./PyCharmProjects/hamlet/
- Open the AnacondaPrompt.
- Type `conda env create -f ./PycharmProjects/hamlet/env.yml`
- Take care to set the correct (absolute) path to your cloned repository.
- Open PyCharm
- Go to 'File->Open'
- Navigate to PyCharmProjects and open hamlet
- When the project has opened, go to
`File->Settings->Project->Python Interpreter->Show all->Add->Conda Environment
->Existing environment->Select folder->OK`
- Go to gurobi.com
- Create an account with your university email
- When the account has been activated, log in and download the newest Gurobi solver.
- Go to Academia->Academic Program and Licenses
- Follow the installation instructions under "Individual Academic Licenses" to activate your copy of Gurobi
- Navigate to ./PycharmProjects/hamlet/01 - examples
- Execute 01_create_scenario.py, followed by 02_execute_scenario.py
- When the simulation has completed (this may take some time, depending on your system),
analyze the results by executing 03_analyze_scenario.py (no analysis available yet)
- Look at the output plots under hamlet/05_results/example_singlemarket/analysis/ (once implemented)
Feel free to contact us if you want to contribute to this project, cooperate on an interesting research question or just to ask about the project.
Markus Doepfert
markus.doepfert@tum.de
Research Associate @ TUM ENS
Copyright (C) 2023 TUM-ENS
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/.