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E.ON EBC RWTH Aachen University

TEASER - Tool for Energy Analysis and Simulation for Efficient Retrofit

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TEASER (Tool for Energy Analysis and Simulation for Efficient Retrofit) allows fast generation of archetype buildings with low input requirements and the export of individual dynamic simulation models for the below-mentioned Modelica libraries. These libraries all use the framework of Modelica IBPSA library. TEASER is being developed at the RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate.

The full documentation of TEASER including examples and description of modules, classes and functions can be found at the website:

This GitHub page will be used to further develop the package and make it available under the MIT License.

If you have any questions regarding TEASER feel free to contact us at [email protected].

Description

Energy supply of buildings in urban context currently undergoes significant changes. The increase of renewable energy sources for electrical and thermal energy generation will require flexible and secure energy storage and distribution systems. To reflect and consider these changes in energy systems and buildings, dynamic simulation is one key element, in particular when it comes to thermal energy demand on minutely or hourly scale. Sparse and limited access to detailed building information as well as computing times are challenges for building simulation on urban scale. In addition, data acquisition and modeling for Building Performance Simulation (BPS) are time consuming and error-prone. To enable the use of BPS on urban scale we present the TEASER tool, an open framework for urban energy modeling of building stocks. TEASER provides an easy interface for multiple data sources, data enrichment (where necessary) and export of ready-to-run Modelica simulation models for all libraries supporting the Modelica IBPSA library.

Version

TEASER is an ongoing research project, the current version is still a pre-release.

How to use TEASER

Examples and jupyter notebooks

We provide different examples to show the usage of TEASER. Check out the files under teaser/examples or the jupyter-notebooks available here: docs/jupyter-notebooks. If you just want to read the example on github, check them here: docs/examples.

Dependencies

TEASER is currently tested against Python 3.7 up to 3.11. Older versions of Python may still work, but are no longer actively supported. Using a Python distribution is recommended as they already contain (or easily support installation of) many Python packages (e.g. SciPy, NumPy, pip, PyQT, etc.) that are used in the TEASER code. Two examples of those distributions are:

  1. https://winpython.github.io/ WinPython comes along with a lot of Python packages (e.g. SciPy, NumPy, pip, PyQT, etc.)..
  2. http://conda.pydata.org/miniconda.html Conda is an open source package management system and environment management system for installing multiple versions of software packages and their dependencies and switching easily between them.

In addition, TEASER requires some specific Python packages:

  1. Mako: template Engine install on a python-enabled command line with pip install -U mako
  2. pandas: popular data analysis library install on a python-enabled command line with pip install -U pandas
  3. pytest: Unit Tests engine install on a python-enabled command line with pip install -U pytest

Installation

The best option to install TEASER is to use pip:

pip install teaser

If you actively develop TEASER you can clone this repository by using:

git clone [SSH-Key/Https]

and then run:

pip install -e [Path/to/your/Teaser/Clone] which will install the local version of TEASER.

How to contribute to the development of TEASER

You are invited to contribute to the development of TEASER. You may report any issues by using the Issues button. Furthermore, you are welcome to contribute via Pull Requests. The workflow for changes is described in our Wiki.

How to cite TEASER

  • TEASER: an open tool for urban energy modelling of building stocks. Remmen P., Lauster M., Mans M., Fuchs M., Osterhage T., Müller D.. Journal of Building Performance Simulation, February 2017, pdf, bibtex

TEASER related publications

  • CityGML Import and Export for Dynamic Building Performance Simulation in Modelica. Remmen P., Lauster M., Mans M., Osterhage T., Müller D.. BSO16, p.329-336, September 2016, pdf, bibtex

  • Scalable Design-Driven Parameterization of Reduced Order Models Using Archetype Buildings with TEASER. Lauster M., Mans M., Remmen P., Fuchs M., Müller D.. BauSIM2016, p.535-542, September 2016, pdf

  • Refinement of Dynamic Non-Residential Building Archetypes Using Measurement Data and Bayesian Calibration Remmen P., Schäfer J., Müller D.. Building Simulation 2019, September 2019, pdf

  • Selecting statistical indices for calibrating building energy models. Vogt, M., Remmen P., Lauster M., Fuchs M. , Müller D.. Building and Environment 144, pages 94-107, October 2018. bibtex

  • The Institute of Energy Efficiency and Sustainable Building published a parametric study of TEASER where all functions and parameters used in TEASER are gathered and explained. The publication can be found here.

License

TEASER is released by RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, under the MIT License.

Acknowledgements

This work was supported by the Helmholtz Association under the Joint Initiative “Energy System 2050 – A Contribution of the Research Field Energy”.

Parts of TEASER have been developed within public funded projects and with financial support by BMWi (German Federal Ministry for Economic Affairs and Energy).