Examples

This folder contains several example files which help with the understanding of AixCaliBuHA.

Getting started

You have three ways of accessing the examples:

  • Only via markdown to read. Use the .md-files under examples/docs

  • Offline using jupyter-notebook. Use the .ipynb-files under examples/jupyter_notebooks

  • Offline using python. Use the .py-files under examples. While these examples should run in any IDE, we advise using PyCharm.

For the latter two, be sure to:

  1. Create a clean environment of python 3.7 or 3.8. In Anaconda run: conda create -n py38_ebcpy python=3.8

  2. Activate the environment in your terminal. In Anaconda run: activate py38_ebcpy

  3. Clone the library using git clone --recurse-submodules https://github.com/RWTH-EBC/AixCaliBuHA

  4. Install the library using pip install -e AixCaliBuHA

We have two models to show the calibration process for different components inside typical building and HVAC systems.

  • Example model A: This model is of a heat pump system supplying heat to a room using a radiator. The models are based on the AixLib.

    img.png

  • Example model B: This model is of a pump and a valve from the Modelica Standard Library.

    img.png

Currently, example A runs only on windows. Example B runs on both linux and windows. Additionally, you need Dymola installed for the first example of model A. If you don’t have Dymola, just follow example B or skip the first example. It’s not vital to understand this framework, it just helps to understand the energy system analysis prior to calibration. To follow a specific example A or B, execute the first and second example for the case, for instance e1_A. The examples 3-5 are written for both, so just alter the parameter in the if __name__ == '__main__' section, for instance EXAMPLE = A to EXAMPLE = B.

What can I learn in the examples?

e1_A_energy_system_analysis.py and e1_B_energy_system_analysis.py

  1. Learn how to analyze the model of your energy system

  2. Improve your SimulationAPI knowledge

  3. Improve your skill-set on TimeSeriesData

  4. Generate some measured data to later use in a calibration

e2_A_optimization_problem_definition.py and e2_B_optimization_problem_definition.py

  1. Learn how to formulate your calibration problem using our data_types

  2. Get to know TunerParas

  3. Get to know Goals

  4. Get to know CalibrationClass

  5. Learn how to merge multiple classes

e3_sensitivity_analysis_example.py

  1. Learn how to execute a sensitivity analysis

  2. Learn how to automatically select sensitive tuner parameters

e4_calibration_example.py

  1. Learn the settings for a calibration

  2. Learn how to use both Single- and MultiClassCalibration

  3. Learn how to validate your calibration

e5_automated_process.py

  1. Learn how to run everything in one script

e6_multiprocessing_calibration_example.py

  1. Just as in e4, learn how to set up a calibration, this time while using multiprocessing

  2. Install and use pandas==1.3.5 and tables==3.6.1