Technology perspectives for short and medium term use in multivalent systems
This repository contains additional information and data relating to the research project HTWP from the authors M. Fritz, J. Freißmann and I. Tuschy. It serves to allow for reproduction of the obtained results.
The authors J. Freißmann, M.Fritz and Prof. Dr.-Ing. Ilja Tuschy are part of the Center for Sustainable Energy Systems (ZNES) of the University of Applied Sciences and Europa-Universität Flensburg. The research project was funded by the Gesellschaft für Energie und Klimaschutz Schleswig-Holstein (EKSH) as part of the HWT Energie und Klimaschutz program. ARCOTS Industriekälte AG served as the industry partner. The authors are grateful for the support from both partners.
This folder contains the heat pump models used to generate characteristics for the combined investment and dispatch optimization. On the main level, the HeatPumpBase class serves as the blueprint for all heat pump models. The HeatPumpSimple and HeatPumpPC classes inherit from the base class and implement all necessary methods.
In addition to that, this directory contains an input and an output folder.
All necessary input files for the analyzed heat pumps are placed in this folder. To use those for the different district heating system models, the temperatures in the strands 'B' and 'C', as well as the part load parameter ranges in the 'offdesign' field of the input files, have to be adjusted. Additionally, 'CEPCI.json' stores the cost values of the Chemical Engineering Plant Cost Index.
The 'output' folder is empty by default but will contain output generated by the heat pump models, such as state diagrams, as well as partload and logging data.
This folder contains the files for carrying out the combined investment and dispatch optimization as well as the dispatch optimization. This requires auxiliary files, such as those for economic functions and helpers. It also contains a postprocessing file for processing the results. In addition to control files, the folders for the various district heating systems (primary network, sub network, and 4GDH network) are also stored.
The 'input' folder contains the necessary input data for the combined investment and dispatch optimization. Generally, this includes a JSON file of the constant parameters (no variation throughout the observed period) and a CSV file of the time dependent data.
This folder serves as a container for the output data of the combined investment and dispatch optimization. For each setup, there are optimized capacities and unit commitment time series, as well as key parameters and unit cost. Additionally, the results are visualized in plots that allow an even more detailed analysis than provided in the final report.
To achieve reproducible results, the necessary dependencies are saved in the requirements.txt file. In a clean environment from the root directory, the installation from this file should allow the full reproduction of the results. The steps could look like this:
conda create -n my_new_env python=3.10
conda activate my_new_env
python -m pip install -r requirements.txt