# SHaKE Module 5 Practical Exercise  
## DHC Modelling and Energy Performance Assessment  
### Advanced systems in District Heating and Cooling

This exercise package is part of Module 5 of the SHaKE educational package on District Heating and Cooling (DHC) systems.

The package contains Python scripts, Jupyter Notebooks and supporting input/model files for DHC modelling. The code allows learners to assess the energy performance of DHC networks and substations, analyse operational data and explore selected performance improvement and malfunction detection concepts.

## Purpose of the exercise

The practical exercise helps learners apply concepts covered in Module 5, including:

- DHC network performance assessment,
- analysis of return temperatures,
- substation-level performance evaluation,
- detection of operational issues,
- numerical modelling of DHC systems,
- interpretation of simulation and output data.

The exercise may be used for classroom activities, group work, homework assignments, short technical reports or oral presentations.

## Package structure

The package should keep the following folder structure:

```text
SHaKE_Module_5_Practical_Exercise/
  README.md
  DHC_main.py
  Network_analysis.ipynb
  Substation_analysis.ipynb
  Images/
  Inputs/
  Models/
  Outputs/
```

Please do not rename or move the folders, as the scripts and notebooks rely on this structure.

For international/public use, the model folder should be named:

```text
Models
```

If any script still refers to:

```text
Modèles
```

the path should be updated to:

```text
Models
```

## Main files

### `DHC_main.py`

Main Python script used for DHC network simulation and analysis.

### `Network_analysis.ipynb`

Jupyter Notebook for network-level analysis. It can be used to explore DHC network behaviour, input data, modelling results and performance indicators.

### `Substation_analysis.ipynb`

Jupyter Notebook for substation-level analysis. It supports the investigation of substation operation, performance and possible malfunction-related indicators.

## Required folders

### `Inputs/`

Contains the input data files required by the scripts and notebooks.

Typical input files may include:

- `Entrees_Albi_10min_30j.xlsx`
- `DonneesSST_Albi24.xlsx`
- `DonneesReseau_Albi24.xlsx`

### `Models/`

Contains model files and supporting Python components required by the simulation scripts.

### `Images/`

Contains figures or visual resources used by the notebooks or generated during the analysis.

### `Outputs/`

Contains generated output files. Depending on the analysis, new results may be saved here when the scripts or notebooks are executed.

## Software requirements

To use the exercise package, learners need:

- Python 3.x
- Jupyter Notebook or JupyterLab
- common scientific Python libraries, such as:
  - `numpy`
  - `pandas`
  - `matplotlib`
  - `openpyxl`

Additional dependencies may be required depending on the local Python environment and the specific model files used.

## How to use the exercise

1. Download the ZIP package.
2. Extract the ZIP file to a local folder.
3. Keep the original folder structure unchanged.
4. Open Jupyter Notebook or JupyterLab.
5. Open either:
   - `Network_analysis.ipynb`, or
   - `Substation_analysis.ipynb`.
6. Run the notebook cells in order.
7. Review the generated figures, tables and output files.
8. Use the results for discussion, reporting or assessment.

## Suggested learning tasks

Learners may be asked to:

- describe the main input data used in the analysis,
- identify key DHC performance indicators,
- analyse the effect of return temperature on network performance,
- compare different substation or network behaviours,
- interpret generated plots and output data,
- discuss possible causes of non-optimal operation,
- prepare a short technical report or presentation based on the results.

## Notes for educators

Educators may adapt the exercise depending on the level of the course, available teaching time and learners’ prior knowledge.

The package can be used as:

- a guided classroom exercise,
- a group-based project task,
- an individual homework assignment,
- a numerical modelling demonstration,
- a case study for discussing DHC performance improvement and malfunction detection.

## SHaKE project

This material has been developed as part of the SHaKE project:

**Sharing Heat and Knowledge on Energy Communities (SHaKE)**  
Erasmus+ KA220-HED Cooperation Partnerships in Higher Education  
Project No.: 2023-1-HU01-KA220-HED-000160219  

Project website:  
https://www.shakeproject-dhc.eu/

## Licence

Unless otherwise stated, this material is licensed under a Creative Commons Attribution 4.0 International Licence (CC BY 4.0).

Users may share and adapt the material, provided that appropriate credit is given to the SHaKE project and the authors, a link to the licence is provided, and any changes are indicated.